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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

New Era Towards Autonomous Additive Manufacturing: A Review of Recent Trends and Future Perspectives

Abstract The Additive Manufacturing (AM) landscape has significantly transformed in alignment with Industry 4.0 principles, primarily driven by the integration of Artificial Intelligence (AI) and Digital Twin (DT). However, current Intelligent Additive Manufacturing (IAM) systems face limitations such as fragmented AI tool usage and suboptimal human-machine interaction (HMI). This paper reviews existing IAM solutions, emphasizing control, monitoring, process autonomy, and end-to-end integration, and identifies key limitations, such as the absence of a high-level controller for global decision-making. To address these gaps, we propose a transition from IAM to Autonomous Additive Manufacturing (AAM), featuring a hierarchical framework with four integrated layers: knowledge, generative solution, operational, and cognitive. In the cognitive layer, AI agents notably enable machines to independently observe, analyze, plan, and execute operations that traditionally require human intervention. These capabilities streamline production processes and expand the possibilities for innovation, particularly in sectors like in-space manufacturing (ISM). Additionally, this paper discusses the role of AI in self-optimization and lifelong learning, positing that the future of AM will be characterized by a symbiotic relationship between human expertise and advanced autonomy, fostering a more adaptive, resilient manufacturing ecosystem.

Fan, Haolin↗
DOE OSTI2025

Neural architecture codesign for fast physics applications

We develop a pipeline to streamline neural architecture codesign for physics applications to reduce the need for ML expertise when designing models for novel tasks. Our method employs neural architecture search and network compression in a two-stage approach to discover hardware efficient models. This approach consists of a global search stage that explores a wide range of architectures while considering hardware constraints, followed by a local search stage that fine-tunes and compresses the most promising candidates. We exceed performance on various tasks and show further speedup through model compression techniques such as quantization-aware-training and neural network pruning. We synthesize the optimal models to high level synthesis code for FPGA deployment with the hls4ml library. Additionally, our hierarchical search space provides greater flexibility in optimization, which can easily extend to other tasks and domains. We demonstrate this with two case studies: Bragg peak finding in materials science and jet classification in high energy physics, achieving models with improved accuracy, smaller latencies, or reduced resource utilization relative to the baseline models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

32 examples of LLM applications in materials science and chemistry: towards automation, assistants, agents, and accelerated scientific discovery

Abstract Large language models (LLMs) are reshaping many aspects of materials science and chemistry research, enabling advances in molecular property prediction, materials design, scientific automation, knowledge extraction, and more. Recent developments demonstrate that the latest class of models are able to integrate structured and unstructured data, assist in hypothesis generation, and streamline research workflows. To explore the frontier of LLM capabilities across the research lifecycle, we review applications of LLMs through 32 total projects developed during the second annual LLM hackathon for applications in materials science and chemistry, a global hybrid event. These projects spanned seven key research areas: (1) molecular and material property prediction, (2) molecular and material design, (3) automation and novel interfaces, (4) scientific communication and education, (5) research data management and automation, (6) hypothesis generation and evaluation, and (7) knowledge extraction and reasoning from the scientific literature. Collectively, these applications illustrate how LLMs serve as versatile predictive models, platforms for rapid prototyping of domain-specific tools, and much more. In particular, improvements in both open source and proprietary LLM performance through the addition of reasoning, additional training data, and new techniques have expanded effectiveness, particularly in low-data environments and interdisciplinary research. As LLMs continue to improve, their integration into scientific workflows presents both new opportunities and new challenges, requiring ongoing exploration, continued refinement, and further research to address reliability, interpretability, and reproducibility.

Computer Science↗
DOE OSTI2025

Hosting downscaled decision-relevant community data products in ESGF2-US

As regionally-relevant high-resolution Earth system data is increasingly relied upon across scientific, policy, and practitioner communities, there is an urgent need for coordinated and federated infrastructure to store, manage, standardize, and distribute decision-relevant community data products. Substantial effort is required to ensure that these products, which are often critical for regional impact assessments and decision-making, are findable, accessible, interoperable, and reusable. The Earth System Grid Federation US project (ESGF2-US) is addressing this challenge by expanding its open-source, distributed platform to support the hosting and dissemination of downscaled Earth system datasets. This expansion includes aligning new downscaled datasets with developing community standards for metadata and file structure, consistent with existing ESGF archives. This includes ensuring CF-compliance, applying CMORization where appropriate, and developing tools to streamline user access. In this paper, we highlight the technical and coordination work required to bring downscaled data into ESGF2-US and aim to inform the broader Earth system data user community about the growing availability and utility of these curated resources.

