High Thermal Conductivity of Submicrometer Aluminum Nitride Thin Films Sputter-Deposited at Low Temperature.

Aluminum nitride (AlN) is one of the few electrically insulating materials with excellent thermal conductivity, but high-quality films typically require exceedingly hot deposition temperatures (>1000 °C). For thermal management applications in dense or high-power integrated circuits, it is important to deposit heat spreaders at low temperatures (<500 °C), without affecting the underlying electronics. Here, we demonstrate 100 nm to 1.7 µm thick AlN films achieved by low-temperature (<100 °C) sputtering, correlating their thermal properties with their grain size and interfacial quality, which we analyze by X-ray diffraction, transmission X-ray microscopy, as well as Raman and Auger spectroscopy. Controlling the deposition conditions through the partial pressure of reactive N2, we achieve an ∼3× variation in thermal conductivity (∼36-104 W m-1 K-1) of ∼600 nm films, with the upper range representing one of the highest values for such film thicknesses at room temperature, especially at deposition temperatures below 100 °C. Defect densities are also estimated from the thermal conductivity measurements, providing insight into the thermal engineering of AlN that can be optimized for application-specific heat spreading or thermal confinement.

Patterned Adhesion Layer Enables Rugged Pd-MIS Hydrogen Sensors.

Rugged Pd-metal-insulator-semiconductor (Pd-MIS) hydrogen sensors for detecting charge-exchange particles in fusion reactors have been constructed by utilizing a novel patterned adhesion layer. Poor adhesion at the interface between Pd and SiO2 is a common failure mode for Pd-MIS devices, severely limiting the Pd thickness and their usefulness as hydrogen sensors. The mechanical integrity of the Pd coatings is of particular importance in magnetic fusion energy research where the Pd-MIS diodes are used to measure hydrogen charge-exchange neutral fluence at the wall in tokamaks. In this application, particularly thick Pd contacts are desirable to prevent damage caused by high-energy particles; however, such thick Pd coatings are prone to mechanical failure due to blistering and wire bond detachment during construction or operation. A continuous Ti or Cr adhesion layer is not possible for this application since it would interfere with H uptake at the SiO2 interface, which is essential for the device to generate a response. In this work, we demonstrate that a patterned Cr interlayer substantially improves adhesion while still providing access for hydrogen to reach the SiO2-Pd interface.

Single-Particle Measurements Reveal the Origin of Low Solar-to-Hydrogen Efficiency of Rh-Doped SrTiO3 Photocatalysts.

Solar-powered photochemical water splitting using suspensions of photocatalyst nanoparticles is an attractive route for economical production of green hydrogen. SrTiO3-based photocatalysts have been intensely investigated due to their stability and recently demonstrated near-100% external quantum yield (EQY) for water splitting using wavelengths below 360 nm. To extend the optical absorption into the visible, SrTiO3 nanoparticles have been doped with various transition metals. Here we demonstrate that doping SrTiO3 nanoparticles with 1% Rh introduces midgap acceptor states which reduce the free electron concentration by 5 orders of magnitude, dramatically reducing built-in potentials which could otherwise separate electron-hole (e-h) pairs. Rhodium states also function as recombination centers, reducing the photocarrier lifetime by nearly 2 orders of magnitude and the maximum achievable EQY to 10%. Furthermore, the absence of built-in electric fields within Rh-doped SrTiO3 nanoparticles suggests that modest e-h separation can be achieved by exploiting a difference in mobility between electrons and holes.

Room-Temperature Pseudo-Solid-State Iron Fluoride Conversion Battery with High Ionic Conductivity.

Li-metal batteries (LMBs) employing conversion cathode materials (e.g., FeF3) are a promising way to prepare inexpensive, environmentally friendly batteries with high energy density. Pseudo-solid-state ionogel separators harness the energy density and safety advantages of solid-state LMBs, while alleviating key drawbacks (e.g., poor ionic conductivity and high interfacial resistance). In this work, a pseudo-solid-state conversion battery (Li-FeF3) is presented that achieves stable, high rate (1.0 mA cm-2) cycling at room temperature. The batteries described herein contain gel-infiltrated FeF3 cathodes prepared by exchanging the ionic liquid in a polymer ionogel with a localized high-concentration electrolyte (LHCE). The LHCE gel merges the benefits of a flexible separator (e.g., adaptation to conversion-related volume changes) with the excellent chemical stability and high ionic conductivity (∼2 mS cm-1 at 25 °C) of an LHCE. The latter property is in contrast to previous solid-state iron fluoride batteries, where poor ionic conductivities necessitated elevated temperatures to realize practical power levels. The stable, room-temperature Li-FeF3 cycling performance obtained with the LHCE gel at high current densities paves the way for exploring a range of architectures including flexible, three-dimensional, and custom shape batteries.

