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DOE OSTI2025

Structural Characterization of the Platinum Nanoparticle Hydrogen-Evolving Catalyst Assembled on Photosystem I by Light-Driven Chemistry

Directed assembly of abiotic catalysts onto biological redox protein frameworks is of interest as an approach for the synthesis of biohybrid catalysts that combine features of both synthetic and biological materials. In this report, we provide a multiscale characterization of the platinum nanoparticle (NP) hydrogen-evolving catalysts that are assembled by light-driven reductive precipitation of platinum from an aqueous salt solution onto the photosystem I protein (PSI), isolated from cyanobacteria as trimeric PSI. The resulting PSI-NP assemblies were analyzed using a combination of X-ray energy-dispersive spectroscopy (XEDS), high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM), small-angle X-ray scattering (SAXS), and high-energy X-ray scattering with atomic pair distribution function (PDF) analyses. The results show that the PSI-supported NPs are approximately 1.8 nm diameter disk-shaped particles that assemble at discrete sites with 145 Å separation. This separation is too large to be consistent with NP nucleation and growth at a site adjacent to the F B cofactor site. Instead, we suggest a mechanism for NP growth at hydrophobic sites on the PSI stromal surface. The NPs photoreductively assembled on the PSI stromal surface are found to be analogous to the nanostructures produced by successive cycles of atomic layer deposition (ALD) of platinum onto 40 nm porous anodic alumina oxide supports, although the mechanisms for nucleation appear to differ. In conclusion, this work establishes a foundation for the investigation of the reductive assembly of abiotic metal catalysts at sites connected to photochemically reducing equivalent production in PSI.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Distilling the Evolving Contributions of Anthropogenic Aerosols and Greenhouse Gases to Large‐Scale Low‐Frequency Surface Ocean Changes Over the Past Century

Abstract Anthropogenic aerosols (AER) and greenhouse gases (GHG)—the leading drivers of the forced historical change—produce different large‐scale climate response patterns, with correlations trending from negative to positive over the past century. To understand what caused the time‐evolving comparison between GHG and AER response patterns, we apply a low‐frequency component analysis to historical surface ocean changes from CESM1 single‐forcing large‐ensemble simulations. While GHG response is characterized by its first leading mode, AER response consists of two distinct modes. The first one, featuring long‐term global AER increase and global cooling, opposes GHG response patterns up to the mid‐twentieth century. The second one, featuring multidecadal variations in AER distributions and interhemispheric asymmetric surface ocean changes, appears to reinforce the GHG warming effect over recent decades. AER thus can have both competing and synergistic effects with GHG as their emissions change temporally and spatially.

Dong, Yue↗

DOE OSTI2025

Expanding on the ability of trivalent actinides to support microbial alcohol metabolism in evolved methylotrophic bacterium

The 4 f elements, known as the lanthanides, have only recently been recognized as biologically essential metals. These elements can be found in the active site of certain alcohol dehydrogenase (ADH) enzymes, which are used by methylotrophic bacteria to metabolize simple alcohols such as methanol and ethanol. The 5 f elements, known as the actinides, often show similar chemical behaviour to the lanthanides and recent reports demonstrated that americium (Am) and curium (Cm) can replace lanthanides in certain ADHs to yield a catalytically competent enzyme and support bacterial life. In this work, we expand on these results to show the trivalent ions actinium (Ac3+), americium (Am3+), curium (Cm3+), berkelium (Bk3+), and californium (Cf3+) all support growth of an evolved strain of the model methylotroph Methylobacterium extorquens AM1. Further in vitro experiments using a reconstituted ethanol dehydrogenase enzyme confirm the ability of this enzyme to utilize trivalent actinide ions.

Woods, Joshua J↗

DOE OSTI2024

Machine learning-guided discovery of gas evolving electrode bubble inactivation

The adverse effects of electrochemical bubbles on the performance of gas-evolving electrodes are well known, but studies on the degree of adhered bubble-caused inactivation, and how inactivation changes during bubble evolution are limited. We study electrode inactivation caused by oxygen evolution while using surface engineering to control bubble formation. We find that the inactivation of the entire projected area, as is currently believed, is a poor approximation which leads to non-physical results. Using a machine learning-based image-based bubble detection method to analyze large quantities of experimental data, we show that bubble impacts are small for surface engineered electrodes which promote high bubble projected areas while maintaining low direct bubble contact. We thus propose a simple methodology for more accurately estimating the true extent of bubble inactivation, which is closer to the area which is directly in contact with the bubbles.

