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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.

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At least 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A First-Principles Approach to Modeling Surface Site Stabilities on Multimetallic Catalysts

The study of multimetallic alloys and the multitude of possible surface compositions have sparked a tremendous interest in engineering low-cost materials with high activity and selectivity in heterogeneous catalysis. Multimetallic systems provide complementary functionalities and an unprecedented tunability when designing catalyst formulations. However, due to their immense structural and compositional complexity, the investigation and identification of an optimal catalyst is a tedious and time-consuming process, both experimentally and theoretically. Therefore, theoretical design principles are highly desirable to accelerate the screening of catalyst structures across the vast compositional space. In this paper, we introduce a simple and general model for predicting the site stability of multimetallic surfaces and nanoparticles, which is based on physical principles. The model requires only a small set of density functional theory (DFT) calculations of metal atom binding energies on monometallic and dilute alloy surface slabs to optimize the parameters in the simple model. The resulting model allows for the quantification of the stability of any particular atom site in any conceivable chemical environment across a wide range of morphologies, sizes, and arrangements by interpolating the derived parameters from a monometallic system to a completely diluted alloyed system. Herein, we demonstrate the robustness of the model across an extensive data set of transition metal alloy surfaces and 147-atoms cuboctahedral nanoparticles (NPs) composed of IrRhRu and PtPdRu. In conclusion, our approach yields mean absolute errors of ≈0.15 (IrRhRu), 0.20 (PtPdRu), 0.19 (IrRhRu NP), and 0.26 (PtPdRu NP) eV relative to site binding energies calculated using DFT.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Towards photocathodes with elongated lifetimes and high quantum efficiency by passivating with two dimensional materials

Photocathodes are key components of electron injectors for X-ray free electron laser and X-ray energy recovery linacs, which generate brilliant, ultrafast, and coherent X-rays for the exploration of matter with ultrahigh resolutions in both space and time. Whereas alkali-based semiconducting photocathodes display a higher quantum efficiency (QE) in the visible light spectrum than their metallic counterparts, their lifetimes are much shorter due to the high reactivity of alkali-based surfaces to the residual gases in the vacuum chamber. Overcoming the tradeoff between QE and lifetimes has been a great challenge in the accelerator community. Here in this paper, based on ab initio density functional calculations, we propose an approach to overcome this tradeoff by coating with atomically thin two-dimensional (2D) nanomaterials. On one hand, the 2D coating layers can enhance the lifetimes of photocathodes by preventing the chemical reactions with the residual gases. On the other hand, the 2D coating layers can effectively engineer the work function of photocathodes, thus controlling their QE. A monolayer of insulating BN reduces the work function, whereas a monolayer of semi-metallic graphene or semiconducting molybdenum disulfide (MoS 2 ) increases the work function. This phenomenon originates from the induced interfacial dipoles. The reduction of work function by BN implies that it is capable of maintaining the high QE of semiconducting photocathodes in addition to enhance their lifetimes. This study advances our understandings on the surface chemistry of coated photocathodes and opens new technological avenues to fabricate photocathodes with high QE and longer lifetimes.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Analysis of GPU Data Access Patterns on Complex Geometries for the D3Q19 Lattice Boltzmann Algorithm

GPU performance of the lattice Boltzmann method (LBM) depends heavily on memory access patterns. When implemented with GPUs on complex domains, typically, geometric data is accessed indirectly and lattice data is accessed lexicographically. Although there are a variety of other options, no study has examined the relative efficacy between them. Here, we examine a suite of memory access schemes via empirical testing and performance modeling. We find strong evidence that semi-direct is often better suited than the more common indirect addressing, providing increased computational speed and reducing memory consumption. For the layout, we find that the Collected Structure of Arrays (CSoA) and bundling layouts outperform the common Structure of Array layout; on V100 and P100 devices, CSoA consistently outperforms bundling, however the relationship is more complicated on K40 devices. When compared to state-of-the-art practices, our recommendations lead to speedups of 10–40 percent and reduce memory consumption up to 17 percent. Using performance modeling and computational experimentation, we determine the mechanisms behind the accelerations. We demonstrate that our results hold across multiple GPUs on two leadership class systems, and present the first near-optimal strong results for LBM with arterial geometries run on GPUs.

