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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The DECam MAGIC Survey: Spectroscopic Follow-up of the Most Metal-poor Stars in the Distant Milky Way Halo *

In this work, we present high-resolution spectroscopic observations for six metal-poor stars with [Fe/H] < –3 (including one with [Fe/H] < –4), selected using narrowband Ca ii HK photometry from the DECam MAGIC Survey. The spectroscopic data confirm the accuracy of the photometric metallicities and allow for the determination of chemical abundances for 16 elements, from carbon to barium. The program stars have chemical abundances consistent with the [Fe/H] < –3 range. A kinematic/dynamical analysis suggests that all program stars belong to the distant Milky Way halo population (heliocentric distances 35 < d helio /kpc ≲ 55), including three with high-energy orbits that might have been associated with the Magellanic system and one, J0026−5445, having parameters consistent with being a member of the Sagittarius stream. The remaining two stars show kinematics consistent with the Gaia-Sausage/Enceladus dwarf galaxy merger. J0433−5548, with [Fe/H] = –4.12, is a carbon-enhanced ultra metal-poor star, with [C/Fe] = +1.73. This star is believed to be a bona fide second-generation star, and its chemical abundance pattern was compared with yields from metal-free supernova models. Results suggest that J0433−5548 could have been formed from a gas cloud enriched by a single supernova explosion from an ∼11 M ⊙ star in the early Universe. The successful identification of such objects demonstrates the reliability of photometric metallicity estimates, which can be used for target selection and statistical studies of faint targets in the Milky Way and its satellite population. These discoveries illustrate the power of measuring chemical abundances of metal-poor Milky Way halo stars to learn more about early galaxy formation and evolution.

CEMP stars↗
DOE OSTI2023

Global polarization of hyperons and spin alignment of vector mesons in quark matters

Relativistic heavy ion collider (RHIC) as a dedicated nuclear facility has made a few major discoveries in physics. This year marks the 30th year STAR Collaboration formation and the 23th year of STAR detector operation and data collection at RHIC. In the last two decades, STAR has collected many datasets, exhibiting scientific versatility and flexibility of the RHIC facility. The total dataset in the first year is less than 1 million good events, and currently there are about 1 billion events per dataset. The Global Hyperon Polarization was proposed in 2004. This immediately prompted the STAR Collaboration to search for this phenomenon from the early datasets. The null results were presented at Quark Matter Conference in Shanghai in 2006 and subsequently published. Although there were peripheral and continuous efforts in the following decade, no positive result has been observed experimentally. This situation changed in the following decade with the upgrade of high data rate and time-of-flight (TOF) detector and the progress of the Beam Energy Scan Phase I (BES-I). The experimental discoveries of the global polarization of hyperons in 2017 and the spin alignment of vector mesons in 2023 at RHIC-STAR confirm the theory which was established nearly twenty years ago. The theory and these measurements open the way to studying the properties of the hot and dense nuclear matter created in high-energy heavy ion collisions from a new degree of freedom, spin. We briefly review these discoveries from the proposals of theory to the experimental measurements, and summarize the related measurements at the existing facilities and the theoretical explanations to the original proposal. The basic understanding and the original proposal are still valid and fundamental, that is, the angular momentum of system can transform into a spin effect observable in experiment. However, it appears that in each case a new model is needed to explain the new experimental observation. We need a more basic theory to help us unify all these spin related phenomena. Over the past five years, STAR has successfully installed 3 new detectors and we have begun to see the physical analysis results from datasets with those new functions. What makes the STAR detector viable after 20 years of operation is its continuous evolution through successful upgrades, with new scientific programs added year by year. The next big thing is to forward upgrade a tracking system (3 layers of silicon strips and 4 layers of sTGC chambers) and a calorimetry system (electromagnetic and hadronic calorimeters). In addition to studying the spin structure of protons by using the polarized proton beams at RHIC, the upgrades also provide a unique ability to investigate the origin of Λ Global Polarization as a function of rapidity and rapidity (de-)correlations in Au+Au collisions.

