Search NASA⌕ Search

SEARCH · Search NASA

Results for “defect evolution”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Design Principles for Efficient and Stable Water Splitting Photoelectrocatalysts

Photoelectrochemical water splitting is a promising avenue for sustainable production of hydrogen used in the chemical industry and hydrogen fuel cells. The basic components of most photoelectrochemical water splitting systems are semiconductor light absorbers coupled to electrocatalysts, which perform the desired chemical reactions. A critical challenge for the design of these systems is the lack of stability for the majority of desired semiconductors under operating water splitting conditions. One strategy to address this issue is to protect the semiconductor by covering it with a stabilizing insulator layer, creating a metal–insulator–semiconductor (MIS) architecture, which has demonstrated improved stability. In addition to enhanced stability, the insulator layer may significantly affect the electron and hole transfer, which governs the recombination rates. Furthermore, the insertion of an insulator layer leads to the introduction of additional insulator/electrocatalyst and insulator/semiconductor interfaces. These interfaces can impact the system’s performance significantly, and they need to be carefully engineered to optimize the efficiencies of MIS systems. In this Account, we describe our recent progress in shedding light on the critical role of the insulator and the interfaces on the performance of MIS systems. We discuss our findings by focusing on the concrete example of planar n-type Si protected by a HfO 2 insulator layer and coupled to a Ni or Ir electrocatalyst that performs the oxygen evolution reaction, one of the water splitting half-reactions. To improve our fundamental understanding of the insulator layer, we precisely control the HfO 2 insulator thickness using atomic layer deposition (ALD), and we perform a series of rigorous electrochemical experiments coupled with theory and modeling. We demonstrate that by tuning the insulator thickness, we can control the flux and recombination of photogenerated electrons and holes to optimize the generated photovoltage. Despite optimizing the thickness, we find that the maximum generated photovoltage in MIS systems is often significantly lower than the upper performance limit, i.e., there are additional losses in the system that could not be addressed by optimizing the insulator thickness. We identify the sources of these losses and describe strategies to minimize them by a combination of improving the semiconductor light absorption, removing nonidealities associated with interfacial defects, and finding alternative insulators with improved charge carrier selectivity. Finally, we quantify the improvements that can be obtained by implementing these specific strategies. Our collective work outlines strategies to analyze MIS systems, identify the sources of efficiency losses, and optimize the design to approach the fundamental performance limits. Furthermore, these general approaches are broadly applicable to photoelectrochemical materials that utilize sunlight to produce value-added chemicals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Tetracene Functionalized Si(111) Achieves Enhanced Solar-to-Chemical Energy Conversion via Molecular Acceptor States

The properties of semiconductor|liquid interfaces play a critical role in determining the efficiency of solar-to-hydrogen (STH) conversion. Here, we investigate how molecular functionalization of Si(111) and Si(111)|TiO 2 surfaces impacts photoelectrochemical (PEC) hydrogen production efficiency. We find that functionalization of ∼3% of the atop sites of Si(111) with either 9-anthracene (Anth) or 5-tetracene (Tet), with the remaining sites passivated by methyl groups, provides substrates with high electronic quality and low surface oxide densities, as determined by X-ray photoelectron spectroscopy (XPS) measurements. Surface photovoltage (SPV) spectroscopy shows that surfaces modified with Anth or Tet exhibit an increased photovoltage, with Tet-functionalized surfaces yielding an additional 192 meV relative to methyl-terminated Si(111), indicating improved charge separation for Si-Tet. Further improvement in onset potential was achieved by replacing a nitrogen-containing TiO 2 atomic layer deposition (ALD) precursor (TDMAT) with a precursor lacking nitrogen (TTIP), which eliminates the parasitic defect band in the TiO 2 overlayer (p-Si(111)-Tet|TTIP-TiO 2 |Pt: V OC = +0.283 ± 0.041 V vs RHE). Density functional theory (DFT) analysis demonstrates that compared with Anth-modified Si(111), the Tet-modified surface exhibits more hybridized Si(111)-Tet states closer to the silicon band edges. Mercury contact current–voltage (I–V, dark) measurements quantified the relative interfacial density of states of Si-Tet, Si-Anth and Si-Me surfaces─revealing that the interfacial state density was highest for Si-Tet. This suggests that such hybridized interfaces serve to capture better photoexcited charge, which enables facile electron transfer to molecular acceptors in solution. Altogether, the data indicate that beneficial hybrid molecular LUMO surface states interacting with the Si conduction band edge results in improved hydrogen evolution (HER) performance for p-Si devices.

