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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Superconductivity in dilute SrTiO 3 : A review

Doped SrTiO 3 , one of the most dilute bulk systems to display superconductivity, is perhaps the first example of an unconventional superconductor, as it does not fit into the standard BCS paradigm. More than five decades of research has revealed a rich temperature-carrier concentration phase diagram that showcases a superconducting dome, proximity to a putative quantum critical point, Lifshitz transitions, a multi-gap pairing state and unusual normal-state transport properties. Research has also extended beyond bulk SrTiO 3 , ushering the new field of SrTiO 3 -based heterostructures. Because many of these themes are also featured in other quantum materials of contemporary interest, recent years have seen renewed interest in SrTiO 3 . Here, we review the challenges and recent progress in elucidating the superconducting state of this model system. At the same time that its extreme dilution requires to revisit several of the approximations that constitute the successful Migdal–Eliashberg description of electron–phonon superconductivity, including the suppression of the Coulomb repulsion via the Tolmachev–Anderson–Morel mechanism, it opens interesting routes for alternative pairing mechanisms whose applicability remains under debate. For instance, pairing mechanisms involving longitudinal optical phonons have to overcome the hurdles created by the anti-adiabatic nature of the pairing interaction, whereas mechanisms that rely on the soft transverse optical phonons associated with incipient ferroelectricity face challenges related to the nature of the electron–phonon coupling. Proposals in which pairing is mediated by plasmons or promoted locally by defects are also discussed. In conclusion, we finish by surveying the existing evidence for multi-band superconductivity and outlining promising directions that can potentially shed new light on the rich problem of superconductivity in SrTiO 3 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

In-situ monitoring of atomically dispersed Pt sites supported on OMS-2 during CO 2 activation

Atomically dispersed catalysts have drawn great interest lately, as they showcase a high density of active sites, selectivity, and high turnover frequencies in oxidation chemistry due to labile oxygen activation. In contrast, the applications of these catalysts have lagged in reduction reactions due to the ambiguity caused by the sintering and restructuring of active sites. To bridge this gap, the evolution of Pt 4+ isomorphically substituted into an octahedral molecular sieve structure (OMS-2) under reductive conditions was correlatively characterized using multiple in-situ analytical techniques such as ambient pressure X-ray photoelectron spectroscopy, environmental transmission electron microscopy, and solid-state nuclear magnetic resonance. The surface dynamics of the Pt single atoms were revealed during the Reverse Water Gas Shift (RWGS) reaction, where the active sites were identified as two-coordinated platinum single atoms. Under reaction, we show nonbinding atoms adjacent to the single atoms restructured the motif of the single atoms to Pt 2+ via ion mobility of potassium, increasing the activation energy by 25.6 kJ/mol. Here, this work also highlights the potential for increased stability of the single atom sites via isomorphic substitution of the metal oxide support, since the Pt-OMS-2 catalyst retained activity for about 33 h before deactivation, after which nanoparticles were observed in TEM images. This work offers a new perspective in single atom synthesis using the metal oxide as the host for the single atom site, instead of adatoms on the surface

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Optimizing Distributed Energy Resources and building retrofits with the strategic DER-CAModel

The pressuring need to reduce the import of fossil fuels as well as the need to dramatically reduce CO 2 emissions in Europe motivated the European Commission (EC) to implement several regulations directed to building owners. Most of these regulations focus on increasing the number of energy efficient buildings, both new and retrofitted, since retrofits play an important role in energy efficiency. Overall, this initiative results from the realization that buildings will have a significant impact in fulfilling the 20/20/20-goals of reducing the greenhouse gas emissions by 20%, increasing energy efficiency by 20%, and increasing the share of renewables to 20%, all by 2020. The Distributed Energy Resources Customer Adoption Model (DER-CAM) is an optimization tool used to support DER investment decisions, typically by minimizing total annual costs or CO 2 emissions while providing energy services to a given building or microgrid site. This document shows enhancements made to DER-CAM to consider building retrofit measures along with DER investment options. Specifically, building shell improvement options have been added to DER-CAM as alternative or complementary options to investments in other DER such as PV, solar thermal, combined heat and power, or energy storage. The extension of the mathematical formulation required by the new features introduced in DER-CAM is presented and the resulting model is demonstrated at an Austrian Campus building by comparing DER-CAM results with and without building shell improvement options. Strategic investment results are presented and compared to the observed investment decision at the test site. Results obtained considering building shell improvement options suggest an optimal weighted average U value of about 0.53 W/(m 2 K) for the test site. This result is approximately 25% higher than what is currently observed in the building, suggesting that the retrofits made in 2002 were not optimal. Furthermore, the results obtained with DER-CAM illustrate the complexity of interactions between DER and passive measure options, showcasing the need for a holistic optimization approach to effectively optimize energy costs and CO 2 emissions. Lastly, the simultaneous optimization of building shell improvements and DER investments enables building owners to take one step further towards nearly zero energy buildings (nZEB) or nearly zero carbon emission buildings (nZCEB), and therefore support the 20/20/20 goals.