Physics↗
DOE OSTI2025

Fractional quantization in insulators from Hall to Chern

The discovery of the integer and fractional quantum Hall effects naturally prompted the question of whether these effects can be realized without a magnetic field. Answering this is fundamentally important and requires a synthesis of the concepts of band topology, quantum geometry and electronic correlations. Here we summarize the basic concepts of both fractional Chern and fractional topological insulators and illustrate them with the theoretical lattice models that support the flat Chern bands in which the states were first predicted. We then examine their experimental realizations in twisted bilayer transition metal dichalcogenides and moiré rhombohedral few-layer graphene. Here, we also discuss the future challenges and opportunities in this research field.

Quantum Hall↗
DOE OSTI2022

Enabling FAIR data in Earth and environmental science with community-centric (meta)data reporting formats

Abstract Research can be more transparent and collaborative by using Findable, Accessible, Interoperable, and Reusable (FAIR) principles to publish Earth and environmental science data. Reporting formats—instructions, templates, and tools for consistently formatting data within a discipline—can help make data more accessible and reusable. However, the immense diversity of data types across Earth science disciplines makes development and adoption challenging. Here, we describe 11 community reporting formats for a diverse set of Earth science (meta)data including cross-domain metadata (dataset metadata, location metadata, sample metadata), file-formatting guidelines (file-level metadata, CSV files, terrestrial model data archiving), and domain-specific reporting formats for some biological, geochemical, and hydrological data (amplicon abundance tables, leaf-level gas exchange, soil respiration, water and sediment chemistry, sensor-based hydrologic measurements). More broadly, we provide guidelines that communities can use to create new (meta)data formats that integrate with their scientific workflows. Such reporting formats have the potential to accelerate scientific discovery and predictions by making it easier for data contributors to provide (meta)data that are more interoperable and reusable.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Learning Molecular Mixture Property Using Chemistry-Aware Graph Neural Network

Recent advances in machine learning (ML) are expediting materials discovery and design. One significant challenge facing ML for materials is the expansive combinatorial space of potential materials formed by diverse constituents and their flexible configurations. This complexity is particularly evident in molecular mixtures, a frequently explored space for materials, such as battery electrolytes. Owing to the complex structures of molecules and the sequence-independent nature of mixtures, conventional ML methods have difficulties in modeling such systems. Here, we present MolSets, a specialized ML model for molecular mixtures, to overcome the difficulties. Representing individual molecules as graphs and their mixture as a set, MolSets leverages a graph neural network and the deep sets architecture to extract information at the molecular level and aggregate it at the mixture level, thus addressing local complexity while retaining global flexibility. We demonstrate the efficacy of MolSets in predicting the conductivity of lithium battery electrolytes and highlight its benefits in the virtual screening of the combinatorial chemical space. Published by the American Physical Society 2024

Zhang, Hengrui (ORCID:0000000231831654)↗
DOE OSTI2022

Portability for GPU-accelerated molecular docking applications for cloud and HPC: can portable compiler directives provide performance across all platforms?

High-throughput structure-based screening of drug-like molecules has become a common tool in biomedical research. Recently, acceleration with graphics processing units (GPUs) has provided a large performance boost for molecular docking programs. Both cloud and high-performance computing (HPC) resources have been used for large screens with molecular docking programs; while NVIDIA GPUs have dominated cloud and HPC resources, new vendors such as AMD and Intel are now entering the field, creating the problem of software portability across different GPUs. Ideally, software productivity could be maximized with portable programming models that are able to maintain high performance across architectures. While in many cases compiler directives have been used as an easy way to offload parallel regions of a CPU-based program to a GPU accelerator, they may also be an attractive programming model for providing portability across different GPU vendors, in which case the porting process may proceed in the reverse direction: from low-level, architecture-specific code to higher-level directive-based abstractions. MiniMDock is a new mini-application (miniapp) designed to capture the essential computational kernels found in molecular docking calculations, such as are used in phar-maceutical drug discovery efforts, in order to test different solutions for porting across GPU architectures. Here we extend MiniMDock to GPU offloading with OpenMP directives, and compare to performance of kernels using CUDA and HIP on NVIDIA and AMD GPUs, respectively, as well as across different compilers, exploring performance bottlenecks. We document this reverse-porting process, from highly optimized device code to a higher-level version using directives, compare code structure, and describe barriers that were overcome in this effort.

