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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Expanding Repository Data Available For Sharing and Knowledge Discovery

Some of the hardest space biology and space health challenges require data-intensive, bioinformatic, meta-analytical, and computer-assisted research approaches. These challenges include examining interdisciplinary space life science research across experiments and across interacting spaceflight hazards (radiation, altered gravity, confinement, hostile-closed environments, distance-duration from Earth). The approaches to confront these challenges involve mining multiple datasets simultaneously from various hierarchical organizations of biological complexity, all while concurrently evaluating how experimental design factors affect endpoints of standard assays. To enable this field, it is essential that principal investigators (PIs) submit data in a structure so it can be maximally re-used. The purpose of the NASA Ames Life Sciences Data Archive (ALSDA) is to collect, curate, and make publicly available all non-human space-relevant biological data. ALSDA must also ensure data are open-access, and maximally findable, accessible, interoperable, and reusable (FAIR). The scope of ALSDA data collected and submitted by PIs include subject and study design metadata, assay metadata parameters, raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). ALSDA recently integrated into a collaborative group of Open Science projects to facilitate a suite of new tools and workflows that will improve data submission, accessibility, and reusability by implementing digital data submission agreements, and adopting the data management system originally developed by NASA GeneLab. ALSDA intends to bring current biological repository data and all future collected data into this new scientific data reuse reality. This new suite of tools will enable ALSDA to deploy a science curation system using scientific assay configurations for the data submission portal. It will capture essential assay parameters according to established standards in each sub-field within biology. The submission portal expedites data collection by enhancing ease of PI data submission, providing a user interface and specificity for which data is to be submitted. Data submissions can be brought into cutting-edge informatic analysis portals to enable mining of physiological, behavioral, biochemical, and imaging datasets in conjunction with ‘omics-level datasets. As ALSDA datasets are submitted, curated, and published (e.g., micro-computed tomography, histology, pulse oximetry, serum metabolites, magnetic resonance imaging, intraocular pressure, novel object recognition, etc.), the merging together of spaceflight data along this multi-hierarchical complexity of biology will enable informatics and data-intensive approaches resulting in knowledge discoveries across missions, space hazards, and biological disciplines.

Biology↗
NASA NTRSDate not supplied

Expanding Repository Data Available For Sharing And Knowledge Discovery

Some of the hardest space biology and space health challenges require data-intensive, bioinformatic, meta-analytical, and computer-assisted research approaches. These challenges include examining interdisciplinary space life science research across experiments and across interacting spaceflight hazards (radiation, altered gravity, confinement, hostile-closed environments, distance-duration from Earth). The approaches to confront these challenges involve mining multiple datasets simultaneously from various hierarchical organizations of biological complexity, all while concurrently evaluating how experimental design factors affect endpoints of standard assays. To enable this field, it is essential that principal investigators (PIs) submit data in a structure so it can be maximally re-used. The purpose of the NASA Ames Life Sciences Data Archive (ALSDA) is to collect, curate, and make publicly available all non-human space-relevant biological data. ALSDA must also ensure data are open-access, and maximally findable, accessible, interoperable, and reusable (FAIR). The scope of ALSDA data collected and submitted by PIs include subject and study design metadata, assay metadata parameters, raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). ALSDA recently integrated into a collaborative group of Open Science projects to facilitate a suite of new tools and workflows that will improve data submission, accessibility, and reusability by implementing digital data submission agreements, and adopting the data management system originally developed by NASA GeneLab. ALSDA intends to bring current biological repository data and all future collected data into this new scientific data reuse reality. This new suite of tools will enable ALSDA to deploy a science curation system using scientific assay configurations for the data submission portal. It will capture essential assay parameters according to established standards in each sub-field within biology. The submission portal expedites data collection by enhancing ease of PI data submission, providing a user interface and specificity for which data is to be submitted. Data submissions can be brought into cutting-edge informatic analysis portals to enable mining of physiological, behavioral, biochemical, and imaging datasets in conjunction with ‘omics-level datasets. As ALSDA datasets are submitted, curated, and published (e.g., micro-computed tomography, histology, pulse oximetry, serum metabolites, magnetic resonance imaging, intraocular pressure, novel object recognition, etc.), the merging together of spaceflight data along this multi-hierarchical complexity of biology will enable informatics and data-intensive approaches resulting in knowledge discoveries across missions, space hazards, and biological disciplines.

