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At least 667 records · Page 37

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DOE OSTI2025

Plastoquinone redox status influences carboxysome integrity via a RpaA ‐ and reactive oxygen species‐dependent regulatory network

SUMMARY Carboxysomes are bacterial microcompartments that encapsulate Rubisco and are a core component of the cyanobacterial carbon concentration mechanism (CCM). While carboxysome number, size, and spatial organization vary in different environmental conditions (CO 2 , light availability, redox state, temperature, and light quality), the molecular mechanisms underlying this potentially adaptive process remain elusive. Herein, we observe that mutants of the circadian rhythm/metabolism factor, Regulator of Phycobilisome Association A (RpaA), exhibit a striking breakdown of carboxysomes under certain environmental conditions. We find that conditions leading to overreduction of the plastoquinone (PQ) pool (mixotrophic growth, high irradiance, or chemical inhibition of electron transfer from PQ to the cytochromeb 6 fcomplex) are accompanied by an elevated generation of reactive oxygen species (ROS) and correlate with the loss of carboxysome integrity. Carboxysome breakdown is reversed by environmental conditions or chemical inhibitors that prevent PQ overreduction and accompanying ROS generation. Taken together, our data support a novel link between the redox status of the PQ pool and carboxysome integrity. Our results have implications for the fundamental understanding of cyanobacterial energy‐balancing pathways and may indicate new research directions for understanding how the carboxysome is remodeled in response to changing environments.

Plant Sciences↗

DOE OSTI2024

Landau-phonon polaritons in Dirac heterostructures

Polaritons are light-matter quasiparticles that govern the optical response of quantum materials at the nanoscale, enabling on-chip communication and local sensing. Here, we report Landau-phonon polaritons (LPPs) in magnetized charge-neutral graphene encapsulated in hexagonal boron nitride (hBN). These quasiparticles emerge from the interaction of Dirac magnetoexciton modes in graphene with the hyperbolic phonon polariton modes in hBN. Using infrared magneto-nanoscopy, we reveal the ability to completely halt the LPP propagation in real space at quantized magnetic fields, defying the conventional optical selection rules. The LPP-based nanoscopy also tells apart two fundamental many-body phenomena: the Fermi velocity renormalization and field-dependent magnetoexciton binding energies. Our results highlight the potential of magnetically tuned Dirac heterostructures for precise nanoscale control and sensing of light-matter interaction.

36 MATERIALS SCIENCE↗

DOE OSTI2024

High-precision chemical quantum sensing in flowing monodisperse microdroplets

A method is presented for high-precision chemical detection that integrates quantum sensing with droplet microfluidics. Using nanodiamonds (ND) with fluorescent nitrogen-vacancy (NV) centers as quantum sensors, rapidly flowing microdroplets containing analyte molecules are analyzed. A noise-suppressed mode of optically detected magnetic resonance is enabled by pairing controllable flow with microwave control of NV electronic spins, to detect analyte-induced signals of a few hundredths of a percent of the ND fluorescence. Using this method, paramagnetic ions in droplets are detected with low limit-of-detection using small analyte volumes, with exceptional measurement stability over >10 3 s. In addition, these droplets are used as microconfinement chambers by co-encapsulating ND quantum sensors with various analytes such as single cells, suggesting wide-ranging applications including single-cell metabolomics and real-time intracellular measurements from bioreactors. Important advances are enabled by this work, including portable chemical testing devices, amplification-free chemical assays, and chemical imaging tools for probing reactions within microenvironments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Anomalous superconductivity in twisted MoTe 2 nanojunctions

Introducing superconductivity in topological materials can lead to innovative electronic phases and device functionalities. Here, we present a unique strategy for quantum engineering of superconducting junctions in moiré materials through direct, on-chip, and fully encapsulated 2D crystal growth. We achieve robust and designable superconductivity in Pd-metalized twisted bilayer molybdenum ditelluride (MoTe 2 ) and observe anomalous superconducting effects in high-quality junctions across ~20 moiré cells. Unexpectedly, the junction develops enhanced, instead of weakened, superconducting behaviors, exhibiting fluctuations to a higher critical magnetic field compared to its adjacent Pd 7 MoTe 2 superconductor. In addition, the critical current further exhibits a notable V-shaped minimum at zero magnetic field. These features are unexpected in conventional Josephson junctions and absent in junctions of natural bilayer MoTe 2 created using the same approach. We discuss implications of these observations, including the possible formation of mixed even- and odd-parity superconductivity at the moiré junctions. Our results also demonstrate a pathway to engineer and investigate superconductivity in fractional Chern insulators.

