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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 37 records · Page 2

Middleware for a Heterogeneous CAV Fleet

This paper introduces CAN to ROS, a model-based code generation tool used in development, testing, and deployment of a heterogeneous fleet of vehicles with robotic sensing in ROS. Code generation supports two main features: (1) self-configuration for deployment in a heterogeneous vehicle fleet, and (2) quick iteration for testing and development of reading vehicle sensors and robotic control. This tool features the ability to detect the vehicle it is in and regenerate and rebuild itself at runtime to provide the proper two-way bridge between ROS and the sensed on-board vehicle sensor network. Code generation relies on a per-model defined JSON to map a CAN database (DBC) to the desired ROS topic names and message types. The live ROS publishing of CAN messages allows for instant feedback, and the code regeneration allows for adjustments in DBC or vehicle JSON to iteratively hone in on new vehicle signals. Generated ROS nodes are written in C++ for runtime use in lightweight embedded computers. This has been tested in vehicles from three different Original Equipment Manufacturers (OEMs), and can be extended to support a wide array of vehicles. By using a unifying ROS specification, a heterogeneous set of vehicles can be unified into a fleet with abstracted model-specific details; this opens the door for developing cross-model software applications for vehicle control, connected vehicle applications, or fleet monitoring systems.

42 ENGINEERING↗

Rational design of a genetically encoded NMR zinc sensor

Elucidating the biochemical roles of the essential metal ion, Zn 2+ , motivates detection strategies that are sensitive, selective, quantitative, and minimally invasive in living systems. Fluorescent probes have identified Zn 2+ in cells but complementary approaches employing nuclear magnetic resonance (NMR) are lacking. Recent studies of maltose binding protein (MBP) using ultrasensitive 129 Xe NMR spectroscopy identified a switchable salt bridge which causes slow xenon exchange and elicits strong hyperpolarized 129 Xe chemical exchange saturation transfer (hyper-CEST) NMR contrast. To engineer the first genetically encoded, NMR-active sensor for Zn 2+ , we converted the MBP salt bridge into a Zn 2+ binding site, while preserving the specific xenon binding cavity. The zinc sensor (ZS) at only 1 μM achieved ‘turn-on’ detection of Zn 2+ with pronounced hyper-CEST contrast. This made it possible to determine different Zn 2+ levels in a biological fluid via hyper-CEST. ZS was responsive to low-micromolar Zn 2+ , only modestly responsive to Cu 2+ , and nonresponsive to other biologically important metal ions, according to hyper-CEST NMR spectroscopy and isothermal titration calorimetry (ITC). Protein X-ray crystallography confirmed the identity of the bound Zn 2+ ion using anomalous scattering: Zn 2+ was coordinated with two histidine side chains and three water molecules. Penta-coordinate Zn 2+ forms a hydrogen-bond-mediated gate that controls the Xe exchange rate. Metal ion binding affinity, 129 Xe NMR chemical shift, and exchange rate are tunable parameters via protein engineering, which highlights the potential to develop proteins as selective metal ion sensors for NMR spectroscopy and imaging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Earth Abundant Oxidation Catalysts for Removal of Contaminants of Emerging Concern from Wastewater: Homogeneous Catalytic Screening of Monomeric Complexes

Twenty novel Mn, Fe, and Cu complexes of ethylene cross-bridged tetraazamacrocycles with potentially copolymerizable allyl and benzyl pendant arms were synthesized and characterized. Multiple X-ray crystal structures demonstrate the cis-folded pseudo-octahedral geometry forced by the rigidifying ethylene cross-bridge and show that two cis coordination cites are available for interaction with substrate and oxidant. The Cu complexes were used to determine kinetic stability under harsh acidic and high-temperature conditions, which revealed that the cyclam-based ligands provide superior stabilization with half-lives of many minutes or even hours in 5 M HCl at 50–90 °C. Cyclic voltammetry studies of the Fe and Mn complexes reveal reversible redox processes indicating stabilization of Fe 2+ /Fe 3+ and Mn 2+ /Mn 3+ /Mn 4+ oxidation states, indicating the likelihood of catalytic oxidation for these complexes. Finally, dye-bleaching experiments with methylene blue, methyl orange, and rhodamine B demonstrate efficient catalytic decolorization and allow selection of the most successful monomeric catalysts for copolymerization to produce future heterogeneous water purification materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structure of the rabies virus glycoprotein trimer bound to a prefusion-specific neutralizing antibody