life science↗
NASA NTRS1995

User's manual for CBS3DS, version 1.0

CBS3DS is a computer code written in FORTRAN 77 to compute the backscattering radar cross section of cavity backed apertures in infinite ground plane and slots in thick infinite ground plane. CBS3DS implements the hybrid Finite Element Method (FEM) and Method of Moments (MoM) techniques. This code uses the tetrahedral elements, with vector edge basis functions for FEM in the volume of the cavity/slot and the triangular elements with the basis functions for MoM at the apertures. By virtue of FEM, this code can handle any arbitrarily shaped three-dimensional cavities filled with inhomogeneous lossy materials; due to MoM, the apertures can be of any arbitrary shape. The User's Manual is written to make the user acquainted with the operation of the code. The user is assumed to be familiar with the FORTRAN 77 language and the operating environment of the computer the code is intended to run.

Reddy, C. J.↗
NASA NTRS1999

Ninth Thermal and Fluids Analysis Workshop Proceedings

The Ninth Thermal and Fluids Analysis Workshop (TFAWS 98) was held at the Ohio Aerospace Institute in Cleveland, Ohio from August 31 to September 4, 1998. The theme for the hands-on training workshop and conference was "Integrating Computational Fluid Dynamics and Heat Transfer into the Design Process." Highlights of the workshop (in addition to the papers published herein) included an address by the NASA Chief Engineer, Dr. Daniel Mulville; a CFD short course by Dr. John D. Anderson of the University of Maryland; and a short course by Dr. Robert Cochran of Sandia National Laboratories. In addition, lectures and hands-on training were offered in the use of several cutting-edge engineering design and analysis-oriented CFD and Heat Transfer tools. The workshop resulted in international participation of over 125 persons representing aerospace and automotive industries, academia, software providers, government agencies, and private corporations. The papers published herein address issues and solutions related to the integration of computational fluid dynamics and heat transfer into the engineering design process. Although the primary focus is aerospace, the topics and ideas presented are applicable to many other areas where these and other disciplines are interdependent.

Sakowski, Barbara↗
DOE OSTI2025

DriveSense: A Noise-Resilient Framework for Driving Mode Identification

Accurate drive mode classification is essential for enhancing the reliability and predictive maintenance of heavy-duty electric trucks. This study proposes a novel fuzzy logic-based framework, DriveSense, for real-time drive mode classification, addressing key challenges such as sensor noise, transitional behaviors, and computational efficiency. The proposed approach integrates a two-stage filtering pipeline, combining adaptive outlier removal and a dynamic Kalman filter to enhance data quality. A fuzzy inference system with smoothened trapezoidal membership functions is then applied to classify driving modes into standstill, constant speed, acceleration, and deceleration while mitigating the effects of noise and edge cases. Performance evaluation using real-world and simulated drive cycles demonstrates significant improvements in classification accuracy (up to 97.8%), F1-score (up to 0.97), and robustness against noise, while reducing false positives. Comparative analysis against baseline models, demonstrates DriveSense’s superior accuracy and generalizability across diverse driving patterns. The framework’s lightweight and interpretable fuzzy inference engine operates with low computational latency, ensuring compatibility with real-time embedded systems typical of heavy-duty electric trucks. Moreover, DriveSense models transitional behaviors through overlapping fuzzy sets and adaptive borderline classification logic, enabling smooth identification of subtle shifts such as rolling stops or gradual deceleration. These results highlight DriveSense’s potential to enhance predictive maintenance strategies, reduce downtime, and support scalable, fleet-wide diagnostics.