Science & Technology - Other Topics↗

DOE OSTI2026

A conserved glycan motif induces broadly reactive functional antibodies against the zoonotic pathogen Streptococcus suis

Streptococcus suis is a largely neglected but emerging bacterial zoonotic pathogen of global concern for animal welfare, antibiotic resistance development, and human health. No effective vaccines are now available. Here, we identified and characterized the function and structure of two cell wall polysaccharide variants in pathogenic S. suis strains using genetic deletion and (heterologous) complementation, lectin staining, glycan composition analysis, and specialized NMR spectroscopy. Both glycan variants were anionic polymers that differed in the presence of glucose in the side chain as a result of allelic variation in a glycosyltransferase gene. Deletion of this variable glycosyltransferase revealed an identical glycan “core” and affected S. suis morphology and lysozyme resistance. Immunization of pigs with this core domain elicited antibodies that recognized antigenically diverse pathogenic S. suis strains and induced complement deposition on encapsulated pathogenic S. suis strains. This study provides valuable insights for developing next-generation glycoconjugate vaccines, whereby a single-glycan target could protect against the emerging zoonotic pathogen S. suis.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Chiral-structured heterointerfaces enable durable perovskite solar cells

Mechanical failure and chemical degradation of device heterointerfaces can strongly influence the long-term stability of perovskite solar cells (PSCs) under thermal cycling and damp heat conditions. Here, we report chirality-mediated interfaces based on R-/S-methylbenzyl-ammonium between the perovskite absorber and electron-transport layer to create an elastic yet strong heterointerface with increased mechanical reliability. This interface harnesses enantiomer-controlled entropy to enhance tolerance to thermal cycling–induced fatigue and material degradation, and a heterochiral arrangement of organic cations leads to closer packing of benzene rings, which enhances chemical stability and charge transfer. The encapsulated PSCs showed retentions of 92% of power-conversion efficiency under a thermal cycling test (-40°C to 85°C; 200 cycles over 1200 hours) and 92% under a damp heat test (85% relative humidity; 85°C; 600 hours).

14 SOLAR ENERGY↗

DOE OSTI2025

Microfluidic droplets with amended culture media cultivate a greater diversity of soil microorganisms

ABSTRACT Uncultivated but abundant soil microorganisms have untapped potential for producing broad ranges of natural products, as well as for bioremediation. However, cultivating soil microorganisms while maintaining a broad microorganism diversity to enable phenotyping and functional analysis of as diverse individual isolates as possible remains challenging. In this study, we developed and tested the ability of several culture media formulations that contain defined soil metabolites or soil extracts to maintain microorganism diversity during culture. We also assessed their performance in microfluidic droplet cultivation where single-soil microorganism isolates were encapsulated and cultivated in picoliter-volume water-in-oil emulsion droplets to enable clonal growth needed for downstream functional analyses. Our results show that droplet cultivation with media supplemented by soil extract or soil metabolites enables the recovery of soil microorganisms with higher diversity (up to 1.5-fold higher richness) compared to bulk cultivation methods. Importantly, 1.7-fold more of less abundant (<1%) phyla and 11-fold more of unique genera were recovered, demonstrating the utility of this method for interrogating highly diverse soil microorganisms for broad ranges of applications. IMPORTANCE Although soil microorganisms hold a significant value in bioproduction and bioremediation, only a small fraction—less than 1%—can be cultured under specific media and cultivation conditions. This indicates that there are ample opportunities in harvesting the diverse environmental microorganisms if isolating and recovering these uncultured microorganisms are possible. This paper presents a new cultivation technique composed of isolating single-soil microorganism cell from anin situsoil microorganism community in microfluidic droplets and conducting in-droplet cultivation in media supplemented by soil extract or soil metabolites. This method enables the recovery of a broader diversity of the original microorganism community, laying the groundwork for a high-throughput phenotyping of these diverse microorganisms from their natural habitats.

