The solution processability of ionogel solid electrolytes has recently garnered attention in the Li-ion battery community as a means to address the interface and fabrication issues commonly associated with most solid electrolytes. However, the trapped ionic liquid (ILE) component has hindered the electrochemical performance. In this report we present a process to tune the properties by replacing the ILE in a silica-based ionogel after fabrication with a liquid component befitting the desired application. Electrochemical cycling under various conditions showcases gels containing different liquid components incorporated into LiFePO4 (LFP)/gel/Li cells: high power (455 W kg–1 at a 1 C discharge) systems using carbonates, low temperatures (-40 °C) using ethers, or high temperatures (100 °C) using ionic liquids. Fabrication of additive-manufactured cells utilizing the exchanged carbonate-based system is demonstrated in a planar LFP/Li4Ti5O12 (LTO) system, where a marked improvement over an ionogel is found in terms of rate capability, capacity, and cycle stability (118 vs 41 mA h g–1 at C/4). This process represents a promising route to create a separator-less cell, potentially in complex architectures, where the electrolyte properties can be facilely tuned to meet the required conditions for a wide range of battery chemistries while maintaining a uniform electrolyte access throughout cast electrodes.
This project was broadly motivated by the need for new hardware that can process information such as images and sounds right at the point of where the information is sensed (e.g. edge computing). The project was further motivated by recent discoveries by group demonstrating that while certain organic polymer blends can be used to fabricate elements of such hardware, the need to mix ionic and electronic conducting phases imposed limits on performance, dimensional scalability and the degree of fundamental understanding of how such devices operated. As an alternative to blended polymers containing distinct ionic and electronic conducting phases, in this LDRD project we have discovered that a family of mixed valence coordination compounds called Prussian blue analogue (PBAs), with an open framework structure and ability to conduct both ionic and electronic charge, can be used for inkjet-printed flexible artificial synapses that reversibly switch conductance by more than four orders of magnitude based on electrochemically tunable oxidation state. Retention of programmed states is improved by nearly two orders of magnitude compared to the extensively studied organic polymers, thus enabling in-memory compute and avoiding energy costly off-chip access during training. We demonstrate dopamine detection using PBA synapses and biocompatibility with living neurons, evoking prospective application for brain - computer interfacing. By application of electron transfer theory to in-situ spectroscopic probing of intervalence charge transfer, we elucidate a switching mechanism whereby the degree of mixed valency between N-coordinated Ru sites controls the carrier concentration and mobility, as supported by density functional theory (DFT) .
The present study has used a variety of characterization techniques to determine the products and reaction pathways involved in the rechargeable Li-FeS2 system. We revisit both the initial lithiation and subsequent cycling of FeS2 employing an ionic liquid electrolyte to investigate the intermediate and final charge products formed under varying thermal conditions (room temperature to 100 °C). The detection of Li2S and hexagonal FeS as the intermediate phases in the initial lithiation and the electrochemical formation of greigite, Fe3S4, as a charge product in the rechargeable reaction differ significantly from previous reports. The conditions for Fe3S4 formation are shown to be dependent on both the temperature (∼60 °C) and the availability of sulfur to drive a FeS to Fe3S4 transformation. Upon further cycling, Fe3S4 transforms to a lower sulfur content iron sulfide phase, a process which coincides with the loss of sulfur based on the new reaction pathways established in this work. The connection between sulfur loss, capacity fade, and charge product composition highlights the critical need to retain sulfur in the active material upon cycling.
Conversion cathodes represent a viable route to improve rechargeable Li+ battery energy densities, but their poor electrochemical stability and power density have impeded their practical implementation. Here, we explore the impact cell fabrication, electrolyte interaction, and current density have on the electrochemical performance of FeS2/Li cells by deconvoluting the contributions of the various conversion and intercalation reactions to the overall capacity. By varying the slurry composition and applied pressure, we determine that the capacity loss is primarily due to the large volume changes during (de)lithiation, leading to a degradation of the conductive matrix. Through the application of an external pressure, the loss is minimized by maintaining the conductive matrix. Further, we determine that polysulfide loss can be minimized by increasing the current density (>C/10), thus reducing the sulfur formation period. Analysis of the kinetics determines that the conversion reactions are rate-limiting, specifically the formation of metallic iron at rates above C/8. While focused on FeS2, our findings on the influence of pressure, electrolyte interaction, and kinetics are broadly applicable to other conversion cathode systems.
A well-posed physics-based compact model for a three-terminal silicon–oxide–nitride–oxide–silicon (SONOS) synaptic circuit element is presented for use by neuromorphic circuit/system engineers. Based on technology computer aided design (TCAD) simulations of a SONOS device, the model contains a nonvolatile memristor with the state variable QM representing the memristor charge under the gate of the three-terminal element. By incorporating the exponential dependence of the memristance on QM and the applied bias V for the gate, the compact model agrees quantitatively with the results from TCAD simulations as well as experimental measurements for the drain current. The compact model is implemented through VerilogA in the circuit simulation package Cadence Spectre and reproduces the experimental training behavior for the source–drain conductance of a SONOS device after applying writing pulses ranging from –12 V to +11 V, with an accuracy higher than 90%.
The controlled fabrication of vertical, tapered, and high-aspect ratio GaN nanowires via a two-step top-down process consisting of an inductively coupled plasma reactive ion etch followed by a hot, 85% H3PO4 crystallographic wet etch is explored. The vertical nanowires are oriented in the [0001] direction and are bound by sidewalls comprising of 3362 ¯ } semipolar planes which are at a 12° angle from the [0001] axis. High temperature H3PO4 etching between 60 °C and 95 °C result in smooth semipolar faceting with no visible micro-faceting, whereas a 50 °C etch reveals a micro-faceted etch evolution. High-angle annular dark-field scanning transmission electron microscopy imaging confirms nanowire tip dimensions down to 8–12 nanometers. The activation energy associated with the etch process is 0.90 ± 0.09 eV, which is consistent with a reaction-rate limited dissolution process. The exposure of the 3362 ¯ } type planes is consistent with etching barrier index calculations. The field emission properties of the nanowires were investigated via a nanoprobe in a scanning electron microscope as well as by a vacuum field emission electron microscope. The measurements show a gap size dependent turn-on voltage, with a maximum current of 33 nA and turn-on field of 1.92 V nm−1 for a 50 nm gap, and uniform emission across the array.
The performance of solid-state electrochemical systems is intimately tied to the potential and lithium distributions across electrolyte-electrode junctions that give rise to interface impedance. Here, we combine two operando methods, Kelvin probe force microscopy (KPFM) and neutron depth profiling (NDP), to identify the rate-limiting interface in operating Si-LiPON-LiCoO2 solid-state batteries by mapping the contact potential difference (CPD) and the corresponding Li distributions. The contributions from ions, electrons, and interfaces are deconvolved by correlating the CPD profiles with Li-concentration profiles and by comparisons with first-principles-informed modeling. We find that the largest potential drop and variation in the Li concentration occur at the anode-electrolyte interface, with a smaller drop at the cathode-electrolyte interface and a shallow gradient within the bulk electrolyte. Correlating these results with electrochemical impedance spectroscopy following battery cycling at low and high rates confirms a long-standing conjecture linking large potential drops with a rate-limiting interfacial process.
An intriguing new class of two-dimensional (2D) materials based on metal-organic frameworks (MOFs) has recently been developed that displays electrical conductivity, a rarity among these nanoporous materials. The emergence of conducting MOFs raises questions about their fundamental electronic properties, but few studies exist in this regard. Here, we present an integrated theory and experimental investigation to probe the effects of metal substitution on the charge transport properties of M-HITP, where M = Ni or Pt and HITP = 2,3,6,7,10,11-hexaiminotriphenylene. The results show that the identity of the M-HITP majority charge carrier can be changed without intentional introduction of electronically active dopants. We observe that the selection of the metal ion substantially affects charge transport. Using the known structure, Ni-HITP, we synthesized a new amorphous material, a-Pt-HITP, which although amorphous is nevertheless found to be porous upon desolvation. Importantly, this new material exhibits p-type charge transport behavior, unlike Ni-HITP, which displays n-type charge transport. These results demonstrate that both p- and n-type materials can be achieved within the same MOF topology through appropriate choice of the metal ion.