ESGF↗
DOE OSTI2025

NGPINT V3: a containerized orchestration Python software for discovery of next-generation protein–protein interactions

Abstract Summary Batch yeast two-hybrid (Y2H) assays, leveraged with next-generation sequencing, have afforded successful innovations for the analysis of protein–protein interactions. NGPINT is a Conda-based software designed to process the millions of raw sequencing reads resulting from Y2H–next-generation interaction screens. Over time, increasing compatibility and dependency issues have prevented clean NGPINT installation and operation. A system-wide update was essential to continue effective use with its companion software, Y2H-SCORES. We present NGPINT V3, a containerized implementation built with both Singularity and Docker, allowing accessibility across virtually any operating system and computing environment. Availability and implementation This update includes streamlined dependencies and container images hosted on Sylabs (https://cloud.sylabs.io/library/schuyler/ngpint/ngpint) and Dockerhub (https://hub.docker.com/r/schuylerds/ngpint), facilitating easier adoption and integration into high-throughput and cloud-computing workflows. Full instructions and software can be also found in the GitHub repository https://github.com/Wiselab2/NGPINT_V3 and Zenodo https://doi.org/10.5281/zenodo.15256036.

Biochemistry & Molecular Biology↗
DOE OSTI2026

Meta2DB: Curated Shotgun Metagenomic Feature Sets and Metadata for Health State Prediction

Meta2DB is a curated metagenomic and metadata database that provides structurally consistent microbiome taxonomy feature count tables for 13 897 samples across 84 studies, 23 disease states, and 34 geographical locations. All samples were uniformly processed using a streamlined metagenomic classification pipeline that employs a unique and comprehensive reference database indexed to contain all sequences across all kingdoms of life that were present in the NCBI Nucleotide (nt) database retrieved on 4 January 2023. This pipeline leverages high-performance computing (HPC) resources at Lawrence Livermore National Laboratory and was used to process 50TB of publicly available raw metagenomic sequence data. Extensive metadata curation was carried out through a combination of manual curation and automated parsing, producing a consistent inter-study metadata table specifically structured to facilitate training of ML models for prediction of human health.

Kok, C [Lawrence Livermore National Laboratory (LL↗
DOE OSTI2025

Stable hypermutators revealed by the genomic landscape of genes involved in genome stability among yeast species

Mutator phenotypes are short-lived due to the rapid accumulation of deleterious mutations. Yet, recent observations reveal that certain fungi can undergo prolonged accelerated evolution after losing genes involved in DNA repair. Here, we surveyed 1,154 yeast genomes representing nearly all known yeast species of the subphylum Saccharomycotina (phylum Ascomycota) to examine the relationship between reduced gene repertoires broadly associated with genome stability functions (e.g., DNA repair, cell cycle) and elevated evolutionary rates. We identified three distantly related lineages—encompassing 12% of species—that had both the most streamlined sets of genes involved in genome stability (specifically DNA repair) and the highest evolutionary rates in the entire subphylum. Two of these “faster-evolving lineages” (FELs)—a subclade within the order Pichiales and the Wickerhamiella/Starmerella (W/S) clade (order Dipodascales)—are described here for the first time, while the third corresponds to a previously documented Hanseniaspora FEL. Examination of genome stability gene repertoires revealed a set of genes predominantly absent in these three FELs, suggesting a potential role in the observed acceleration of evolutionary rates. In the W/S clade, genomic signatures are consistent with a substantial mutational burden, including pronounced A|T bias and endogenous DNA damage. Interestingly, we found that the W/S clade also contains DNA repair genes possibly acquired through horizontal gene transfer, including a photolyase of bacterial origin. These findings highlight how hypermutators can persist across macroevolutionary timescales, potentially linked to the loss of genes related with genome stability, with horizontal gene transfer as a possible avenue for partial functional compensation.