25 ENERGY STORAGE↗
DOE OSTI2025

OR-AGENT framework – Architecting electrified heavy-duty drayage applications

The widespread adoption of zero-emission vehicles in heavy-duty (HD) commercial freight transportation faces considerable technoeconomic challenges. For heavy-duty trucks, ensuring high uptime, cost parity with diesel, and safety standards is especially critical as these vehicles operate over long distances with heavy loads, where any downtime or off-nominal behaviors significantly impacts logistics, productivity, and the total cost of ownership. Unlike traditional diesel refueling, BEV charging infrastructure must be co-optimized with vehicle deployment, operational demands, and grid capacity to ensure cost-effective and reliable freight operations. However, the lack of a standardized ownership and service model has led to a fragmented approach—where commercial vehicle operators may invest in, own, and maintain both vehicle/batteries and charging/energy infrastructure. This disconnect may exclude energy service providers from the equation, forcing fleet operators to explore ‘behind-the-fence’ energy solutions that increase capital investment, operational downtime, overhead costs, and, in some cases, net carbon emissions. To address these issues, this study introduces OR-AGENT (Optimal Regional Architecture Generation for Efficient National Transport), a comprehensive modeling framework that integrates powertrain architectures, charging infrastructures, and energy backbone systems into a cohesive strategy. In this paper, OR-AGENT is applied to develop an interconnected systems architecture for energy efficiency and resiliency enhancement of heavy-duty drayage vehicles at the Port of Savannah, GA. This framework showcases an interconnected systems approach to electrifying heavy-duty drayage vehicles at the Port of Savannah, GA. The study assessed BEVs with 400–1200 kWh battery capacities, accounting for seasonal variations in weather and freight routing. A diverse charging mix (150 kW–1250 kW) was evaluated alongside grid capacity constraints, cost, and carbon intensity analysis, leading to the development of a strategic microgrid/Distributed Energy Resources (DER) deployment architecture to ensure a reliable and sustainable transition. However, the findings also highlight the need for alternative zero-emission solutions for remaining trips, such as larger batteries, electrified roadways, hydrogen powertrains, or net-zero emission fuels. In conclusion, the findings are incorporated into a Total Cost of Ownership (TCO) model to identify optimal architectures for an interconnected electrified ecosystem.

Commercial vehicles↗
DOE OSTI2024

Theoretical modeling of a bottom-raised oscillating surge wave energy converter structural loadings and power performances

Here, this study presents theoretical formulations to evaluate the fundamental parameters and performance characteristics of a bottom-raised oscillating surge wave energy converter (OSWEC) device. Employing a flat plate assumption and potential flow formulation in elliptical coordinates, closed-form equations for the added mass, radiation damping, and excitation forces/torques in the relevant pitch-pitch and surge-pitch directions of motion are developed and used to calculate the system's response amplitude operator and the forces and moments acting on the foundation. The model is benchmarked against numerical simulations using WAMIT and WEC-Sim, showcasing excellent agreement. The sensitivity of plate thickness on the analytical hydrodynamic solutions is investigated over several thickness-to-width ratios ranging from 1:80 to 1:10. The results show that as the thickness of the benchmark OSWEC increases, the deviation of the analytical hydrodynamic coefficients from the numerical solutions grows from 3% to 25%. Differences in the excitation forces and torques, however, are contained within 12%. While the flat plate assumption is a limitation of the proposed analytical model, the error is within a reasonable margin for use in the design space exploration phase before a higher-fidelity (and thus more computationally expensive) model is employed. A parametric study demonstrates the ability of the analytical model to quickly sweep over a domain of OSWEC dimensions, illustrating the analytical model's utility in the early phases of design.