Biotechnology & Applied Microbiology↗

DOE OSTI2026

Many paths, similar destinations: viruses and bacterial microcompartments form polyhedra inside cells

A large number of biological entities assemble into icosahedral structures, and these are ubiquitous throughout nature. Examples include eukaryotic and prokaryotic viral capsids and more recently discovered bacterial microcompartments. Viral capsids and bacterial microcompartments are both composed of pentameric and hexameric subunits; however, they differ in the type of cargo they encapsulate: nucleic acid or protein. Also, both depart from strict icosahedral symmetry: while this is less common in viruses, among bacterial microcompartments, diverse and heterogeneous polyhedra are common. We review shared principles and key distinctions between the self-directed assembly of various icosahedral architectures and their polyhedral variants in nature and explore the concept that there are multiple paths, influenced by their cargo, to arriving at similar protein cage morphologies.

bacterial microcompartments↗

DOE OSTI2026

Integral Kernel Methods for Nonlinear Parabolic-Elliptic Systems

Nonlinear parabolic-elliptic systems arise in many physical, biological, and chemical phenomena such as chemotaxis, ion transport, self-gravitating particles, and Brownian vortices. Existing methods struggle with the strong coupling and high nonlinearity and nonlocality of some of these systems, especially the ill-conditioned, convection-dominated problems. To overcome numerical difficulties, current approaches rely on initial guesses, preconditioning, or iterative techniques with no convergence guarantees. They might suffer from poor scalability, large memory usage, and difficulty to parallelize. Inspired by the connection of parabolic-elliptic systems to stochastic processes, we introduce a novel meshless, monolithic, and fully explicit method that naturally encapsulates the elliptic and parabolic operators into a single step which updates each node deterministically with global information. By being fully quadrature-based, it avoids solving systems of discretized equations and does not utilize initial guesses or preconditioning, while requiring little memory and being easy to parallelize. We first derive the method in an integral kernel formulation with quadratic complexity in the number of integration nodes and then leverage kernel-independent fast multipole methods (FMM) to present a scalable algorithm with linear complexity. We provide numerical examples for the Poisson-Nernst-Planck equations in one, two, and three dimensions, together with the derivation of the integral kernel for each case. Furthermore, the examples demonstrate the fast convergence and scalability of the FMM-accelerated algorithm, as well as its suitability for convection-dominated problems, making it competitive against traditional PDE solvers.

PDE systems↗

DOE OSTI2025

Reconstructing f ( T ) gravity and exploring the torsion driven warm inflationary cosmology

The current paper reports an investigation of a warm inflationary scenario in the context of f(T) gravity for a spatially flat FLRW universe. In our model, inflation is driven purely by the torsional sector of f(T) gravity, without introducing any additional scalar fields. We focus on the high dissipative regime (R >> 1), reconstruct the Hubble parameter as a function of the e-folding number N, and derive the slow-roll parameters ε 1 (N) and ε 2 (N). The study has encapsulated the dynamics of inflation and its duration under strong dissipation. The dissipative coefficient Γ is modeled with a temperature-dependent power-law form, linking the inflationary dynamics to thermal corrections and the particle content of the early universe. The analysis has affirmed that the torsion-induced energy density ρ T successfully transitions to radiation energy density ρ rad , facilitating a graceful exit from inflation. Finally, we have validated our model by comparing the scalar spectral index and tensor-to-scalar ratio with Planck 2018 results, demonstrating consistency within observational bounds. Additionally, it is verified that the thermal domination condition T * /H > 1 and the torsion dominance condition ρ T /ρ rad > 1 are satisfied.

