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DOE OSTI2024

InP- and GaAs-Based 0.6 eV GaInAs Devices for Thermophotovoltaics and Laser Power Conversion

Emerging applications such as thermal energy grid storage, waste heat recovery and portable power generation require efficient thermophotovoltaic (TPV) converters tuned to temperatures near 1000 Degrees Celsius or below. Metamorphic GaInAs with larger lattice constants than InP present a promising option for these needs. The ability to grow these devices on GaAs substrates instead of more expensive InP would enhance the scalability of these devices. In this talk, we present inverted metamorphic Ga0.3In0.7As photovoltaic converters with sub-0.60 eV bandgaps grown on InP and GaAs substrates. These devices are realized using InAsP or GaInP/InAsP compositionally graded buffers which exhibit threading dislocation densities of 1.3 +/- 0.6 x 106 cm-2 and 8.9 +/- 1.7 x 106 cm-2 on InP and GaAs, respectively. Despite this difference in defect density, the devices generate similar open-circuit voltages of 0.386 V and 0.383 V, respectively, under irradiance producing a short-circuit current density of -10 A/cm2, with bandgap-voltage offsets of 0.20 and 0.21 V. We estimate their thermophotovoltaic efficiency using these measurements coupled with broadband reflectance measurments. The InP-based cell is estimated to yield 1.09 W/cm2 at 1100 Degrees Celsius vs. 0.92 W/cm2 for the GaAs-based cell, with TPV efficiencies of 16.8 vs. 9.2%. Both devices are limited by sub-bandgap absorption, which we assess largely occurs in the graded buffers. We estimate that the 1100 Degrees Celsius thermophotovoltaic efficiencies would increase to 24.0% and 20.7% in structures with the graded buffer removed, if previously demonstrated reflectance is achieved. These devices also have application as laser power converters in the 2.0-2.3 um atmospheric window. We estimate efficiencies of 36.8% and 32.5% under 2.0 um monochromatic irradiance of 1.86 W/cm2 and 2.81 W/cm2, respectively.

ENGINEERING,MATERIALS SCIENCE,SOLAR ENERGY↗

DOE OSTI2017

Multi-Scale Ordered Cell Structure for Cost Effective Production of Hydrogen by HTWS

Production of hydrogen using an electrochemical device provides for large scale, high efficiency conversion and storage of electrical energy. When renewable electricity is used for conversion of steam to hydrogen, a low-cost and low emissions pathway to hydrogen production emerges. This project was intended to demonstrate a high efficiency High Temperature Water Splitting (HTWS) stack for the electrochemical production of low cost H2. The innovations investigated address the limitations of the state of the art through the use of a novel architecture that introduces macro-features to provide mechanical support of a thin electrolyte, and micro-features of the electrodes to lower polarization losses. The approach also utilizes a combination of unique sets of fabrication options that are scalable to achieve manufacturing cost objectives. The development of HTWS process and device is guided by techno-economic and life cycle analyses.

08 HYDROGEN↗

DOE OSTI2025

In Situ Study of Resistive Switching in a Nitride‐Based Memristive Device

Abstract Resistive switching (RS) devices with ultra‐low‐voltage threshold and reliable switching repeatability exhibits great potential applications in energy‐efficient data storage and neuromorphic computing. Understanding switching mechanisms at nanoscale is critical to design RS devices with improved performance. In this work, a lamella memristive device using focused ion beam (FIB) method based on the metal/TiO x /TiN/Si structure device is fabricated. In situ transmission electron microscopy (TEM) and current–voltage ( I–V ) characteristic demonstrate that the lamella device shows a volatile RS behavior with a threshold switching at ≈ ± 0.4 V. In situ scanning transmission electron microscopy (STEM) experiments with electron energy loss spectroscopy (EELS) reveal that the charge carriers such as oxygen vacancies migrate under positive/negative DC bias and modulate Schottky barriers at the top and bottom metal/semiconductor interfaces. The RS mechanism of the lamella device is based on the Schottky barriers modulation and Joule heating assisted electric field triggered thermal runaway (FTTR) occurred at the metal/semiconductor interfaces. The fundamental insights gained from this study presents a perspective on interface‐type RS devices processing and opens up new technological opportunities of fabricating ultra‐low‐energy memristive devices.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Companion Assisted Software Based Remote Attestation in SCADA Networks