DNA repair↗
DOE OSTI2025

MolViewSpec: a Mol* extension for describing and sharing molecular visualizations

Data visualization is a pivotal component of a structural biologist’s arsenal. The Mol* Viewer makes molecular visualizations available to broader audiences via most web browsers. While Mol* provides a wide range of functionality, it has a steep learning curve and is only available via a JavaScript interface. To enhance the accessibility and usability of web-based molecular visualization, we introduce MolViewSpec (molstar.org/mol-view-spec), a standardized approach for defining molecular visualizations that decouples the definition of complex molecular scenes from their rendering. Scene definition can include references to commonly used structural, volumetric, and annotation data formats together with a description of how the data should be visualized and paired with optional annotations specifying colors, labels, measurements, and custom 3D geometries. Developed as an open standard, this solution paves the way for broader interoperability and support across different programming languages and molecular viewers, enabling more streamlined, standardized, and reproducible visual molecular analyses. MolViewSpec is freely available as a Mol* extension and a standalone Python package.

Midlik, Adam [European Bioinformatics Institute (U↗
DOE OSTI2025

Enhancing lipid production in plant cells through automated high-throughput genome engineering and phenotyping

Plant bioengineering is a time-consuming and labor-intensive process with no guarantee of achieving desired traits. Here, we present a fast, automated, scalable, high-throughput pipeline for plant bioengineering (FAST-PB) in maize (Zea mays) and Nicotiana benthamiana. FAST-PB enables genome editing and product characterization by integrating automated biofoundry engineering of callus and protoplast cells with single-cell matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). We first demonstrated that FAST-PB could streamline Golden Gate cloning, with the capacity to construct 96 vectors in parallel. Using FAST-PB in protoplasts, we found that PEG2050 increased transfection efficiency by over 45%. For proof-of-concept, we established a reporter-gene-free method for CRISPR editing and phenotyping via mutation of high chlorophyll fluorescence 136. We show that diverse lipids were enhanced up to 6-fold using CRISPR activation of lipid controlling genes. In callus cells, an automated transformation platform was employed to regenerate plants with enhanced lipid traits through introducing multigene cassettes. Lastly, FAST-PB enabled high-throughput single-cell lipid profiling by integrating MALDI-MS with the biofoundry, protoplast, and callus cells, differentiating engineered and unengineered cells using single-cell lipidomics. Furthermore, these innovations massively increase the throughput of synthetic biology, genome editing, and metabolic engineering and change what is possible using single-cell metabolomics in plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Targeted genetic manipulation and yeast-like evolutionary genomics in the green alga Auxenochlorella

Auxenochlorella spp. are diploid oleaginous green algae whose streamlined genomes can be readily manipulated by homologous recombination, making them highly amenable to discovery research and bioengineering. Vegetatively diploid organisms experience specific evolutionary phenomena, including allodiploid hybridization, mitotic recombination, loss-of-heterozygosity, and aneuploidy; however, studies of these forces have largely focused on yeasts. Here, we present a telomere-to-telomere phased diploid genome assembly of Auxenochlorella UTEX 250-A (haploid length 22 Mb) and introduce a genetic toolkit for site-specific manipulation of the nuclear genome in multiple strains, featuring several selectable markers, inducible promoters, and fluorescent reporters for protein localization. UTEX 250-A is an allodiploid hybrid of Auxenochlorella protothecoides and Auxenochlorella symbiontica, two species differentiated by extensive chromosomal rearrangements. UTEX 250-A haplotypes are a mosaic of each parental species following mitotic recombination, and two chromosomes are trisomic. Loss-of-heterozygosity events are pervasive across Auxenochlorella and can evolve rapidly in the laboratory. High-quality structural annotation yielded ∼7,500 genes per haplotype. Auxenochlorella have experienced gene family loss and reduction, including core photosynthesis genes, and exhibit periodic adenine and cytosine methylation at promoters and gene bodies, respectively. Approximately 10% of genes, especially those involved in DNA repair and sex, overlap antisense long noncoding RNAs, which may participate in a regulatory mechanism. We demonstrate the utility of Auxenochlorella for fundamental research by knockout of a chlorophyll biosynthesis enzyme, and confirm one trisomy by allele-specific transformation. These results demonstrate the generality of several evolutionary forces associated with vegetative diploidy and provide a foundation for the use of Auxenochlorella as a reference organism.