The galvanostatic intermittent titration technique (GITT) is widely used to evaluate solid-state diffusion coefficients in electrochemical systems. However, the existing analysis methods for GITT data require numerous assumptions, and the derived diffusion coefficients typically are not independently validated. To investigate the validity of the assumptions and derived diffusion coefficients, we employ a direct-pulse fitting method for interpreting the GITT data that involves numerically fitting an electrochemical pulse and subsequent relaxation to a one-dimensional, single-particle, electrochemical model coupled with non-ideal transport to directly evaluate diffusion coefficients. Our non-ideal diffusion coefficients, which are extracted from GITT measurements of the intercalation regime of FeS2 and independently verified through discharge predictions, prove to be 2 orders of magnitude more accurate than ideal diffusion coefficients extracted using conventional methods. We further extend our model to a polydisperse set of particles to show the validity of a single-particle approach when the modeled radius is proportional to the total volume-to-surface-area ratio of the system.
The understanding and control of charge carrier interactions with defects at buried insulator/semiconductor interfaces is essential for achieving optimum performance in modern electronics. Here, we report on the use of scanning ultrafast electron microscopy (SUEM) to remotely probe the dynamics of excited carriers at a Si surface buried below a thick thermal oxide. Our measurements illustrate a previously unidentified SUEM contrast mechanism, whereby optical modulation of the space-charge field in the semiconductor modulates the electric field in the thick oxide, thus affecting its secondary electron yield. By analyzing the SUEM contrast as a function of time and laser fluence we demonstrate the diffusion mediated capture of excited carriers by interfacial traps.
This project aimed to identify the performance-limiting mechanisms in mid- to far infrared (IR) sensors by probing photogenerated free carrier dynamics in model detector materials using scanning ultrafast electron microscopy (SUEM). SUEM is a recently developed method based on using ultrafast electron pulses in combination with optical excitations in a pump- probe configuration to examine charge dynamics with high spatial and temporal resolution and without the need for microfabrication. Five material systems were examined using SUEM in this project: polycrystalline lead zirconium titanate (a pyroelectric), polycrystalline vanadium dioxide (a bolometric material), GaAs (near IR), InAs (mid IR), and Si/SiO 2 system as a prototypical system for interface charge dynamics. The report provides detailed results for the Si/SiO 2 and the lead zirconium titanate systems.
Automated vehicles (AV) hold great promise for improving safety, as well as reducing congestion and emissions. In order to make automated vehicles commercially viable, a reliable and highperformance vehicle-based computing platform that meets ever-increasing computational demands will be key. Given the state of existing digital computing technology, designers will face significant challenges in meeting the needs of highly automated vehicles without exceeding thermal constraints or consuming a large portion of the energy available on vehicles, thus reducing range between charges or refills. The accompanying increases in energy for AV use will place increased demand on energy production and distribution infrastructure, which also motivates increasing computational energy efficiency.
Understanding the impact of high-energy electron radiation on device characteristics remains critical for the expanding use of semiconductor electronics in space-borne applications and other radiation harsh environments. Here, we report on in situ measurements of high-energy electron radiation effects on the hole diffusion length in low threading dislocation density homoepitaxial bulk n-GaN Schottky diodes using electron beam induced current (EBIC) in high-voltage scanning electron microscopy mode. Despite the large interaction volume in this system, quantitative EBIC imaging is possible due to the sustained collimation of the incident electron beam. This approach enables direct measurement of electron radiation effects without having to thin the specimen. Using a combination of experimental EBIC measurements and Monte Carlo simulations of electron trajectories, we determine a hole diffusion length of 264 ± 11 nm for n-GaN. Irradiation with 200 kV electron beam with an accumulated dose of 24 × 1016 electrons cm−2 led to an approximate 35% decrease in the minority carrier diffusion length.
Advanced GaN power devices are promising for many applications in high power electronics but performance limitations due to material quality in etched-and-regrown junctions prevent their widespread use. Carrier diffusion length is a critical parameter that not only determines device performance but is also a diagnostic of material quality. Here we present the use of electron-beam induced current to measure carrier diffusion lengths in continuously grown and etched-and-regrown GaN pin diodes as models for interfaces in more complex devices. Variations in the quality of the etched-and-regrown junctions are observed and shown to be due to the degradation of the n-type material. We observe an etched-and-regrown junction with properties comparable to a continuously grown junction.
The rapidly increasing use of electronics in high-radiation environments and the continued evolution in transistor architectures and materials demand improved methods to characterize the potential damaging effects of radiation on device performance. Here, electron-beam-induced current is used to map hot-carrier transport in model metal-oxide semiconductor field-effect transistors irradiated with a 300 KeV focused He+ beam as a localized line spanning across the gate and bulk Si. By correlating the damage to the electronic properties and combining these results with simulations, the contribution of spatially localized radiation damage on the device characteristics is obtained. This identified damage, caused by the He+ beam, is attributed to localized interfacial Pb centers and delocalized positive fixed-charges, as surmised from simulations. Comprehension of the long-term interaction and mobility of radiation-induced damage are key for future design of rad-hard devices.
Liquid organic hydrogen carriers such as alcohols and polyols are a high-capacity means of transporting and reversibly storing hydrogen that demands effective catalysts to drive the (de)hydrogenation reactions under mild conditions. We employed a combined theory/experiment approach to develop MOF-74 catalysts for alcohol dehydrogenation and examine the performance of the open metal sites (OMS), which have properties analogous to the active sites in high-performance single-site catalysts and homogeneous catalysts. Methanol dehydrogenation was used as a model reaction system for assessing the performance of five monometallic M-MOF-74 variants (M = Co, Cu, Mg, Mn, Ni). Co-MOF-74 and Ni-MOF-74 give the highest H2 productivity. However, Ni-MOF-74 is unstable under reaction conditions and forms metallic nickel particles. To improve catalyst activity and stability, bimetallic (NixMg1-x)-MOF-74 catalysts were developed that stabilize the Ni OMS and promote the dehydrogenation reaction. An optimal composition exists at (Ni0.32Mg0.68)-MOF-74 that gives the greatest H2 productivity, up to 203 mL gcat-1 min-1 at 300 °C, and maintains 100% selectivity to CO and H2 between 225-275 °C. The optimized catalyst is also active for the dehydrogenation of other alcohols. DFT calculations reveal that synergistic interactions between the open metal site and the organic linker lead to lower reaction barriers in the MOF catalysts compared to the open metal site alone. This work expands the suite of hydrogen-related reactions catalyzed by MOF-74 which includes recent work on hydroformulation and our earlier reports of aryl-ether hydrogenolysis. Moreover, it highlights the use of bimetallic frameworks as an effective strategy for stabilizing a high density of catalytically active open metal sites. This journal is
We evaluate the sensitivity of neuromorphic inference accelerators based on silicon-oxide-nitride-oxide-silicon (SONOS) charge trap memory arrays to total ionizing dose (TID) effects. Data retention statistics were collected for 16 Mbit of 40-nm SONOS digital memory exposed to ionizing radiation from a Co-60 source, showing good retention of the bits up to the maximum dose of 500 krad(Si). Using this data, we formulate a rate-equation-based model for the TID response of trapped charge carriers in the ONO stack and predict the effect of TID on intermediate device states between 'program' and 'erase.' This model is then used to simulate arrays of low-power, analog SONOS devices that store 8-bit neural network weights and support in situ matrix-vector multiplication. We evaluate the accuracy of the irradiated SONOS-based inference accelerator on two image recognition tasks - CIFAR-10 and the challenging ImageNet data set - using state-of-the-art convolutional neural networks, such as ResNet-50. We find that across the data sets and neural networks evaluated, the accelerator tolerates a maximum TID between 10 and 100 krad(Si), with deeper networks being more susceptible to accuracy losses due to TID.