Critical infrastructure such as power generation and water distribution systems have become a priority target in cyber warfare because of their recent computerization and introduction to the internet. As a result, Supervisory Control and Data Acquisition (SCADA) system security has become a hot topic in academic and industrial research. Among these topics, Remote Attestation is a security method intended to detect the presence of fileless malware in remote devices as they continue to operate. This allows for the detection of malware in the absence of long-term storage artifacts before symptoms of compromise begin to appear. In general, a trusted device (the verifier) makes a request for evidence of innocence from the untrusted device (the prover). In software-based schemes, the verifier can then measure the delay between its request and the prover’s response. If this delay is greater than the known computational time of the evidence gathering algorithm performed by the prover, then evidence may have been forged. Multi-hop networks often introduce too much network jitter to allow accurate measurement of prover response time, which limits the effectiveness of software based Remote Attestation in a real-world setting. In this work, we introduce a companion device that the verifier can trust to perform a subset of attestation, thereby removing any network jitter. This device is a Field Programmable Gate Array (FPGA) that is physically connected to the prover. We provide a communication protocol between the verifier, prover, and companion. To evaluate our scheme, we simulate it in a common SCADA network environment under normal and heavy traffic loads. Our simulations are performed in the discrete event network simulator NS-3, and we perform statistical analysis over our results to show that our scheme allows for tight timing constraints to be placed on the prover such that the verifier can more easily determine the validity of the evidence that it receives.

Johnson, William A.↗

DOE OSTI2018

NREL Topic 1 Final Report: Cohesive Application of Standards-Based Connected Devices to Enable Clean Energy Technologies

This document is the final report of a two-year development, test, and demonstration project entitled 'Cohesive Application of Standards-Based Connected Devices to Enable Clean Energy Technologies.' The project was part of the National Renewable Energy Laboratory's (NREL) Integrated Network Test-bed for Energy Grid Research and Technology (INTEGRATE) initiative. The Electric Power Research Institute (EPRI) and a team of partners were selected by NREL to carry out a project to develop and test how smart, connected consumer devices can act to enable the use of more clean energy technologies on the electric power grid. The project team includes a set of leading companies that produce key products in relation to achieving this vision: thermostats, water heaters, pool pumps, solar inverters, electric vehicle supply equipment, and battery storage systems. A key requirement of the project was open access at the device level - a feature seen as foundational to achieving a future of widespread distributed generation and storage. The internal intelligence, standard functionality and communication interfaces utilized in this project result in the ability to integrate devices at any level, to work collectively at the level of the home/business, microgrid, community, distribution circuit or other. Collectively, the set of products serve as a platform on which a wide range of control strategies may be developed and deployed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Magnetic Solitons and Thickness‐Dependent Magnetization Reversal in Interconnected Helical Nanowire Arrays

By expanding magnetic nanostructures into the third dimension, it is possible to introduce new interactions and realize new forms of magnetic textures and emergent phenomena. Consequently, this unlocks new opportunities for applications in data storage, unconventional computing and sensing by utilizing 3D devices with enhanced functionalities. Connected magnetic nanowires offer a unique platform for applications such as neuromorphic computing due to their tunability and the presence of multiple transport pathways. However to realize this promise, it is necessary to further our understanding of how to locally control the magnetization in 3D, nanowire-based geometries. In this work we show the formation of magnetic domain walls, vortices, anti-vortices, and linked vortex-anti-vortex pairs in interconnected helical nanowire arrays. We show how wire diameter and 3D geometric design can control the states that form and reveal the magnetization reversal mechanism. Hence, we demonstrate this to be a highly tunable system, where the magnetization can be readily reconfigured by an external magnetic field.

