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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Multiple Degradation Mechanisms in Reinforced Concrete Structures, Modeling and Risk Analysis

The overarching goal of this project is to complement ongoing Department of Energy (DOE) Light Water Reactor Sustainability (LWRS)-funded Grizzly concrete modeling development efforts by providing improved multi-physics models for incorporation into the Grizzly and BlackBear codes. Objectives of this work identified at the outset of this project include: 1. Coupling between mechanical damage and transport processes. The mechanical damage will be characterized by nonlinear mechanical constitutive models appropriate for concrete used in nuclear power plants (NPPs). 2. Improved representation of the coupling among the transport process, building on the current moisture and thermal transport models in Grizzly. The parameters for coupling among heat and mass transport in the multi-physics model will be experimentally determined. 3. Coupling among different scale levels of concrete constituents, fine and coarse aggregates, cement paste, hydration products, and pore structure. 4. Probabilistic analysis of the random nature of the heterogeneous concrete structure and the environmental factors (ambient temperature and humidity) and their multiple effects on concrete deterioration. 5. Benchmark verification, validation and uncertainty quantification of the thermo-hygro- chemo-mechanical (THCM) concrete formulation. The end goal of this work was to provide a comprehensive and robust simulation capability that can be applied at the engineering scale for analysis of realistic deterioration scenarios in NPP concrete structures.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Two-Stage Assembly of Nanoparticle Superlattices with Multiscale Organization

Self-assembly processes, while promising for enabling the fabrication of complexly organized nanomaterials from nanoparticles, are often limited in creating structures with multiscale order. These limitations are due to difficulties in practically realizing the assembly processes required to achieve such complex organizations. For a long time, a hierarchical assembly attracted interest as a potentially powerful approach. However, due to the experimental limitations, intermediate-level structures are often heterogeneous in composition and structure, which significantly impacts the formation of large-scale organizations. Here, we introduce a two-stage assembly strategy: DNA origami frames scaffold a coordination of nanoparticles into designed 3D nanoclusters, and then these clusters are assembled into ordered lattices whose types are determined by the clusters’ valence. Through modulating the nanocluster architectures and intercluster bindings, we demonstrate the successful formation of complexly organized nanoparticle crystals. To conclude, the presented two-stage assembly method provides a powerful fabrication strategy for creating nanoparticle superlattices with prescribed unit cells.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Tungsten-dioxo single-site heterogeneous catalyst on carbon: synthesis, structure, and catalysis

This study investigates the application of a novel third-row metal, tungsten, to carbon-supported single-site metal-oxo heterogeneous catalysis. Tungsten is a green and earth-abundant metal, but an unexplored candidate in this role. The carbon (AC = activated carbon)-supported tungsten dioxo complex, AC/WO 2 was prepared via grafting of (DME)WO 2 Cl 2 (DME = 1,2-dimethoxyethane) onto high-surface-area activated carbon. AC/WO 2 was fully characterized by ICP-OES, XPS, EXAFS, XANES, SMART-EM, and DFT. W 4d 7/2 XPS and W L III -Edge XANES assign the oxidation state as W(VI), while EXAFS reveals two W=O double and two W–O single bonds at distances of 1.73 and 1.92 Å, respectively. These data align well with DFT computational results, supporting the structure as Carbon(–μ-O–) 2 M(=O) 2 . SMART-EM verifies that single W(VI) catalytic sites are bonded in an out-of-plane manner. The catalytic performance of air- and water-stable AC/WO 2 is compared to that of AC/MoO 2 . AC/WO 2 is more active and selective than the molybdenum analog in mediating alcohol dehydration of various substrates, and is recyclable. Notably, AC/WO 2 is an effective and recyclable catalyst for primary aliphatic alcohol dehydration and forms no dehydrogenation side products in contrast to AC/MoO 2 . However, AC/WO 2 is less effective in epoxidation and PET depolymerization. Overall, this work demonstrates the potential of carbon-supported third row metals for future studies.

02 PETROLEUM↗
DOE OSTI2020

Challenge and opportunity in remote epitaxy

The tutorial focuses on the fundamentals and applications of heterogeneously integrated structures using 1D, 2D, and 3D materials from the growth of 3D materials on 2D materials, and various lift-off technologies to heterogeneous integration of electronic/optoelectronic devices.

