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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Cosmic millicharge background and reheating probes

We demonstrate that the searches for dark sector particles can provide probes of reheating scenarios, focusing on the cosmic millicharge background produced in the early universe. We discuss two types of millicharge particles (mCPs): either with, or without, an accompanying dark photon. These two types of mCPs have distinct theoretical motivations and cosmological signatures. We discuss constraints from the overproduction and mCP-baryon interactions of the mCP without an accompanying dark photon, with different reheating temperatures. We also consider the ∆n eff constraints on the mCPs from kinetic mixing, varying the reheating temperature. The regions of interest in which the accelerator and other experiments can probe the reheating scenarios are identified in this paper for both scenarios. These probes can potentially allow us to set an upper bound on the reheating temperature down to ~ 10 MeV, much lower than the previously considered upper bound from inflationary cosmology at around ~ 10 16 GeV. In addition, we derive a new “distinguishability condition”, in which the two mCP scenarios may be differentiated by combining cosmological and theoretical considerations. Finally, we discuss the implications of dedicated mCP searches, future CMB-S4 observations, and the target for experiments when considering the minimally allowed reheating temperature.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Elucidating grain boundary energy minimization mechanisms in textured Ca-doped alumina with inclination-dependent Monte Carlo Potts simulations

The grain growth behavior of textured Ca-doped alumina is compared to Monte Carlo Potts (MCP) simulations to investigate the effect of anisotropic grain boundary (GB) properties on local boundary migration. Experimentally, the growth of textured Ca-doped alumina results in highly elongated grains. The relative GB energy distribution is measured using the thermal groove method before and after heat treating at 1600°C, finding that high energy GBs are eliminated during grain growth. No significant difference in the GB energy distributions is found between the long and short axes of the elongated grains, suggesting that anisotropic mobility may be responsible for the grain shape. However, MCP simulations with anisotropic mobility as a function of plane inclination do not result in grains with distinct morphologies, regardless of the degree of anisotropy introduced. The final grain shape after grain growth of textured Ca-doped alumina resembles that of the MCP simulations using an anisotropic GB energy as a cosine function of plane inclination. Several energy functions are tested and only those that mathematically impose a torque (second derivative of energy with respect to the plane inclination angle) result in elongated grains. Although area reduction is the dominant energy minimization mechanism, these results suggest that local GB migration is affected by anisotropic GB energy and torque and alternative mechanisms like GB replacement and reorientation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

UV-Vis spectrophotometric determination of rare earth elements (REE) speciation at near-neutral to alkaline pH. Part II: hydrolysis of Er from 25 to 75 °C

Aqueous speciation of rare earth elements (REE) controls their mobilization, fractionation, and enrichment in the natural waters. Geochemical modeling of their speciation is key to improve our understanding of the formation of economic mineral deposits, for developing mineral separation and mine tailing recovery technologies, and for characterizing the geochemistry of thermal water. However, our ability to predict the fate of REE in a wide pH and temperature range is limited by the scarcity of thermodynamic data for the REE hydroxyl complexes. In part I of this study (H. J. Han and A. P. Gysi, Dalton Trans., 2024, 53, 13129–13141), the optical properties of m-cresol purple (mCP) were determined using UV-Vis spectrophotometry between 25 and 75 °C in order to develop a method for deriving the hydrolysis constants of erbium (Er). Here, UV-Vis spectrophotometry experiments were conducted as a function of temperature between 35 and 75 °C to determine the hydrolysis of Er in near-neutral to alkaline solutions using mCP as an in situ pH color indicator. Here, the experiments were conducted with Er concentrations from 0 to ~0.253 mmol kg –1 in low ionic strength solutions (≤0.001 mol kg –1 ).