3D Nanomagnetism↗

DOE OSTI2020

Structure of the Electrical Double Layer at the Interface between an Ionic Liquid and Tungsten Oxide in Ion-Gated Transistors

The structure of electrical double layers at electrified interfaces is of utmost importance for electrochemical energy storage as well as printable, flexible, and bioelectronic devices, such as ion-gated transistors (IGTs). Here we report a study based on atomic force microscopy force–distance profiling on electrical double layers forming at the interface between the ionic liquid 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide and sol–gel films of mesoporous tungsten oxide. Here, we successfully followed, under in operando conditions, the evolution of the arrangement of the ions at the interface with the tungsten oxide films used as channel materials in IGTs. Our work sheds light on the mechanism of operation of IGTs, thus offering the possibility of optimizing their performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Ultralight Conductive Silver Nanowire Aerogels

Low-density metal foams have many potential applications in electronics, energy storage, catalytic supports, fuel cells, sensors, and medical devices. Here in this work, we report a new method for fabricating ultralight, conductive silver aerogel monoliths with predictable densities using silver nanowires. Silver nanowire building blocks were prepared by polyol synthesis and purified by selective precipitation. Silver aerogels were produced by freeze-casting nanowire aqueous suspensions followed by thermal sintering to weld the nanowire junctions. As-prepared silver aerogels have unique anisotropic microporous structures, with density precisely controlled by the nanowire concentration, down to 4.8 mg/cm 3 and an electrical conductivity up to 51 000 S/m. Lastly, mechanical studies show that silver nanowire aerogels exhibit “elastic stiffening” behavior with a Young’s modulus up to 16 800 Pa.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Manipulating Ferroelectrics through Changes in Surface and Interface Properties

Ferroelectric materials are used in many applications of modern technologies including information storage, transducers, sensors, tunable capacitors, and other novel device concepts. In many of these applications, the ferroelectric properties, such as switching voltages, piezoelectric constants, or stability of nanodomains, are crucial. For any application, even for material characterization, the material itself needs to be interfaced with electrodes. On the basis of the structural, chemical, and electronic properties of the interfaces, the measured material properties can be determined by the interface. This is also true for surfaces. However, the importance of interfaces and surfaces and their effect on experiments are often neglected, which results in many dramatically different experimental results for nominally identical samples. Therefore, it is crucial to understand the role of the interface and surface properties on internal bias fields and the domain switching process. Here, the nanoscale ferroelectric switching process and the stability of nanodomains for Pb(Zr,Ti)O 3 thin films are investigated by using scanning probe microscopy. Interface and surface properties are modulated through the selection/redesign of electrode materials as well as tuning the surface-near oxygen vacancies, which both can result in changes of the electric fields acting across the sample, and consequently this controls the measured ferroelectric and domain retention properties. By understanding the role of surfaces and interfaces, ferroelectric properties can be tuned to eliminate the problem of asymmetric domain stability by combining the effects of different electrode materials. Lastly, this study forms an important step toward integrating ferroelectric materials in electronic devices.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2016

Nanoionics and Nanocatalysts: Conformal Mesoporous Surface Scaffold for Cathode of Solid Oxide Fuel Cells

Nanoionics has become increasingly important in devices and systems related to energy conversion and storage. Nevertheless, nanoionics and nanostructured electrodes development has been challenging for solid oxide fuel cells (SOFCs) owing to many reasons including poor stability of the nanocrystals during fabrication of SOFCs at elevated temperatures. In this study, a conformal mesoporous ZrO 2 nanoionic network was formed on the surface of La 1–x Sr x MnO 3 /yttria-stabilized zirconia (LSM/YSZ) cathode backbone using Atomic Layer Deposition (ALD) and thermal treatment. The surface layer nanoionic network possesses open mesopores for gas penetration, and features a high density of grain boundaries for enhanced ion-transport. The mesoporous nanoionic network is remarkably stable and retains the same morphology after electrochemical operation at high temperatures of 650–800 °C for 400 hours. The stable mesoporous ZrO 2 nanoionic network is further utilized to anchor catalytic Pt nanocrystals and create a nanocomposite that is stable at elevated temperatures. As a result, the power density of the ALD modified and inherently functional commercial cells exhibited enhancement by a factor of 1.5–1.7 operated at 0.8 V at 750 °C.