Kumar, Praveen [Oak Ridge National Laboratory (ORN↗
NASA NTRS1996

High-Performance Parallel Analysis of Coupled Problems for Aircraft Propulsion

This research program dealt with the application of high-performance computing methods to the numerical simulation of complete jet engines. The program was initiated in January 1993 by applying two-dimensional parallel aeroelastic codes to the interior gas flow problem of a bypass jet engine. The fluid mesh generation, domain decomposition and solution capabilities were successfully tested. Attention was then focused on methodology for the partitioned analysis of the interaction of the gas flow with a flexible structure and with the fluid mesh motion driven by these structural displacements. The latter is treated by a ALE technique that models the fluid mesh motion as that of a fictitious mechanical network laid along the edges of near-field fluid elements. New partitioned analysis procedures to treat this coupled three-component problem were developed during 1994 and 1995. These procedures involved delayed corrections and subcycling, and have been successfully tested on several massively parallel computers, including the iPSC-860, Paragon XP/S and the IBM SP2. For the global steady-state axisymmetric analysis of a complete engine we have decided to use the NASA-sponsored ENG10 program, which uses a regular FV-multiblock-grid discretization in conjunction with circumferential averaging to include effects of blade forces, loss, combustor heat addition, blockage, bleeds and convective mixing. A load-balancing preprocessor tor parallel versions of ENG10 was developed. During 1995 and 1996 we developed the capability tor the first full 3D aeroelastic simulation of a multirow engine stage. This capability was tested on the IBM SP2 parallel supercomputer at NASA Ames. Benchmark results were presented at the 1196 Computational Aeroscience meeting.

Felippa, C. A.↗
DOE OSTI2018

Plasma Surface Interactions: Bridging from the Surface to the Micron Frontier through Leadership Class Computing (Final Technical Progress Report)

The performance demands on plasma-facing components (PFCs) in future fusion power plants are beyond the capability of current materials. In defining the plasma-surface interaction (PSI), it is evident that three coupled spatial regions influence PFC materials evolution and performance. These regions consist of (1) the edge and scrape-off layer region of the plasma, (2) the near-surface material response to extreme thermal and particle fluxes under the influence of, and feedback to, the plasma sheath, and (3) the structural material’s response to an intense, 14 MeV peaked neutron spectrum, which produces very high concentrations of transmuted elements through (n,p) and (n,α) reactions and structural material property degradation. The objective of this project is to develop and deploy validated, high-performance simulation tools capable of predicting the performance of tungsten-based plasma-facing components (PFCs) in a burning fusion plasma environment, which includes modeling surface morphology evolution in either erosion or re-deposition regimes, and the recycling of hydrogen species. This requires the development of a leadership-scale computational code to predict PFC behavior that is well integrated to a suite of multiscale modeling techniques to bridge the scales needed to address complex physical and computational issues at the plasma surface interface and the transition region below the surface where neutron damage processes in the bulk dominate material behavior. Successful completion of this project will provide PFC simulation tools to evaluate steady-state performance of tungsten-based PFC and divertor components in burning plasma environments. This will enable the identification of critical experiments to confirm whether practical PFC solutions exist for magnetic fusion energy beyond ITER. More specifically, the research activities within this project focus on two broadly defined research thrusts: 1) Developing a new simulation code, Xolotl-PSI to predict PFC operating lifetime and performance, that is specifically designed to take advantage of leadership class computing facilities; and 2) Integrating and applying discrete particle-based, as well as continuum-based, multiscale modeling techniques to provide scientific discovery of the mechanisms controlling PFC and bulk materials evolution under fusion plasma and 14-MeV neutron exposure; in this thrust, the challenge of scale-bridging between atomistic/microstructural modeling and the continuum-scale of PFC device performance is achieved through multiscale modeling techniques. Throughout the grant period, research at UMass Amherst focused on the atomic-scale analysis of the dynamics and kinetics (transport and reactions) of small mobile helium clusters near surfaces and grain boundaries in plasma-exposed tungsten, as well as the proper parameterization and incorporation of these processes into our SciDAC team’s continuum-level cluster dynamics code (Xolotl). Our work also included characterization of large-scale molecular-dynamics (MD) simulation results of helium implantation into tungsten based on the findings of our analysis and comparisons of Xolotl simulation predictions with the large-scale MD simulation results for Xolotl validation purposes; emphasis was placed on the impact of helium cluster dynamics/kinetics on tungsten surface morphology, near-surface tungsten structure, and helium retention. Furthermore, our work included initiation of a research program on evaluating the impact of structural defects in tungsten due to plasma exposure (such as helium nanobubbles) on tungsten’s thermophysical properties, focusing on lattice thermal conductivity. Our studies contributed to a fundamental understanding of the effects of plasma-surface interactions on the dynamical response of plasma-facing materials in nuclear fusion devices and the development of predictive hierarchical multiscale computational tools for the quantitative description of the material’s dynamical response to plasma exposure.