Lake, Jack R.↗

DOE OSTI2026

The ever-evolving active site: transformation of single atoms to extended structures during the Rh-catalyzed reverse water–gas shift reaction

At low temperatures (< 400°C), single atoms of Rh supported on rutile TiO 2 (rTiO 2 ) are responsible for the formation of CO during the reverse water gas shift (RWGS), while methane production is associated with the Rh-TiO 2 interface due to the correlation between methane formation rates and the volume-averaged Rh nanoparticle diameter. As the temperature is increased to >540°C, there is a notable increase in CO selectivity and methane production rates tend towards zero. The time to reach zero depends on the temperature but independent of the initial Rh structure (single atoms and/or nanoparticles), which is controlled by the catalyst preparation method (wetness impregnation versus colloidal nanoparticles). At 600°C and > 4 h time on stream, the catalytic behaviour becomes completely agnostic to the initial Rh structure as well as weight loading, and the catalysts are highly selective for the reverse water gas-shift reaction. Post-reaction HR-TEM image analysis confirms Rh nanoparticles crystallize/order during the reaction; at 400°C, most of the Rh particles are disordered, while at 600°C, they are more ordered (i.e., development of defined faceting). Infrared spectroscopy of CO adsorption on Rh nanoparticles confirms the appearance of defined facets after annealing in nitrogen at high temperatures. Annealing the Rh/rTiO 2 catalysts prior to the RWGS reaction demonstrates the structural transformation of Rh depends only on time and temperature and not on reactant or product fugacity. Sites responsible for stabilizing Rh single atoms are no longer competent at higher temperatures, enabling their integration into existent nanoparticles. As the reaction temperature is increased to temperatures >540°C, the dominant active site for CO production evolves from single atoms to extended Rh structures.

36 MATERIALS SCIENCE↗

DOE OSTI2024

A comparison of compact, presumably young with extended, evolved radio active galactic nuclei

Context.The triggering and evolution of active galactic nuclei (AGNs) and the interaction of the AGN with its host galaxy is an important topic in extragalactic astrophysics. Radio sources with peaked spectra (peaked spectrum sources, PSS) and compact symmetric objects (CSO) are powerful, compact, and presumably young AGNs and therefore particularly suitable to study aspects of the AGN-host connection. Aims.We use a statistical approach to investigate properties of a PSS-CSO sample that are related to host galaxies and could potentially shed light on the link between host galaxies and AGNs. The main goal is to compare the PSS-CSO sample with a matching comparison sample of extended sources (ECS) to see if the two have significant differences. Methods.We analysed composite spectra, diagnostic line diagrams, multi-band spectral energy distributions (MBSEDs), star formation (SF) indicators, morphologies, and cluster environments for a sample of 121 PSSs and CSOs for which spectra are available from the Sloan Digital Sky Survey (SDSS). The statistical results were compared with those of the ECS sample, where we generally considered the two subsamples of quasi-stellar objects (QSOs) and radio galaxies separately. The analysis is based on a large set of archival data in the spectral range from the ultraviolet to mid-infrared. Results.We find significant differences between the PSS-CSO and the ECS sample. In particular, we find that the ECS sample has a higher proportion of passive galaxies with a lower star formation activity. This applies to both sub-samples (QSOs or radio galaxies) as well as to the entire sample. The star formation rates of the PSS-CSO host galaxies with available data are typically in the range ∼0 to 5 ℳ ⊙ yr −1 , and the stellar masses are in the range 3 × 10 11 to 10 12 ℳ ⊙ . Secondly, in agreement with previous results, we find a remarkably high proportion of PSS-CSO host galaxies with merger signatures. The merger fraction of the PSS-CSO sample is 0.61 ± 0.07, which is significantly higher than that of the comparison sample (0.15 ± 0.06). We suggest that this difference can be explained by assuming that the majority of the PSSs and CSOs cannot evolve to extended radio sources and are therefore not represented in our comparison sample.

