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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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DOE OSTI2023

Rethinking the Price Formation Problem–Part 2: Rewarding Flexibility and Managing Price Risk

In this study, part 1 of this two-part paper describes the impact that uncertainty has on the design and analysis of price formation policies in the non-convex auctions conducted by U.S. wholesale electricity market operators. Using first a toy model and then a large-scale test system, Part 2 demonstrates the difference in prices under the idealized benchmark of ex ante convex hull pricing defined in Part 1 versus existing methods, in particular documenting the potential for suppression of volatility and therefore under-compensation of flexibility by existing methods. The examples highlight that inefficient spot price formation can induce inefficient forward commitments of generators, necessitating out-of-market intervention to restore a reliable and efficient operating plan.Given the potential side effects of existing policies for investment and operation, we suggest two elements in a reoriented approach to the price formation problem: first ensuring that prices exhibit full-strength volatility, and second ensuring that risk-averse market participants have sufficient ability to manage this volatility.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Space to Air High-Altitude Region Adjoint Neutron Transport

Neutrons from an atmospheric nuclear explosion can be detected by sensors in orbit. Current tools for characterizing the neutron energy spectrum assume a known source and use forward transport to recreate the detector response. In realistic scenarios the true source is unknown, making this an inefficient, iterative approach. In contrast, the adjoint approach directly solves for the source spectrum, enabling source reconstruction. The time–energy fluence at the satellite and adjoint transport equation allow a Monte Carlo method to characterize the neutron source’s energy spectrum directly in a new model: the Space to High-Altitude Region Adjoint (SAHARA) model. A new adjoint source event estimator was developed in SAHARA to find feasible solutions to the neutron transport problem given the constraints of the adjoint environment. This work explores SAHARA’s development and performance for mono-energetic and continuous neutron energy sources. In general, the identified spectra were shifted towards energies approximately 5% lower than the true source spectra, but SAHARA was able to capture the correct spectral shapes. Continuous energy sources, including real-world sources Fat Man and Little Boy, resulted in identifiable spectra that could have been produced by the same distribution as the true sources as demonstrated by two-dimensional (2D) Kolmogorov–Smirnov tests.

LaMere, Zachary W.↗
DOE OSTI2020

Computing and AI for Pandemic Response: Looking Forward

This virtual symposium was held to highlight the impact the U.S. Department of Energy’s (DOE) National Virtual Biotechnology Laboratory (NVBL) has had utilizing the unique capabilities of the DOE to tackle the science and technology challenges associated with COVID-19, and to discuss areas in which the NVBL can have impact in the future. With perspectives from Chris Fall, Director, Office of Science, DOE, and William A. Bookless, Principal Deputy Administrator of the National Nuclear Security Administration, the event featured Presentations from lead investigators reporting progress in: Epidemiological modeling, Therapeutics, Testing, Understanding transport of the virus, and Solving issues around supply chain challenges. In addition, keynote speakers from outside the NVBL discussed the upcoming science and technology needs in computing, testing and surveillance, and vaccines. The event was aimed at the S&T community, media, and general public.

Brase, James M.↗
DOE OSTI2021

Artificial spin ice: Paths forward

Artificial spin ice systems are lithographically prepared arrays of interacting nanoscale magnetic moments with collective behavior resulting from the chosen array geometry. These many-body systems are unusual in that their simple constituent elements can be configured to design their interactions with exquisite control. They can then be probed experimentally over a remarkably large range of time scales and length scales, including imaging of the individual moments. The study of artificial spin ice has broadened well beyond the original focus on systems with connection to spin ice and ice models, and now the term is used in reference to many other structures that exhibit a much wider range of physical phenomena. Here in this perspective, we review progress in the field of artificial spin ice since its inception more than a decade ago. We then discuss prospects for future directions – continuing the exploration of nanomagnetism, statistical spin models, and the potential for technological devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Targeting hydroxycinnamoyl CoA: shikimate hydroxycinnamoyl transferase for lignin modification in Brachypodium distachyon