36 MATERIALS SCIENCE↗
DOE OSTI2025

xGFabric: Coupling Sensor Networks and HPC Facilities with Private 5G Wireless Networks for Real-Time Digital Agriculture

Advanced scientific applications require coupling distributed sensor networks with centralized high-performance computing facilities. Citrus Under Protective Screening (CUPS) exemplifies this need in digital agriculture, where citrus research facilities are instrumented with numerous sensors monitoring environmental conditions and detecting protective screening damage. CUPS demands access to computational fluid dynamics codes for modeling environmental conditions and guiding real-time interventions like water application or robotic repairs. These computing domains have contrasting properties: sensor networks provide low-performance, limited-capacity, unreliable data access, while high-performance facilities offer enormous computing power through high-latency batch processing. Private 5G networks present novel capabilities addressing this challenge by providing low latency, high throughput, and reliability necessary for near-real-time coupling of edge sensor networks with HPC simulations. This work presents xGFabric, an end-to-end system coupling sensor networks with HPC facilities through Private 5G networks. The prototype connects remote sensors via 5G network slicing to HPC systems, enabling real-time digital agriculture simulation.

Digital Agriculture↗
NASA NTRS1993

Analysis of a high speed civil transport configuration at subsonic flow conditions using a Navier-Stokes solver

Computations of three dimensional vortical flows over a generic High Speed Civil Transport (HSCT) configuration with an aspect ratio of 3.04 are performed using a thin-layer Navier-Stokes solver. The HSCT cruise configuration is modeled without leading or trailing edge flap deflections and without engine nacelles. The flow conditions, which correspond to tests done in the NASA Langley 8-Foot Transonic Pressure Tunnel (TPT), are a subsonic Mach number of 0.3 and Reynolds number of 4.4 million for a range-of-attack (-.23 deg to 17.78 deg). The effects of the farfield boundary location with respect to the body are investigated. The boundary layer is assumed turbulent and simulated using an algebraic turbulence model. The key features of the vortices and their interactions are captured. Grid distribution in the vortex regions is critical for predicting the correct induced lift. Computed forces and surface pressures compare reasonably well with the experimental TPT data.

Lessard, Victor R.↗
DOE OSTI2021

Erosion of focus rings in capacitively coupled plasma etching reactors

In plasma etching reactors, the structure surrounding the wafer, often called a focus ring (FR), plays an important role in maintaining uniform fluxes of reactants across the wafer. The FR is typically made of dielectric materials. During the plasma etching process, the sheath that forms over the wafer to accelerate ions anisotropically into the surface extends over the FR. Electrical charging of the FR modifies the sheath relative to that over the wafer. On the one hand, one wants the sheath to be uniform across the wafer-FR boundary to enable uniform fluxes to the edge of the wafer. On the other hand, maintaining a high voltage sheath over the FR will erode the FR, which is undesirable as the FR is a consumable component that must be periodically replaced in high volume manufacturing. In this work, we computationally investigated the consequences of dielectric constant ε of the FR materials on erosion of the FR. The series capacitance of the FR and its underlying structure is typically smaller than that of the wafer and its underlying structure. As a result, the FR charges quickly relative to the wafer, which then reduces the voltage across the sheath on top of the FR. The ion energy and angular distributions (IEADs) striking the FR are, therefore, generally lower in energy with a broader angular distribution. With ε = 2, the ion energies striking the middle to the outer edge of the FR are 30–180 eV, whereas for ε = 100, the ion energies are 120–380 eV. At the transition between the wafer and the FR, there is a skew in the IEAD as large as 15° that results from the difference in sheath thickness above the wafer and the FR. This skew and the erosion rate across the FR are functions of the dielectric constant of the FR material. With low ε, the FR charges quickly, less plasma is produced above the FR, and there is less voltage across the sheath that results in less FR erosion. Increasing ε of the FR produces a higher sheath voltage as well as higher ion fluxes over the FR, which increases erosion, while the skew at the edge of the wafer is less severe. Further, the material of the subsurface portion of the FR, which dominates its capacitance, is an important consideration in the design of the substrate assembly.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Bragg edge imaging (BEI) of B12W and M8N socket sections of the Arecibo telescope