Astronomy & Astrophysics↗

DOE OSTI2024

Evolving dual-trait EPSP synthase variants using a synthetic yeast selection system

The enzyme 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) functions in the shikimate pathway which is responsible for the production of aromatic amino acids and precursors of other essential secondary metabolites in all plant species. EPSPS is also the molecular target of the herbicide glyphosate. While some plant EPSPS variants have been characterized with reduced glyphosate sensitivity and have been used in biotechnology, the glyphosate insensitivity typically comes with a cost to catalytic efficiency. Thus, there exists a need to generate additional EPSPS variants that maintain both high catalytic efficiency and high glyphosate tolerance. Here, we create a synthetic yeast system to rapidly study and evolve heterologous EPSP synthases for these dual traits. Using known EPSPS variants, we first validate that our synthetic yeast system is capable of recapitulating growth characteristics observed in plants grown in varying levels of glyphosate. Next, we demonstrate that variants from mutagenesis libraries with distinct phenotypic traits can be isolated depending on the selection criteria applied. By applying strong dual-trait selection pressure, we identify a notable EPSPS mutant after just a single round of evolution that displays robust glyphosate tolerance (K i of nearly 1 mM) and improved enzymatic efficiency over the starting point (~2.5 fold). Finally, we show the crystal structure of corn EPSPS and the top resulting mutants and demonstrate that certain mutants have the potential to outperform previously reported glyphosate-resistant EPSPS mutants, such as T102I and P106S (denoted as TIPS), in whole-plant testing. Altogether, this platform helps explore the trade-off between glyphosate resistance and enzymatic efficiency.

Science & Technology - Other Topics↗

DOE OSTI2026

Evolving language of pediatric anxiety in electronic health records

Objectives This study aimed to identify and quantify semantic drift (ie, the change in semantic meaning over time) within expert-defined anxiety-related (AR) terminology and compare it to common electronic health record (EHR) vocabulary across longitudinal pediatric clinical notes. Materials and Methods A corpus of pediatric clinical notes from 2009 to 2022 was analyzed using computational methods. Semantic drift for each term was quantified using cosine similarity between annual temporal word embeddings. Contextual meaning was examined through changes in nearest neighbors across years. The Laws of Semantic Change were applied to assess the influence of word frequency and polysemy. Vocabulary terms were categorized as AR or common EHR. Results 98% of AR terminology maintained a cosine similarity between 0.00 and 0.50, indicating moderate semantic stability, whereas 90% of common EHR terms remained between 0.00 and 0.25, showing greater contextual stability overall. Frequent terms exhibited minimal change (Frequency Coefficient = 0.04), whereas highly polysemous or abbreviated terms showed less stability (Polysemy Coefficient = 0.630). AR terminology drifted more slowly than general EHR vocabulary (Type Coefficient = −0.179), further supported by significant year–type interactions (Coef = −0.09 to −0.523). Discussion Although anxiety-related terminology demonstrates slower semantic drift than general EHR vocabulary, subtle contextual shifts still occur that may affect downstream interpretability and retrieval in automated systems. Conclusion Continuous linguistic monitoring and adaptive modeling are essential to maintain semantic fidelity and ensure the long-term reliability of clinical decision support systems as healthcare documentation evolves.

Pediatric anxiety disorders↗

DOE OSTI2026

The Dark Energy Survey supernova program: a reanalysis of cosmology results and evidence for evolving dark energy with an updated Type Ia supernova calibration

We present improved cosmological constraints from a re-analysis of the Dark Energy Survey (DES) 5-year sample of Type Ia supernovae (DES-SN5YR). This re-analysis includes an improved photometric cross-calibration, recent white dwarf observations to cross-calibrate between DES and low-redshift surveys, retraining the salt3 light-curve model and fixing a numerical approximation in the host-galaxy colour law. Our fully recalibrated sample, which we call DES-Dovekie, comprises ~1600 likely Type Ia SNe from DES and ~200 low-redshift SNe from other surveys. With DES-Dovekie, we obtain Ω m = 0.330 ± 0.015 in flat Lambda-cold dark matter (⁠ΛCDM) which changes Ω m by –0.022 compared to DES-SN5YR. Combining DES-Dovekie with cosmic microwave background data from Planck, Atacama Cosmology Telescope, and South Pole Telescope and the DESI DR2 measurements in a flat CDM cosmology, we find ω 0 = –0.803 ± 0.054 and ω a = –0.72 ± 0.21⁠. Our results hold a significance of 3.2σ, reduced from 4.2σ for DES-SN5YR, to reject the null hypothesis that the data are compatible with the cosmological constant. This significance is equivalent to a Bayesian model preference odds of approximately 5:1 in favour of the flat ω 0 ω a CDM model. Using generally accepted thresholds for model preference, our updated data exhibits only a weak preference for evolving dark energy.

dark energy↗

DOE OSTI2026

A roadmap toward scaling, reasoning and self-evolving foundation models for nuclear and particle physics