42 ENGINEERING↗
DOE OSTI2022

Module-Level Thermal Interface Material Degradation in HALT

Abstract In this study, thermal interface material (TIM) degradation is driven through highly accelerated life test (HALT) using temperature cycling with a prescribed vibrational acceleration for two commercially available materials having thermal conductivities of 6.0 and 8.5 W/m K. HALT specimens were prepared by applying TIM through a 4-mil stencil over AlSiC baseplates in the shape of those used in Wolfspeed CAS325M12HM2 power electronics modules. Baseplates were mounted onto aluminum carrier blocks with embedded thermocouples to characterize the thermal resistance across the baseplate and TIM layer. Thermal dissipation into the top of the baseplates was provided by a custom heating block, which mimics the size and placement of the die junctions in CAS325 modules, applying power loads of 200, 300, and 400 W. After initial characterization, samples were transferred to the HALT chamber with one set of samples exposed to temperature cycling only (TCO) and the other temperature cycling and vibration (TCV). Both sample sets were cycled between temperature extremes of −40 °C and 180 °C with vibrations applied at a peak acceleration of 3.21 Grms. After hundreds of cycles, samples were reevaluated to assess changes in thermal resistance to provide an accelerated measure of TIM degradation. This allows for reliability prediction of useful lifetime (illustrated in a solar inverter case study herein), as well as to provide a basis for developing an accelerated testing method to related temperature cycling to faster methods of degradation. Such techniques provide a means to develop maintenance schedules for power modules for ensuring sufficient thermal performance over the operating lifetime.

Engineering↗
DOE OSTI2024

Effect of Engineered Cracks in Catalyst Layers on PEMFC Catalyst Layer Durability

Proton exchange membrane fuel cells (PEMFCs) are expected to play a pivotal role in decarbonizing the transportation sector, and particularly heavy-duty vehicles (HDVs). However, improvements in durability are needed for PEMFCs to compete with state-of-the-art power sources for HDVs. Here, we examine how catalyst layer (CL) cracks that are engineered affect the CL durability by using patterned silicon templates to control the CL crack density at the micrometer scale. Electrochemical analyses show that the initial PEMFC performance is relatively unaffected by crack density, but the performance after durability testing was strongly affected. Specifically, CLs with high crack density showed higher performance relative to CLs without cracks after application of a carbon corrosion accelerated stress test. Electrochemical analyses coupled with X-ray computed tomography and scanning transmission electron microscopy with energy dispersive X-ray spectroscopy showed that the cracks provide shorter oxygen diffusion pathways to reaction sites, leading to decreased oxygen transport resistance. Additionally, we observed that the catalyst durability is unaffected by cracks. Our results provide a mechanistic explanation of the role of cracks in CL durability.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

NEML2 - THE NEW ENGINEERING MATERIAL MODEL LIBRARY, VERSION 2

SF-22-157 NEML2 is an extension of an earlier open source code developed at ANL (SF-xxxx) called NEML. These libraries provide tools for constructing and using models of engineering materials, with a focus on high temperature materials for nuclear reactor applications. The software include tools for setting up material models, calibrating models, storing models for later use in other simulations, and running simple "material point" simulations of the material behavior. The main difference between NEML and NEML2 is the new software has been complete restructured to run on GPUs and other accelerators in order to improve the performance of methods used to train constitutive models against data and to improve the performance of the final models in production environments, like finite element software. While over time we expect NEML2 to become more-or-less feature complete with NEML we are filing a new software disclosure because (1) the library has been complete restructured and (2) we want to host NEML2 in a separate repository.

MESSNER, MARK↗
DOE OSTI2017

Co-Optima Project E2.2.2: Accelerate Development of ACI/LTC Fuel Effects on RCCI Combustion

Many advanced combustion approaches have demonstrated potential for achieving diesel-like thermal efficiency but with much lower pollutant emissions of particulate matter (PM) and nitrogen oxides (NOx). RCCI is one advanced combustion concept, which makes use of in-cylinder blending of two fuels with differing reactivity for improved control of the combustion phasing and rate (Reitz et al., 2015). Previous research and development at ORNL has demonstrated successful implementation of RCCI on a light-duty multi-cylinder engine over a wide range of operating conditions (Curran et al., 2015). Several challenges were encountered when extending the research to practical applications, including limits to the operating range, both for high and low loads. Co-optimizing the engine and fuel aspects of the RCCI approach might allow these operating limits to be overcome. The in-cylinder mechanisms by which fuel properties interact with engine operating condition variables is not well understood, however, in part because RCCI is a new combustion concept that is still being developed, and limited data have been acquired to date, especially using in-cylinder optical/imaging diagnostics. The objective of this work is to use in-cylinder diagnostics in a heavy-duty single-cylinder optical engine at SNL to understand the interplay between fuel properties and engine hardware and operating conditions for RCCI in general, and in particular for the light-duty multi-cylinder all-metal RCCI engine experiments at ORNL.