Rabies infection is nearly 100% lethal if untreated and kills more than 50,000 people annually, many of them children. Existing rabies vaccines target the rabies virus glycoprotein (RABV-G) but generate short-lived immune responses, likely because the protein is heterogeneous under physiological conditions. Here, we report the 3.39 Å cryo–electron microscopy structure of trimeric, prefusion RABV-G complexed with RVA122, a potently neutralizing human antibody. RVA122 binds to a quaternary epitope at the top of RABV-G, bridging domains and stabilizing RABV-G protomers in a prefusion state. RABV-G trimerization involves side-to-side interactions between the central α helix and adjacent loops, rather than contacts between central helices, and interactions among the fusion loops at the glycoprotein base. These results provide a basis from which to develop improved rabies vaccines based on RABV-G stabilized in the prefusion conformation.

59 BASIC BIOLOGICAL SCIENCES↗

Digital Twins for Data Centers

Fueled by an unprecedented adoption of AI (Artificial Intelligence), data centers are becoming the largest growing consumers of energy. Digital Twins provide living digital models of physical systems that enable data-driven analysis and application of AI to better manage selective aspects of the data center and drive efficiency for sustainability. Digital twins have emerged as a way to create virtual prototypes of physical artifacts, which may be used in a variety of contexts. Physical artifacts include airplanes, factories, or even static objects, such as bridges or dams. Digital twin helps monitor changes and assist in predicting planned or unplanned behaviors of physical objects. In this paper, we discuss digital twins for data centers.

97 MATHEMATICS AND COMPUTING↗

Influence of Markovianity and self-consistency on time-resolved spectral functions of driven quantum systems

We present a systematic comparison of the real-time Dyson expansion (RTDE) with established nonequilibrium Green's function (GF) approaches for simulating driven, interacting quantum systems. Focusing on density matrix dynamics, time-off-diagonal GFs, and time-resolved photoemission spectra, we benchmark RTDE against fully self-consistent Kadanoff-Baym equation (KBE) calculations, the generalized Kadanoff-Baym ansatz, and exact diagonalization for small systems using second-order many-body perturbation theory. Using a driven two-band Hubbard model, we show that mean-field single-particle density matrix trajectories provide a reliable baseline for RTDE across a broad range of interaction strengths and excited-carrier populations. Further, RTDE accurately captures correlation effects in the GFs, including long-lived oscillations and revivals that are strongly suppressed by the overdamping inherent to self-consistent KBE schemes. As a consequence, RTDE resolves rich nonequilibrium spectral structure in time-resolved photoemission, such as interaction- and population-dependent quasiparticle splittings and band gap renormalization, which are largely washed out in self-consistent approaches yet are present in exact solutions. Furthermore, our results demonstrate that RTDE bridges the gap between mean-field propagation and full two-time KBE simulations, retaining favorable linear scaling while capturing essential dynamical correlations relevant for ultrafast spectroscopy.

Electronic structure↗

Nanoscale chromatin imaging and analysis platform bridges 4D chromatin organization with molecular function

Extending across multiple length scales, dynamic chromatin structure is linked to transcription through the regulation of genome organization. However, no individual technique can fully elucidate this structure and its relation to molecular function at all length and time scales at both a single-cell level and a population level. Here, we present a multitechnique nanoscale chromatin imaging and analysis (nano-ChIA) platform that consolidates electron tomography of the primary chromatin fiber, optical super-resolution imaging of transcription processes, and label-free nano-sensing of chromatin packing and its dynamics in live cells. Using nano-ChIA, we observed that chromatin is localized into spatially separable packing domains, with an average diameter of around 200 nanometers, sub-megabase genomic size, and an internal fractal structure. The chromatin packing behavior of these domains exhibits a complex bidirectional relationship with active gene transcription. Furthermore, we found that properties of PDs are correlated among progenitor and progeny cells across cell division.