Foundation models have revolutionized artificial intelligence, with Large Language Models demonstrating unprecedented capabilities in multimodal understanding, reasoning and tool use. Nuclear and particle physics stands at a critical juncture where similar transformative potential awaits realization. The field generates exabytes of experimental data, exascale simulations, and decades of theoretical insights — yet these remain largely disconnected from modern Artifical Intelligence (AI) capabilities, with most physics AI applications confined to narrow, task-specific models that suffer from domain shifting when applied to real experimental data. We present a roadmap for FM4NPP (Foundation Model for Nuclear and Particle Physics), systematically scaling from current proof-of-concept models to trillion-parameter architectures capable of autonomous discovery. Our approach advances three critical frontiers: unified data infrastructure integrating detector data, scientific knowledge and computational tools across global facilities; multi-facility foundation models enabling cross-experiment knowledge transfer and accelerated discovery; and agentic AI capabilities for reasoning and autonomous tool use. The resulting self-evolving FM4NPP will transform physics research by converting time-intensive data analysis, theory derivation and computational bottlenecks into rapid AI–human collaborative discovery. This paradigm shift promises to fundamentally accelerate scientific progress in nuclear and particle physics, enabling researchers to focus on high-level insights while AI handles routine analysis and explores vast parameter spaces beyond human capacity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Soft X-Ray Tomography Has Evolved into a Powerful Tool for Revealing Cell Structures

Over the past three decades, soft X-ray tomography (SXT) has rapidly evolved from a proof-of-concept microscopy method into a high-throughput quantitative imaging modality. This advancement enables researchers to address central questions in cell biology. Despite its relatively short developmental period compared to light and electron microscopy, SXT has emerged as a powerful imaging technology. It enables measuring chemical changes in cellular organelles, analyzing three-dimensional structures of whole cells and creating digital cellular models to study cell motility. We discuss the unique nature of SXT to visualize cells without fixation or labeling, enabling quantitative analyses of organelle chemical composition. We explore SXT microscopes available worldwide, SXT segmentation software, and the diverse cell types studied using this technique. We conclude with emerging directions in SXT imaging, including a brief discussion of recent discoveries that are highly influential and likely to become integral to cell biology textbooks.

Weinhardt, Venera↗

DOE OSTI2024

Evolve CAPP

Final Evolve CAPP project presentation to DOE-NETL

Bishop, Richard↗

DOE OSTI2024

Evolve CAPP

Introduction and updates on the Evolve CAPP project to the Virginia Tech Southwest Center Advisory Council.

Bishop, Richard↗

DOE OSTI2026

Time-Evolved Hetero-Alkali Interphases Enable Long-Life Sulfide-Based Anode-Free Solid-State Batteries

Sulfide-based anode-free solid-state batteries (AFSSBs) offer compelling advantages in terms of energy density and safety, yet their practical implementation is severely hindered by undesirable interfacial reactions between sulfide solid electrolytes (SEs) and freshly plated lithium (Li), as well as non-uniform Li plating/stripping behavior. Herein, an effective interfacial stabilization strategy by incorporating sodium bis(fluorosulfonyl)imide (NaFSI) additive into the Li5.4PS4.4Cl1.6 (LPSC) is investigated. Unlike conventional Li-based additives that form static passivation layers, NaFSI introduces a transient hetero-alkali chemistry that kinetically governs interphase evolution during fresh Li plating. NaFSI induces a timesequenced interphase evolution: an initial NaF/LiF-rich layer that suppresses early sulfide reduction, followed by a LiF/Li3N-rich layer that optimizes Li⁺ transport during repeated anode-free cycling. This evolved robust and fast ion conducting layer mitigates interfacial impedance growth, enhances Li + transport kinetics, and suppresses localized Li growth and filamentary shorting. As a result, the anode-free full cell with NaFSI modified LPSC as the interlayer exhibits an excellent cycling stability over 500 cycles at 0.2 C with a capacity retention of 77.6%, whereas the cell with bare LPSC suffers from rapid capacity decay after 100 cycles, retaining only 32.1% of its initial capacity. This work establishes dynamic heteroalkali additive chemistry as a general strategy to kinetically program solid-solid interphases, guiding the interface design in anode-free solid-state batteries.