58 GEOSCIENCES↗
DOE OSTI2026

Proposal for a dedicated search for millicharged and fractionally charged particles at LANL

In this paper, we propose an experiment, LANSCE-mQ, aiming to detect fractionally charged and millicharged particles (mCPs) using an 800 MeV proton beam fixed target at the Los Alamos Neutron Science Center (LANSCE) facility at Los Alamos National Laboratory. This search can shed new light on numerous fundamental questions, including charge quantization, the predictions of string theories and grand unification theories, the gauge symmetry of the Standard Model, dark sector models, and the tests of cosmic reheating. We propose to install two-layer scintillation detectors made of plastic (such as EJ-200) or CeBr 3 to search for mCPs. Dedicated geant4 detector simulations and in situ measurements have been conducted to obtain a preliminary determination of the background rate. The dominant backgrounds are beam-induced neutrons and coincident dark current signals from the photomultiplier tubes, while beam-induced high-energy photons ( γ ’s) and cosmic muons are subdominant. We determined that LANSCE-mQ, the dedicated mCP experiment, has the leading mCP sensitivity for mass between ∼ 1 and 300 MeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

DOE Repository Metadata Profile (DRMP): A Metadata Framework for Advancing Interoperability and AI Readiness Across Scientific Repositories

The Department of Energy (DOE) funds a diverse and distributed ecosystem of repositories that steward scientific data, publications, and software across its research programs, user facilities, and national laboratories. While significant progress has been made in standardizing dataset-level metadata, the metadata describing repositories themselves (their identity, governance, access interfaces, policies, and technical capabilities) remains inconsistent and fragmented across DOE-funded systems. This variability limits discoverability, interoperability, automated validation, and AI-driven analysis, all of which are increasingly essential for modern scientific workflows. To address this gap, the DOE Data Curation Working Group (DCWG) developed the DOE Repository Metadata Profile (DRMP). The DRMP is a practical, community-driven framework that defines how repositories can describe themselves in a consistent, machine-actionable, and scalable manner. The DRMP is not a new metadata schema. Instead, it is a mapping profile and structured element set capturing the essential characteristics of DOE repositories. It harmonizes repository-level metadata across six widely adopted community schemas: RE3Data; DCAT-US v3; Schema.org; Dublin Core; DataCite 4.6; and PREMIS 3.0. This harmonization eliminates reinvention and enables interoperability within DOE and across the broader scientific ecosystem. A core objective of the DRMP is to reduce burden on repositories by allowing them to reuse their existing metadata through a Rosetta-style crosswalk rather than redesigning local implementations. The profile introduces a three-level conformance model that supports incremental adoption: • Level 1 – Minimum Viable Record (MVR): foundational identification elements required for workflows, project registration, and basic repository presence. • Level 2 – Interoperable: structured metadata enabling alignment with national and international discovery systems. • Level 3 – AI-Ready: enhanced provenance, policy transparency, fixity, semantic context, and capabilities that support automated reasoning, model training governance, and machine-assisted curation. To support implementation, the DRMP includes JSON Schema definitions, OpenAPI patterns, and MCP templates that allow repositories to publish machine-readable metadata directly within existing platforms. These resources are modular and lightweight, enabling adoption without major architectural change. Adopting the DRMP enables repositories to: • Enhance discoverability and interoperability by aligning identifiers, classifications, and descriptive elements across widely used schema standards. • Support federated discovery and cross-registration across DOE systems, Data.gov, and international catalogs. • Enable AI agents and workflow orchestration systems to interpret repository-level metadata within the American Science Cloud (AmSC) through Model Context Protocol (MCP)-based context publication. • Demonstrate alignment with DOE’s open science, stewardship, and FAIR data priorities. This guidance represents a community-driven step forward. Through voluntary adoption and continued feedback, the DRMP advances a cohesive, machine-actionable description of DOE repositories that supports FAIR data practices, preparing the infrastructure for AI-enabled research, and strengthening the discoverability and reuse of DOE’s scientific outputs.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

Beyond curvature-driven grain growth: Insights from fully anisotropic Monte Carlo Potts simulations