Group theory↗
DOE OSTI2025

Evolution of the Electronic Gap of Directly Synthesized Versus Mechanically Transferred WS 2 Monolayer to Multilayer Films

The electronic properties of 2D materials play a critical role in determining their potential for device applications. Despite rapid developments in 2D semiconductors, studies of fundamental electronic parameters, including the electronic gap and ionization energy, are limited, with significant discrepancies in reported values. The study focuses on tungsten disulfide (WS₂) and investigates the electronic structure of films comprising an increasing number of layers deposited with two different methods: direct synthesis via metal–organic chemical vapor deposition (MOCVD) and additive mechanical transfer of exfoliated single layers. The films are characterized via Raman, UV–vis, and photoluminescence spectroscopies, as well as ultraviolet photoelectron and inverse photoemission spectroscopies (UPS/IPES). The electronic gap of WS₂ is found to decrease from 2.43 eV for the monolayer to 1.97 eV for the trilayer, indicating a bulk transition at the trilayer thickness. This reduction in the electronic gap is primarily due to the downward shift of the conduction band minimum relative to the valence band maximum. A comparative analysis with MOCVD-grown WS₂ reveals a slightly larger electronic gap for MOCVD-grown samples, attributed to differences in defect densities. The electronic levels evaluated through UPS/IPES highlight the significant influence of preparation methods on the electronic properties of WS₂.

2D materials↗
DOE OSTI2025

Active Learning Surrogates for Integrating Electron Microscopy and Computational Insights from Simulations in Autonomous Experiments

Artificial Intelligence (AI) combined with simulations and experiments has great potential to accelerate scientific discovery across technology and pharmaceuticals. However, the gap between simulations and experiments is challenging due to disparities in time and scale, making it difficult to estimate properties like energy and electronic states from experiments, and to provide feedback based on theoretical insights.Our research addresses the challenge by developing unique deep kernel based surrogate models that learns from microscopic images, mapping structural features to energy differences from defect formation. We start with full-training using simulated images to determine optimal settings, establishing a baseline for active learning. Using these settings from the baseline, active learning is trained, and predicts structures along simulation trajectories based on uncertainty and energetic stability, thus reducing data requirements, simulation time and computational costs. The results demonstrate that the model achieves a low average error margin of approximately 0.03 meV, indicating good performance. To enhance feature extraction and reconstruction capabilities, we developed an autoencoder-decoder as additional surrogate to create latent space to capture essential features, enabling precise comparisons between simulations and experiments. The results from this model achieved a reconstruction loss of around 0.2 and accurately reconstructed molecular structures.Overall, this work advances the steering of experiments through computational simulations by employing a surrogate models that actively predicts the trajectories of structural evolution, achieving time-to-solution comparable to experimental measurements.

Saranathan, Gayathri [Hewlett-Packard]↗
DOE OSTI2023

Dependence of simulated radiation damage on crystal structure and atomic misfit in metals

This study investigates the evolution of radiation damage in three metals in the low temperature and high radiant flux regime using molecular statics and a Frenkel pair accumulation method to simulate up to 2.0 displacements per atom. The metals considered include Fe, equiatomic CrCoNi, and a fictitious metal with similar bulk properties to the CrCoNi composed of a single atom type referred to as an A-atom. CrCoNi is found to sustain higher concentrations of dislocations than either the Fe or A-atom systems and more stacking faults than the A-atom system. The results suggest that the difference between the concentrations of vacancies and interstitials is substantially smaller for CrCoNi than the A-atom system, perhaps reflecting that the sink capture radius is smaller in CrCoNi due to the roughened potential energy landscape. A model that partitions the major contributions from defects to the stored energy is described, and serves to highlight a general need for higher fidelity approaches to point defect identification.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The microstructure effects on irradiation response of ferritic – martensitic steels