25 ENERGY STORAGE↗

DOE OSTI2025

Evolving Dark Sector and the Dark Dimension Scenario

String theory naturally leads to the expectation that dark energy is not stable, and may be evolving as captured by the Swampland de Sitter conjectures. Moreover, motivated by the distance conjecture, a unification of dark sector has been proposed, where the smallness of dark energy leads to one extra dimension of micron size with dark matter being the Kaluza--Klein graviton excitations in this extra dimension. We consider the natural possibility that the radius of the dark dimension varies as the dark energy decreases, leading to the variation of the dark matter mass. This correlates the decrease of the dark energy with the variation of the dark matter mass as they depend on the variations of a scalar field $ϕ$ controlling the radius of the extra dimension. A simple realization of this idea for small range of $ϕ$ is adequately captured by choosing a potential which is locally of the form $V=V_0\ {\rm exp}(-cϕ)$ and dark matter mass $m_{\rm DM}=m_0\ {\rm exp}(-c' ϕ)$ where the sign of $ϕ$ is chosen such that $c'\geq 0$ while we have two choices for the sign of $c$ depending on whether the dark dimension expands or shrinks when the dark energy dominates. We find excellent agreement with recent experimental data from DESI DR2 combined with SN measurements (from DES, Union3 or Pantheon+) and reproduces the same significance as CPL parametrization with the added benefit of providing a natural explanation for the apparent phantom behavior ($w<-1$) reported by DESI and DES based on a physical model. DESI and SN datasets independently favor non-zero values of $c'$ and $c$, respectively, both lying within the expected $\mathcal{O}(1)$ range suggested by the Swampland criteria. Moreover, our best fit value $c'\simeq 0.05 \pm 0.01$ is remarkably consistent with the experimental upper bound of $c'\lesssim 0.2$ demanded by the lack of detection of fifth force in the dark sector.

Cosmology and Nongalactic Astrophysics (astro-ph.C↗

DOE OSTI2025

An evolving Coupled Model Intercomparison Project phase 7 (CMIP7) and Fast Track in support of future climate assessment

The Coupled Model Intercomparison Project (CMIP) coordinates community-based efforts to answer key and timely climate science questions, facilitate delivery of relevant multi-model simulations through shared infrastructure, and support national and international climate assessments. Generations of CMIP have evolved through extensive community engagement from punctuated phasing into more continuous support for the design of experimental protocols, infrastructure for data publication and access, and public delivery of climate information. We identify four fundamental research questions motivating a seventh phase of coupled model intercomparison relating to patterns of sea surface temperature change, changing weather, the water–carbon–climate nexus, and tipping points. Key CMIP7 advances include an expansion of baseline experiments, a focus on CO 2 -emissions-driven experiments, sustained support for community MIPs, periodic updating of historical forcings and diagnostics requests, and a collection of prioritized experiments, or the “Assessment Fast Track”, drawn from community MIPs to support climate research, assessment, and service goals across prediction and projection, characterization, attribution, and process understanding.

Environmental sciences↗

DOE OSTI2025

Examining Constituent Redistribution in U-19Pu-10Zr Fuel as it Evolves with Local Burnup

While constituent redistribution is a known irradiation behavior in U-Pu-Zr fuel, new data have shown it is more complex than our current understanding and predictive capabilities. The size and composition of redistributed rings evolve as a function of pin composition, burnup, geometry, and irradiation temperature. In this work, we extract microstructural information from optical microscopy conducted on U-19Pu-10Zr pins (irradiated between 1.9 at. % and 11.6 at. % peak burnup). Both manual image analysis techniques and machine learning-assisted segmentation are used to quantify the thicknesses of the cladding, fuel-cladding interaction layers, and rings of fuel constituent redistribution in addition to pore distribution. These microstructural features and individual redistributed regions affect local thermomechanical properties, and identifying the relationship between burnup and constituent redistribution will improve accurate prediction of advanced reactor fuel performance.

Constituent Redistribution↗

DOE OSTI2025

Shape‐Evolving Structured Liquids

Migration, division, and reconfiguration - functions essential to living systems - are driven by active processes. Developing synthetic mimics is an outstanding challenge. Lipid bilayers that bound natural systems are locally deformed by active species, e.g., microtubules, but the resulting non-equilibrium shapes relax when active species motion ceases, and the shape changes lack immediate control. A fully synthetic system is described, driven by active particles encapsulated by a reconfigurable nanoparticle-surfactant membrane that undergoes shape fluctuations reminiscent of living cells. These shape changes are preserved after particle activity stops. Surfactant concentration tunes the interfacial tension over three orders of magnitude, making on-demand shape evolution possible. Directional migration, division, and reconfiguration across multiple scales are possible, leading to a new class of biomimetic, reconfigurable, and responsive materials, paving the way for autonomous synthetic machines.

Kim, Paul Y↗