Abstract Background Hydroxycinnamoyl CoA: shikimate hydroxycinnamoyl transferase (HCT) is a central enzyme of the so-called “esters” pathway to monolignols. As originally envisioned, HCT functions twice in this pathway, to form coumaroyl shikimate and then, in the “reverse” direction, to convert caffeoyl shikimate to caffeoyl CoA. The discovery of a caffeoyl shikimate esterase (CSE) that forms caffeic acid directly from caffeoyl shikimate calls into question the need for the reverse HCT reaction in lignin biosynthesis. Loss of function of HCT gives severe growth phenotypes in several dicot plants, but less so in some monocots, questioning whether this enzyme, and therefore the shikimate shunt, plays the same role in both monocots and dicots. The model grass Brachypodium distachyon has two HCT genes, but lacks a classical CSE gene. This study was therefore conducted to evaluate the utility of HCT as a target for lignin modification in a species with an “incomplete” shikimate shunt. Results The kinetic properties of recombinant B. distachyon HCTs were compared with those from Arabidopsis thaliana , Medicago truncatula , and Panicum virgatum (switchgrass) for both the forward and reverse reactions. Along with two M. truncatula HCTs, B. distachyon HCT2 had the least kinetically unfavorable reverse HCT reaction, and this enzyme is induced when HCT1 is down-regulated. Down regulation of B. distachyon HCT1, or co-down-regulation of HCT1 and HCT2, by RNA interference led to reduced lignin levels, with only modest changes in lignin composition and molecular weight. Conclusions Down-regulation of HCT1, or co-down-regulation of both HCT genes, in B. distachyon results in less extensive changes in lignin content/composition and cell wall structure than observed following HCT down-regulation in dicots, with little negative impact on biomass yield. Nevertheless, HCT down-regulation leads to significant improvements in biomass saccharification efficiency, making this gene a preferred target for biotechnological improvement of grasses for bioprocessing.

09 BIOMASS FUELS↗
DOE OSTI2024

Modeling Ni Coarsening and Migration in the Hydrogen Electrode of Solid oxide Cells under Operating Conditions

Ni coarsening and migration is the most important degradation in the hydrogen electrode of solid oxide cells. This presentation reviews our works on Ni coarsening and migration in NETL over the past years. We used simulation techniques including phase-field modeling and density function theory to investigate possible mechanisms of Ni coarsening and migration, including self-diffusion of Ni, diffusion of gaseous Ni(OH)2, surface diffusion of Ni(OH)x and Ni-YSZ wettability change, and examined the effect of operating conditions on these mechanisms. So far, none of the mechanisms can fully explain the experiments. Remaining questions and possible paths forward are summarized and discussed.

Lei, Yinkai↗
DOE OSTI2024

The Jefferson Lab Eta Factory Experiment and Applications of PbWO4 Calorimeters in Future Experimental Facilities

The goal of the new JLab Eta Factory (JEF) experiment, conducted with the GlueX detector in Hall D at Jefferson Lab, is to perform measurements of various ¿(') decays with a primary focus on rare neutral modes. The experiment’s physics program ranges from precision tests of low-energy QCD to searches for gauge bosons with masses below 1 GeV that could couple the Standard Model (SM) sector to the dark sector. The experiment will collect a high-statistics data sample of ¿(') mesons produced via a beam of tagged photons. The GlueX detector features a large, nearly uniform acceptance for both neutral and charged particles, enabling efficient identification of complex multi-particle final states. To meet the requirements of the JEF experiment, the inner section of the forward lead-glass calorimeter in the GlueX detector has been upgraded with lead tungstate (PbWO4) scintillating crystals. PbWO4 offers exceptional characteristics, such as a small radiation length and Molire radius, and large light yield, that make it ideal for constructing high- granularity, high-resolution, radiation-hard detectors. These properties enable excellent spatial separation and energy resolution of reconstructed electromagnetic showers, establishing PbWO4 as the material of choice for many high-precision experiments. The JEF experiment began data collection in April 2025 and will operate concurrently with the GlueX experiment, whose primary objective is the search for gluonic excitations in the meson spectrum. I will give an overview of the JEF experiment, the GlueX detector, and the feasibility of further upgrades to support future ¿ physics studies. Special attention will be given to the newly constructed PbWO4 scintillating calorimeter and recent advancements in calorimeter instrumentation.