Bulk 14-nm FinFET technology was irradiated in a heavy-ion environment (42-MeV Si ions) to study the possibility of displacement damage (DD) in scaled technology devices, resulting in drive current degradation with increased cumulative fluence. These devices were also exposed to an electron beam, proton beam, and cobalt-60 source (gamma radiation) to further elucidate the physics of the device response. Annealing measurements show minimal to no 'rebound' in the ON-state current back to its initial high value; however, the OFF-state current 'rebound' was significant for gamma radiation environments. Low-temperature experiments of the heavy-ion-irradiated devices reveal increased defect concentration as the result for mobility degradation with increased fluence. Furthermore, the subthreshold slope (SS) temperature dependence uncovers a possible mechanism of increased defect bulk traps contributing to tunneling at low temperatures. Simulation work in Silvaco technology computer-aided design (TCAD) suggests that the increased OFF-state current is a total ionizing dose (TID) effect due to oxide traps in the shallow trench isolation (STI). The significant SS elongation and ON-state current degradation could only be produced when bulk traps in the channel were added. Heavy-ion irradiation on bulk 14-nm FinFETs was found to be a combination of TID and DD effects.
In-memory computing based on non-volatile resistive memory can significantly improve the energy efficiency of artificial neural networks. However, accurate in situ training has been challenging due to the nonlinear and stochastic switching of the resistive memory elements. One promising analog memory is the electrochemical random-access memory (ECRAM), also known as the redox transistor. Its low write currents and linear switching properties across hundreds of analog states enable accurate and massively parallel updates of a full crossbar array, which yield rapid and energy-efficient training. While simulations predict that ECRAM based neural networks achieve high training accuracy at significantly higher energy efficiency than digital implementations, these predictions have not been experimentally achieved. In this work, we train a 3 × 3 array of ECRAM devices that learns to discriminate several elementary logic gates (AND, OR, NAND). We record the evolution of the network’s synaptic weights during parallel in situ (on-line) training, with outer product updates. Due to linear and reproducible device switching characteristics, our crossbar simulations not only accurately simulate the epochs to convergence, but also quantitatively capture the evolution of weights in individual devices. The implementation of the first in situ parallel training together with strong agreement with simulation results provides a significant advance toward developing ECRAM into larger crossbar arrays for artificial neural network accelerators, which could enable orders of magnitude improvements in energy efficiency of deep neural networks.
The III-nitride semiconductors have many attractive properties for field-emission vacuum electronics, including high thermal and chemical stability, low electron affinity, and high breakdown fields. Here, we report top-down fabricated gallium nitride (GaN)-based nanoscale vacuum electron diodes operable in air, with record ultralow turn-on voltages down to ∼0.24 V and stable high field-emission currents, tested up to several microamps for single-emitter devices. We leverage a scalable, top-down GaN nanofabrication method leading to damage-free and smooth surfaces. Gap-dependent and pressure-dependent studies provide new insights into the design of future, integrated nanogap vacuum electron devices. The results show promise for a new class of high-performance and robust, on-chip, III-nitride-based vacuum nanoelectronics operable in air or reduced vacuum.
Digital computing is nearing its physical limits as computing needs and energy consumption rapidly increase. Analogue-memory-based neuromorphic computing can be orders of magnitude more energy efficient at data-intensive tasks like deep neural networks, but has been limited by the inaccurate and unpredictable switching of analogue resistive memory. Filamentary resistive random access memory (RRAM) suffers from stochastic switching due to the random kinetic motion of discrete defects in the nanometer-sized filament. In this work, this stochasticity is overcome by incorporating a solid electrolyte interlayer, in this case, yttria-stabilized zirconia (YSZ), toward eliminating filaments. Filament-free, bulk-RRAM cells instead store analogue states using the bulk point defect concentration, yielding predictable switching because the statistical ensemble behavior of oxygen vacancy defects is deterministic even when individual defects are stochastic. Both experiments and modeling show bulk-RRAM devices using TiO2-X switching layers and YSZ electrolytes yield deterministic and linear analogue switching for efficient inference and training. Bulk-RRAM solves many outstanding issues with memristor unpredictability that have inhibited commercialization, and can, therefore, enable unprecedented new applications for energy-efficient neuromorphic computing. Beyond RRAM, this work shows how harnessing bulk point defects in ionic materials can be used to engineer deterministic nanoelectronic materials and devices.
Ashby, David; Choi, Christopher S.; Edwards, Martin A.; Talin, A.A.; White, Henry S.; Dunn, Bruce S.
It is well established that the miniaturization of batteries has not kept pace with the miniaturization of electronics. Three-dimensional (3D) batteries, which were developed with the intent of improving microbattery performance, have had limited success because of fabrication challenges and material constraints. Solid-state, 3D batteries have been particularly susceptible to these shortcomings. In this paper, we demonstrate that the incorporation of a high-conductivity, solid electrolyte is the key to achieving a nonplanar solid-state battery with high areal capacity and high power density. The model 2.5D platform used in this study is a modification of the more typical 3D configuration in that it is comprised of a cathode array of pillars (3D) and a planar (two-dimensional, 2D) anode. This 2.5D geometry exploits the use of a high-conductivity, ionogel electrolyte (10-3 S cm-1), which interpenetrates the 3D electrode array. The 2.5D battery offers high areal energy densities from the post array, while the high-conductivity, solid electrolyte enables high power densities (3.7 mWh cm-2 at 2.8 mW cm-2). The reported solid-state 2.5D device exceeds the energy and power densities of any 3D solid-state system and the derived multiphysics model provides guidance for achieving significantly higher energy and power densities.
Materials exhibiting metal-to-insulator transitions (MITs) could enable low power neuromorphic computing, but progress is hindered by insufficient mechanistic understanding. In this issue of Matter, Banerjee and colleagues describe with intricate detail a new MIT mechanism in β′-CuxV2O5, with potential applications to neuromorphic computing. Materials exhibiting metal-to-insulator transitions (MITs) could enable low power neuromorphic computing, but progress is hindered by insufficient mechanistic understanding. In this issue of Matter, Banerjee and colleagues describe with intricate detail a new MIT mechanism in β′-CuxV2O5, with potential applications to neuromorphic computing.
Terahertz (THz) technology has shown promise for several applications, but limitations in sources and detectors have prevented broader adoption. Existing THz detectors are rigid, planar, and fabricated using complex technology, making it difficult to integrate into systems. Here we demonstrate THz detectors fabricated by inkjet printing on submicrometer thick, ultraflexible substrates. By developing p- and n-type carbon nanotube inks, we achieve optically thick p–n junction and p-type devices, enabling antenna-free pixels for THz imaging. By further designing and folding the printed devices, we realize origami-inspired architectures with improved performance over single devices, achieving a noise-equivalent power of 12 nW/Hz1/2 at room temperature with no voltage bias. Our approach opens avenues for nonplanar, foldable, deployable, insertable, and retractable THz detectors for applications in nondestructive inspection.
