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.
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 to mitigate 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.
Researchers present a Li-ion synaptic transistor for analog computation (LISTA). LISTA is an all solidstate, nonvolatile redox transistor (NVRT) with a resistance switching mechanism based upon the intercalation of Li-ion dopants into a channel of Li1-xCoO2. The researchers also demonstrate that an NVRT device is advantageous for neuromorphic applications because it utilizes the low energy process of ion insertion/extraction for resistance switching while maintaining nonvolatility.
Here, 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—V—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.
Talin, Albert A.; Ruzmetov, Dmitry; Kolmakov, Andrei; Mckelvey, Kim; El Gabaly, Farid; Ware, Nicholas; Dunn, Bruce; White, Henry
Realization of safe, long cycle life and simple to package solid-state rechargeable batteries with high energy and power density has been a long-standing goal of the energy storage community.[1,2] Much of the research activity has been focused on developing new solid electrolytes with high Li ionic conductivity. In addition, LiPON, the only solid electrolyte currently used in commercial thin film solid state Li-ion batteris (SSLIBs), has a conductivity of ~10-6 S/cm, compared to ~0.01 S/cm typically observed for liquid organic electrolytes[3].
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.
The thermal conductivity of n- and p-type doped gallium nitride (GaN) epilayers having thicknesses of 3-4 μm was investigated using time domain thermoreflectance. Despite possessing carrier concentrations ranging across 3 decades (1015-1018cm-3), n-type layers exhibit a nearly constant thermal conductivity of 180 W/mK. The thermal conductivity of p-type epilayers, in contrast, reduces from 160 to 110 W/mK with increased doping. These trends - and their overall reduction relative to bulk - are explained leveraging established scattering models where it is shown that, while the decrease in p-type layers is partly due to the increased impurity levels evolving from its doping, size effects play a primary role in limiting the thermal conductivity of GaN layers tens of microns thick. Device layers, even of pristine quality, will therefore exhibit thermal conductivities less than the bulk value of 240 W/mK owing to their finite thickness.