25 ENERGY STORAGE↗

DOE OSTI2023

Enriching 2D transition metal borides via MB XMenes (M = Fe, Co, Ir): Strong correlation and magnetism

Recently, two-dimensional (2D) FeSe-like anti-MXenes (or XMenes), composed of late d-block transition metal M and p-block nonmetal X elements, have been both experimentally and theoretically investigated. Here, we select three 2D borides FeB, CoB and IrB for a deeper investigation by including strong correlation effects, as a fertile ground for understanding and applications. Using a combination of Hubbard corrected first-principles calculations and Monte Carlo simulations, FeB and CoB are found to be ferro- and anti-ferro magnetic, contrasting with the non-magnetic nature of IrB. The metallic FeB XMene monolayer, superior to most of the MXenes or MBenes, exhibits robust ferromagnetism, driven by intertwined direct-exchange and super-exchange interactions between adjacent Fe atoms. The predicted Curie temperature ($T$ C ) of the FeB monolayer via the Heisenberg model reaches an impressive 425 K, with the easy-axis oriented out-of-plane and high magnetic anisotropic energy (MAE). The asymmetry in the spin-resolved transmission spectrum induces a thermal spin current, providing an opportunity for spin filtration. In conclusion, this novel 2D FeB material is expected to hold great promise as an information storage medium and find applications in emerging spintronic devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2018

Stabilization and control of topological magnetic solitons via magnetic nanopatterning of exchange bias systems

Stabilizing and manipulating topological magnetic quasiparticles in thin films is of great interest for potential applications in data storage and information processing. Here, we present a strategy for stabilizing magnetic vortices and Bloch lines with controlled position, vorticity, and chirality in a continuous exchange bias system. By tailoring vectorially the unidirectional anisotropy of the system at the nanoscale, via thermally assisted magnetic scanning probe lithography, we show experimentally and via micromagnetic simulations the non-volatile creation of vortex-antivortex pairs. In addition, we demonstrate the deterministic stabilization of cross and circular Bloch lines within patterned Néel magnetic domain walls. This work enables the implementation of complex functionalities based on the control of tailored topological spin-textures in spintronic and magnonic nanodevices.

Magnetic ordering↗

DOE OSTI2019

Shear strain-induced anisotropic domain evolution in mixed-phase BiFeO 3 epitaxial films

Understanding and controlling the domain evolution under external stimuli in multiferroic thin films is critical to realizing nano-electronic devices, including for non-volatile memory, data storage, sensors, and optoelectronics. In this article, we studied the shear-strain effect on the domain evolution with temperature in highly strained BiFeO 3 thin films on rhombohedral LaAlO 3 sub-strates using a high-resolution synchrotron X-ray diffraction three dimensional-reciprocal space mapping (3D-RSM) technique. The results revealed significant biaxial, anisotropic, evolution behaviors of the mixed-phase ( M C + R' / T' phases) BiFeO 3 ferro-electric domains along the in-plane [100] and [010] axes. These biaxial, anisotropic, evolution behaviors were attributed to the shear-strain-modulated transition pathways of the mixed-phase ferroelectric domains. This viewpoint was further verified in the BiFeO 3 /LaSrAlO 4 (001) system in which no anisotropic evolution behaviors of the mixed-phase domains were found. This work sheds light on the quantitative analysis of domain evolution in multi-domain systems and demonstrates that the shear-strain effect could act as an effective tool to manipulate the domain behavior and control novel functionalities of ferroelectric thin films.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Eigenvalue-Based Micromagnetic Analysis of Switching in Spin-Torque-Driven Structures

We present an eigenvalue-based approach for studying the magnetization dynamics in magnetic nanostructures driven by spintronic excitations, such as spin-transfer torque and spin-orbit torque. The approach represents the system dynamics in terms of normal oscillation modes (eigenstates) with corresponding complex eigenfrequencies. The dynamics is driven by a small number of active eigenstates and often considering just a single eigenstate is sufficient. We develop a perturbation theory that provides semianalytical dynamic solutions by using eigenstates for the case in the absence of damping and spintronic excitations as a basis. The approach provides useful insights into dynamics in such systems and allows solving several difficulties in their modeling, such as extracting the switching current in magnetic random-access memories and understanding switching mechanisms. We show that the presented approach directly predicts the critical switching current, i.e., switching current for an infinite time. The approach also provides solutions for the switching dynamics allowing the switching current to be obtained for a finite switching time, provided that the system symmetry is broken, e.g., by tilting the polarizer, so that switching by a finite pulse is possible.