59 BASIC BIOLOGICAL SCIENCES↗

Brochure for the DOE Office of Science Workshop on Envisioning Frontiers in AI and Computing for Biological Research

In February of 2025 a joint ASCR/BER workshop was held to identify key transformational research directions for understanding biology using artificial intelligence (AI), digital twins and high-performance (HPC) computational methods to facilitate scientific discovery and innovation in support of the Department of Energy mission. AI technologies offer exciting new groundbreaking methods to analyze large volumes of complex biological data, thereby greatly accelerating the ability to understand, predict, and design biological processes for beneficial purposes. In the laboratory, the bridging of AI-enabled automated experimental technologies, HPC and digital twins will provide potent tools for researchers to explore the fundamental nature of biology and harness its inherent metabolic potential for a variety of beneficial purposes. The focus of this workshop was on how high-performance computational methods can impact this objective by exploring digital twins, foundational models, and data-driven approaches with applications to advance automated laboratory experiments, modeling of complex living systems and engineering new functions into plants and microbial systems relevant to DOE mission. Workshop attendees with expertise in plant science, microbiology, mathematics, computer science, and AI assessed the current state of the science, trends, and AI challenges at the interface of plant and microbial systems biology and computational science to identify opportunities for high-impact research. This collaborative effort capitalized on ASCR's advancements in applied mathematics, computer science, and Exascale systems, and BER's expertise in basic genomics-enabled research on DOE relevant plant and microbial systems. The workshop culminated in four key priority research directions to guide future research and development within DOE Office of Science programs.

59 BASIC BIOLOGICAL SCIENCES↗

Warped and Hooked: Mapping the Magellanic Clouds in Three Dimensions Using Red Clump Stars

The Large Magellanic Cloud (LMC) and Small Magellanic Cloud (SMC) are the Milky Way’s nearest interacting galaxy pair, offering a unique laboratory for studying tidal effects on galactic disks. Despite extensive survey efforts, the 3D geometry of the Magellanic Clouds, particularly the putative warp of the LMC, remains poorly constrained due to incompleteness in their crowded centers and the low stellar density of their peripheries, which demand wide-field coverage. Using red clump (RC) stars as standard candles, corrected for age- and metallicity-dependent population effects with empirically calibrated color–magnitude relations and spatially resolved star formation histories, we construct the most detailed distance map of the Magellanic system to date. Based on ∼2.3 million RC stars from Gaia Data Release 3 combined with modern reddening maps, we measure median heliocentric distances of 50.62 ± 2.32 kpc for the LMC (to ∼23°) and 60.75 ± 2.85 kpc for the SMC (to ∼12°). The maps reveal substructures including the LMC Northern Arm, southern hooks, the Magellanic Bridge, and SMC peripheral overdensities, with refreshed distance estimates. Fitting the LMC disk within 7° yields a global inclination of $i=25\mathop{.}\limits^{^\circ }32\pm 0\mathop{.}\limits^{^\circ }10$ and a line-of-nodes position angle of $\theta = 142\mathop{.}\limits^{^\circ }34\pm 0\mathop{.}\limits^{^\circ }21$. Most strikingly, we find the LMC periphery is warped azimuthally into a U-shaped structure reaching a vertical amplitude of ∼7 kpc at a radius of ∼15 kpc. In future work, we will perform detailed comparisons with live N-body simulations to assess possible formation scenarios for the LMC warp.

79 ASTRONOMY AND ASTROPHYSICS↗

Keeping it simple: simplified frameworks for long-lived particles at neutrino facilities