Thavappiragasam, Mathialakan↗
DOE OSTI2024

Enhancing the hunt for new phenomena in dijet final states using anomaly detection filters at the high-luminosity large Hadron Collider

In the realm of dijet searches in high-energy physics, a significant challenge has emerged: with experiments producing more and more data, the traditional methods of using analytic functions to describe dijet mass spectra start to fail. Here, to address this, we suggest the application of an anomaly detection approach to eliminate less interesting background events based on event final states. This method not only bypasses the limitations of conventional background models but also significantly enhances our ability to detect potential signals of new physics. Through simulations that mimic the conditions of the upcoming high-luminosity large Hadron collider, we demonstrate the strength and efficiency of this approach in dealing with large data volumes. The integration of unsupervised machine learning into our experimental framework paves the way for a promising avenue to unveil hidden physics discoveries within the overwhelming influx of data.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

BMC Caller: a webtool to identify and analyze bacterial microcompartment types in sequence data

Bacterial microcompartments (BMCs) are protein-based organelles found across the bacterial tree of life. They consist of a shell, made of proteins that oligomerize into hexagonally and pentagonally shaped building blocks, that surrounds enzymes constituting a segment of a metabolic pathway. The proteins of the shell are unique to BMCs. They also provide selective permeability; this selectivity is dictated by the requirements of their cargo enzymes. We have recently surveyed the wealth of different BMC types and their occurrence in all available genome sequence data by analyzing and categorizing their components found in chromosomal loci using HMM (Hidden Markov Model) protein profiles. To make this a “do-it yourself” analysis for the public we have devised a webserver, BMC Caller (https://bmc-caller.prl.msu.edu), that compares user input sequences to our HMM profiles, creates a BMC locus visualization, and defines the functional type of BMC, if known. Shell proteins in the input sequence data are also classified according to our function-agnostic naming system and there are links to similar proteins in our database as well as an external link to a structure prediction website to easily generate structural models of the shell proteins, which facilitates understanding permeability properties of the shell. Additionally, the BMC Caller website contains a wealth of information on previously analyzed BMC loci with links to detailed data for each BMC protein and phylogenetic information on the BMC shell proteins. Our tools greatly facilitate BMC type identification to provide the user information about the associated organism’s metabolism and enable discovery of new BMC types by providing a reference database of all currently known examples.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Autonomous Flow Electrochemistry for Accelerated Catalyst Discovery

Our objective is to develop an Autonomous Chemical Experimentation (ACE) platform that accelerates discovery of new catalytic transformations and other energy-relevant chemical reactions and processes. We intentionally designed ACE to be highly modular, both with respect to its rapid deployment to different chemistries and experimental workflows as well as incorporation of a wide range of different AI algorithms. In addition to the development of the core software architecture, initial efforts were made to incorporate Large Language Models to provide human-interpretable reasoning of the optimizer’s actions, and to develop a user-friendly graphical interface for experimental researchers. ACE was demonstrated using a flow electrocatalysis platform containing an inline FTIR spectrometer for real-time analysis and quantification of the reaction outcome. Human-in-the-loop experiments were performed in which a human researcher conducted an experiment using electrode potentials suggested by ACE, then fed the spectral data back to ACE for decision making. After confirming the successful function of the optimizer, efforts were next directed to automation of the hardware and performed full autonomy tests using three reactions: catalytic oxidation of formate, catalytic oxidation of cyclohexanol, and oxidation of hydroquinone. These studies confirm that ACE can close the loop between reaction execution, analysis, and optimization. They also reveal that more improved product detection methods will be essential for ACE to make well-informed decisions for reactions with low conversions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Base Excision Repair: Mechanisms and Impact in Biology, Disease, and Medicine