Microstructural optimization to achieve greater mechanical strength has been one of the focuses in ferritic–martensitic steels development. However, these optimized microstructures’ effects on the radiation response are not well known. In this work, two ferritic–martensitic steels (9Cr-NbMo and 9Cr-Ta) underwent neutron irradiation in the High Flux Isotope Reactor, and their room-temperature post-irradiation tensile properties and microstructure evolutions were investigated and compared. These two steels exhibit similar pre-irradiation tensile behavior, and their yield strengths are higher than that of other ferritic–martensitic steels by about 200–250 MPa. Microstructural characterization on pre-irradiated materials reveals a smaller grain size in 9Cr-Ta (2.8 ± 0.3 μm in 9Cr-Ta versus 4.3 ± 0.5 μm in 9Cr-NbMo) but higher dislocation density and precipitate density in 9Cr-NbMo. As is common for ferritic–martensitic steels at low irradiation temperatures (less than about 0.45T m ), irradiation-induced hardening at 400 °C was observed for both alloys. Irradiation at 490 °C causes the two alloys to exhibit different tensile behavior: 9Cr-Ta softens by 208 MPa in yield stress, whereas 9Cr-NbMo maintains strength. Additionally, microstructural characterizations were performed, including precipitate growth, dislocation, and defect formation. Using the barrier hardening model for microstructure–property correlation, the softening in irradiated 9Cr-Ta is primarily attributed to the significant dislocation recovery, while the strength lost from the slight dislocation recovery in 9Cr-NbMo was compensated by the additional strength from the irradiation-induced cavities. The microstructure effect (primarily precipitate, dislocation and boundary) on the radiation response is discussed herein.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Selective laser melting of 304L stainless steel: Role of volumetric energy density on the microstructure, texture and mechanical properties

The role of volumetric energy density on the microstructural evolution, texture and mechanical properties of 304L stainless steel parts additively manufactured via selective laser melting process is investigated. 304L is chosen because it is a potential candidate to be used as a matrix in a metal matrix composite with nanoparticles dispersion for energy and high temperature applications. The highest relative density of 99 %±0.5 was achieved using a volumetric energy density of 1400 J/mm 3 . Both XRD analysis and Scheil simulation revealed the presence of a small trace of the delta ferrite phase, due to rapid solidification within the austenitic matrix of 304L. Here, a fine cellular substructure ranged between 0.4–1.8 μm, was detected across different energy density values. At the highest energy density value, a strong texture in the direction of [100] was identified. At lower energy density values, multicomponent texture was found due to high nucleation rate and the existing defects. Yield strength, ultimate tensile strength, and microhardness of samples with a relative density of 99 % were measured to be 540 ± 15 MPa, 660 ± 20 MPa and 254 ± 7 HV, respectively and higher than mechanical properties of conventionally manufactured 304L stainless steel. Heat treatment of the laser melted 304L at 1200 °C for 2 h, resulted in the nucleation of recrystallized equiaxed grains followed by a decrease in microhardness value from 233 ± 3 HV to 208 ± 8 HV due to disappearance of cellular substructure.

304L stainless steel↗
DOE OSTI2022

Additive Manufacturing Flaw Assessment Methodology

An evolution fatigue data and flaw tolerance of components produced using the Powder Bed Fusion (PBF) Additive Manufacturing (AM) process is documented in this report. Initial differences in fatigue data for AM components compared to smooth bar fatigue data indicated a need for a more detailed analysis of AM data available in technical literature. The investigation was initiated to support the development of a fatigue analysis methodology for AM components to support the of codification of AM technology for pressure equipment. The project was initiated to collect and analyze stainless steel 304L and 316L AM fatigue test data and corresponding process and quality information to develop S-N and E-N based fatigue data representation. Additional AM fatigue test data including Inconel Ti-6-4 and aluminum alloys were also considered for comparison purposes Metallic AM parts tend to contain various forms of defects distributed throughout the part. If an AM part is subjected to fatigue loading in service, a fatigue analysis needs to be performed during the design process to ensure an acceptable service life for the part. Post-process machining and polishing do not to improve fatigue resistance in any significant degree. The low cycle fatigue regime is of particular interest to this project in support of flaw acceptance criteria currently under development by ASME’s BPTCS/BNCS. Internal defects become exposed as external surface defects during machining for the machining of the AM part to final dimensions. This implies that as long as inherent AM defects are within a controlled limit in terms of both size and distribution characteristics, the corresponding fatigue test data in terms of either S-N (stress life) or E-N (strain life) can be investigated and characterized to establish fatigue properties of AM parts for design and fatigue evaluation purposes. The resulting S-N or E-N curves and their scatter bands can be used to derive fatigue design allowable stress values by capturing the effects of distributed discontinuities within an acceptable limit.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The effect of Cr alloying on defect migration at Ni grain boundaries