Tunable Intervalence Charge Transfer in Ruthenium Prussian Blue Analog Enables Stable and Efficient Biocompatible Artificial Synapses.

Emerging concepts for neuromorphic computing, bioelectronics, and brain-computer interfacing inspire new research avenues aimed at understanding the relationship between oxidation state and conductivity in unexplored materials. This report expands the materials playground for neuromorphic devices to include a mixed valence inorganic 3D coordination framework, a ruthenium Prussian blue analog (RuPBA), for flexible and biocompatible artificial synapses that reversibly switch conductance by more than four orders of magnitude based on electrochemically tunable oxidation state. The electrochemically tunable degree of mixed valency and electronic coupling between N-coordinated Ru sites controls the carrier concentration and mobility, as supported by density functional theory computations and application of electron transfer theory to in situ spectroscopy of intervalence charge transfer. Retention of programmed states is improved by nearly two orders of magnitude compared to extensively studied organic polymers, thus reducing the frequency, complexity, and energy costs associated with error correction schemes. This report demonstrates dopamine-mediated plasticity of RuPBA synapses and biocompatibility of RuPBA with neuronal cells, evoking prospective application for brain-computer interfacing.

ECRAM Materials, Devices, Circuits and Architectures: A Perspective.

Non-von-Neumann computing using neuromorphic systems based on two-terminal resistive nonvolatile memory elements has emerged as a promising approach, but its full potential has not been realized due to the lack of materials and devices with the appropriate attributes. Unlike memristors, which require large write currents to drive phase transformations or filament growth, electrochemical random access memory (ECRAM) decouples the "write" and "read" operations using a "gate" electrode to tune the conductance state through charge-transfer reactions, and every electron transferred through the external circuit in ECRAM corresponds to the migration of ≈1 ion used to store analogue information. Like static dopants in traditional semiconductors, electrochemically inserted ions modulate the conductivity by locally perturbing a host's electronic structure; however, ECRAM does so in a dynamic and reversible manner. The resulting change in conductance can span orders of magnitude, from gradual increments needed for analog elements, to large, abrupt changes for dynamically reconfigurable adaptive architectures. In this in-depth perspective, the history of ECRAM, the recent progress in devices spanning organic, inorganic, and 2D materials, circuits, architectures, the rich portfolio of challenging, fundamental questions, and how ECRAM can be harnessed to realize a new paradigm for low-power neuromorphic computing are discussed.

Quantifying the Influence of Defects on Selectivity of Electrodes Encapsulated by Nanoscopic Silicon Oxide Overlayers.

Encapsulation of electrocatalysts and photocatalysts with semipermeable nanoscopic oxide overlayers that exhibit selective transport properties is an attractive approach to achieve high redox selectivity. However, defects within the overlayers─such as pinholes, cracks, or particle inclusions─may facilitate local high rates of parasitic reactions by creating pathways for facile transport of undesired reactants to exposed active sites. Scanning electrochemical microscopy (SECM) is an attractive method to determine the influence of defects on macroscopic performance metrics thanks to its ability to measure the relative rates of competing electrochemical reactions with high spatial resolution over the electrode. Here, we report the use of SECM to determine the influence of overlayer defects on the selectivity of silicon oxide (SiOx) encapsulated platinum thin-film electrocatalysts operated under conditions where two competing reactions─the hydrogen evolution and Fe(III) reduction reactions─can occur. After an SECM methodology is described to determine spatially resolved selectivity, representative selectivity maps are correlated with the location of defects that are characterized by optical, electron, and atomic force microscopies. This analysis reveals that certain types of defects in the oxide overlayer are responsible for ∼60-90% of the partial current density toward the undesired Fe(III) reduction reaction. By correcting for defect contributions to Fe(III) reduction rates, true Fe(III) permeability values for the SiOx overlayers were determined to be over an order of magnitude lower than permeabilities determined from analyses that ignore the presence of defects. Finally, different types of defects were studied revealing that defect morphology can have varying influence on both redox selectivity and calculated permeability. This work highlights the need for spatially resolved measurements to evaluate the performance of oxide-encapsulated catalysts and understand their performance limits.