Base excision repair (BER) corrects forms of oxidative, deamination, alkylation, and abasic single-base damage that appear to have minimal effects on the helix. Since its discovery in 1974, the field has grown in several facets: mechanisms, biology and physiology, understanding deficiencies and human disease, and using BER genes as potential inhibitory targets to develop therapeutics. Within its segregation of short nucleotide (SN-) and long patch (LP-), there are currently six known global mechanisms, with emerging work in transcription- and replication-associated BER. Knockouts (KOs) of BER genes in mouse models showed that single glycosylase knockout had minimal phenotypic impact, but the effects were clearly seen in double knockouts. However, KOs of downstream enzymes showed critical impact on the health and survival of mice. BER gene deficiency contributes to cancer, inflammation, aging, and neurodegenerative disorders. Medicinal targets are being developed for single or combinatorial therapies, but only PARP and APE1 have yet to reach the clinical stage.

5′-Gap↗
DOE OSTI2020

Atmospheric Escape From TOI-700 d: Venus versus Earth Analogs

The recent discovery of an Earth-sized planet (TOI-700 d) in the habitable zone of an early-type M-dwarf by the Transiting Exoplanet Survey Satellite constitutes an important advance. In this Letter, we assess the feasibility of this planet to retain an atmosphere – one of the chief ingredients for surface habitability – over long timescales by employing state-of-the-art magnetohydrodynamic models to simulate the stellar wind and the associated rates of atmospheric escape. We take two major factors into consideration, namely, the planetary atmospheric composition and magnetic field. In all cases, we determine that the atmospheric ion escape rates are potentially a few orders of magnitude higher than the inner Solar system planets, but TOI-700 d is nevertheless capable of retaining a 1 bar atmosphere over gigayear timescales for certain regions of the parameter space. The simulations show that the unmagnetized TOI-700 d with a 1 bar Earth-like atmosphere could be stripped away rather quickly (< 1 gigayear), while the unmagnetized TOI-700 d with a 1 bar CO 2 -dominated atmosphere could persist for many billions of years; we find that the magnetized Earth-like case falls in between these two scenarios. We also discuss the prospects for detecting radio emission of the planet (thereby constraining its magnetic field) and discerning the presence of an atmosphere.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

In‐Silico Device Performance Prediction of Cosensitizer Dye Pairs for Dye‐Sensitized Solar Cells

Abstract Endeavors in the field of dye‐sensitized solar cells (DSCs) have shown great promise when adopting a data‐driven approach to materials discovery, such as successful molecular‐scale predictions of light‐harvesting chromophores. However, predictions of DSC dyes would become much more sophisticated if a molecular‐to‐macroscopic DSC device prediction methodology existed. Thereby, a fully computational pipeline is presented that predicts device‐performance parameters of DSCs which contain varying dye combinations. Optimal pairing of complementary dyes is identified via a data‐driven workflow that affords cosensitized DSCs with maximum power‐conversion efficiencies. Six high‐performing DSC dyes are paired with partner dyes that are screened from a database of 8488 compounds using sequential heuristic filters. Existing models that predict short‐circuit‐current density ( J SC ) and open‐circuit voltage ( V OC ) parameters are adapted to predict singly sensitized and cosensitized DSC performance. The predictions for J sc values of singly sensitized devices match experimental literature values with comparable accuracy to more computationally costly methods. Five out of six dye pairings are predicted to have greater J SC values when cosensitized compared to their corresponding singly sensitized devices, including two pairs that show strong J sc boosts of +13% and +12% when cosensitized. Thus, the prospect of an entirely in‐silico prediction pipeline for DSC performance that can be used to realize the fully automated design of optimized cosensitized DSCs is demonstrated.