Mass transport along grain boundaries in alloys depends not only on the atomic structure of the boundary, but also its chemical make-up. In this work, we use molecular dynamics to examine the effect of Cr alloying on interstitial and vacancy-mediated transport at a variety of grain boundaries in Ni. We find that, in general, Cr tends to reduce the rate of mass transport, an effect which is greatest for interstitials at pure tilt boundaries. However, there are special scenarios in which it can greatly enhance atomic mobility. Cr tends to migrate faster than Ni, though again this depends on the structure of the grain boundary. Further, grain boundary mobility, which is sometimes pronounced for pure Ni grain boundaries, is eliminated on the time scales of our simulations when Cr is present. We conclude that the enhanced transport and grain boundary mobility often seen in this system in experimental studies is the result of non-equilibrium effects and is not intrinsic to the alloyed grain boundary. These results provide new insight into the role of grain boundary alloying on transport that can help in the interpretation of experimental results and the development of predictive models of materials evolution.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Determining the Ensemble N -Representability of Reduced Density Matrices

The N-representability problem for reduced density matrices remains a fundamental challenge in electronic structure theory. Following our previous work that employs a unitary-evolution algorithm based on an adaptive derivative-assembled pseudo-Trotter variational quantum algorithm to probe pure-state N-representability of reduced density matrices [J. Chem. Theory Comput. 2024, 20, 9968], in this work we propose a practical framework for determining the ensemble N-representability of a p-body matrix. This is accomplished using a purification strategy that embeds an ensemble state into a pure state defined on an extended Hilbert space, such that the reduced density matrices of the purified state reproduce those of the original ensemble. By iteratively applying variational unitaries to an initial purified state, the proposed algorithm minimizes the Hilbert-Schmidt distance between its p-body reduced density matrix and a specified target p-body matrix, which serves as a measure of the N-representability of the target. This methodology facilitates both error correction of defective ensemble reduced density matrices and quantum-state reconstruction on a quantum computer, offering a route for density-matrix refinement. We validate the algorithm with numerical simulations on systems of two, three, and four electrons in both simple models as well as molecular systems at finite temperature, demonstrating its robustness.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Electrochemical Evolution of Fuel Cell Platinum Nanocatalysts on Carbon Nanotubes at the Atomic Scale

The evolution of Pt nanoparticles supported on carbon nanotubes is analyzed before and after electrochemical potential cycling, using identical location aberration-corrected transmission electron microscopy, for applications in proton exchange membrane fuel cells. The work is focused on the half-cell accelerated stress test protocol of potential cycles ranging between 1.0 and 1.5 V RHE to represent the start-up/shutdown settings of a fuel cell vehicle. The research work reveals that particle migration and coalescence are key mechanisms for a reduction in the Pt nanoparticle surface area at the early stages of potential cycling. Further, the mechanism for particle movement and coalescence is attributed to carbon corrosion, catalyzed either by Pt or by bulk corrosion of the carbon nanotubes. Carbon corrosion results in the appearance of carbon vacancies at the carbon nanotube/Pt nanoparticle interface during cycling, as well as the formation of edge and surface defects. During cycling, the concentration of the dissoluble Pt increases. As soon as a significant amount is reached, subnanometer/atomic clusters emerge on the carbon nanotube support, which can move and coalesce, or redeposit on the surface of larger particles through Ostwald ripening.

25 ENERGY STORAGE↗
DOE OSTI2021

Revealing the effect of local stresses on twin growth mechanisms in titanium using synchrotron X-ray diffraction

Deformation twinning has a significant impact on the evolution of microstructure and mechanical response in hexagonal close packed (hcp) metals. Understanding the physical mechanisms associated with twin nucleation and growth processes is important to enable the broad use of hcp metals. While both nucleation and growth are conditioned by the local stress state, few studies have quantified it in bulk deformed samples. In this study, we reveal the effects of local stresses on twin thickening using in-situ synchrotron experiments with differential aperture X-ray microscopy. High purity Ti is deformed under four-point bending to activate {1012} tensile twins. Further, 3D stress fields with a spatial resolution of 0.5μm are mapped in the vicinity of low and high macroscopic Schmid factor (MSF) twins growing inside a grain. Reconciling this experimental analysis with recent twin growth models reveals that the growth of low MSF twins is limited by the nucleation of twin growth defects in the high-purity Ti sample. While growth-inducing defect nucleation may occur in many places on the interface of the high resolved shear stress (RSS)/MSF twin, the nucleation rate of twinning disconnections for the low MSF twin is high only at the end of the twin near a stress concentration. Once nucleated, these defects easily propagate into lower RSS regions of the grain resulting in twin growth. This work highlights the importance of stress concentrations not only for twin (embryo) nucleation, but also to the growth process of twins, particularly in low MSF twins.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Thermal Evolution of Internal Strain in Doped PbTe