02 PETROLEUM↗
DOE OSTI2020

CDFG Extraction Tool for LLVM

With the dawn of the exascale era, computer scientists and engineers are faced with tremendous challenges across all facets of the HPC system - scalability, performance, reliability, and power consumption. In particular, the power-performance benefit from one processor generation to the next is seeing ever-diminishing returns and will require fundamental changes in the way we approach computation. In fact, it is likely that different applications will require different types of accelerators in order to meet power, performance, and reliability requirements at scale. One potential type of accelerator, a dataflow architecture, diverges from the traditional sequentially executed instruction model into one that reflects the inherent instruction-level parallelism in a program. This work presents the initial steps toward a tool that can extract the control-dataflow graph from an application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Turning Normal to Abnormal: Reversing CO 2 /C2–Hydrocarbon Selectivity in HKUST–1

Metal–organic frameworks (MOFs) can efficiently purify hydrocarbons from CO 2 , but their rapid saturation, driven by preferential hydrocarbon adsorption, requires energy-intensive adsorption–desorption processes. To address these challenges, an innovative approach is developed, enabling control over MOF flexibility through densification and defect engineering, resulting in an intriguing inverse CO 2 /C2 hydrocarbon selectivity. Here, in this study, the densification process induces the shearing of the crystal lattice and contraction of pores in a defective CuBTC MOF. These changes have led to a remarkable transformation in selectivity, where the originally hydrocarbon-selective CuBTC MOF becomes CO 2 -selective. The selectivity values for densified CuBTC are significantly reversed when compared to its powder form, with notable improvements observed in CO 2 /C 2 H 6 (4416 vs 0.61), CO 2 /C 2 H 4 (15 vs 0.28), and CO 2 /C 2 H 2 (4 vs 0.2). The densified material shows impressive separation, regeneration, and recyclability during dynamic breakthrough experiments with complex quinary gas mixtures. Simulation studies indicate faster CO 2 passage through the tetragonal structure of densified CuBTC compared to C 2 H 2 . Experimental kinetic diffusion studies confirm accelerated CO 2 diffusion over hydrocarbons in the densified MOF, attributed to its small pore window and minimal interparticle voids. This research introduces a promising strategy for refining existing and future MOF materials, enhancing their separation performance.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Future-proofing photovoltaics module reliability through a unifying predictive modeling framework

Solar energy, especially photovoltaics (PV), plays a significant role in the global energy transition required for decarbonization. Technological advancements in increasing efficiencies coupled with cost reductions through economies of scale made PV a cost-competitive energy source set to exceed the milestone of 1 TW globally deployed capacity in 2022. However, ongoing downward price pressure coupled with increasing service life expectations creates tremendous challenges for reliability engineers in ensuring the safe and reliable operation of PV modules and systems over the anticipated service life. Today's reliability research efforts aim for module lifetimes of up to 50 years. Still, our current tools fall short in accurately assessing degradation mechanisms and failure modes over such extended periods. We argue that the well-established PV reliability learning cycle needs to be accelerated to keep up with the rapid technological advancements and high expectations that are put on PV and its role in the global energy transition. In this article, we explore the evolution of the PV reliability learning cycle and highlight the significance that predictive modeling capabilities will have on future PV module reliability. We propose creating a unifying modeling framework - which once established will enable the holistic assessment of PV module reliability, accelerate the PV reliability learning cycle, and bring us closer to quantitative service life predictions of PV modules.

14 SOLAR ENERGY↗
DOE OSTI2020

Catalytic bias in oxidation–reduction catalysis

Cataytic bias refers to the propensity of a reaction catalyst to effect a different rate acceleration in one direction versus the other in a chemical reaction under non-equilibrium conditions. In biocatalysis, the inherent bias of an enzyme is often advantagous to augment the innate thermodynamics of a reaction to promote efficiency and fidelity in the coordination of catabolic and anabolic pathways. In industrial chemical catalysis a directional cataltyic bias is a sought after property in facilitating the engineering of systems that couple catalysis with harvest and storage of for example fine chemicals or energy compounds. Interestingly, there is little information about catalytic bias in biocatalysis likely in large part due to difficulties in developing tractible assays sensitive enough to study detailed kinetics. For oxidation–reduction reactions, colorimetric redox indicators exist in a range of reduction potentials to provide a mechanism to study both directions of reactions in a fairly facile manner. The current short review attempts to define catalytic bias conceptually and to develop model systems for defining the parameters that control catalytic bias in enzyme catalyzed oxidation–reduction catalysis.