Somov, Alexander↗
DOE OSTI2022

DUNE Software and High Performance Computing

DUNE, like other HEP experiments, faces a challenge related to matching execution patterns of our production simulation and data processing software to the limitations imposed by modern high-performance computing facilities. In order to efficiently exploit these new architectures, particularly those with high CPU core counts and GPU accelerators, our existing software execution models require adaptation. In addition, the large size of individual units of raw data from the far detector modules pose an additional challenge somewhat unique to DUNE. Here we describe some of these problems and how we begin to solve them today with existing software frameworks and toolkits. We also describe ways we may leverage these existing software architectures to attack remaining problems going forward. This whitepaper is a contribution to the Computational Frontier of Snowmass21.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

KEBLM: Knowledge-Enhanced Biomedical Language Models

Pretrained language models (PLMs) have demonstrated strong performance on many natural language processing (NLP) tasks. Despite their great success, these PLMs are typically pretrained only on unstructured free texts without leveraging existing structured knowledge bases that are readily available for many domains, especially scientific domains. As a result, these PLMs may not achieve satisfactory performance on knowledge-intensive tasks such as biomedical NLP. Comprehending a complex biomedical document without domain-specific knowledge is challenging, even for humans. Inspired by this observation, we propose a general framework for incorporating various types of domain knowledge from multiple sources into biomedical PLMs. We encode domain knowledge using lightweight adapter modules, bottleneck feed-forward networks that are inserted into different locations of a backbone PLM. For each knowledge source of interest, we pretrain an adapter module to capture the knowledge in a self-supervised way. We design a wide range of self-supervised objectives to accommodate diverse types of knowledge, ranging from entity relations to description sentences. Once a set of pretrained adapters is available, we employ fusion layers to combine the knowledge encoded within these adapters for downstream tasks. Each fusion layer is a parameterized mixer of the available trained adapters that can identify and activate the most useful adapters for a given input. Our method diverges from prior work by including a knowledge consolidation phase, during which we teach the fusion layers to effectively combine knowledge from both the original PLM and newly-acquired external knowledge using a large collection of unannotated texts. After the consolidation phase, the complete knowledge-enhanced model can be fine-tuned for any downstream task of interest to achieve optimal performance. Extensive experiments on many biomedical NLP datasets show that our proposed framework consistently improves the performance of the underlying PLMs on various downstream tasks such as natural language inference, question answering, and entity linking. These results demonstrate the benefits of using multiple sources of external knowledge to enhance PLMs and the effectiveness of the framework for incorporating knowledge into PLMs. Finally, while primarily focused on the biomedical domain in this work, our framework is highly adaptable and can be easily applied to other domains, such as the bioenergy sector.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2022

U.S. Department of Energy: National Virtual Biotechnology Laboratory (Technical Report)

With funding from the CARES Act, the U.S Department of Energy (DOE) established the National Virtual Biotechnology Laboratory (NVBL) in March 2020 to address key challenges associated with the COVID-19 crisis. The NVBL brought together the broad scientific and technical expertise and resources of DOE’s 17 national laboratories to help tackle medical supply shortages, discover potential drugs to fight the virus, develop and validate COVID-19 testing methods, model disease spread and impact across the nation, and understand virus transport in buildings and the environment. National laboratory resources leveraged for this effort include a suite of world-leading user facilities broadly available to the research community, such as light and neutron sources, nanoscale science research centers, sequencing and biocharacterization facilities, and high-performance computing facilities. As part of the NVBL framework, DOE rapidly assembled five project teams to (1) identify new targets for medical therapeutics; (2) develop innovations in testing capabilities; (3) provide epidemiological and logistical support; (4) understand viral fate and transport in the environment; and (5) address supply chain bottlenecks by harnessing extensive additive manufacturing capabilities. Each research team was charged with defining high-impact projects that could be completed in a 6-month sprint while coordinating their developments with academia, other government agencies, and the private sector. Within months, NVBL teams used DOE’s high-performance computers and light and neutron sources to identify promising candidates for antibodies and antivirals that universities and drug companies are now evaluating. NVBL researchers also developed new diagnostic targets and sample collection approaches, and supported efforts by the U.S. Food and Drug Administration, Centers for Disease Control and Prevention, and U.S. Department of Defense to establish national guidelines used in administering millions of tests. Researchers used artificial intelligence and high-performance computing to produce near-real-time data analysis to forecast disease transmission, stress on public health infrastructure, and economic impact, which supported decision-makers at the local, state, and national levels. To minimize virus uptake and protect human health, NVBL teams studied how to control indoor virus movement. Researchers also produced innovations in materials and advanced manufacturing that mitigated shortages in test kits and personal protective equipment, creating nearly 1,000 new jobs. Through its NVBL framework, DOE has contributed significantly to the nation’s COVID response, demonstrating in only a few months the critical impact of its national laboratories. NVBL’s accomplishments demonstrate not only the powerful resource represented by DOE’s national laboratories working together to meet national needs, but also the effectiveness of the integrated NVBL framework for rapidly responding to emergencies with research and development solutions. Going forward, the NVBL is poised to apply the unique capabilities and expertise of the national laboratory complex to future national and international emergencies, both natural and engineered. Through this framework, DOE will continue to be an integral component of agency-wide efforts to prepare for and respond to biorisks and other crises. This technical report describes the goals, progress, and results of NVBL’s five project teams—Molecular Design for COVID-19 Therapeutics, COVID-19 Testing, Epidemiological Modeling, Viral Fate and Transport, and Materials and Manufacturing of Critical Supplies—and lists each team’s publications and research output.