Ghosh, Moli [Amity University, Kolkata (India); Mr↗

DOE OSTI2024

SmartFuse: Reconfigurable Smart Switches to Accelerate Fused Collectives in HPC Applications

Communication switches have sometimes been augmented to process collectives (e.g., the IBM BlueGene project and the Mellanox SHArP switch). In this work, we find that there is a great acceleration opportunity through the further augmentation of switches to accelerate more complex functions that combine communication with computation. We consider three types of such functions. The first is fully-fused collectives built by fusing multiple existing collectives like Allreduce with Alltoall. The second is semi-fused collectives built by combining a collective with another computation. The third we refer to as higher-order collectives built by combining multiple computations and communications, such as to perform matrix-matrix multiply (PGEMM). In this work, we propose a framework called SmartFuse to accelerate fused collective functions. The core of SmartFuse is a reconfigurable smart switch to support these operations. The semi/fully fused collectives are implemented with a CGRAlike architecture, while higher-order collectives are implemented with a more specialized computational unit that can also schedule communication. Supporting our framework is software to evaluate and translate relevant parts of the input program, compile them into a control data flow graph, and then map this graph to the switch hardware. The proposed framework, once deployed, has the strong potential to accelerate existing HPC applications transparently by encapsulation within an MPI implementation. Experimental results show that this approach improves the performance of the PGEMM kernel, MINIFE, and AMG by, on average, 94%, 15%, and 13%, respectively.

Haghi, Pouya↗

DOE OSTI2024

The Effect of Sulfuric Acid Anodization on the Electrochemical Properties of Aluminum Alloy AlSi 10 Mg Prepared by Selective Laser Melting

Aluminum alloy, AlSi 10 Mg, prepared by selective laser melt (SLM) fabrication was anodized in 9.8% sulfuric acid (Type II) at 15 V for a total of 23 min. Experiments were performed to study the potentiostatic anodization process and its effects on the oxide coating morphology, thickness, and electrochemical properties of the alloy. Prior to anodization, the alloy microstructure is composed of aluminum cells encapsulated in a silicon network. Anodizing the abraded and polished AlSi 10 Mg surface produced a porous oxide layer with a thickness of 5μm. The oxide coating weight was 698 ± 29 mg/ft 2 . The oxide coating forms in the aluminum cells that are isolated from one another by the silicon eutectic phase. In electrochemical tests, the anodic and cathodic potentiodynamic polarization currents were suppressed by factors of 15× and 215×, respectively, as compared to the unanodized controls. The data indicate the anodic oxide coating suppresses the cathodic more than the anodic reaction rate. Linear polarization resistance (R p ) values increased by 279× after anodization. The corrosion current density values (j corr ) decreased by 133× after anodization. Taken together, the electrochemical data indicate the anodic oxide coating (unsealed) increases the corrosion resistance of the SLM alloy by two orders of magnitude.

Electrochemistry↗

DOE OSTI2024

Deeplynx Airflow Provider Package

The DeepLynx Airflow Provider Package is a python package used to interact with the data warehouse DeepLynx when using the workflow orchestration tool Apache Airflow. This python package is packaged together using the airflow package standard so that it can be easily installed and used in any Apache Airflow environment. This package is meant to encapsulate the DeepLynx API for use in Airflow so that any interactions with DeepLynx that a user may want to use in their Airflow workflow can be easily accomplished using this provider package. This allows us to develop, implement, and test our DeepLynx-Airflow interactions in one provider package repository, and then easily install and use this package in any airflow instance. This DeepLynx Airflow Provider Package will be used extensively by the DeepLynx DAG repository.

Cavaluzzi, JackM↗

DOE OSTI2024

Nodeman: A Node Management Tool For Hpc Clusters

NodeMan is a command line tool to manage nodes in an HPC cluster. At it's core, it is an extensible framework composed of bash scripting and GNU parallel. HPC System Administrator will find it useful in that it encapsulates desired functions and allows them to be assembled in a way familiar to administrators - through pipes. In fact, NodeMan functions can work with common command line tools as long as they use stdin/stdout. System Administrators can construct moderately complex logic and filtering on a compact command line that would normally require a substantial shell script. In the spirit of clush and pdsh, it is able to run commands remotely on nodes. Additionally, NodeMan is more flexible. For example, it can interact with IPMI and naturally processes node lists for orchestrating different tools. The library of useful pre-built functions is growing. System administrators can easily create new functions and make it their own.