Kim, Jeehwan↗
DOE OSTI2023

The Relationship between Ionic Conductivity and Solvation Structures of Localized High-Concentration Fluorinated Electrolytes for Lithium-Ion Batteries

Localized high concentration electrolyte (LHCE) combines a diluent with high concentration electrolyte (HCE), offering promising properties. The ions, solvent, and diluent interact to form a complex heterogenous liquid structure, where high salt concentration clusters are embedded in diluent. Optimizing LHCE for desired electrolyte properties like high ionic conductivity, low viscosity, effective solid electrolyte interphase (SEI) formability, within the vast chemical and compositional design space requires deeper understanding and theoretical guidance. For this work, we investigated the structures and conductivity of LHCEs based on a fluorinated solvent with two different diluents at varying concentrations. The 2,2,3,3-tetrafluoropropyl trifluoroacetate (TFPTFA) enters the solvation cluster due to its stronger Li-ion interactions, whereas 1,1,2,2-tetrafuoroethyl 2,2,2-trifuoroethyl ether (TFETFE) enters only at extremely high diluent concentrations. The ionic conductivity increases with decreasing diluent concentrations, with a slope change during cluster percolation. Overall, TFETFE demonstrates higher effectiveness than TFPTFA, forming higher local salt concentration clusters, and resulting in higher ionic conductivity.

cluster chemistry↗
DOE OSTI2025

Understanding the optoelectronic properties of doped 2D organic-inorganic halide perovskite quantum wells: towards efficient quantum well IR photodetectors

Metal halide perovskite (MHP) multiple quantum wells which consist of multilayers of alternate organic and inorganic layers exhibit large exciton binding energies due to the dielectric confinement between the inorganic and organic layers. These naturally formed multiple quantum wells have strong spin-orbit coupling (SOC) due to the presence of heavy elements in their crystal structures. Although the fundamental properties of 2D MHPs are far from being entirely understood, it is widely accepted that their band edge absorption coefficient results from strong exciton interactions. However, studies demonstrating how different exciton interactions and doping effects influence electronic traps and disorder on the band edge absorption coefficient of 2D MHPs have not been demonstrated. Understanding these interactions in MHPs will allow us to access low energy optical transitions for the fabrication of solution processable short-to-mid-wavelength IR photodetectors (1 – 8 μm). Moreover, upon doping, it is possible to move the Fermi energy into the conduction band (CB) to favorably promote the transport of charges in a working device. Herein, we study the development of 2D MHPs having strong SOC, high carrier mobility, and tunable quantum well structures. Our studies shed light on the design and modulation of fundamental physical phenomena by carefully elucidating the role of dopants (n-type and p-type), exciton heterogeneity, orientation, structure, and bias stress effects on the performance of MHPs as potential IR photodetectors.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Statement of Work: Toward AI-driven additive manufacturing for metal-ceramic composite structures

The project scope is to investigate the compatibility of various ceramic and metal powder composite feedstock development, implement AI algorithms for in-situ monitoring and parameter optimization of binder jet 3D printing to achieve reliable and robust metal/ceramic and/or ceramic/ceramic composite components, and create a generative design framework for heterogeneous composite structures incorporating metals and ceramic-based materials to achieve specific mechanical properties. Funded is the effort and travel by the faculty advisor at University of California Berkeley in support of the work of their students and the related collaborative research and development effort.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Solving complex nanostructures with ptychographic atomic electron tomography

Abstract Transmission electron microscopy (TEM) is essential for determining atomic scale structures in structural biology and materials science. In structural biology, three-dimensional structures of proteins are routinely determined from thousands of identical particles using phase-contrast TEM. In materials science, three-dimensional atomic structures of complex nanomaterials have been determined using atomic electron tomography (AET). However, neither of these methods can determine the three-dimensional atomic structure of heterogeneous nanomaterials containing light elements. Here, we perform ptychographic electron tomography from 34.5 million diffraction patterns to reconstruct an atomic resolution tilt series of a double wall-carbon nanotube (DW-CNT) encapsulating a complex ZrTe sandwich structure. Class averaging the resulting tilt series images and subpixel localization of the atomic peaks reveals a Zr 11 Te 50 structure containing a previously unobserved ZrTe 2 phase in the core. The experimental realization of atomic resolution ptychographic electron tomography will allow for the structural determination of a wide range of beam-sensitive nanomaterials containing light elements.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Tiling Framework for Heterogeneous Computing of Matrix based Tiled Algorithms