CHL27↗
DOE OSTI2025

Stokes-dependent droplet collection efficiency on a NACA 0012 airfoil from droplet-informed simulations with statistical overloading

Accurate modelling of ice accretion on aircraft wings requires analysing droplet impingement on the surface to optimize the design of ice-protection systems. We perform Euler–Lagrange simulations of a droplet-laden flow impinging on a NACA 0012 airfoil. Our study includes water droplets with eight discrete sizes ranging from 1 to 160 microns. We vary the free-stream velocity of the incoming airflow in the range 60 ≤ U ≤ 240 m s −1 and the chord length of the airfoil in the range 0.5 ≤ c ≤ 2 m. Due to the dilute nature of supercooled clouds, one-way coupling is used in the simulations. The effects of droplet breakup and collision are also neglected. To reduce the computational cost, we employ statistical overloading of droplets, allowing us to simulate millions of impinging droplets in a time span on the order of milliseconds. Our results show that the droplet collection efficiency, which measures the likelihood of droplet impingement on the airfoil surface, increases with droplet size and free-stream velocity but decreases with airfoil size. We demonstrate that collection efficiency, impingement velocity and impingement angle are primarily dictated by a single non-dimensional parameter, the droplet Stokes number. We also identify a critical stagnation-streamline Stokes number below which impingements do not occur and use it to estimate the minimum droplet size for impingement. In addition, we observe droplet behaviour to become Stokes number independent at large values of the Stokes number. This article is part of the theme issue ‘Heat and mass transfer in frost and ice’.

Science & Technology - Other Topics↗
DOE OSTI2025

Second-order renormalized Hamiltonian of Yukawa theory

Using the renormalization group procedure for effective particles we calculate the effective Hamiltonians in the theory of a fermion field coupled to a scalar field via the Yukawa interaction. The theory is renormalized by the addition of counterterms. Necessary counterterms are determined by computing matrix elements of the effective Hamiltonian. All calculations are performed up to the second order in the expansion in powers of the coupling constant. Renormalized effective Hamiltonians are well-defined symmetric forms acting in the Fock space as opposed to the renormalized bare Hamiltonian, which is not well defined without regularization. We introduce computational techniques that should streamline higher-order calculations and may be of independent interest.

Ab initio calculations↗
DOE OSTI2025

Closing the Accuracy Gap in Tandem Photovoltaic Testing: An Accessible and Efficient Spectral Tuning Method Using LED-Based Simulators for Research Laboratories and Industry

Accurate performance calibration of multijunction (MJ) solar cells is critical for advancing this technology toward large-scale terrestrial application, yet existing testing methods developed by photovoltaics calibration laboratories remain prohibitively complex and resource intensive for most research laboratories. Current approaches rely on expensive multisource simulators and/or intricate spectral tuning algorithms, limiting accessibility and hindering standardized comparisons of emerging MJ technologies such as perovskite-based tandems. This paper introduces a streamlined spectral irradiance adjustment method for light-emitting diode (LED)-based solar simulators, which are increasingly adopted in the photovoltaics community due to their versatility and cost-effectiveness. The method we present bins LED channels into groups based on the number of junctions of the MJ photovoltaic device under test (DUT) and their corresponding band gaps and incorporates an automated tuning algorithm that eliminates the need to adjust each channel’s irradiance individually. This tuning algorithm requires the relative spectral responsivities of both the DUT and a broadband reference cell, as well as a calibrated spectroradiometer. Measurement validation across various MJ devices, including III-V and perovskite/silicon tandems, demonstrates excellent agreement within 1% with well-established xenon-tungsten multisource simulators and associated tuning algorithms. By enabling precise spectral tuning with readily available equipment and a simple tuning algorithm, our approach bridges the measurement accuracy gap between research laboratories and accredited testing facilities, fostering more reliable device comparisons and accelerating the translation of MJ technologies into real-world energy systems.