14 SOLAR ENERGY↗
DOE OSTI2024

Physics-Guided Continual Learning for Predicting Emerging Aqueous Organic Redox Flow Battery Material Performance

Aqueous organic redox flow batteries (AORFBs) have gained popularity in renewable energy storage due to their low cost, environmental friendliness and scalability. The rapid discovery of aqueous soluble organic (ASO) redox-active materials necessitates efficient machine learning surrogates for predicting battery performance. The physics-guided continual learning (PGCL) method proposed in this study can incrementally learn data from new ASO electrolytes while addressing catastrophic forgetting issues in conventional machine learning. Using a AORFB database with a thousand potential materials generated by a 780 $\text{cm}^2$ interdigitated cell model, PGCL incorporates AORFB physics to optimize the continual learning task formation and training strategies to retain previously learned battery material knowledge. Finally, the trained PGCL demonstrates its capability in assessing emerging ASO materials within the established parameter space when evaluated with the dihydroxyphenazine isomers.

25 ENERGY STORAGE↗
DOE OSTI2021

Metabolite discovery through global annotation of untargeted metabolomics data

Liquid chromatography–high-resolution mass spectrometry (LC-MS)-based metabolomics aims to identify and quantify all metabolites, but most LC-MS peaks remain unidentified. Here we present a global network optimization approach, NetID, to annotate untargeted LC-MS metabolomics data. The approach aims to generate, for all experimentally observed ion peaks, annotations that match the measured masses, retention times and (when available) tandem mass spectrometry fragmentation patterns. Peaks are connected based on mass differences reflecting adduction, fragmentation, isotopes, or feasible biochemical transformations. Global optimization generates a single network linking most observed ion peaks, enhances peak assignment accuracy, and produces chemically informative peak–peak relationships, including for peaks lacking tandem mass spectrometry spectra. Applying this approach to yeast and mouse data, we identified five previously unrecognized metabolites (thiamine derivatives and N-glucosyl-taurine). Isotope tracer studies indicate active flux through these metabolites. Furthermore, NetID applies existing metabolomic knowledge and global optimization to substantially improve annotation coverage and accuracy in untargeted metabolomics datasets, facilitating metabolite discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Correlation between hemolytic activity, cytotoxicity and systemic in vivo toxicity of synthetic antimicrobial peptides

The use of non-standard toxicity models is a hurdle in the early development of antimicrobial peptides towards clinical applications. Herein we report an extensive in vitro and in vivo toxicity study of a library of 24 peptide-based antimicrobials with narrow spectrum activity towards veterinary pathogens. The haemolytic activity of the compounds was evaluated against four different species and the relative sensitivity against the compounds was highest for canine erythrocytes, intermediate for rat and human cells and lowest for bovine cells. Selected peptides were additionally evaluated against HeLa, HaCaT and HepG2 cells which showed increased stability towards the peptides. Therapeutic indexes of 50–500 suggest significant cellular selectivity in comparison to bacterial cells. Three peptides were administered to rats in intravenous acute dose toxicity studies up to 2– 8 × MIC. None of the injected compounds induced any systemic toxic effects in vivo at the concentrations employed illustrating that the correlation between the different assays is not obvious. This work sheds light on the in vitro and in vivo toxicity of this class of promising compounds and provides insights into the relationship between the different toxicity models often employed in different manners to evaluate the toxicity of novel bioactive compounds in general.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Corrugation-driven symmetry breaking in magic-angle twisted bilayer graphene