Tiling matrix operations can improve the load balancing and performance of applications on heterogeneous computing resources. Writing a tile-based algorithm for each operation with a traditional, hand-tuned tiling approach that uses for loops in C/C++ is cumbersome and error prone. Moreover, it must enable and support the heterogeneous memory management of data objects and also explore architecture-supported, native, tiled-data transfer APIs instead of copying the tiled data to continuous memory before the data transfer. The tiling framework provides a tiled data structure for heterogeneous memory mapping and parameterization to a heterogeneous task specification API. We have integrated our tiled framework into MatRIS (Math kernels library using IRIS). IRIS is a heterogeneous run-time framework with a heterogeneous programming model, memory model, and task execution model. Experiments reveal that the tiled framework for BLAS operations has improved the programmability of tiled BLAS and improved performance by ~20% when compared against the traditional method that copies the data to continuous memory locations for heterogeneous computing.

Miniskar, Narasinga Rao↗
DOE OSTI2025

Non-Covalent Interactions and Helical Packing in Thiophene-Phenylene Copolymers: Tuning Solid-State Ordering and Charge Transport for Organic Field-Effect Transistors

In this study, we introduce two thiophene-phenylene-thiophene (TPT) polymers designed to leverage noncovalent intramolecular interactions to regulate main-chain conformation and enhance solid-state ordering. By incorporating unsubstituted thiophene (T) or bithiophene (2T) units, we reveal striking divergence in the thermal, morphological, and optoelectronic properties of the resulting films, facilitated by these noncovalent interactions. Using a combination of computational and experimental approaches, we show that annealing yields remarkably different polymer conformations and, consequently, charge transport properties. TPT-T undergoes a significant structural transformation, adopting a more planar backbone conformation and a highly crystalline, edge-on molecular orientation. In contrast, the introduction of a single additional thiophene unit in TPT-2T leads to a more isotropic molecular orientation with a slight preference for face-on alignment, resulting in a heterogeneous film structure that hinders charge transport despite achieving tighter molecular packing. Remarkably, despite being composed of achiral components, TPT-2T develops chirality upon annealing, indicating the formation of a helical conformation. Organic field-effect transistor measurements reveal that the well-ordered alignment in annealed TPT-T films results in higher charge carrier mobility and a narrower distribution of mobility values than in TPT-2T. These findings provide critical insights into the structure−property relationships of conjugated polymers, offering guidance for optimizing molecular design and processing strategies for highperformance organic electronic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Learning a general model of single phase flow in complex 3D porous media

Modeling effective transport properties of 3D porous media, such as permeability, at multiple scales is challenging as a result of the combined complexity of the pore structures and fluid physics—in particular, confinement effects which vary across the nanoscale to the microscale. While numerical simulation is possible, the computational cost is prohibitive for realistic domains, which are large and complex. Although machine learning (ML) models have been proposed to circumvent simulation, none so far has simultaneously accounted for heterogeneous 3D structures, fluid confinement effects, and multiple simulation resolutions. By utilizing numerous computer science techniques to improve the scalability of training, we have for the first time developed a general flow model that accounts for the pore-structure and corresponding physical phenomena at scales from Angstrom to the micrometer. Using synthetic computational domains for training, our ML model exhibits strong performance (R 2 = 0.9) when tested on extremely diverse real domains at multiple scales.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Learning a General Model of Single Phase Flow in Complex 3D Porous Media