Modern-day accelerator neutrino facilities are excellent venues for searches for new-physics particles. Many distinct new-physics models predict overlapping signatures and phenomenology in these experiments. In this work, we advocate for the adoption of simplified frameworks when studying these types of new-physics signatures, which are characterized by a small number of primary variables, including particle masses, lifetimes, and production and decay modes/rates that most directly control signal event rates and kinematics. In particular, taking the example of long-lived particles that decay inside a neutrino detector as a test case, we study formulate and study simplified frameworks in the context of light scalars/fermions produced in kaon decays which then decay into final states containing an electron-positron pair. We show that using these simplified frameworks can allow for individual experimental analyses to be applicable to a wide variety of specific model scenarios. As a side benefit, we demonstrate that using this approach can allow for the T2K collaboration, by reinterpreting its search for Heavy Neutral Leptons, to be capable of setting world-leading limits on the Higgs-Portal Scalar model. Furthermore, we argue the simplified framework interpretation can serve as a bridge to model identification in the hopeful detection of a new-physics signal. As an illustration, we perform a first determination of the likelihood that, in the presence of a new-physics signal in a detector like the DUNE ND-GAr, multiple different new-physics hypotheses (such as the Higgs-Portal Scalar and Heavy Neutral Lepton ones) can be disentangled. We demonstrate that this model discrimination is favorable for some portions of detectable new-physics parameter space but for others, it is more challenging.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Design of metal-mediated protein assemblies via hydroxamic acid functionalities

The self-assembly of proteins into sophisticated multicomponent assemblies is a hallmark of all living systems and has spawned extensive efforts in the construction of novel synthetic protein architectures with emergent functional properties. Protein assemblies in nature are formed via selective association of multiple protein surfaces through intricate noncovalent protein-protein interactions, a challenging task to accurately replicate in the de novo design of multiprotein systems. In this protocol, we describe the application of metal-coordinating hydroxamate (HA) motifs to direct the metal-mediated assembly of polyhedral protein architectures and 3D crystalline protein frameworks (protein-MOFs). This strategy has been implemented using an asymmetric cytochrome cb562 monomer through selective, concurrent association of Fe 3+ and Zn 2+ ions to form polyhedral cages. Furthermore, the use of ditopic HA linkers as bridging ligands with metal-binding protein nodes has allowed the construction of crystalline 3D protein-MOF lattices. The protocol is divided into two major sections: (1) the development of a Cys-reactive HA molecule for protein derivatization and self-assembly of protein-HA conjugates into polyhedral cages and (2) the synthesis of ditopic HA bridging ligands for the construction of ferritin-based protein-MOFs using symmetric metal-binding protein nodes. Furthermore, protein cages can be analyzed using analytical ultracentrifugation (AUC), transmission electron microscopy (TEM) and single-crystal X-ray diffraction (sc-XRD) techniques. HA-mediated protein-MOFs are formed in sitting-drop vapor diffusion crystallization trays and are probed via sc-XRD and multi-crystal small-angle X-ray scattering (SAXS) measurements. Ligand synthesis, construction of HA-mediated assemblies, and post-assembly analysis as described in this protocol can be performed by a graduate-level researcher within six weeks.

36 MATERIALS SCIENCE↗

Highly Conjugated Porphyrin Arrays Enable Optical Resolution of Ferromagnetic and Antiferromagnetic Aligned States of the Triplet Exciton and an Incorporated Stable Radical

Well-defined photogenerated molecular spin systems have potential utility in spintronics and quantum information science (QIS). Because molecular magnetic, optical, and electronic properties can be controlled by design, diverse spin systems can be prepared at modest temperatures. Photogenerated molecular spin systems often involve states prepared from the interaction of excitons and charges. Resolving the nature of electron spin alignment in photogenerated spin states described by the coupling of a triplet exciton and a stable radical commonly relies on EPR spectroscopy. Here, we describe ethyne-bridged (porphinato)metal ( PM n ) oligomers that incorporate a macrocycle-bound Cu(II) radical center. Upon photoexcitation of such PM n arrays, a singdoublet ( 2 S 1 ) state is formed; ultrafast internal conversion (IC) then produces a tripdoublet ( 2 T 1 ) state, which undergoes intersystem crossing (ISC) to produce a tripquartet ( 4 T 1 ) state, before relaxation to the ground state ( 2 S 0 ). These highly conjugated Cu(II) radical-containing PMn arrays enable direct observation of copper porphyrin 2 T 1 → 4 T 1 ISC dynamics from the biexponential decay of the near-infrared (NIR) 2,4 T 1 → 2,4 T n transient absorption manifold. Multireference n-electron valence perturbation theory (NEVPT2) computations illuminate how PM n electronic structure controls the relaxation dynamics of these long-lived (>10 ns) electronically excited multiplet states. These studies show that highly conjugated and polarizable porphyrin arrays incorporating stable spin centers provide rare π-delocalized systems where the ferromagnetic and antiferromagnetic alignment between a triplet exciton and a stable radical are both spectrally resolved and addressable using transient optical spectroscopy at wavelengths exceeding 1 μm, providing new opportunities to QIS.