42 ENGINEERING↗

DOE OSTI2025

Harnessing ionic complexity: A modeling approach for hierarchical ionic circuit design

Since the 1950s, soft ionic devices have evolved from individual components to an expanding library of sensors, actuators, signal transmitters, and processors. However, integrating these components into complex, multifunctional systems remains challenging due to the nonintuitive and nonlinear interactions between ionic elements. In this work, we address these fundamental challenges by developing a lumped element model that enables interrogation of the physics that governs ionic circuits, as well as rapid design and optimization. Our model captures features specific to ionic charge carriers, while preserving the hierarchical design flexibility and computational efficiency of traditional circuit modeling. We demonstrate that our model can not only fit individual device behavior but also accurately predict the behavior of larger circuits formed by combining those devices. Additionally, we show how our tool utilizes the intrinsic nonlinearities of ionic systems to enable extended functionality, revealing how factors such as ion enrichment, ion leakage, and polymer charge density influence performance. Lastly, we present a fully ionic power supply, sensor, control system, and actuator for a soft robot that adapts its motion in response to environmental salt, illustrating the tool’s potential to accelerate advancements in chemical sensing, biointerfacing, biomimetic systems, and adaptive materials.

42 ENGINEERING↗

DOE OSTI2019

Demonstration of Machine Learning-Based Model-Independent Stabilization of Source Properties in Synchrotron Light Sources

Synchrotron light sources, arguably among the most powerful tools of modern scientific discovery, are presently undergoing a major transformation to provide orders of magnitude higher brightness and transverse coherence enabling the most demanding experiments. In these experiments, overall source stability will soon be limited by achievable levels of electron beam size stability, presently on the order of several microns, which is still 1–2 orders of magnitude larger than already demonstrated stability of source position and current. Until now source size stabilization has been achieved through corrections based on a combination of static predetermined physics models and lengthy calibration measurements, periodically repeated to counteract drift in the accelerator and instrumentation. In this paper, we now demonstrate for the first time how the application of machine learning allows for a physics- and model-independent stabilization of source size relying only on previously existing instrumentation. Such feed-forward correction based on a neural network that can be continuously online retrained achieves source size stability as low as 0.2 μm (0.4%) rms, which results in overall source stability approaching the subpercent noise floor of the most sensitive experiments.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

DDStore: Distributed Data Store for Scalable Training of Graph Neural Networks on Large Atomistic Modeling Datasets

Graph neural networks (GNNs) are a class of Deep Learning models used in designing atomistic materials for effective screening of large chemical spaces. To ensure robust prediction, GNN models must be trained on large volumes of atomistic data on leadership class supercomputers. Even with the advent of modern architectures that consist of multiple storage layers that include node-local NVMe devices in addition to device memory for caching large datasets, extreme-scale model training faces I/O challenges at scale.We present DDStore, an in-memory distributed data store designed for GNN training on large-scale graph data. DDStore provides a hierarchical, distributed, data caching technique that combines data chunking, replication, low-latency random access, and high throughput communication. DDStore achieves near-linear scaling for training a GNN model using up to 1000 GPUs on the Summit and Perlmutter supercomputers, and reaches up to a 6.15x reduction in GNN training time compared to state-of-the-art methodologies.

Choi, Jong Youl↗

DOE OSTI2018

Theory and Computation for Mesoscopic Materials Modeling

Accurate and efficient computational modeling of material behavior is essential to the DOE's mission of advancing the development of devices and components needed for power generation and storage. One of the outstanding challenges in atomistic simulation of condensed systems, such as solids, liquids, and glasses, is access to experimentally meaningful length and time scales. The project developed and improved several solution methods to overcome these challenges: diffusive molecular dynamics, adaptive kinetic Monte Carlo, coarse-graining of transition state theory, finite temperature coarse-graining methods for crystalline defects, and optimization-based atomistic-to-continuum coupling methods.

97 MATHEMATICS AND COMPUTING↗