The mechanical degradation of all-solid-state Li-ion batteries (ASSLBs) is expected to be more severe than that in traditional Li-ion batteries with liquid electrolytes due to the additional mechanical constraints imposed by the solid electrolyte on the deformation of electrodes. Cracks and fractures could occur both inside the solid electrolyte (SE) and at the SE/electrode interfconce. A coupled electrochemical-mechanical model was developed and solved by the Finite Element Method (FEM) to evaluate the stress development in ASSLBs. Two sources of volume change were considered, namely the expansion/shrinkage of electrodes due to lithium concentration change and the interphase formation at the SE/electrode interface due to the decomposition of SEs. The most plausible solid electrolyte decomposition reactions and their associated volume change were predicted by density functional theory (DFT) calculations. It was found that the stress associated with a volume change due to solid electrolyte decomposition can be much more significant than that of electrode volumetric changes associated with Li insertion/extraction. This model can be used to design 3D ASSLB architectures to minimize their internal stress generation.
Plasmonic antennas and metasurfaces can effectively control light-matter interactions, and this facilitates a deterministic design of optical materials properties, including structural color. However, these optical properties are generally fixed after synthesis and fabrication, while many modern-day optics applications require active, low-power, and nonvolatile tuning. These needs have spurred broad research activities aimed at identifying materials and resonant structures capable of achieving large, dynamic changes in optical properties, especially in the challenging visible spectral range. In this work, we demonstrate dynamic tuning of polarization-dependent gap plasmon resonators that contain the electrochromic oxide WO3. Its refractive index in the visible changes continuously from n = 2.1 to 1.9 upon electrochemical lithium insertion and removal in a solid-state device. By incorporating WO3 into a gap plasmon resonator, the resonant wavelength can be shifted continuously and reversibly by up to 58 nm with less than 2 V electrochemical bias voltage. The resonator can remain in a tuned state for tens of minutes under open circuit conditions.
Efficiency bottlenecks inherent to conventional computing in executing neural algorithms have spurred the development of novel devices capable of 'in-memory' computing. Commonly known as 'memristors,' a variety of device concepts including conducting bridge, vacancy filament, phase change, and other types have been proposed as promising elements in artificial neural networks for executing inference and learning algorithms. In this article, we review the recent advances in memristor technology for neuromorphic computing and discuss strategies for addressing the most significant performance challenges, including nonlinearity, high read/write currents, and endurance. As an alternative to two-terminal memristors, we introduce the three-terminal electrochemical memory based on the redox transistor (RT), which uses a gate to tune the redox state of the channel. Decoupling the 'read' and 'write' operations using a third terminal and storage of information as a charge-compensated redox reaction in the bulk of the transistor enables high-density information storage. These properties enable low-energy operation without compromising analog performance and nonvolatility. We discuss the RT operating mechanisms using organic and inorganic materials, approaches for array integration, and prospects for achieving the device density and switching speeds necessary to make electrochemical memory competitive with established digital technology.
Neuromorphic computers based on analogue neural networks aim to substantially lower computing power by reducing the need to shuttle data between memory and logic units. Artificial synapses containing nonvolatile analogue conductance states enable direct computation using memory elements; however, most nonvolatile analogue memories require high write voltages and large current densities and are accompanied by nonlinear and unpredictable weight updates. Here, we develop an inorganic redox transistor based on electrochemical lithium-ion insertion into LiXTiO2 that displays linear weight updates at both low current densities and low write voltages. The write voltage, as low as 200 mV at room temperature, is achieved by minimizing the open-circuit voltage and using a low-voltage diffusive memristor selector. We further show that the LiXTiO2 redox transistor can achieve an extremely sharp transistor subthreshold slope of just 40 mV/decade when operating in an electrochemically driven phase transformation regime.
Analog crossbars have the potential to reduce the energy and latency required to train a neural network by three orders of magnitude when compared to an optimized digital ASIC. The crossbar simulator, CrossSim, can be used to model device nonidealities and determine what device properties are needed to create an accurate neural network accelerator. Experimentally measured device statistics are used to simulate neural network training accuracy and compare different classes of devices including TaOx ReRAM, Lir-Co-Oz devices, and conventional floating gate SONOS memories. A technique called 'Periodic Carry' can overcomes device nonidealities by using a positional number system while maintaining the benefit of parallel analog matrix operations.
With low-cost and simple processing, organic electrochromic polymers have attracted considerable attention as a promising material platform for flexible and low-energy-consuming optoelectronic devices. However, typical electrochromic polymers can only be switched from natural-colored to oxidized-transparent states. As a result, the complexity of combining several distinct polymers to achieve a full-color gamut has significantly limited the niche applications of electrochromic polymers. Here in this paper we report an electrochromic polymer based on 4,7-di((3,3-dimethyl-3,4-dihydro-2H-thieno[3,4-b][1,4]dioxepine-3-yl)-3,4-ethylenedioxythiophene) (PEP), which exhibits fast full-color reversible tuning capability and good stability. Furthermore, a red-green-blue flexible electrochromic device just based on poly(PEP) was fabricated, which offers an effective approach to dynamically manipulate color and enables a variety of optoelectronic applications.
Neuromorphic computers could overcome efficiency bottlenecks inherent to conventional computing through parallel programming and readout of artificial neural network weights in a crossbar memory array. However, selective and linear weight updates and <10-nanoampere read currents are required for learning that surpasses conventional computing efficiency. We introduce an ionic floating-gate memory array based on a polymer redox transistor connected to a conductive-bridge memory (CBM). Selective and linear programming of a redox transistor array is executed in parallel by overcoming the bridging threshold voltage of the CBMs. Synaptic weight readout with currents <10 nanoamperes is achieved by diluting the conductive polymer with an insulator to decrease the conductance. The redox transistors endure >1 billion write-read operations and support >1-megahertz write-read frequencies.
HKUST-1 or Cu3BTC2 (BTC = 1,3,5-benzenetricarboxylate) is a prototypical metal-organic framework (MOF) that holds a privileged position among MOFs for device applications, as it can be deposited as thin films on various substrates and surfaces. Recently, new potential applications in electronics have emerged for this material when HKUST-1 was demonstrated to become electrically conductive upon infiltration with 7,7,8,8-tetracyanoquinodimethane (TCNQ). However, the factors that control the morphology and reactivity of the thin films are unknown. Here, we present a study of the thin-film growth process on indium tin oxide and amorphous Si prior to infiltration. From the unusual bimodal, non-log-normal distribution of crystal domain sizes, we conclude that the nucleation of new layers of Cu3BTC2 is greatly enhanced by surface defects and thus difficult to control. We then show that these films can react with methanolic TCNQ solutions to form dense films of the coordination polymer Cu(TCNQ). This chemical conversion is accompanied by dramatic changes in surface morphology, from a surface dominated by truncated octahedra to randomly oriented thin platelets. The change in morphology suggests that the chemical reaction occurs in the liquid phase and is independent of the starting surface morphology. The chemical transformation is accompanied by 10 orders of magnitude change in electrical conductivity, from <10-11 S/cm for the parent Cu3BTC2 material to 10-1 S/cm for the resulting Cu(TCNQ) film. The conversion of Cu3BTC2 films, which can be grown and patterned on a variety of (nonplanar) substrates, to Cu(TCNQ) opens the door for the facile fabrication of more complex electronic devices.
Electronic synaptic devices are important building blocks for neuromorphic computational systems that can go beyond the constraints of von Neumann architecture. Although two-terminal memristive devices are demonstrated to be possible candidates, they suffer from several shortcomings related to the filament formation mechanism including nonlinear switching, write noise, and high device conductance, all of which limit the accuracy and energy efficiency. Electrochemical three-terminal transistors, in which the channel conductance can be tuned without filament formation provide an alternative platform for synaptic electronics. Here, an all-solid-state electrochemical transistor made with Li ion–based solid dielectric and 2D α-phase molybdenum oxide (α-MoO3) nanosheets as the channel is demonstrated. These devices achieve nonvolatile conductance modulation in an ultralow conductance regime (<75 nS) by reversible intercalation of Li ions into the α-MoO3 lattice. Based on this operating mechanism, the essential functionalities of synapses, such as short- and long-term synaptic plasticity and bidirectional near-linear analog weight update are demonstrated. Simulations using the handwritten digit data sets demonstrate high recognition accuracy (94.1%) of the synaptic transistor arrays. These results provide an insight into the application of 2D oxides for large-scale, energy-efficient neuromorphic computing networks.