Recent improvements in the efficiency of heat-to-electricity energy conversion in lead chalcogenide thermoelectrics involve reducing the thermal conductivity by incorporating large amounts of internal strain. The extent to which typical lead chalcogenide processing techniques (such as doping, ball milling, and densification) increase internal strain and dislocation density must be quantified to improve materials design. In this study, neutron powder diffraction is leveraged to evaluate the internal strain introduced by ball milling in doped and undoped powders. Doping with Na and/or Eu increases internal strain beyond ball milling alone, with the greatest increase from combining the two dopants. Strain recovery occurs in each powder above 400 K but can be suppressed by co-doping, indicating a strong dopant–dislocation interaction in this system. Therefore, high-temperature processing of PbTe powders should be avoided if high internal strain is desired. Low-temperature densification and/or rapid pressing techniques may be key to maintaining internal strain in the final pressed pellet. The diffraction peak asymmetry and correlated elastic softening measured in pressed PbTe pellets in past studies were not observed in the precursor powders measured here, suggesting that measurements of the Debye temperature on final pressed pellets are required to examine the influence of defect-induced elastic softening on thermal conductivity. This work provides key guidance for defect engineering to maximize internal strain and thermoelectric performance in PbTe thermoelectrics.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Manipulating Na/TM Ratio‐Driven Structural Heterogeneity of O3‐NaNi 1/3 Fe 1/3 Mn 1/3 O 2 Cathode for High‐Voltage Sodium‐Ion Batteries

The stability of O3-type NaNi 1/3 Fe 1/3 Mn 1/3 O 2 under high-voltage cycling is dictated by how synthesis encodes lattice strain and redox heterogeneity. Here, in this study, the role of Na:TM stoichiometry is systematically resolved by tuning the NaOH:precursor ratio during solid-state synthesis. The stoichiometric condition (Na:TM = 1.00) yields minimized microstrain, enabling uniform O3–P3 phase evolution and homogeneous multi-metal redox with preserved octahedral symmetry. In contrast, Na-excess compositions inherit disordered intermediates and heterogeneous distortion fields that trigger abrupt multiphase transitions and promote localized charge redistribution. In situ XRD captures the divergence in phase-transition pathways, TXM resolves particle-level redox heterogeneity, and XANES corroborates a stronger and more reversible Fe redox contribution at stoichiometry, shifting to diminished Fe participation and spatially inhomogeneous redox at higher Na content. These results establish Na:TM stoichiometry as a critical synthesis parameter controlling both structural coherence and redox stability. Electrochemically, the stoichiometric composition exhibits smooth voltage profiles with minimal polarization growth and retains nearly 80% of its initial capacity after 100 cycles even at an extended 4.2 V cutoff, whereas Na-excess compositions show significantly reduced initial coulombic efficiency and rapid voltage fade. Precise stoichiometric tuning provides a scalable route to defect-suppressed O3 frameworks, enabling structurally resilient, high-voltage sodium-layered cathodes.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Kinetic Simulations of Microstructural Evolution (KSOME)

"Kinetic simulations of microstructural evolution" (KSOME) is an object Kinetic Monte Carlo (OMKC) simulation code. It is developed to simulate microstructural evolution in materials during irradiation. KSOME is developed from ground up with priority given to the flexibility, ease of upgradability, and computation efficiency, in that order. With previously developed simulation codes, various processes (more precisely, the diffusion-reaction processes) that can occur in a system were hardwired into the code. Hence, to perform higher fidelity simulations, a significant coding effort was required every time to incorporate either a more accurate description of existing processes or new processes. With KSOME, the necessity for frequent code upgrades whenever there is a need to perform higher fidelity simulations is either eliminated or reduced significantly. In KSOME, the categories of various diffusion-reaction processes and the data-management system are hardwired, while the execution of the diffusion-reaction processes specific to a system is specified via input files. In the present version of KSOME, the analytical expression required to calculate defect interaction radii are inputted via a text file. However, the ability to parse mathematical expressions from a text file can be extended to input the analytical expression to calculate other defect properties; including the expressions to calculate the change in the migration barriers of mobile defects due to long-range interaction with extended defects

Nandipati, Giridhar [Pacific Northwest National La↗
DOE OSTI2022

A fusion relevant data-driven engineering void swelling model for 9Cr tempered martensitic steels