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

Surface conduction and reduced electrical resistivity in ultrathin noncrystalline NbP semimetal

The electrical resistivity of conventional metals such as copper is known to increase in thin films as a result of electron-surface scattering, thus limiting the performance of metals in nanoscale electronics. Here, in this study, we find an unusual reduction of resistivity with decreasing film thickness in niobium phosphide (NbP) semimetal deposited at relatively low temperatures of 400°C. In films thinner than 5 nanometers, the room temperature resistivity (~34 microhm centimeters for 1.5-nanometer-thick NbP) is up to six times lower than the resistivity of our bulk NbP films, and lower than conventional metals at similar thickness (typically about 100 microhm centimeters). The NbP films are not crystalline but display local nanocrystalline, short-range order within an amorphous matrix. Our analysis suggests that the lower effective resistivity is caused by conduction through surface channels, together with high surface carrier density and sufficiently good mobility as the film thickness is reduced. These results and the fundamental insights obtained here could enable ultrathin, low-resistivity wires for nanoelectronics beyond the limitations of conventional metals.

42 ENGINEERING↗
DOE OSTI2025

Ensuring High-Purity Liquid Argon for the LBNF FDC: Collaborative Cryogenics Research Between UNICAMP and Fermilab

Ensuring High-Purity Liquid Argon for the LBNF FDC: Collaborative Cryogenics Research Between UNICAMP and Fermilab R. Doubnik1, M. Adamowski1, F. de M. Blaszczyk1, A. Hahn1, D. Montanari1, R. Mrowca1, Z. West1, C. Adriano2, T. P.M. Alegre2, D. Correia2, A. A. B. Machado2, E. Segreto2, R. G. Gonçalves3, E. M. Assaf6, J. M. Assaf3, D. Cardoso3, M. B. Fontes4, H. Da Motta4, D. Noriler5, P. J. G. Pagliuso2. 1 Fermi National Accelerator Laboratory, PO Box 500, Batavia IL 60510, United States. 2 “Gleb Wataghin” Institute of Physics, UNICAMP, Campinas-SP, 13083-859, Brazil. 3 CPqMAE - Research Center on Advanced Materials and Energy, Federal University of São Carlos (UFSCar), São Carlos, 13565-905, Brazil. 4 The Brazilian Center for Research in Physics (CBPF), Rio de Janeiro-RJ, 22290-180, Brazil. 5 School of Chemical Engineering, UNICAMP, Campinas-SP, 13083-859, Brazil. 6 São Carlos Institute of Chemistry, University of São Paulo, São Carlos-SP, 13566-590, Brazil. Email: rdoubnik@fnal.gov Abstract. The Long-Baseline Neutrino Facility (LBNF) located at the Sanford Underground Research Facility (SURF) in Lead, South Dakota, hosts the Deep Underground Neutrino Experiment (DUNE). This experiment employs cryostats containing nearly 70,000 metric tons of high-purity liquid argon (LAr). Ensuring LAr purity is critical for achieving the required electron lifetime, which directly impacts the experiment’s signal-to-noise ratio. The Horizontal Drift (HD) detector demands an electron lifetime exceeding 3 ms within its 3.5 m drift, equivalent to less than 100 parts-per-trillion (ppt) Oxygen contamination, while the Vertical Drift (VD) detector requires over 6 ms electron lifetime within its 6.0 m drift, corresponding to less than 50 ppt Oxygen contamination. To mitigate Nitrogen (N2) quenching of scintillation light, N2 contamination must remain below 1 ppm, as higher levels can result in up to a 20 % loss of light. The Brazil State University of Campinas (UNICAMP) significantly contributes to LBNF FDC through the development of argon purification and regeneration systems for HD and VD cryostats. UNICAMP designed and constructed the Purification Liquid Argon Cryostat (PuLArC), a small-scale test facility holding approximately 90 liters of LAr. Tests using PuLArC demonstrated that 1.2 kg of Li-FAU zeolite could reduce N₂ contamination from 20-50 ppm to 0.1-1.0 ppm within 1-2 hours. Tests at Fermilab’s Iceberg cryostat (2,596 liters) confirmed scalability, with 3 kg of Li-FAU reducing N₂ contamination from ~5 ppm to <1 ppm over 96 hours cycles without active circulation. This presentation will detail the research methods, test setups, and results, showcasing the potential of Li-FAU as an alternative to Molecular Sieve 4A for large-scale LAr systems. This advancement enhances DUNE's precision and demonstrates the impact of international collaboration on cryogenic research.