Because of their extraordinary surface areas and tailorable porosity, metal-organic frameworks (MOFs) have the potential to be excellent sensors of gas-phase analytes. MOFs with open metal sites are particularly attractive for detecting Lewis basic atmospheric analytes, such as water. Here, we demonstrate that thin films of the MOF HKUST-1 can be used to quantitatively determine the relative humidity (RH) of air using a colorimetric approach. HKUST-1 thin films are spin-coated onto rigid or flexible substrates and are shown to quantitatively determine the RH within the range of 0.1-5% RH by either visual observation or a straightforward optical reflectivity measurement. At high humidity (>10% RH), a polymer/MOF bilayer is used to slow the transport of H2O to the MOF film, enabling quantitative determination of RH using time as the distinguishing metric. Finally, the sensor is combined with an inexpensive light-emitting diode light source and Si photodiode detector to demonstrate a quantitative humidity detector for low humidity environments.
Detailed understanding of solid–solid interface structure–function relationships is critical for the improvement and wide deployment of all-solid-state batteries. The interfaces between lithium phosphorous oxynitride (LiPON) solid electrolyte material and lithium metal anode, and between LiPON and LixCoO2 cathode, have been reported to generate solid–electrolyte interphase (SEI)-like products and/or disordered regions. Using electronic structure calculations and crystalline LiPON models, we predict that LiPON models with purely P−N−P backbones are kinetically inert towards lithium at room temperature. In contrast, transfer of oxygen atoms from low-energy LixCoO2(104) surfaces to LiPON is much faster under ambient conditions. The mechanisms of the primary reaction steps, LiPON structural motifs that readily reacts with lithium metal, experimental results on amorphous LiPON to partially corroborate these predictions, and possible mitigation strategies to reduce degradations are discussed. LiPON interfaces are found to be useful case studies for highlighting the importance of kinetics-controlled processes during battery assembly at moderate processing temperatures.
Pearse, Alexander; Schmitt, Thomas; Sahadeo, Emily; Stewart, David M.; Kozen, Alexander; Gerasopoulos, Konstantinos; Talin, A.A.; Lee, Sang B.; Rubloff, Gary W.; Gregorczyk, Keith E.
Three-dimensional thin-film solid-state batteries (3D TSSB) were proposed by Long et al. in 2004 as a structure-based approach to simultaneously increase energy and power densities. Here, we report experimental realization of fully conformal 3D TSSBs, demonstrating the simultaneous power-and-energy benefits of 3D structuring. All active battery components - electrodes, solid electrolyte, and current collectors - were deposited by atomic layer deposition (ALD) onto standard CMOS processable silicon wafers microfabricated to form arrays of deep pores with aspect ratios up to approximately 10. The cells utilize an electrochemically prelithiated LiV2O5 cathode, a very thin (40-100 nm) Li2PO2N solid electrolyte, and a SnNx anode. The fabrication process occurs entirely at or below 250 °C, promising compatibility with a variety of substrates as well as integrated circuits. The multilayer battery structure enabled all-ALD solid-state cells to deliver 37 μAh/cm2·μm (normalized to cathode thickness) with only 0.02% per-cycle capacity loss. Conformal fabrication of full cells over 3D substrates increased the areal discharge capacity by an order of magnitude while simulteneously improving power performance, a trend consistent with a finite element model. This work shows that the exceptional conformality of ALD, combined with conventional semiconductor fabrication methods, provides an avenue for the successful realization of long-sought 3D TSSBs which provide power performance scaling in regimes inaccessible to planar form factor cells.
Neuromorphic devices are becoming increasingly appealing as efficient emulators of neural networks used to model real world problems. However, no hardware to date has demonstrated the necessary high accuracy and energy efficiency gain over CMOS in both (1) training via backpropagation and (2) in read via vector matrix multiplication. Such shortcomings are due to device non-idealities, particularly asymmetric conductance tuning in response to uniform voltage pulse inputs. Here, by formulating a general circuit model for capacitive ion-exchange neuromorphic devices, we show that asymmetric nonlinearity in organic electrochemical neuromorphic devices (ENODes) can be suppressed by an appropriately chosen write scheme. Simulations based upon our model suggest that a nonlinear write-selector could reduce the switching voltage and energy, enabling analog tuning via a continuous set of resistance states (100 states) with extremely low switching energy (∼170 fJ • μm-2). This work clarifies the pathway to neural algorithm accelerators capable of parallelism during both read and write operations.
Stewart, David M.; Pearse, Alexander J.; Kim, Nam S.; Fuller, Elliot J.; Talin, A.A.; Gregorczyk, Keith; Lee, Sang B.; Rubloff, Gary W.
Major advances in thin-film solid-state batteries (TFSSBs) may capitalize on 3D structuring using high-aspect-ratio substrates such as nanoscale pits, pores, trenches, flexible polymers, and textiles. This will require conformal processes such as atomic layer deposition (ALD) for every active functional component of the battery. Here we explore the deposition and electrochemical properties of SnO2, SnNy, and SnOxNy thin films as TFSSB anode materials, grown by ALD using tetrakisdimethylamido(tin), H2O, and N2 plasma as precursors. By controlling the dose ratio between H2O and N2, the N-O fraction can be tuned between 0% N and 95% N. The electrochemical properties of these materials were tested across a composition range varying from pure SnO2, to SnON intermediates, and pure SnNy. In TFSSBs, the SnNy anodes are found to be more stable during cycling than the SnO2 or SnOxNy films, with an initial reversible capacity beyond that of Li-Sn alloying, retaining 75% of their capacity over 200 cycles compared to only 50% for SnO2. Furthermore, the performance of the SnOxNy anodes indicates that SnNy anodes should not be negatively impacted by small levels of O contamination.
Li metal is the preferred anode material for all-solid-state Li batteries. However, a stable plating and stripping of Li metal at the anode-solid electrolyte interface remains a significant challenge particularly at practically feasible current densities. This problem usually relates to high and/or inhomogeneous Li-electrode-electrolyte interfacial impedance and formation and growth of high-aspect-ratio dendritic Li deposits at the electrode-electrolyte interface, which eventually shunt the battery. To better understand details of Li metal plating, we use operando electron microscopy and Auger spectroscopy to probe nucleation, growth, and stripping of Li metal during cycling of a model solid-state Li battery as a function of current density and oxygen pressure. We find a linear correlation between the nucleation density of Li clusters and the charging rate in an ultrahigh vacuum, which agrees with a classical nucleation and growth model. Moreover, the trace amount of oxidizing gas (≈10-6 Pa of O2) promotes the Li growth in a form of nanowires due to a fine balance between the ion current density and a growth rate of a thin lithium-oxide shell on the surface of the metallic Li. Interestingly, increasing the partial pressure of O2 to 10-5 Pa resumes Li plating in a form of 3D particles. Our results demonstrate the importance of trace amounts of preexisting or ambient oxidizing species on lithiation processes in solid-state batteries.
The family of three-dimensional topological insulators opens new avenues to discover novel photophysics and to develop novel types of photodetectors. ZrTe5 has been shown to be a Dirac semimetal possessing unique topological, electronic, and optical properties. Here, we present spatially resolved photocurrent measurements on devices made of nanoplatelets of ZrTe5, demonstrating the photothermoelectric origin of the photoresponse. Because of the high electrical conductivity and good Seebeck coefficient, we obtain noise-equivalent powers as low as 42 pW/Hz1/2, at room temperature for visible light illumination, at zero bias. We also show that these devices suffer from significant ambient reactivity, such as the formation of a Te-rich surface region driven by Zr oxidation as well as severe reactions with the metal contacts. This reactivity results in significant stresses in the devices, leading to unusual geometries that are useful for gaining insight into the photocurrent mechanisms. Our results indicate that both the large photothermoelectric response and reactivity must be considered when designing or interpreting photocurrent measurements in these systems.