42 ENGINEERING↗
DOE OSTI2024

Grid Integration of Renewable Energy and Energy Storage

Grid integration of renewable energy and energy storage requires forward-looking planning process, and increased emphasizes on reliability, resilience, and equity. Power-electronics based energy generation including solar, wind, distributed energy resources (DERs), and various types of grid-tied energy storage and emerging loads, are reshaping grid operator's understanding on interconnection level performance and responses. This paper will present the ongoing work at PNNL related to power electronics R&D, energy modeling and analysis, and a wide spectrum of grid stability studies and technologies in support of grid integration of renewable energy and energy storage.

Power Electronics, grid integration of renewable e↗
DOE OSTI2020

Phase Contrast Imaging Diagnostic on DIII-D (1994-2007); Phase Contrast Imaging Diagnostic on DIII-D and Alcator C-Mod (2007-2010); Experimental Study of Waves, Turbulence and Transport, and Model Validation with Phase Contrast Imaging on DIII-D and Alcator C-Mod (2010-2012); Phase Contrast Imaging Diagnostic Upgrade on DIII-D for Measuring High-k Turbulence and Alfven modes (2021-2016); Phase Contrast Imaging Diagnostic Upgrade on DIII-D for Full Multi-Scale Measurements (2016-2020) (Final Report)

This report describes the first twenty-five years of development and use of the Phase Contrast Imaging (PCI) diagnostic for measuring plasma fluctuations on the DIII–D tokamak. One of the key challenges in moving tokamak technology forward to the stage of a nuclear reactor remains understanding how energy and particles are transported across the magnetic field by the action of turbulence and waves, and PCI provides a highly flexible and capable measurement of these fluctuations. The PCI diagnostic uses a laser beam to probe the plasma and optical filtering to produce an amplitude variation on a linear detector array which provides an image of the density waves in the plasma. The PCI covers an exceptional range in frequency and wavelength of the measured fluctuations, allowing observation of plasma-sized magnetohydrodynamic (MHD) modes and ion- and electron-scale turbulence. Modulation of the beam amplitude allows measurement of radio frequency (RF) waves.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Universal Input-Output Model of GFM Functions and Data-Driven Verification Methods

An overarching goal of the UNiversal Interoperability for grid-Forming Inverters (UNIFI) Consortium is to develop vendor agnostic specifications and guidelines that ensure interoperability of gridforming (GFM) inverter-based resources (IBRs) without requiring vendors or system operators to reveal proprietary information. These UNIFI principles and specifications are envisioned to apply to a wide range of technologies and systems. The initial work on the UNIFI principles and specifications has focused on performance requirements and high-level aspirational principles outlined in [1]. Going forward, a key question is how to translate such high-level requirements and principles into rigorous specifications that can be enforced and validated for a wide range of IBRs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Resummation for lattice QCD calculation of generalized parton distributions at nonzero skewness