The UCSB database on cavity evolution in 9-12Cr tempered martensitic steels (TMS), includes the results for both dual heavy and helium ion (DII), and High Flux Isotope Reactor (HFIR) in situ helium injection (ISHI) neutron irradiations at 500°C. These results were combined with literature single ion and fission neutron irradiation data to derive a model for the void volume fraction, f v , as a function of displacements per atom (dpa) and transmutant helium concentrations in atomic parts per million (appm). The scientific foundation for the paper is described in a companion paper entitled “Cavity Evolution and Void Swelling in Dual Ion Irradiated Tempered Martensitic Steels”. Here, in this study, we show that f v (dpa, He/dpa) is described by the incubation dose, dpa i , for the onset of void growth, and the post-incubation growth rate, f v ’(%/dpa). Both dpa i and f v ’ decrease with increasing He/dpa at > ~ 5. The dpa i is also lower for the ISHI neutron irradiations at the same He/dpa. Single heavy ion and fission reactor neutron irradiations, with low He/dpa ratios, have a much larger dpa i . Based on a combined analysis of DII, single ion, ISHI and fission neutron data, we further show that the post-incubation f v data analyzed here have a common empirical curve shape, with f v ’ reaching up to ~ 0.2%/dpa at very high dpa. We also show that f v ’ can be predicted based on a physical model of defect partitioning between evolving sinks. At 500°C and fusion relevant He/dpa ≈ 10, the best-fit model predicts nominal swelling, S = f v /(1-f v ), of ~ 1.1, 4.9 and 16% at 50, 100 and 200 dpa, respectively. The physically motivated, data-driven model includes estimated uncertainties for both dpa i and f v ’.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Morphology-driven oxygen evolution performance of NiO x nanostructures and implications for hole transport in perovskite solar cells

Morphology-controlled nanostructures provide an effective strategy to modulate both oxygen evolution reaction (OER) activity and photovoltaic performance in perovskite solar cells (PSCs). However, achieving low OER overpotentials and high power conversion efficiency (PCE) simultaneously through morphology engineering remains challenging. In this work, nickel oxide (NiO x ) nanostructures with spindle-like (NiO x -NS) and plate-like (NiO x -NP) morphologies were synthesized and evaluated as bi-functional OER catalysts and hole transport layers (HTLs) in inverted PSCs. Structural and thermal analyses reveal that NiO x -NS crystallizes into a cubic phase at a lower temperature (300 °C), whereas NiO x -NP requires higher calcination temperatures, reflecting differences in precursor microstructure. Electrochemical measurements indicate that NiO x -NS calcined at 300 °C delivers the lowest OER overpotential (395 mV at 10 mA cm −2 ), outperforming NiO x -NP calcined at 400 °C (565 mV) and 500 °C (474 mV). This enhanced activity is ascribed to favorable surface strain, increased defect density, and advantageous facet exposure. When used as HTLs, NiO x -NS also delivers the highest PCE (13.25%) among all tested devices, exceeding those based on NiO x -NP and commercial NiO x , owing to improved hole extraction and interfacial contact. Overall, this study highlights the importance of morphology control and thermal processing in tailoring NiO x for multifunctional nanomaterials in electrocatalytic and photovoltaic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Demonstration of Decentralized Physics-Driven Learning

In typical artificial neural networks, neurons adjust according to global calculations of a central processor, but in the brain, neurons and synapses self-adjust based on local information. Contrastive learning algorithms have recently been proposed to train physical systems, such as fluidic, mechanical, or electrical networks, to perform machine-learning tasks from local evolution rules. However, to date, such systems have only been implemented in silico due to the engineering challenge of creating elements that autonomously evolve based on their own response to two sets of global boundary conditions. Here, we introduce and implement a physics-driven contrastive learning scheme for a network of variable resistors, using circuitry to locally compare the response of two identical networks subjected to the two different sets of boundary conditions. Using this method, our system effectively trains itself, optimizing its resistance values without the use of a central processor or external information storage. Once the system is trained for a specified allostery, regression, or classification task, the task is subsequently performed rapidly and automatically by the physical imperative to minimize power dissipation in response to the given voltage inputs. Here, we demonstrate that, unlike typical computers, such learning systems are robust to extreme damage (and thus manufacturing defects) due to their decentralized learning. Our twin-network approach is therefore readily scalable to extremely large or nonlinear networks, where its distributed nature will be an enormous advantage; a laboratory network of only 500 edges will already outpace its in silico counterpart.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