The atomic force microscope (AFM) offers a rich observation window on the nanoscale, yet many dynamic phenomena are too fast and too weak for direct AFM detection. Integrated cavity-optomechanics is revolutionizing micromechanical sensing; however, it has not yet impacted AFM. Here, we make a groundbreaking advance by fabricating picogram-scale probes integrated with photonic resonators to realize functional AFM detection that achieve high temporal resolution (<10 ns) and picometer vertical displacement uncertainty simultaneously. The ability to capture fast events with high precision is leveraged to measure the thermal conductivity (η), for the first time, concurrently with chemical composition at the nanoscale in photothermal induced resonance experiments. The intrinsic η of metal-organic-framework individual microcrystals, not measurable by macroscale techniques, is obtained with a small measurement uncertainty (8%). The improved sensitivity (50×) increases the measurement throughput 2500-fold and enables chemical composition measurement of molecular monolayer-thin samples. Our paradigm-shifting photonic readout for small probes breaks the common trade-off between AFM measurement precision and ability to capture transient events, thus transforming the ability to observe nanoscale dynamics in materials.
Metal organic frameworks (MOFs) are extended, nanoporous crystalline compounds consisting of metal ions interconnected by organic ligands. Their synthetic versatility suggest a disruptive class of opto - electronic materials with a high degree of electrical tunability and without the property - degrading disorder of organic conductors. In this project we determined the factors controlling charge and energy transport in MOFs and evaluated their potential for thermoelectric energy conversion. Two strategies for a chieving electronic conductivity in MOFs were explored: 1) using redox active 'guest' molecules introduced into the pores to dope the framework via charge - transfer coupling (Guest@MOF), 2) metal organic graphene analogs (MOGs) with dispersive band structur es arising from strong electronic overlap between the MOG metal ions and its coordinating linker groups. Inkjet deposition methods were developed to facilitate integration of the guest@MOF and MOG materials into practical devices.
Metal organic frameworks (MOFs) have recently attracted great attentions for the thermoelectric (TE) applications, owing to their intrinsic low thermal conductivity, but their TE efficiencies are still low due to the poor electronic transport properties. Here, various synthetic strategies have been designed to optimize the electronic properties of MOFs. Using a series of first principle calculations and band theory, we explore the effect of structural topology and redox matching between the metal and coordinated atoms on the TE transport properties. In conclusion, the presented results provide a fundamental guidance for optimizing electronic charge transport of existing MOFs, and for designing yet to be discovered conductive MOFs for thermoelectric applications.
Analog resistive memories promise to reduce the energy of neural networks by orders of magnitude. However, the write variability and write nonlinearity of current devices prevent neural networks from training to high accuracy. We present a novel periodic carry method that uses a positional number system to overcome this while maintaining the benefit of parallel analog matrix operations. We demonstrate how noisy, nonlinear TaOx devices that could only train to 80% accuracy on MNIST, can now reach 97% accuracy, only 1% away from an ideal numeric accuracy of 98%. On a file type dataset, the TaOx devices achieve ideal numeric accuracy. In addition, low noise, linear Li1-xCoO2 devices train to ideal numeric accuracies using periodic carry on both datasets.
Devices based on GaN have shown great promise for high power electronics, including their potential use as radiation tolerant components. An important step to realizing high power diodes is the design and implementation of an edge termination tomitigate field crowding, which can lead to premature breakdown. However, little is known about the effects of radiation on edge termination functionality. We experimentally examine the effects of proton irradiation on multiple field ring edge terminations in high power vertical GaN PIN diodes using in operando imaging with electron beam induced current (EBIC). We find that exposure to proton irradiation influences field spreading in the edge termination as well as carrier transport near the anode. By using depth-dependent EBIC measurements of hole diffusion length in homoepitaxial n-GaN we demonstrate that the carrier transport effect is due to a reduction in hole diffusion length following proton irradiation.
Several active areas of research in novel energy storage technologies, including three-dimensional solid state batteries and passivation coatings for reactive battery electrode components, require conformal solid state electrolytes. We describe an atypical atomic layer deposition (ALD) process for a member of the lithium phosphorus oxynitride (LiPON) family, which is employed as a thin film lithium-conducting solid electrolyte. The reaction between lithium tert-butoxide (LiOtBu) and diethyl phosphoramidate (DEPA) produces conformal, ionically conductive thin films with a stoichiometry close to Li2PO2N between 250 and 300 °C. Unusually, the P/N ratio of the films is always 1, indicative of a particular polymorph of LiPON that closely resembles a polyphosphazene. Films grown at 300 °C have an ionic conductivity of (6.51 ± 0.36) × 10-7 S/cm at 35 °C and are functionally electrochemically stable in the window from 0 to 5.3 V versus Li/Li+. We demonstrate the viability of the ALD-grown electrolyte by integrating it into full solid state batteries, including thin film devices using LiCoO2 as the cathode and Si as the anode operating at up to 1 mA/cm2. The high quality of the ALD growth process allows pinhole-free deposition even on rough crystalline surfaces, and we demonstrate the successful fabrication and operation of thin film batteries with ultrathin (<100 nm) solid state electrolytes. Finally, we show an additional application of the moderate-temperature ALD process by demonstrating a flexible solid state battery fabricated on a polymer substrate.
The brain is capable of massively parallel information processing while consuming only ~1-100 fJ per synaptic event1,2. Inspired by the efficiency of the brain, CMOS-based neural architectures3 and memristors4,5 are being developed for pattern recognition and machine learning. However, the volatility, design complexity and high supply voltages for CMOS architectures, and the stochastic and energy-costly switching of memristors complicate the path to achieve the interconnectivity, information density, and energy efficiency of the brain using either approach. Here we describe an electrochemical neuromorphic organic device (ENODe) operating with a fundamentally different mechanism from existing memristors. ENODeswitches at lowvoltage and energy (<10 pJ for 103 μm2 devices), displays >500 distinct, non-volatile conductance states within a~1V range, and achieves high classification accuracy when implemented in neural network simulations. Plastic ENODes are also fabricated on flexible substrates enabling the integration of neuromorphic functionality in stretchable electronic systems6,7. Mechanical flexibility makes ENODes compatible with three-dimensional architectures, opening a path towards extreme interconnectivity comparable to the human brain.
The insertion/extraction of lithium into/from various host materials is the basic process by which lithium-ion batteries reversible store charge. This process is generally accompanied by strain in the host material, inducing stress which can lead to capacity loss. Therefore, understanding of both the structural changes and the associated stress – investigated almost exclusively separate to date – is a critical factor for developing high-performance batteries. Here, we report an in situ method, which utilizes Raman spectroscopy in parallel with optical interferometry to study effects of varying charging rates (C-rates) on the structure and stress in a V2O5 thin film cathode. Abrupt stress changes at specific crystal phase transitions in the Li[sbnd]V[sbnd]O system are observed and the magnitude of the stress changes with the amount of lithium inserted into the electrode are correlated. A linear increase in the stress as a function of x in LixV2O5 is observed, indicating that C-rate does not directly contribute to larger intercalation stress. However, a more rapid increase in disorder within the LixV2O5 layers is correlated with higher C-rate. Ultimately, these experiments demonstrate how the simultaneous stress/Raman in situ approach can be utilized as a characterization platform for investigating various critical factors affecting lithium-ion battery performance.