From neutron user principal investigator: We kindly request the public release of three neutron imaging datasets through ONCat. All datasets were collected from two forensic specimens, B12W and M8N, sectioned from zinc-filled steel-wire sockets recovered from the collapsed Arecibo Telescope. The dataset titled “Neutron radiographs of B12W and M8N socket sections of the Arecibo telescope” contains normalized two-dimensional (2D) neutron radiographs of the specimens, showing the geometry and spatial distribution of the steel wires embedded within the zinc matrix, as well as internal features such as voids and cracks. The dataset titled “Neutron computed tomography of B12W and M8N socket sections of the Arecibo telescope” contains normalized 2D neutron projection images acquired over a range of specimen rotation angles for one selected region of each specimen. These projection images were used to reconstruct three-dimensional (3D) tomographic volumes that reveal the embedded-wire geometry and internal defects. The dataset titled “Bragg edge imaging (BEI) of B12W and M8N socket sections of the Arecibo telescope” contains six time-of-flight (TOF) neutron imaging datasets, three from each specimen, acquired at regions of interest selected based on the radiographs. The spatially resolved 2D TOF images show the zinc matrix and embedded steel wires, and the wavelength-dependent neutron transmission data were used to characterize crystallographic texture within the zinc. All components and their condition are in the public domain as they are the property of the National Science Foundation (NSF). The neutron imaging data, part geometries, and detailed forensic information have been widely published in the Arecibo Telescope Collapse Forensic Report by Thornton Tomasetti Engineers and others (NASA report and NASEM report).

Bilheux, Hassina↗
NASA NTRSDate not supplied

Nondestructive Evaluation for the Space Shuttle's Wing Leading Edge

The loss of the Space Shuttle Columbia highlighted concerns about the integrity of the Shuttle's thermal protection system, which includes Reinforced Carbon-Carbon (RCC) on the leading edge. This led NASA to investigate nondestructive evaluation (NDE) methods for certifying the integrity of the Shuttle's wing leading edge. That investigation was performed simultaneously with a large study conducted to understand the impact damage caused by errant debris. Among the many advanced NDE methods investigated for applicability to the RCC material, advanced digital radiography, high resolution computed tomography, thermography, ultrasound, acoustic emission and eddy current systems have demonstrated the maturity and success for application to the Shuttle RCC panels. For the purposes of evaluating the RCC panels while they are installed on the orbiters, thermographic detection incorporating principal component analysis (PCA) and eddy current array scanning systems demonstrated the ability to measure the RCC panels from one side only and to detect several flaw types of concern. These systems were field tested at Kennedy Space Center (KSC) and at several locations where impact testing was being conducted. Another advanced method that NASA has been investigating is an automated acoustic based detection system. Such a system would be based in part on methods developed over the years for acoustic emission testing. Impact sensing has been demonstrated through numerous impact tests on both reinforced carbon-carbon (RCC) leading edge materials as well as Shuttle tile materials on representative aluminum wing structures. A variety of impact materials and conditions have been evaluated including foam, ice, and ablator materials at ascent velocities as well as simulated hypervelocity micrometeoroid and orbital debris impacts. These tests have successfully demonstrated the capability to detect and localize impact events on Shuttle's wing structures. A first generation impact sensing system has been designed for the next Shuttle flight and is undergoing final evaluation for deployment on the Shuttle's first return to flight. This system will employ wireless accelerometer sensors that were qualified for other applications on previous Shuttle flights. These sensors will be deployed on the wing's leading edge to detect impacts on the RCC leading edge panels. The application of these methods will help to insure the continued integrity of the Shuttle wing's leading edge system as the Shuttle flights resume and until their retirement.