14 SOLAR ENERGY↗

Metaplastic and energy-efficient biocompatible graphene artificial synaptic transistors for enhanced accuracy neuromorphic computing

CMOS-based computing systems that employ the von Neumann architecture are relatively limited when it comes to parallel data storage and processing. In contrast, the human brain is a living computational signal processing unit that operates with extreme parallelism and energy efficiency. Although numerous neuromorphic electronic devices have emerged in the last decade, most of them are rigid or contain materials that are toxic to biological systems. In this work, we report on biocompatible bilayer graphene-based artificial synaptic transistors (BLAST) capable of mimicking synaptic behavior. The BLAST devices leverage a dry ion-selective membrane, enabling long-term potentiation, with ~50 aJ/µm 2 switching energy efficiency, at least an order of magnitude lower than previous reports on two-dimensional material-based artificial synapses. The devices show unique metaplasticity, a useful feature for generalizable deep neural networks, and we demonstrate that metaplastic BLASTs outperform ideal linear synapses in classic image classification tasks. With switching energy well below the 1 fJ energy estimated per biological synapse, the proposed devices are powerful candidates for bio-interfaced online learning, bridging the gap between artificial and biological neural networks.

97 MATHEMATICS AND COMPUTING↗

Advancing Solar Innovation for Low and Moderate-Income Households (Final Technical Report)

The overarching goal of this project was to deepen the understanding of the social and economic aspects of solar adoption, with a specific eye towards any pathways or barriers that could be identified that directly impact low and moderate-income households. Specific objectives included (1) identifying and assessing significant non-economic barriers that complicate the ability of LMI households to adopt and benefit from solar, even under scenarios with low economic barriers; (2) assessing the differential ability of groups to benefit from solar adoption based on their ability to invest in different solar innovations; (3) explaining why some LMI communities nonetheless experience significantly higher rates of solar adoption and benefit than others; (4) developing a methodological model for generating data addressing key issues to the project; and (5) designing and developing an interactive web portal that aggregates existing datasets, provides researchers trend analysis capabilities, standardizes project protocols for other states and communities; provides the opportunities for researchers using the same protocol in other communities to upload their results; and engages with the general public by providing them the ability to upload their own perspectives and stories of solar technology adoption. Through a common framework for conducting semi-structured field interviews. In partnership with cooperative extension services, in conjunction with survey research and the aggregation of existing solar adoption datasets, this study has identified that currently ,there is a strong values alignment and knowledge access challenge that continues to affect solar adoption. Participants in this study – many of whom are either low or moderate-income and/or live in underserved rural communities do not believe solar is an option where they live or believe solar is appropriate for their lifestyle. This perception challenge is further exacerbated by the absolute dearth of adopters in most communities and a total lack of local marketing for solar energy. What marketing that does exist is geared towards audiences other than those in the participant's community, reinforcing a perception that 22% of survey respondents (n = 1,551) have: that solar energy is not meant for them and their community. Overcoming these serious human challenges pertaining to knowledge and marketing are critical to reducing the customer acquisition costs incurred amongst LMI communities and especially those in rural America where the opportunities solar provides to increase local energy resilience, security, all while engaging in personal stewardship of the planet could align with local values. Community-Based Social Marketing, built in partnership with community leaders and geared towards meeting local visions of ideal life, is a near term opportunity to bridge the gap between local priorities and national market and policy imperatives for solar while moving towards the administration's goals for renewable energy as part of a just and equitable decarbonization program. The tools and methods developed for this study can serve as a template for identifying other specific local challenges for solar adoption in other state, and provide the opportunity for a common data framework for understanding system-wide trends and barriers to achieving uptake of residential solar in communities that may, ultimately, benefit the most from the technology.