13 HYDRO ENERGY↗
DOE OSTI2024

Coal-derived conductive pavement for winter de-icing: prototype, modeling, and simulation

Existing pavement de-icing methods result in high installation and maintenance costs, traffic delays, excessive weariness and corrosion, and negative environmental and safety impacts. To overcome these challenges, this paper presents an innovative pathway to designing and constructing smart self-heating pavements using a low-cost coal-char bearing asphalt material. The conductive asphalt incorporates coal char, i.e., a key byproduct of the coal pyrolysis process, into the Stone Mastic Asphalt (SMA) mixture. This asphalt containing coal-derived solid carbon exhibits highly tailorable electrical conductivity, satisfactory mechanical and thermophysical properties, and superior cost-efficiency as compared to other conductive pavement materials. The de-icing performance was also demonstrated by laboratory experiments on a bench-scale prototype. Furthermore, an efficient thermal network model was developed and validated by experiments to investigate the transient thermal behavior and energy performance of the Ohmic heating pavement system. Furthermore, the whole-year energy simulation case studies were conducted on a bridge pavement with an annual energy use of 24.6–1444.8 kWh/m 2 , showcasing its potential in field applications across cool humid, cold humid, and subarctic/arctic climate zones.

42 ENGINEERING↗
DOE OSTI2025

Deformable phrase level attention: A flexible approach for improving AI based medical coding

Objective: Improving the AI-driven automated medical encoding of clinical text plays a vital role in gathering information on the occurrence of diseases to improve population-level health. This work presents a novel attention mechanism designed to enhance text classification models and ensure appropriate classification of medical concepts in unstructured electronic health records. Materials and Methods: We developed a deformable, phrase-level attention mechanism to identify important lexical word-level and contextual phrase-level information from clinical text documents. We evaluated conventional and transformer-based deep learning models that we extended with our attention mechanism on the extraction of critical cancer information (e.g., site, subsite, laterality, histology, behavior) from 629,908 electronic pathology reports and on the automated medical encoding of 52,722 hospital discharge summaries. Results: Transformer-based models with the deformable, phrase-level attention mechanism achieved the best performance on the extraction of critical cancer information from pathology reports. Conventional- and transformer-based models show similar or better performance than their baseline counterparts on the automated medical encoding of clinical documents. Discussion: The addition of phrase-level information allowed models extended with our proposed method to outperform standard word-level attention. Our method showed favorable properties for the real-world application in terms of model robustness and phenotyping. These results indicate that our method is promising for automated data harmonization for common data models. Conclusion: This work proposes a novel deformable, phrase-level attention mechanism that enhances text classification models in the extraction of medical concepts from clinical text documents. We demonstrate strong performances on two clinical text datasets and showcase real-world deployability of our method.

Automated medical encoding↗
DOE OSTI2021

Editorial: Advances in computational molecular biophysics

This special issue of BBA is dedicated to Dr. Jeremy C. Smith on the occasion of his 60th birthday and his more than three decades as a practitioner of computational molecular biophysics. The special issue showcases cutting-edge work in computational molecular biophysics. The senior authors of the manuscripts in this issue are Dr. Smith’s previous or present collaborators. Their articles reflect Dr. Smith’s distinguished career integrating experimental and molecular simulation approaches into a unified description of the function, structure, and dynamics of biomolecules. Each of the articles presented here illustrates one aspect of the broad nature of computational molecular biophysics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Data-driven analysis and prediction of wastewater treatment plant performance: Insights and forecasting for sustainable operations

Here this study presents a comprehensive performance and forecasting analysis of the As-Samra wastewater treatment plant (WWTP) in Jordan, with two main objectives. Firstly, a thorough evaluation of the plant's performance is conducted. The analysis involves independently assessing historical operational conditions, plant production, and their statistical correlations using various statistical techniques. The second objective focuses on developing a data-driven forecasting approach to predict the plant's production one month in advance, using multiple machine learning models. The results highlight the effectiveness of principal component analysis (PCA) in simplifying operational data, revealing distinct operational clusters, and identifying seasonal production patterns while showing correlations between operational conditions and overall power production. The support vector machine (SVM) forecasting model emerged as the top performer, showcasing the potential of a hybrid forecasting approach. The findings offer valuable perspectives for enhancing operational efficiency, refining production planning, and ultimately improving the environmental impact of the plant.