Serr, ScottM↗

DOE OSTI2025

Exascale Julia Grid Optimization

Simple Julia scrips for solving AC power flow, AC optimal power flow, and security-constrained AC optimal power flow. These scripts are intended for experimentation with different (possibly, new) methods, formulations, and settings for solving these power system problem. Their implementation, therefore, intentionally avoids excessive encapsulation, which makes other packages difficult to modify by non-developers.

Petra, Cosmin [Lawrence Livermore National Laborat↗

DOE OSTI2025

Chemist

Chemist is a domain-specific language targeting the QC domain. Chemist has been developed focusing on performance and user-friendliness. Using Chemist, QC tasks are defined using familiar domain concepts such as molecules, wave functions, and operators. The domain objects are hierarchical to ensure a systematic encapsulation of information. Key features of Chemist include: extensibility, the ability to alias existing data, and the ability to succinctly define many common QC tasks.

Richard, Ryan [Ames Laboratory (AMES), Ames, IA (U↗

DOE OSTI2025

Moltensaltpropnet

MoltenSaltPropnet is a physics-informed machine learning framework that aims to predict the thermophysical properties of molten fluoride and chloride salt mixtures, which are crucial for the design and safety of Generation IV molten salt reactors. The code processes data from the Molten-Salt Thermal Properties Database (MSTDB-TP) and the Janz compendium, converting critically evaluated correlations into fast, differentiable surrogate models for density, viscosity, thermal conductivity, and heat capacity across 448 distinct salt systems. The implementation consists of several key components: 1. Data Curation: The code parses and cleans the raw data, normalizing elemental mole fractions and extracting relevant regression coefficients for various thermophysical properties. 2. Feature Engineering: It generates fixed-length numerical descriptors that encapsulate the composition and temperature, incorporating polynomial interaction terms and dimensionality-reduction techniques to optimize model performance. 3. Coefficient Learning: Four different machine learning architectures are employed: a deep residual network (ResNet), a Kolmogorov–Arnold network (KAN), a sparsity-inducing neural network (SNN), and classical regression models. Each model learns to predict coefficients that define the temperature-dependent correlations for the thermophysical properties. 4. Property Reconstruction: The predicted coefficients are used to compute temperature-dependent property values, ensuring positivity and monotonic trends through a composite loss function that enforces physical constraints. 5. User Interface: An open-source web application enables users to filter the database, train task-specific models, and visualize the results, allowing for rapid exploration of candidate salt mixtures. MoltenSaltPropnet bridges the gap between limited experimental data and high-fidelity reactor simulations, providing a powerful tool for researchers in the field of molten salt reactors and advanced nuclear energy systems.

Retamales, Mauricio Eduardo Tano [Idaho National L↗

DOE OSTI2026

OpenStudio®-MCP [SWR-26-035]

OpenStudio®-MCP is a Model Context Protocol (MCP) server that lets AI assistants perform building energy modeling through natural language. Rather than requiring users to learn the OpenStudio® SDK, EnergyPlus® scripting, or Ruby/Python automation, the server translates conversational requests into sequences of tool calls that create models, design HVAC systems, run simulations, and extract results — all within a single chat session. The server's 124 tools are organized into a skills architecture where each skill encapsulates a domain of building energy modeling (envelope, HVAC, loads, weather, simulation, results) behind typed, LLM-friendly interfaces. High-leverage operations like applying ASHRAE 90.1 baseline systems or generating standards-compliant typical buildings are exposed as single tool calls that internally wire dozens of OpenStudio® objects. Bundled measures from ComStock™ and Openstudio® -common-measures-gem are wrapped with dedicated tools and typed arguments rather than exposed through a generic measure interface, so AI models get consistent, error-resistant recipes without needing to discover measure arguments at runtime. A key design decision is structured results extraction: six SQL-based tools return surgical ~300–1,000 token responses (end-use breakdowns, envelope summaries, HVAC sizing, timeseries data) instead of requiring the AI to parse ~100K-token raw HTML reports, making iterative design exploration practical within context window limits. The codebase is designed as a reference implementation — explicit, well-commented, and modular — so that other simulation engines (EnergyPlus® standalone, TRNSYS, DOE-2) can use it as a template for building their own MCP servers.

Ball, Brian [National Laboratory of the Rockies (N↗