Eric I Madaras↗
NASA NTRS2012

High-Speed Edge-Detecting Line Scan Smart Camera

A high-speed edge-detecting line scan smart camera was developed. The camera is designed to operate as a component in a NASA Glenn Research Center developed inlet shock detection system. The inlet shock is detected by projecting a laser sheet through the airflow. The shock within the airflow is the densest part and refracts the laser sheet the most in its vicinity, leaving a dark spot or shadowgraph. These spots show up as a dip or negative peak within the pixel intensity profile of an image of the projected laser sheet. The smart camera acquires and processes in real-time the linear image containing the shock shadowgraph and outputting the shock location. Previously a high-speed camera and personal computer would perform the image capture and processing to determine the shock location. This innovation consists of a linear image sensor, analog signal processing circuit, and a digital circuit that provides a numerical digital output of the shock or negative edge location. The smart camera is capable of capturing and processing linear images at over 1,000 frames per second. The edges are identified as numeric pixel values within the linear array of pixels, and the edge location information can be sent out from the circuit in a variety of ways, such as by using a microcontroller and onboard or external digital interface to include serial data such as RS-232/485, USB, Ethernet, or CAN BUS; parallel digital data; or an analog signal. The smart camera system can be integrated into a small package with a relatively small number of parts, reducing size and increasing reliability over the previous imaging system..

Prokop, Norman F.↗
DOE OSTI2023

Site-Selective Atomic Layer Deposition on Rutile TiO 2 : Selective Hydration as a Route to Target Point Defects

Routes to area-and especially site-selective atomic layer deposition (ALD) remain an enticing challenge in precision surface science, despite the potentially game-changing capability for many energy applications. An unparalleled level of surface reaction control is required to direct ALD to select sites on the same nominal material, for example, targeted growth on distinct phases, facets, step-edges, and/or defects. However, as a sequential surface synthesis method, ALD is uniquely suited to these challenges, including the possibility of selective deposition at defective surface atom arrangements. Here, we computationally identify conditions for site-selective ALD through hydration of surface defects, including oxygen vacancies and titanium interstitials on low-index rutile TiO 2 facets. First-principles computation is used to predict, as a function of temperature, the hydroxylation of defects that are targeted by proton-exchange-mediated ALD processes. In situ ellipsometric measurements of ALD Al 2 O 3 nucleation on TiO 2 (110) single crystals prepared with and without abundant oxygen vacancies demonstrate striking contrast, corroborating computational predictions and revealing a mechanistically clear path to site-selective ALD.

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

Single and dual metal atom catalysts for enhanced singlet oxygen generation and oxygen reduction reaction

We demonstrate rational design of graphene-supported single and dual metal atom catalysts (SACs and DACs) for photocatalytic applications, such as singlet oxygen ( 1 O 2 ) sensitization and H 2 O 2 production. Here we combine density functional theory (DFT) and time-dependent DFT (TD-DFT) calculations with experimental verifications. We found a synergistic effect between triplet sensitization and triplet–triplet (Dexter) energy transfer; both play a role in the photocatalytic activity through the volcano plot of 3d transition metal SACs. More specifically, FeN 4 -SAC exhibits a low ISC energy gap (ΔE ISC ) of 0.039 eV, compared with 0.108 eV for FeNiN8-DACs, both possessing a high Bader charge transfer of 0.366 e- and 0.405 e-, respectively. Guided by these computational results, we synthesized a series of SACs and a DAC and confirmed their structures with scanning transmission electron microscopy (STEM) along with the X-ray absorption near-edge structure (XANES) and extended X-ray absorption fine structure (EXAFS). We then confirm their band structures with low-energy inverse photoemission spectroscopy (LEIPS) and UV-vis-NIR. Subsequently, we synthesized the catalysts for the photooxygenation of anthracene and two-electron oxygen reduction reaction (ORR) to measure their photocatalytic activity. We found that H 2 O 2 production through the two-electron ORR competes with the 1 O 2 generation through Dexter energy transfer. FeN 4 -SAC demonstrates a high photooxygenation conversion of 86% and a high 1 O 2 quantum yield of 1.04, obtained from electron spin resonance (ESR) spectroscopy, with low H 2 O 2 production. In contrast, NiN 4 -SAC exhibits a low 1 O 2 generation and a high H 2 O 2 production mainly because of the high Gibbs free energy of the OOH* intermediate. In conclusion, this work proposes an effective DFT-guided strategy for designing SACs and DACs for various photocatalytic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Unlocking the potential: machine learning applications in electrocatalyst design for electrochemical hydrogen energy transformation