42 ENGINEERING↗
DOE OSTI2022

PyAlbany: A Python interface to the C++ multiphysics solver Albany

Albany is a parallel C++ finite element library for solving forward and inverse problems involving partial differential equations (PDEs). In this paper we introduce PyAlbany, a newly developed Python interface to the Albany library. PyAlbany can be used to effectively drive Albany enabling fast and easy analysis and post-processing of applications based on PDEs that are pre-implemented in Albany. PyAlbany relies on the library PyBind11 to bind Python with C++ Albany code. Here we detail the implementation of PyAlbany and showcase its capabilities through a number of examples targeting a heat-diffusion problem. In particular we consider the following: (1) the generation of samples for a Monte Carlo application, (2) a scalability study, (3) a study of parameters on the performance of a linear solver, and finally (4) a tool for performing eigenvalue decompositions of matrix-free operators for a Bayesian inference application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Nanostructured carbon as highly efficient and stable anodes for ethylene production and power generation in protonic ceramic electrochemical cells

Protonic ceramic electrochemical cells (PCECs) have the potential in reducing the energy input and carbon emissions in ethylene production from ethane dehydrogenation. The performance of conventional perovskite-based anode materials for ethane conversion in PCECs is limited by their low active surface area and proneness to coke deposition. In this work, for the first time, we demonstrate the use of aligned carbon nanotube forests (CNTFs) as a novel anode material for an ethane fueled PCEC to co-produce ethylene and electricity. The CNTF electrode was grown on the electrolyte by the chemical vapor deposition (CVD) method. Highly dispersed iron carbide nanoparticles are formed in situ on the CNTFs during the CVD process, acting as highly active catalysts for ethane dehydrogenation. The novel PCECs show superior catalytic and electrochemical performances to that using conventional perovskite-based anodes. The cell also exhibits excellent durability and anti-coking abilities within 100 h test. This work showcases the promising application of nanostructured carbon, a new class of non-perovskite materials, as the multifunctional electrode materials for PCECs.

03 NATURAL GAS↗
DOE OSTI2023

Few-cycle atomic layer deposition to nanoengineer polybenzimidazole for H 2 /CO 2 separation

Atomic layer deposition (ALD) creates uniform sub-nanometer films on a variety of surfaces and nanopore walls and has been used to modify polymers to improve surface affinity towards specific molecules, solvent resistance, and barrier properties to gases and vapors. Here, for the first time, we demonstrate that few-cycle ALD can be used to engineer functional polymers at a sub-nanometer scale to improve both molecular size-sieving ability and counterintuitively, gas permeability. Particularly, 1-cycle ALD treatment of polybenzimidazole (PBI) by sequential exposure to trimethylaluminum (TMA) and water vapor remarkably increases H 2 permeability by 120% - 270% and H 2 /CO 2 selectivity by 30% at 35–200 °C. The ALD not only deposits an AlOx layer on the surface but also enables the TMA to infiltrate and react with the bulk PBI to form an AlO x network, disrupting polymer chain packing and increasing chain rigidity. The membrane exhibits excellent stability when challenged with simulated syngas, overcoming the permeability/selectivity tradeoff for H 2 /CO 2 separation. In conclusion, this study showcases a facile and scalable way of engineering polymeric membranes at a sub-nanometer level to improve molecular separation performance.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Amorphous-crystalline transition-driven synthesis of Co single-atom catalysts on MoO 3 for enhanced hydrogen evolution in acidic and alkaline media

Single atom catalysts (SACs) dispersed in metal oxide supports offer not only maximized catalyst utilization but also extended modulation capabilities through interactions between the SA and its support. However, achieving facile preparation and ensuring electrochemical durability of such SACs, particularly for hydrogen evolution reaction (HER) applications, remain formidable challenges. Here, our study addresses these issues by employing an amorphous-to-crystalline phase transition in MoO 3 to synthesize a cobalt (Co) SA catalyst. This method facilitates the production of highly selective SA catalysts at low temperatures and ensures their enhanced stability in HER applications. The Co SA MoO 3 catalyst exhibits superior performance in HER, operating effectively in both acidic and alkaline environments. Significantly, it maintains stable HER activity across these diverse electrolytic conditions. Our Density Functional Theory (DFT) calculations provide insights into the exceptional HER performance of Co SA MoO 3 . These calculations reveal that the strong affinity for hydrogen and water, facilitated by the modulation of the p-band orbitals at specific oxygen sites adjacent to the Co SA, establishes a thermoneutral pathway for HER. This study represents a pivotal advancement, showcasing a highly practical and robust single-atom catalyst, marking a significant stride towards sustainable energy solutions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

helixCAM: A platform for programmable cellular assembly in bacteria and human cells