Modeling effective transport properties of 3D porous media, such as permeability, at multiple scales is challenging as a result of the combined complexity of the pore structures and fluid physics—in particular, confinement effects which vary across the nanoscale to the microscale. While numerical simulation is possible, the computational cost is prohibitive for realistic domains, which are large and complex. Although machine learning (ML) models have been proposed to circumvent simulation, none so far has simultaneously accounted for heterogeneous 3D structures, fluid confinement effects, and multiple simulation resolutions. By utilizing numerous computer science techniques to improve the scalability of training, we have for the first time developed a general flow model that accounts for the pore-structure and corresponding physical phenomena at scales from Angstrom to the micrometer. Using synthetic computational domains for training, our ML model exhibits strong performance (R 2 = 0.9) when tested on extremely diverse real domains at multiple scales.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Multiscale petrophysical characterization and flow unit classification of the Minnelusa eolian sandstones

Integration of petrophysical and geological information is critical to simulation of subsurface carbon storage (GCS). In this sense, two depositional facies were identified from the core description and well-log interpretation, namely massive (MS) and cross-bedded (CB) facies groups. Additionally, pore-scale characteristics were studied by a combination of techniques, e.g. Nuclear Magnetic Resonance (NMR) and mercury intrusion capillary pressure (MICP). Scanning electron microscope (SEM) and petrographic analyses show that the pore structure is dominantly controlled by the depositional environment and dolomite cementation. NMR-T 2 distributions of MS and CB facies show triple and quadruple modes, respectively. In addition, MICP of high- and low-permeability MS facies samples, and their CB facies group mixtures were collected. The MS sample pore-throat size distribution is uni-modal, while the triple-modal characteristic of the mixtures indicates heterogeneous pore structures at the sub-core scale for CB facies. The reliably estimates of porosity and permeability for both facies groups via NMR techniques and the MLR (Multiple Linear Regression) approach demonstrate the applicability of these techniques to eolian sandstone. Moreover, irreducible water saturation via the T 2 -cutoff method correlates strongly with T 2LM instead of porosity. Finally, the rock quality index and flow zone indicator were calculated based on Combinable Magnetic Resonance (CMR) log interpretations. This provides direct connection to properties measured in the well. Four flow units were classified for both facies groups. Finally, results show that better reservoir quality with significant heterogeneities is observed in the CB facies. This study highlights the importance integrating multiscale petrophysical properties including facies, pore architecture and diagenesis analysis with core- to log-scale property characterization. The results herein validate our reservoir characterization and flow unit classification in eolian reservoirs.

58 GEOSCIENCES↗
DOE OSTI2024

Implementation of a realistic artificial data generator for crash data generation

In this paper, a framework is outlined to generate realistic artificial data (RAD) as a tool for comparing different models developed for safety analysis. The primary focus of transportation safety analysis is on identifying and quantifying the influence of factors contributing to traffic crash occurrence and its consequences. The current framework of comparing model structures using only observed data has limitations. With observed data, it is not possible to know how well the models mimic the true relationship between the dependent and independent variables. Further, real datasets do not allow researchers to evaluate the model performance for different levels of complexity of the dataset. RAD offers an innovative framework to address these limitations. Hence, we propose a RAD generation framework embedded with heterogeneous causal structures that generates crash data by considering crash occurrence as a trip level event impacted by trip level factors, demographics, roadway and vehicle attributes. Within our RAD generator we employ three specific modules: (a) disaggregate trip information generation, (b) crash data generation and (c) crash data aggregation. For disaggregate trip information generation, we employ a daily activity-travel realization for an urban region generated from an established activity-based model for the Chicago region. We use this data of more than 2 million daily trips to generate a subset of trips with crash data. For trips with crashes crash location, crash type, driver/vehicle characteristics, and crash severity. The daily RAD generation process is repeated for generating crash records at yearly or multi-year resolution. In conclusion, the crash databases generated can be employed to compare frequency models, severity models, crash type and various other dimensions by facility type - possibly establishing a universal benchmarking system for alternative model frameworks in safety literature.