Abstract The discovery of unconventional superconductivity in magic-angle twisted bilayer graphene (tBLG) supported the twist-angle-induced flat band structure predictions made a decade earlier. Numerous physical properties have since been linked to the interlayer twist angle using the flat band prediction as a guideline. However, some key observations like the nematic phase and striped charge order behind the superconductivity are missing in this initial model. Here we show that a thermodynamically stable large out-of-plane displacement, or corrugation of the bilayer, induced by the interlayer twist, demonstrates partially filled states of the flat band structure, accompanied by a broken symmetry, in the magic-angle regime and the presence of symmetry breaking associated with the superconductivity in tBLG. The distinction between low and high corrugation can also explain the observed evolution of the vibrational spectra of tBLG as a function of twist angle. Our observation that large out-of-plane deformation modes enable partial filling of states near the Fermi energy may lead to a strategy for offsetting the effects of disorder in the local twist angle, which suppresses unconventional superconductivity and correlated insulator behavior in magic-angle tBLG.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Warm inflation with a heavy QCD axion

We propose the first model of warm inflation in which the particle production emerges directly from coupling the inflaton to Standard Model particles. Warm inflation, an early epoch of sustained accelerated expansion at finite temperature, is a compelling alternative to cold inflation, with distinct predictions for inflationary observables such as the amplitude of fluctuations, the spectral tilt, the tensor-to-scalar ratio, and non-gaussianities. In our model a heavy QCD axion acts as the warm inflaton whose coupling to Standard Model gluons sources the thermal bath during warm inflation. Axion-like couplings to non-Abelian gauge bosons have been considered before as a successful microphysical theory with emerging thermal friction that can maintain finite temperature during inflation via sphaleron heating. However, the presence of light fermions charged under the non-Abelian group suppresses particle production, hindering a realization of warm inflation by coupling to QCD. We point out that the Standard Model quarks can be heavy during warm inflation if the Higgs field resides in a high-energy second minimum which restores efficient sphaleron heating. A subsequent large reheating temperature is required to allow the Higgs field to relax to its electroweak minimum. Exploring a scenario in which hybrid warm inflation provides the large reheating temperature, we show that future collider and beam dump experiments have discovery potential for a heavy QCD axion taking the role of the warm inflaton.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Bridging Place-Based Astrobiology Education with Genomics, Including Descriptions of Three Novel Bacterial Species Isolated from Mars Analog Sites of Cultural Relevance

Democratizing genomic data science, including bioinformatics, can diversify the STEM workforce and may, in turn, bring new perspectives into the space sciences. In this respect, the development of education and research programs that bridge genome science with “place” and world-views specific to a given region are valuable for Indigenous students and educators. Through a multi-institutional collaboration, we developed an ongoing education program and model that includes Illumina and Oxford Nanopore sequencing, free bioinformatic platforms, and teacher training workshops to address our research and education goals through a place-based science education lens. High school students and researchers cultivated, sequenced, assembled, and annotated the genomes of 13 bacteria from Mars analog sites with cultural relevance, 10 of which were novel species. Students, teachers, and community members assisted with the discovery of new, potentially chemolithotrophic bacteria relevant to astrobiology. This joint education-research program also led to the discovery of species from Mars analog sites capable of producing N-acyl homoserine lactones, which are quorum-sensing molecules used in bacterial communication. Whole genome sequencing was completed in high school classrooms, and connected students to funded space research, increased research output, and provided culturally relevant, place-based science education, with participants naming three novel species described here. Students at St. Andrew's School (Honolulu, Hawai‘i) proposed the name Bradyrhizobium prioritasuperba for the type strain, BL16A T , of the new species (DSM 112479 T = NCTC 14602 T ). The nonprofit organization Kauluakalana proposed the name Brenneria ulupoensis for the type strain, K61 T , of the new species (DSM 116657 T = LMG = 33184 T ), and Hawai‘i Baptist Academy students proposed the name Paraflavitalea speifideiaquila for the type strain, BL16E T , of the new species (DSM 112478 T = NCTC 14603 T ).

59 BASIC BIOLOGICAL SCIENCES↗