Doubnik, Roza [Fermilab]↗
DOE OSTI2025

ADEPT: A Pedagogical Framework for Integrating Agentic AI with Deterministic Scientific Workflows

The integration of Large Language Models (LLMs) into scientific research promises to accelerate discovery, yet a significant gap remains between the dynamic reasoning of Artificial Intelligence (AI) agents and the static, deterministic nature of canonical scientific workflows. This paper introduces ADEPT (Agentic Discovery and Exploration Platform for Tools), a reference architecture and pedagogical framework explicitly designed to bridge this gap. ADEPT's primary mission is to provide a transparent, "glass-box" environment where researchers and engineers can learn to effectively wrap established scientific software (e.g., BLAST, Nextflow pipelines) and compose it into reliable, agent-driven workflows. We describe its modular, multi-server architecture, which leverages the Model Context Protocol (MCP) for tool serving, LangGraph for robust agentic orchestration, and a secure nsjail-based sandbox for safe code execution. By prioritizing architectural clarity, safety, and modularity, ADEPT serves as an extensible blueprint for building trustworthy AI-augmented systems and fosters the collaborative development necessary to responsibly employ agentic AI for science. We provide practical examples of how to adapt and extend this framework, highlighting its utility in workforce development and AI-readiness capabilities across research and development projects.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

FEED Study of CarbonCapture Inc DAC and CarbonCure Utilization Technologies Using United States Steel’s Gary Works Plant Waste Heat (Final Report)

The University of Illinois at Urbana-Champaign (UIUC) led this project to produce a front-end engineering design (FEED) study of an advanced Direct Air Capture and Utilization System (DACUS) system that can remove a minimum of 5,000 tonnes/yr net of carbon dioxide from air (based on cradle-to-gate LCA) and utilizing the CO 2 to produce low carbon intensity ready mix concrete. The designed system, if built, would be larger than any currently existing Direct Air Capture (DAC) collector in the U.S. Such carbon capture technologies are critical to meeting the goals of the DOE’s program to accelerate climate-critical technology. In addition to the power sector, industrial facilities for the manufacture of steel and cement/concrete are among the major sources of anthropogenic CO 2 . DAC is a promising new technology for reducing CO 2 , a potent greenhouse gas, in the atmosphere but is expensive, in part due to the energy required to adsorb and desorb captured CO 2 during cycles. By integrating CarbonCapture Inc. (CCI) DAC modules at United States Steel's Gary Works (USS) and utilizing the site's waste heat, energy, and location this project evaluates the feasibility of utilizing the captured CO 2 and the logistics of transportation. CarbonCapture Inc. has developed an innovative DAC system using novel adsorbents to cost-effectively capture CO 2 . The captured, liquified gas will be trucked to ready-mix concrete plants within the region, the closest of which is approximately 3.5 miles away, where CarbonCure will inject it into concrete during the mixing process at the facilities. The carbon dioxide reacts with concrete, mineralizing into calcium carbonate (CaCO 3 ), permanently locking the greenhouse gas into the matrix of the building material. This FEED study demonstrated a full CO 2 value chain for DACUS from industrial facilities. It also provided a means for Visage Energy Corp. (Visage) to assess the impact of this holistic approach on job creation, regional economic impact, and environmental justice. The project team also included Sargent & Lundy (S&L) to provide the constructability review and costing of the integration of the DAC with the steel plant. Ecotek Engineering USA, LLC designed the outside battery limit (OSBL) infrastructure to connect the DAC and the plant. Activities performed during the project included: (1) Project Management Plan; (2) Technology Maturation Plan (TMP); (3) Initial Workforce Readiness Plan; (4) Workforce Readiness Plan; (5) Front-End Engineering Design (FEED) Study; (6) Project Design Basis; (7) Hazards and Operability (HAZOP) Study; (8) Constructability Review; (9) Project Cost Assessment; (10) Logistics Analysis of CO 2 Transportation to the Utilization Site; (11) Business Case Analysis; (12) Life Cycle Analysis (LCA); (13) Environmental Health and Safety (EH&S) Analysis; (14) Environmental Justice Analysis; and (15) Economic Revitalization and Job Creation Outcomes Analysis. This report provides a summary of the outcomes and results of the project, which was performed between Oct. 1, 2022, through Sept. 30, 2024.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