42 ENGINEERING↗
DOE OSTI2023

Modular droplet injector for sample conservation providing new structural insight for the conformational heterogeneity in the disease-associated NQO1 enzyme

Droplet injection strategies are a promising tool to reduce the large amount of sample consumed in serial femtosecond crystallography (SFX) measurements at X-ray free electron lasers (XFELs) with continuous injection approaches. Here, we demonstrate a new modular microfluidic droplet injector (MDI) design that was successfully applied to deliver microcrystals of the human NAD(P)H:quinone oxidoreductase 1 (NQO1) and phycocyanin. We investigated droplet generation conditions through electrical stimulation for both protein samples and implemented hardware and software components for optimized crystal injection at the Macromolecular Femtosecond Crystallography (MFX) instrument at the Stanford Linac Coherent Light Source (LCLS). Under optimized droplet injection conditions, we demonstrate that up to 4-fold sample consumption savings can be achieved with the droplet injector. In addition, we collected a full data set with droplet injection for NQO1 protein crystals with a resolution up to 2.7 Å, leading to the first room-temperature structure of NQO1 at an XFEL. NQO1 is a flavoenzyme associated with cancer, Alzheimer's and Parkinson's disease, making it an attractive target for drug discovery. Further, our results reveal for the first time that residues Tyr128 and Phe232, which play key roles in the function of the protein, show an unexpected conformational heterogeneity at room temperature within the crystals. These results suggest that different substates exist in the conformational ensemble of NQO1 with functional and mechanistic implications for the enzyme's negative cooperativity through a conformational selection mechanism. Our study thus demonstrates that microfluidic droplet injection constitutes a robust sample-conserving injection method for SFX studies on protein crystals that are difficult to obtain in amounts necessary for continuous injection, including the large sample quantities required for time-resolved mix-and-inject studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Proton Relay for the Rate Enhancement of Electrochemical Hydrogen Reactions at Heterogeneous Interfaces

Proton transfer is critically important to many electrocatalytic reactions, and directed proton delivery could open new avenues for the design of electrocatalysts. However, although this approach has been successful in molecular electrocatalysis, proton transfer has not received the same attention in heterogeneous electrocatalyst design. Here, in this work, we report that a metal oxide proton relay can be built within heterogeneous electrocatalyst architectures and improves the kinetics of electrochemical hydrogen evolution and oxidation reactions. The volcano-type relationship between activity enhancement and pK a of amine additives confirms this improvement; we observe maximum rate enhancement when the pK a of a proton relay matches the pH of the electrolyte solution. Density-functional-theory-based reactivity studies reveal a decreased proton transfer energy barrier with a metal oxide proton relay. These findings demonstrate the possibility of controlling the proton delivery and enhancing the reaction kinetics by tuning the chemical properties and structures at heterogeneous interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Leveraging Large Language Models for Understanding Fundamental Principles of Catalysis

Heterogeneous catalysis presents a distinct challenge for artificial intelligence (AI). Data sets are often small and inconsistently reported, catalyst representations are not standardized, and extracting fundamental knowledge requires integrating performance data, spectroscopic characterizations, and mechanistic models across multiple scales. Language offers a unifying representation across these modalities, making catalysis well suited for leveraging large language models (LLMs). By standardizing how catalytic data is represented, LLMs make dispersed experimental results more accessible to downstream statistical modeling. In this perspective, we focus our discussion around three opportunities where LLMs can significantly contribute to catalysis: (1) text to properties; (2) text to structure; and (3) text to mechanistic models. The discussion is followed by a perspective section on LLM-readiness of data, aligning LLM outputs with scientific correctness, and bridging lab-scale discovery to industrial deployment. Across each area, the most productive applications couple dispersed chemical knowledge with physics-grounded validation to produce verifiable hypotheses and actionable representations.

Catalysts↗
DOE OSTI2025

Radiation-induced vacancy injection in heterogeneous multiphase materials

Understanding the synergy between corrosion and defect dynamics is a key consideration in the development of advanced materials for extreme environments. Here, we reveal a surprising phenomenon for the transport of point defects induced by irradiation in a heterogeneous multiphase structure of a metal and an oxide, similar to that formed under metal corrosion that takes place in most environments. Despite the confinement of the produced damage within the oxide, vacancies were injected into the unirradiated metal and coarsened with dose. Furthermore, the results show that the nature of the oxide layer dictates the defect evolution in the metal layer. This work reveals an interesting mechanism for point defect interactions in multiphase materials, with broad implications in many fields, while also emphasizing the complex coupling between corrosion and irradiation. Corrosion leads to the formation of multiphase materials, while irradiation enhances diffusion within the heterogeneous phases, which can impact corrosion rates.

36 MATERIALS SCIENCE↗