14 SOLAR ENERGY↗

A New Field Instrument for Leaf Volatiles Reveals an Unexpected Vertical Profile of Isoprenoid Emission Capacities in a Tropical Forest

Both plant physiology and atmospheric chemistry are substantially altered by the emission of volatile isoprenoids (VI), such as isoprene and monoterpenes, from plant leaves. Yet, since gaining scientific attention in the 1950’s, empirical research on leaf VI has been largely confined to laboratory experiments and atmospheric observations. Here, we introduce a new field instrument designed to bridge the scales from leaf to atmosphere, by enabling precision VI detection in real time from plants in their natural ecological setting. With a field campaign in the Brazilian Amazon, we reveal an unexpected distribution of leaf emission capacities (EC) across the vertical axis of the forest canopy, with EC peaking in the mid-canopy instead of the sun-exposed canopy surface, and moderately high emissions occurring in understory specialist species. Compared to the simple interpretation that VI protect leaves from heat stress at the hot canopy surface, our results encourage a more nuanced view of the adaptive role of VI in plants. We infer that forest emissions to the atmosphere depend on the dynamic microenvironments imposed by canopy structure, and not simply on canopy surface conditions. We provide a new emissions inventory from 52 tropical tree species, revealing moderate consistency in EC within taxonomic groups. We highlight priorities in leaf volatiles research that require field-portable detection systems. Our self-contained, portable instrument provides real-time detection and live measurement feedback with precision and detection limits better than 0.5 nmol VI m -2 leaf s -1 . We call the instrument ‘PORCO’ based on the gas detection method: photoionization of organic compounds. We provide a thorough validation of PORCO and demonstrate its capacity to detect ecologically driven variation in leaf emission rates and thus accelerate a nascent field of science: the ecology and ecophysiology of plant volatiles.

54 ENVIRONMENTAL SCIENCES↗

A Tunable Multivariate Metal–Organic Framework as a Platform for Designing Photocatalysts

Catalysts for photochemical reactions underlie many foundations in our lives, from natural light harvesting to modern energy storage and conversion, including processes such as water photolysis by TiO 2 . Recently, metal–organic frameworks (MOFs) have attracted large interest within the chemical research community, as their structural variety and tunability yield advantages in designing photocatalysts to address energy and environmental challenges. Here, we report a series of novel multivariate metal–organic frameworks (MTV-MOFs), denoted as MTV-MIL-100. They are constructed by linking aromatic carboxylates and AB 2 OX 3 bimetallic clusters, which have ordered atomic arrangements. Synthesized through a solvent-assisted approach, these ordered and multivariate metal clusters offer an opportunity to enhance and fine-tune the electronic structures of the crystalline materials. Moreover, mass transport is improved by taking advantage of the high porosity of the MOF structure. Combining these key advantages, MTV-MIL-100(Ti,Co) exhibits a high photoactivity with a turnover frequency of 113.7 mol H2 gcat. –1 min –1 , a quantum efficiency of 4.25%, and a space time yield of 4.96 × 10 –5 in the photocatalytic hydrolysis of ammonia borane. Bridging the fields of perovskites and MOFs, this work provides a novel platform for the design of highly active photocatalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural dynamics in proteins induced by and probed with X-ray free-electron laser pulses

X-ray free-electron lasers (XFELs) enable crystallographic structure determination beyond the limitations imposed upon synchrotron measurements by radiation damage. The need for very short XFEL pulses is relieved through gating of Bragg diffraction by loss of crystalline order as damage progresses, but not if ionization events are spatially non-uniform due to underlying elemental distributions, as in biological samples. Indeed, correlated movements of iron and sulfur ions were observed in XFEL-irradiated ferredoxin microcrystals using unusually long pulses of 80 fs. Here, we report a femtosecond time-resolved X-ray pump/X-ray probe experiment on protein nanocrystals. We observe changes in the protein backbone and aromatic residues as well as disulfide bridges. Simulations show that the latter’s correlated structural dynamics are much slower than expected for the predicted high atomic charge states due to significant impact of ion caging and plasma electron screening. This indicates that dense-environment effects can strongly affect local radiation damage-induced structural dynamics.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