14 SOLAR ENERGY↗
DOE OSTI2025

BAGELS for simultaneous polarization, orbit, and optics control in electron storage rings

We present a new method for minimizing the effects of radiative depolarization in electron storage rings by use of a minimal number of special vertical orbit bumps. The bumps can be used to minimize the effects of radiative depolarization while simultaneously maintaining other common benefits of vertical orbits, e.g., transverse coupling and vertical dispersion control. Because simultaneously optimizing the large number of vertical correctors in a ring is operationally infeasible, we use dimensionality reduction to define a minimal number of the most effective groups of vertical correctors that can be optimized during operation, motivating the name “Best Adjustment Groups for ELectron Spin” (BAGELS). The method is streamlined by using suitable “basis bumps” instead of all individual vertical correctors. We define three types of basis bumps for different purposes: (i) generates no delocalized transverse coupling nor delocalized vertical dispersion, (ii) generates no delocalized vertical dispersion, and (iii) generates no delocalized transverse coupling. BAGELS has been essential in the design of the Electron Storage Ring (ESR) of the Electron-Ion Collider (EIC) and will be beneficial for any polarized electron ring, including FCC-ee. HERA and LEP would have likely benefitted as well. We use BAGELS to significantly increase polarization in the 18 GeV EIC-ESR, beyond what is achievable with conventional methods; in the 1-IP lattice, we nearly double the asymptotic polarization, and in the 2-IP lattice, we more than triple the asymptotic polarization. We also use BAGELS to construct knobs that can be used for global coupling correction, and knobs that generate vertical emittance for beam size matching, all while having minimal impacts on the polarization and orbit/optics. Published by the American Physical Society 2025

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

General mass variable flavor number scheme for 𝑍 boson production in association with a heavy quark at hadron colliders

We present a methodology to streamline implementation of massive-quark radiative contributions in calculations with a variable number of active partons in proton-proton collisions. The methodology introduces subtraction and residual heavy-quark parton distribution functions (PDFs) to implement calculations in the Aivazis–Collins–Olness–Tung (ACOT) factorization scheme and its simplified realization in various processes up to the next-to-the-next-to-leading order in the QCD coupling strength. Interpolation tables for bottom-quark subtraction and residual distributions for CT18 NLO and NNLO PDF ensembles are provided in the common LHAPDF6 format. A numerical calculation of 𝑍-boson production with at least one 𝑏 jet at the Large Hadron Collider beyond the lowest order in QCD is considered for illustration purposes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Fully Scalable Randomized Benchmarking Without Motion Reversal

We introduce , a protocol that streamlines traditional RB by using circuits consisting almost entirely of independent identically distributed (IID) layers of gates. BiRB reliably and efficiently extracts the average error rate of a Clifford gate set by sending tensor-product eigenstates of random Pauli operators through random circuits with IID layers. Unlike existing RB methods, BiRB does not use motion reversal circuits—i.e., circuits that implement the identity (or a Pauli) operator—which simplifies both the method and the theory proving its reliability. Furthermore, this simplicity enables scaling BiRB to many more qubits than the most widely used RB methods. Published by the American Physical Society 2024

Hines, Jordan (ORCID:0000000151267256)↗
DOE OSTI2025

Gravitational Wave Scattering via the Born Series: Scalar Tidal Matching to 𝒪⁡(𝐺 7 ) and Beyond

We introduce a novel method to compute gravitational wave amplitudes within the framework of effective field theory. By reinterpreting the Feynman diagram expansion as a Born series, our method offers several key advantages. It directly yields partial wave amplitudes, streamlining the matching with black hole perturbation theory. Long-distance gravitational interactions are unambiguously factorized from short-distance tidal effects, including dissipation, which are systematically incorporated via an in-in worldline effective action. Crucially, at every order in perturbation theory, integrals are expressed in terms of harmonic polylogarithms, enabling an end-to-end computation scalable to arbitrary orders. We illustrate the method with new predictions for scalar black hole Love numbers and their renormalization group equations to 𝒪⁡(𝐺 7 ).

effective field theory↗
DOE OSTI2025

Energy-enhanced expansion of the standard model effective field theory

We formalize energy-scaling arguments in the standard model effective field theory (SMEFT) to estimate the effects of operators up to dimension ten. Our approach relies on weakly coupled UV completions with no presumed large hierarchies between the Wilson coefficients. We introduce a classification based on the number of external legs and an energy-counting parameter. We establish a dual expansion in 𝑣/Λ and 𝐸/Λ. Extending to four-, five-, and six-particle vertices, our framework highlights energy-enhanced operators that dominate high-energy processes at the High Luminosity-Large Hadron Collider. This organization streamlines experimental analyses to only include operators with energetic impact in their analyses and enhances the discoverability of new physics within the SMEFT framework.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