Interactions between cells are indispensable for signaling and creating structure. The ability to direct precise cell-cell interactions would be powerful for engineering tissues, understanding signaling pathways, and directing immune cell targeting. In humans, intercellular interactions are mediated by cell adhesion molecules (CAMs). However, endogenous CAMs are natively expressed by many cells and tend to have cross-reactivity, making them unsuitable for programming specific interactions. Here, we showcase “helixCAM,” a platform for engineering synthetic CAMs by presenting coiled-coil peptides on the cell surface. helixCAMs were able to create specific cell-cell interactions and direct patterned aggregate formation in bacteria and human cells. Based on coiled-coil interaction principles, we built a set of rationally designed helixCAM libraries, which led to the discovery of additional high-performance helixCAM pairs. Finally, we applied this helixCAM toolkit for various multicellular engineering applications, such as spherical layering, adherent cell targeting, and surface patterning.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Tailoring Microbial Fitness Through Computational Steering and CRISPRi-Driven Robustness Regulation

The widespread application of genetically modified microorganisms (GMMs) across diverse sectors underscores the pressing need for robust strategies to mitigate the risks associated with their potential uncontrolled escape. This study merges computational modeling with CRISPR interference (CRISPRi) to refine GMM metabolic robustness. Utilizing ensemble modeling, we achieved high-throughput in silico screening for enzymatic targets susceptible to expression alterations. Translating these insights, we developed functional CRISPRi, boosting fitness control via multiplexed gene knockdown. Our method, enhanced by an insulator-improved gRNA structure and an off-switch circuit controlling a compact Cas12m, resulted in rationally engineered strains with escape frequencies below National Institutes of Health standards. The effectiveness of this approach was confirmed under various conditions, showcasing its ability for secure GMM management. This research underscores the resilience of microbial metabolism, strategically modifying key nodes to halt growth without provoking significant resistance, thereby enabling more reliable and precise GMM control. A record of this paper's transparent peer review process is included in the supplemental information.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Vision of 3D printing with concrete ÔÇö Technical, economic and environmental potentials

A vision is presented on 3D printing with concrete, considering technical, economic and environmental aspects. Although several showcases of 3D printed concrete structures are available worldwide, many challenges remain at the technical and processing level. Currently available high-performance cement-based materials cannot be directly 3D printed, because of inadequate rheological and stiffening properties. Active rheology control (ARC) and active stiffening control (ASC) will provide new ways of extending the material palette for 3D printing applications. From an economic point of view, digitally manufactured concrete (DFC) will induce changes in the stakeholders as well as in the cost structure. Although it is currently too ambitious to quantitatively present the cost structure, DFC presents many potential opportunities to increase cost-effectiveness of construction processes. The environmental impact of 3D printing with concrete has to be seen in relation to the shape complexity of the structure. Implementing structural optimization as well as functional hybridization as design strategies allows the use of material only where is structurally or functionally needed. This design optimization increases shape complexity, but also reduces material use in DFC. As a result, it is expected that for structures with the same functionality, DFC will environmentally perform better over the entire service life in comparison with conventionally produced concrete structures.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Robustness of cement-based materials: From dosage variations to yield stress fluctuations

The idea behind the present work is to assess robustness of fresh cement-based materials (i.e. their ability to display the same properties when submitted to variations in the way they are produced) from a generic and analytical point of view. First, analytical models from literature relating components proportions and yield stress are combined into a multi-scale and physical approach and compared to our experimental yield stress measurements. In the second part, the derivation of these analytical relationships is used to assess robustness as a function of components proportions, which allows for the most sensitive variations to be mapped onto component dosage from a yield stress point of view. In the case of fluid concretes, this approach showcases the interest of working at slightly higher water content and slightly lower aggregates fraction along with benefits of viscosity modifying agents / plasticizers combination.

36 MATERIALS SCIENCE↗