Demonstration of three-dimensional all-solid-state Li-ion batteries (3D SSLIBs) has been a long-standing goal for numerous researchers in the battery community interested in developing high power and high areal energy density storage solutions for a variety of applications. Ideally, the 3D geometry maximizes the volume of active material per unit area, while keeping its thickness small to allow for fast Li diffusion. In this paper, we describe experimental testing and simulation of 3D SSLIBs fabricated using materials and thin-film deposition methods compatible with semiconductor device processing. These 3D SSLIBs consist of Si microcolumns onto which the battery layers are sequentially deposited using physical vapor deposition. The power performance of the 3D SSLIBs lags significantly behind that of similarly prepared planar SSLIBs. Analysis of the experimental results using finite element modeling indicates that the origin of the poor power performance is the structural inhomogeneity of the 3D SSLIB, coupled with low electrolyte ionic conductivity and diffusion rate in the cathode, which lead to highly nonuniform internal current density distribution and poor cathode utilization.
Modern semiconductor devices rely on the transport of minority charge carriers. Direct examination of minority carrier lifetimes in real devices with nanometer-scale features requires a measurement method with simultaneously high spatial and temporal resolutions. Achieving nanometer spatial resolutions at sub-nanosecond temporal resolution is possible with pump-probe methods that utilize electrons as probes. Recently, a stroboscopic scanning electron microscope was developed at Caltech, and used to study carrier transport across a Si p-n junction [ 1 , 2 , 3 ] . In this report, we detail our development of a prototype scanning ultrafast electron microscope system at Sandia National Laboratories based on the original Caltech design. This effort represents Sandia's first exploration into ultrafast electron microscopy.
Motivated by low cost, low toxicity, mechanical flexibility, and conformability over complex shapes, organic semiconductors are currently being actively investigated as thermoelectric (TE) materials to replace the costly, brittle, and non-eco-friendly inorganic TEs for near-ambient-temperature applications. Metal-organic frameworks (MOFs) share many of the attractive features of organic polymers, including solution processability and low thermal conductivity. A potential advantage of MOFs and MOFs with guest molecules (Guest@MOFs) is their synthetic and structural versatility, which allows both the electronic and geometric structure to be tuned through the choice of metal, ligand, and guest molecules. This could solve the long-standing challenge of finding stable, high-TE-performance n-type organic semiconductors, as well as promote high charge mobility via the long-range crystalline order inherent in these materials. In this article, we review recent advances in the synthesis of MOF and Guest@MOF TEs and discuss how the Seebeck coefficient, electrical conductivity, and thermal conductivity could be tuned to further optimize TE performance.
Control of electric fields with edge terminations is critical to maximize the performance of high-power electronic devices. While a variety of edge termination designs have been proposed, the optimization of such designs is challenging due to many parameters that impact their effectiveness. While modeling has recently allowed new insight into the detailed workings of edge terminations, the experimental verification of the design effectiveness is usually done through indirect means, such as the impact on breakdown voltages. In this letter, we use scanning photocurrent microscopy to spatially map the electric fields in vertical GaN p-n junction diodes in operando. We reveal the complex behavior of seemingly simple edge termination designs, and show how the device breakdown voltage correlates with the electric field behavior. Modeling suggests that an incomplete compensation of the p-type layer in the edge termination creates a bilayer structure that leads to these effects, with variations that significantly impact the breakdown voltage.
Xu, Ting; Walter, Erich C.; Agrawal, Amit; Bohn, Christopher; Velmurugan, Jeyavel; Zhu, Wenqi; Lezec, Henri J.; Talin, A.A.
With vibrant colours and simple, roomerature processing methods, electrochromic polymers have attracted attention as active materials for flexible, low-power-consuming devices. However, slow switching speeds in devices realized to date, as well as the complexity of having to combine several distinct polymers to achieve a full-colour gamut, have limited electrochromic materials to niche applications. Here we achieve fast, high-contrast electrochromic switching by significantly enhancing the interaction of light-propagating as deep-subwavelength-confined surface plasmon polaritons through arrays of metallic nanoslits, with an electrochromic polymer-present as an ultra-thin coating on the slit sidewalls. The switchable configuration retains the short temporal charge-diffusion characteristics of thin electrochromic films, while maintaining the high optical contrast associated with thicker electrochromic coatings. We further demonstrate that by controlling the pitch of the nanoslit arrays, it is possible to achieve a full-colour response with high contrast and fast switching speeds, while relying on just one electrochromic polymer.
Gong, Chen; Ruzmetov, Dmitry; Pearse, Alexander; Ma, Dakang; Munday, Jeremy N.; Rubloff, Gary; Talin, A.A.; Leite, Marina S.
The further development of all-solid-state batteries is still limited by the understanding/engineering of the interfaces formed upon cycling. Here, we correlate the morphological, chemical, and electrical changes of the surface of thin-film devices with Al negative electrodes. The stable Al-Li-O alloy formed at the stress-free surface of the electrode causes rapid capacity fade, from 48.0 to 41.5 μAh/cm2 in two cycles. Surprisingly, the addition of a Cu capping layer is insufficient to prevent the device degradation. Nevertheless, Si electrodes present extremely stable cycling, maintaining >92% of its capacity after 100 cycles, with average Coulombic efficiency of 98%.
Metal-organic frameworks (MOFs) are crystalline nanoporous materials comprised of organic electron donors linked to metal ions by strong coordination bonds. Applications such as gas storage and separations are currently receiving considerable attention, but if the unique properties of MOFs could be extended to electronics, magnetics, and photonics, the impact on material science would greatly increase. Recently, we obtained "emergent properties," such as electronic conductivity and energy transfer, by infiltrating MOF pores with "guest" molecules that interact with the framework electronic structure. In this Perspective, we define a path to emergent properties based on the Guest@MOF concept, using zinc-carboxylate and copper-paddlewheel MOFs for illustration. Energy transfer and light harvesting are discussed for zinc carboxylate frameworks infiltrated with triplet-scavenging organometallic compounds and thiophene- and fullerene-infiltrated MOF-177. In addition, we discuss the mechanism of charge transport in TCNQ-infiltrated HKUST-1, the first MOF with electrical conductivity approaching conducting organic polymers. These examples show that guest molecules in MOF pores should be considered not merely as impurities or analytes to be sensed but also as an important aspect of rational design.
This report documents work that was performed under the Laboratory Directed Research and Development project, Science of Battery Degradation. The focus of this work was on the creation of new experimental and theoretical approaches to understand atomistic mechanisms of degradation in battery electrodes that result in loss of electrical energy storage capacity. Several unique approaches were developed during the course of the project, including the invention of a technique based on ultramicrotoming to cross-section commercial scale battery electrodes, the demonstration of scanning transmission x-ray microscopy (STXM) to probe lithium transport mechanisms within Li-ion battery electrodes, the creation of in-situ liquid cells to observe electrochemical reactions in real-time using both transmission electron microscopy (TEM) and STXM, the creation of an in-situ optical cell utilizing Raman spectroscopy and the application of the cell for analyzing redox flow batteries, the invention of an approach for performing ab initio simulation of electrochemical reactions under potential control and its application for the study of electrolyte degradation, and the development of an electrochemical entropy technique combined with x-ray based structural measurements for understanding origins of battery degradation. These approaches led to a number of scientific discoveries. Using STXM we learned that lithium iron phosphate battery cathodes display unexpected behavior during lithiation wherein lithium transport is controlled by nucleation of a lithiated phase, leading to high heterogeneity in lithium content at each particle and a surprising invariance of local current density with the overall electrode charging current. We discovered using in-situ transmission electron microscopy that there is a size limit to lithiation of silicon anode particles above which particle fracture controls electrode degradation. From electrochemical entropy measurements, we discovered that entropy changes little with degradation but the origin of degradation in cathodes is kinetic in nature, i.e. lower rate cycling recovers lost capacity. Finally, our modeling of electrode-electrolyte interfaces revealed that electrolyte degradation may occur by either a single or double electron transfer process depending on thickness of the solid-electrolyte-interphase layer, and this cross-over can be modeled and predicted.