Large-momentum effective theory (LaMET) provides an approach to directly calculate the x-dependence of generalized parton distributions (GPDs) on a Euclidean lattice through power expansion and a perturbative matching. When a parton’s momentum becomes soft, the corresponding logarithms in the matching kernel become non-negligible at higher orders of perturbation theory, which requires a resummation. But the resummation for the off-forward matrix elements at nonzero skewness ξ is difficult due to their multi-scale nature. In this work, we demonstrate that these logarithms are important only in the threshold limit, and derive the threshold factorization formula for the quasi-GPDs in LaMET. We then propose an approach to resum all the large logarithms based on the threshold factorization, which is implemented on a GPD model. We demonstrate that the LaMET prediction is reliable for [−1 + x 0 , −ξ − x 0 ] ∪ [−ξ + x 0 , ξ − x 0 ] ∪ [ξ + x 0 , 1 − x 0 ], where x 0 is a cutoff depending on hard parton momenta. Through our numerical tests with the GPD model, we demonstrate that our method is self-consistent and that the inverse matching does not spread the nonperturbative effects or power corrections to the perturbatively calculable regions.

hadronic spectroscopy↗
DOE OSTI2024

Measurement of the effective leptonic weak mixing angle

Using pp collision data at $\sqrt{s}$ = 13 TeV, recorded by the LHCb experiment between 2016 and 2018 and corresponding to an integrated luminosity of 5.4 fb −1 , the forward-backward asymmetry in the pp → Z/γ* → μ + μ − process is measured. The measurement is carried out in ten intervals of the difference between the muon pseudorapidities, within a fiducial region covering dimuon masses between 66 and 116 GeV, muon pseudorapidities between 2.0 and 4.5 and muon transverse momenta above 20 GeV. These forward-backward asymmetries are compared with predictions, at next-to-leading order in the strong and electroweak couplings. The measured effective leptonic weak mixing angle is ${\sin}^2{\theta}_{\textrm{eff}}^{\ell }=0.23147\pm 0.00044\pm 0.00005\pm 0.00023,$ where the first uncertainty is statistical, the second arises from systematic uncertainties associated with the asymmetry measurement, and the third arises from uncertainties in the fit model used to extract ${\sin}^2{\theta}_{\textrm{eff}}^{\ell }$ from the asymmetry measurement. This result is based on an arithmetic average of results using the CT18, MSHT20, and NNPDF31 parameterisations of the proton internal structure, and is consistent with previous measurements and with predictions from the global electroweak fit.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Nano-enhanced solid-state hydrogen storage: Balancing discovery and pragmatism for future energy solutions

Nanomaterials have revolutionized the battery industry by enhancing energy storage capacities and charging speeds, and their application in hydrogen (H 2 ) storage likewise holds strong potential, though with distinct challenges and mechanisms. H 2 is a crucial future zero-carbon energy vector given its high gravimetric energy density, which far exceeds that of liquid hydrocarbons. However, its low volumetric energy density in gaseous form currently requires storage under high pressure or at low temperature. This review critically examines the current and prospective landscapes of solid-state H 2 storage technologies, with a focus on pragmatic integration of advanced materials such as metal-organic frameworks (MOFs), magnesium-based hybrids, and novel sorbents into future energy networks. These materials, enhanced by nanotechnology, could significantly improve the efficiency and capacity of H 2 storage systems by optimizing H 2 adsorption at the nanoscale and improving the kinetics of H 2 uptake and release. We discuss various H 2 storage mechanisms—physisorption, chemisorption, and the Kubas interaction—analyzing their impact on the energy efficiency and scalability of storage solutions. The review also addresses the potential of “smart MOFs”, single-atom catalyst-doped metal hydrides, MXenes and entropy-driven alloys to enhance the performance and broaden the application range of H 2 storage systems, stressing the need for innovative materials and system integration to satisfy future energy demands. High-throughput screening, combined with machine learning algorithms, is noted as a promising approach to identify patterns and predict the behavior of novel materials under various conditions, significantly reducing the time and cost associated with experimental trials. In closing, we discuss the increasing involvement of various companies in solid-state H 2 storage, particularly in prototype vehicles, from a techno-economic perspective. In conclusion, this forward-looking perspective underscores the necessity for ongoing material innovation and system optimization to meet the stringent energy demands and ambitious sustainability targets increasingly in demand.

25 ENERGY STORAGE↗