3D Printing of Ridged FeS2 Cathodes for Improved Rate Capability and Custom-Form Lithium Batteries.

Additive manufacturing can enable the fabrication of batteries in nonconventional form factors, enabling higher practical energy density due to improved material packing efficiency of power sources in devices. Furthermore, energy density can be improved by transitioning from conventional Li-ion battery materials to lithium metal anodes and conversion cathodes. Iron disulfide (FeS2) is a prominent conversion cathode of commercial interest; however, the direct-ink-write (DIW) printing of FeS2 inks for custom-form battery applications has yet to be demonstrated or optimized. In this work, DIW printing of FeS2 inks is used to systematically investigate the impact of ink solid concentration on rheology, film shape retention on arbitrary surfaces, cathode morphology, and electrochemical cell performance. We find that cathodes with a ridged interface, produced from the filamentary extrusion of highly concentrated FeS2 inks (60-70% solids w/w%), exhibit optimal power, uniformity, and stability when cycled at higher rates (in excess of C/10). Meanwhile, cells with custom-form, wave-shaped electrodes (printed FeS2 cathodes and pressed lithium anodes) are demonstrated and shown to exhibit similar performance to comparable cells in planar configurations, demonstrating the feasibility of printing onto complex geometries. Overall, the DIW printing of FeS2 inks is shown to be a viable path toward the making of custom-form conversion lithium batteries. More broadly, ridging is found to optimize rate capability, a finding that may have a broad impact beyond FeS2 and syringe extrusion.

Imaging Phase Segregation in Nanoscale LixCoO2 Single Particles.

LixCoO2 (LCO) is a common battery cathode material that has recently emerged as a promising material for other applications including electrocatalysis and as electrochemical random access memory (ECRAM). During charge-discharge cycling LCO exhibits phase transformations that are significantly complicated by electron correlation. While the bulk phase diagram for an ensemble of battery particles has been studied extensively, it remains unclear how these phases scale to nanometer dimensions and the effects of strain and diffusional anisotropy at the single-particle scale. Understanding these effects is critical to modeling battery performance and for predicting the scalability and performance of electrocatalysts and ECRAM. Here we investigate isolated, epitaxial LiCoO2 islands grown by pulsed laser deposition. After electrochemical cycling of the islands, conductive atomic force microscopy (c-AFM) is used to image the spatial distribution of conductive and insulating phases. Above 20 nm island thicknesses, we observe a kinetically arrested state in which the phase boundary is perpendicular to the Li-planes; we propose a model and present image analysis results that show smaller LCO islands have a higher conductive fraction than larger area islands, and the overall conductive fraction is consistent with the lithiation state. Thinner islands (14 nm), with a larger surface to volume ratio, are found to exhibit a striping pattern, which suggests surface energy can dominate below a critical dimension. When increasing force is applied through the AFM tip to strain the LCO islands, significant shifts in current flow are observed, and underlying mechanisms for this behavior are discussed. The c-AFM images are compared with photoemission electron microscopy images, which are used to acquire statistics across hundreds of particles. The results indicate that strain and morphology become more critical to electrochemical performance as particles approach nanometer dimensions.

Efficient Electronic Tunneling Governs Transport in Conducting Polymer-Insulator Blends.

Electronic transport models for conducting polymers (CPs) and blends focus on the arrangement of conjugated chains, while the contributions of the nominally insulating components to transport are largely ignored. In this work, an archetypal CP blend is used to demonstrate that the chemical structure of the non-conductive component has a substantial effect on charge carrier mobility. Upon diluting a CP with excess insulator, blends with as high as 97.4 wt % insulator can display carrier mobilities comparable to some pure CPs such as polyaniline and low regioregularity P3HT. In this work, we develop a single, multiscale transport model based on the microstructure of the CP blends, which describes the transport properties for all dilutions tested. The results show that the high carrier mobility of primarily insulator blends results from the inclusion of aromatic rings, which facilitate long-range tunneling (up to ca. 3 nm) between isolated CP chains. This tunneling mechanism calls into question the current paradigm used to design CPs, where the solubilizing or ionically conducting component is considered electronically inert. Indeed, optimizing the participation of the nominally insulating component in electronic transport may lead to enhanced electronic mobility and overall better performance in CPs.