Machine learning (ML) is rapidly emerging as a pivotal tool in the hydrogen energy industry for the creation and optimization of electrocatalysts, which enhance key electrochemical reactions like the hydrogen evolution reaction (HER), the oxygen evolution reaction (OER), the hydrogen oxidation reaction (HOR), and the oxygen reduction reaction (ORR). This comprehensive review demonstrates how cutting-edge ML techniques are being leveraged in electrocatalyst design to overcome the time-consuming limitations of traditional approaches. ML methods, using experimental data from high-throughput experiments and computational data from simulations such as density functional theory (DFT), readily identify complex correlations between electrocatalyst performance and key material descriptors. Leveraging its unparalleled speed and accuracy, ML has facilitated the discovery of novel candidates and the improvement of known products through its pattern recognition capabilities. This review aims to provide a tailored breakdown of ML applications in a format that is readily accessible to materials scientists. Hence, we comprehensively organize ML-driven research by commonly studied material types for different electrochemical reactions to illustrate how ML adeptly navigates the complex landscape of descriptors for these scenarios. We further highlight ML's critical role in the future discovery and development of electrocatalysts for hydrogen energy transformation. Potential challenges and gaps to fill within this focused domain are also discussed. As a practical guide, we hope this work will bridge the gap between communities and encourage novel paradigms in electrocatalysis research, aiming for more effective and sustainable energy solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Ab Initio modeling of Near-Edge EELS spectra for chemisorbed molecules

Abstract Electron energy loss spectroscopy (EELS) has recently been applied to probe chemisorbed molecules on metal nanostructures, but a fundamental understanding of the correlation between these spectra and the electronic structures of the adsorbates has been limited. We report here on the insights afforded by time-dependent density functional theory to decipher the energy loss near edge structure (ELNES) of EELS spectra associated with chemisorption. These first-principles calculations simulate the ELNES-EELS spectra for chemisorbed CO on various facets of Au and Pt. Computational predictions of key signatures such as the ‘red shift’ and reductions in the peak intensity of the 2 π * and 6 σ * peaks, as compared to free CO in the gas phase, are validated in comparison to experimentally collected EELS spectra. These signatures are revealed to arise from changes in the electronic structure in terms of unoccupied density of states associated with the chemisorption process. They are consistent with a Blyholder model that incorporates donation and back-donation of electrons. They are also characteristic of the chemisorption process, such as the choice of metal, site of adsorption and the coverage and distribution of adsorbates. Our simulations thus provide guidelines for the use of ELNES-EELS to characterize the atomic structure and adsorption property of nanostructured surfaces and facilitate the development of advanced nanomaterials for catalytic applications.

Materials Science↗
DOE OSTI2018

Dynamical signature of fractionalization at a deconfined quantum critical point

Deconfined quantum critical points govern continuous quantum phase transitions at which fractionalized (deconfined) degrees of freedom emerge. Here we study dynamical signatures of the fractionalized excitations in a quantum magnet (the easy-plane J-Q model) that realize a deconfined quantum critical point with emergent O(4) symmetry. By means of large-scale quantum Monte Carlo simulations and stochastic analytic continuation of imaginary-time correlation functions, we obtain the dynamic spin-structure factors in the $S^x$ and $S^z$ channels. In both channels, we observe broad continua that originate from the deconfined excitations. We further identify several distinct spectral features of the deconfined quantum critical point, including the lower edge of the continuum and its form factor on moving through the Brillouin zone. We provide field-theoretical and lattice model calculations that explain the overall shapes of the computed spectra, which highlight the importance of interactions and gauge fluctuations to explain the spectral-weight distribution. We make further comparisons with the conventional Landau O(2) transition in a different quantum magnet, at which no signatures of fractionalization are observed. The distinctive spectral signatures of the deconfined quantum critical point suggest the feasibility of its experimental detection in neutron scattering and nuclear magnetic resonance experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