Leite, Marina S.; Ruzmetov, Dmitry; Li, Zhipeng; Bendersky, Leonid A.; Bartelt, Norman C.; Kolmakov, Andrei; Talin, A.A.
The atomistic mechanism for lithiation/delithiation in all-solid-state batteries is still an open question, and the 'holy grail' to engineer devices with extended lifetime. Here, by combining real-time scanning electron microscopy in ultra-high vacuum with electrochemical cycling, we quantify the dynamic degradation of Al anodes in Li-ion all-solid-state batteries, a promising alternative for ultra lightweight devices. We find that AlLi alloy mounds are formed on the top surface of the Al anode and that degradation of battery capacity occurs because of Li trapped in them. Our approach establishes a new platform for probing the real-time degradation of electrodes, and can be expanded to other complex systems, allowing for high throughput characterization of batteries with nanoscale resolution.
Leite, Marina S.; Abashin, Maxim; Lezec, Henri J.; Gianfrancesco, Anthony; Talin, A.A.; Zhitenev, Nikolai B.
The local collection characteristics of grain interiors and grain boundaries in thin-film CdTe polycrystalline solar cells are investigated using scanning photocurrent microscopy. The carriers are locally generated by light injected through a small aperture (50-300 nm) of a near-field scanning optical microscope in an illumination mode. Possible influence of rough surface topography on light coupling is examined and eliminated by sculpting smooth wedges on the granular CdTe surface. By varying the wavelength of light, nanoscale spatial variations in external quantum efficiency are mapped. We find that the grain boundaries (GBs) are better current collectors than the grain interiors (GIs). The increased collection efficiency is caused by two distinct eff ects associated with the material composition of GBs. First, GBs are charged, and the corresponding built-in field facilitates the separation and the extraction of the photogenerated carriers. Second, the GB regions generate more photocurrent at long wavelength corresponding to the band edge, which can be caused by a smaller local band gap. Resolving carrier collection with nanoscale resolution in solar cell materials is crucial for optimizing the polycrystalline device performance through appropriate thermal processing and passivation of defects and surfaces. (Figure Presented).
Oleshko, Vladimir P.; Lam, Thomas; Ruzmetov, Dmitry; Haney, Paul; Lezec, Henri J.; Davydov, Albert V.; Krylyuk, Sergiy; Cumings, John; Talin, A.A.
Complex interfacial phenomena and phase transformations that govern the operation of Li-ion batteries require detailed nanoscale 3D structural and compositional characterization that can be directly related to their capacity and electrical transport properties. For this purpose, we have designed model miniature all solid-state radial heterostructure Li-ion batteries composed of LiCoO2 cathode, LiPON electrolyte and amorphous Si anode shells, which were deposited around metallized high-aspect-ratio Si nanowires as a scaffolding core. Such diagnostic batteries, the smallest, complete secondary Li-ion batteries realized to date, were specifically designed for in situ electrical testing in a field-emission scanning electron microscope and/or transmission electron microscope. The results of electrochemical testing were described in detail in a previous publication (Nano Lett., 2012, 12, 505-511). The model Li-ion batteries allow analysis of the correlations between electrochemical properties and their structural evolution during cycling in various imaging, diffraction and spectroscopic modes down to the atomic level. Employing multimode analytical scanning/transmission electron microscopy imaging coupled with correlative multivariate statistical analysis and tomography, we have analyzed and quantified the 3D morphological and structural arrangement of the batteries, including textured platelet-like LiCoO2 nanocrystallites, buried electrode-electrolyte interfaces and hidden internal defects to clarify effects of scaling on a battery's electrochemical performance. Characterization of the nanoscale interfacial processes using model heterostructure nanowire-based Li-ion batteries provides useful guidelines for engineering of prospective nano-sized building blocks in future electrochemical energy storage systems.
Electro-optical organic materials hold great promise for the development of high-efficiency devices based on exciton formation and dissociation, such as organic photovoltaics (OPV) and organic light-emitting devices (OLEDs). However, the external quantum efficiency (EQE) of both OPV and OLEDs must be improved to make these technologies economical. Efficiency rolloff in OLEDs and inability to control morphology at key OPV interfaces both reduce EQE. Only by creating materials that allow manipulation and control of the intimate assembly and communication between various nanoscale excitonic components can we hope to first understand and then engineer the system to allow these materials to reach their potential. The aims of this proposal are to: 1) develop a paradigm-changing platform for probing excitonic processes composed of Crystalline Nanoporous Frameworks (CNFs) infiltrated with secondary materials (such as a complimentary semiconductor); 2) use them to probe fundamental aspects of excitonic processes; and 3) create prototype OPVs and OLEDs using infiltrated CNF as active device components. These functional platforms will allow detailed control of key interactions at the nanoscale, overcoming the disorder and limited synthetic control inherent in conventional organic materials. CNFs are revolutionary inorganic-organic hybrid materials boasting unmatched synthetic flexibility that allow tuning of chemical, geometric, electrical, and light absorption/generation properties. For example, bandgap engineering is feasible and polyaromatic linkers provide tunable photon antennae; rigid 1-5 nm pores provide an oriented, intimate host for triplet emitters (to improve light emission in OLEDs) or secondary semiconducting polymers (creating a charge-separation interface in OPV). These atomically engineered, ordered structures will enable critical fundamental questions to be answered concerning charge transport, nanoscale interfaces, and exciton behavior that are inaccessible in disordered systems. Implementing this concept also creates entirely new dimensions for device fabrication that could both improve performance, increase durability, and reduce costs with unprecedented control of over properties. This report summarizes the key results of this project and is divided into sections based on publications that resulted from the work. We begin in Section 2 with an investigation of light harvesting and energy transfer in a MOF infiltrated with donor and acceptor molecules of the type typically used in OPV devices (thiophenes and fullerenes, respectively). The results show that MOFs can provide multiple functions: as a light harvester, as a stabilizer and organizer or the infiltrated molecules, and as a facilitator of energy transfer. Section 3 describes computational design of MOF linker groups to accomplish light harvesting in the visible and facilitate charge separation and transport. The predictions were validated by UV-visible absorption spectroscopy, demonstrating that rational design of MOFs for light-harvesting purposes is feasible. Section 4 extends the infiltration concept discussed in Section to, which we now designate as "Molecule@MOF" to create an electrically conducting framework. The tailorability and high conductivity of this material are unprecedented, meriting publication in the journal Science and spawning several Technical Advances. Section 5 discusses processes we developed for depositing MOFs as thin films on substrates, a critical enabling technology for fabricating MOF-based electronic devices. Finally, in Section 6 we summarize results showing that a MOF thin film can be used as a sensitizer in a DSSC, demonstrating that MOFs can serve as active layers in excitonic devices. Overall, this project provides several crucial proofs-of- concept that the potential of MOFs for use in optoelectronic devices that we predicted several years ago [ 3 ] can be realized in practice.
LDRD Project 102662 provided support to pursue experiments aimed at measuring the basic electrodynamic response and possible applications of carbon nanotubes and silicon nanowires at radiofrequency to microwave frequencies, approximately 0.01 to 50 GHz. Under this project, a method was developed to integrate these nanomaterials onto high-frequency compatible co-planar waveguides. The complex reflection and transmission coefficients of the nanomaterials was studied as a function of frequency. From these data, the high-frequency loss characteristics of the nanomaterials were deduced. These data are useful to predict frequency dependence and power dissipation characteristics in new rf/microwave devices incorporating new nanomaterials.