Understanding the Electrochemical Performance of FeS2 Conversion Cathodes.

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. We further 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 Bioinspired Artificial Injury Response System Based on a Robust Polymer Memristor to Mimic a Sense of Pain, Sign of Injury, and Healing.

Flexible electronic skin with features that include sensing, processing, and responding to stimuli have transformed human-robot interactions. However, more advanced capabilities, such as human-like self-protection modalities with a sense of pain, sign of injury, and healing, are more challenging. Herein, a novel, flexible, and robust diffusive memristor based on a copolymer of chlorotrifluoroethylene and vinylidene fluoride (FK-800) as an artificial nociceptor (pain sensor) is reported. Devices composed of Ag/FK-800/Pt have outstanding switching endurance >106  cycles, orders of magnitude higher than any other two-terminal polymer/organic memristors in literature (typically 102 -103 cycles). In situ conductive atomic force microscopy is employed to dynamically switch individual filaments, which demonstrates that conductive filaments correlate with polymer grain boundaries and FK-800 has superior morphological stability under repeated switching cycles. It is hypothesized that the high thermal stability and high elasticity of FK-800 contribute to the stability under local Joule heating associated with electrical switching. To mimic biological nociceptors, four signature nociceptive characteristics are demonstrated: threshold triggering, no adaptation, relaxation, and sensitization. Lastly, by integrating a triboelectric generator (artificial mechanoreceptor), memristor (artificial nociceptor), and light emitting diode (artificial bruise), the first bioinspired injury response system capable of sensing pain, showing signs of injury, and healing, is demonstrated.

The Role of Electrolyte Composition in Enabling Li Metal-Iron Fluoride Full-Cell Batteries.

FeF3 conversion cathodes, paired with Li metal, are promising for use in next-generation secondary batteries and offer a remarkable theoretical energy density of 1947 Wh kg-1 compared to 690 Wh kg-1 for LiNi0.5 Mn1.5 O4 ; however, many successful studies on FeF3 cathodes are performed in cells with a large (>90-fold) excess of Li that disguises the effects of tested variables on the anode and decreases the practical energy density of the battery. Herein, it is demonstrated that for full-cell compatibility, the electrolyte must produce both a protective solid-electrolyte interphase and cathode-electrolyte interphase and that an electrolyte composed of 1:1.3:3 (m/m) LiFSI, 1,2-dimethoxyethane, and 1,1,2,2-tetrafluoroethyl-2,2,3,3-tetrafluoropropyl ether fulfills both these requirements. This work demonstrates the importance of verifying electrode level solutions on the full-cell level when developing new battery chemistries and represents the first full cell demonstration of a Li/FeF3 cell, with both limited Li and high capacity FeF3 utilization.

Fabrication and field emission properties of vertical, tapered GaN nanowires etched via phosphoric acid.

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% H3PO4crystallographic wet etch is explored. The vertical nanowires are oriented in the[0001]direction and are bound by sidewalls comprising of{336¯2}semipolar planes which are at a 12° angle from the [0001] axis. High temperature H3PO4etching 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{336¯2}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-1for a 50 nm gap, and uniform emission across the array.

From n- to p-Type Material: Effect of Metal Ion on Charge Transport in Metal-Organic Materials.

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.

In situ Parallel Training of Analog Neural Network Using Electrochemical Random-Access Memory.

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.

Ultralow Voltage GaN Vacuum Nanodiodes in Air.

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.

Roadmap on emerging hardware and technology for machine learning.

Recent progress in artificial intelligence is largely attributed to the rapid development of machine learning, especially in the algorithm and neural network models. However, it is the performance of the hardware, in particular the energy efficiency of a computing system that sets the fundamental limit of the capability of machine learning. Data-centric computing requires a revolution in hardware systems, since traditional digital computers based on transistors and the von Neumann architecture were not purposely designed for neuromorphic computing. A hardware platform based on emerging devices and new architecture is the hope for future computing with dramatically improved throughput and energy efficiency. Building such a system, nevertheless, faces a number of challenges, ranging from materials selection, device optimization, circuit fabrication and system integration, to name a few. The aim of this Roadmap is to present a snapshot of emerging hardware technologies that are potentially beneficial for machine learning, providing the Nanotechnology readers with a perspective of challenges and opportunities in this burgeoning field.