Grain boundary (GB) motion away from the center of curvature, termed anti-curvature behavior, has recently been observed in 3D experiments but is not predicted by classical grain growth theory. In this study, we investigate this behavior using a novel, fully anisotropic Monte Carlo Potts (MCP) model that incorporates both misorientation and inclination dependencies of GB energy. We perform 3D grain growth simulations with isotropic and anisotropic GB energies to explore the relationship between GB velocity and curvature. Contrary to the classical relation that velocity is a product of reduced mobility and mean curvature, we observe no consistent correlation between velocity and mean curvature for individual GBs, even under isotropic conditions, though there is correlation between the average velocity and curvature for some cases. The 3D simulations exhibit frequent anti-curvature motion regardless of GB energy anisotropy including with isotropic GBs, though larger curvatures occur with anisotropic GB energy functions that promote low-energy GBs. In 2D simulations, anti-curvature behavior only occurs with the anisotropic functions that favor low-energy GBs. This difference between 2D and 3D results suggests that anti-curvature behavior results in part from the increased freedom of motion intrinsic in 3D GB networks. Furthermore, our results support recent experimental observations that demonstrate that simple curvature-driven models are insufficient for describing GB migration in polycrystals.

Anti-curvature↗
DOE OSTI2025

High energy particle detection with large area superconducting microwire array

We present the first detailed study of an 8-channel2×2 mm$^{2}$ WSi superconducting microwire single photondetector (SMSPD) array exposed to 120 GeV proton beam and 8 GeVelectron and pion beam at the Fermilab Test Beam Facility. TheSMSPD detection efficiency was measured for the first time forprotons, electrons, and pions, enabled by the use of a silicontracking telescope that provided precise spatial resolution of30 μm for 120 GeV protons and 130 μm for 8 GeVelectrons and pions. The result demonstrated consistent detectionefficiency across pixels and at different bias currents. Timeresolution of 1.15 ns was measured for the first time for SMSPDwith proton, electron, and pions, enabled by the use of an MCP-PMTwhich provided a ps-level reference time stamp. The resultspresented is the first step towards developing SMSPD array systemsoptimized for high energy particle detection and identification forfuture accelerator-based experiments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Production of microchannel plates using nano-scale additive manufacturing

Microchannel plate (MCP) detectors have been the workhorse detector for many applications, including space borne ultra-violet imaging and spectrographic instruments. Recent advances in additive manufacturing (AM) have enabled fabrication of complex structures with nano-scale resolution facilitating the production of highly customizable MCPs. Using AM to produce MCPs potentially has many advantages over traditional fused glass substrates, including better material control (e.g., more robust glasses or ceramics), better control of microscopic features (e.g., unique pore geometries to improve performance), and better control of macroscopic features (e.g., printing precision curved surfaces for focal plane matching). Through a collaboration with industry, national laboratory, and university partners, small format microcapillary array substrates were produced using a standard polymer photoresin. In conclusion, these substrates were functionalized using atomic layer deposition and their performance was compared to current state-of-the-art Pb-glass and borosilicate-glass MCPs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Atlas-UI-3

SAND2025-14754O Atlas-UI-3 is the third iteration of the LLM chat user interface called Atlas. The tool does not share code with previous versions. It supports chat with large language models (LLMs), connects to retrieval-augmented generation (RAG) servers, features a marketplace/store for model and content providers (MCP), and enables tool calling. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Melander, Darryl [Sandia National Lab. (SNL-CA), L↗
DOE OSTI2026

MADA: Multi-Agent Design Assistant

MADA (Multi-Agent Design Assistant) is a Large Language Model (LLM) powered multi-agent framework that coordinates specialized agents for complex design workflows. The system was designed for HPC workflows with the following agents in mind: 1) A Job Management Agent (JMA) launches and manages ensemble simulations on HPC systems, 2) a Geometry Agent (GA) generates meshes, and 3) an Inverse Design Agent (IDA) proposes new designs informed by simulation outcomes. Our framework reduces cumbersome manual workflow setup, and enables automated design exploration at scale. However, the software also enables users to rapidly create new multi-agent systems. Simply define new agents in a configuration file, giving each their own set of tools (via MCP), and then chat and prompt your new multi-agent system. Is

Gunnarson, BrianS [Lawrence Livermore National Lab↗
DOE OSTI2025

2019 Meander C and Meander Z floodplain groundwater chemistry from the East River Watershed, CO, USA

This dataset includes groundwater geochemistry data from floodplain piezometers collected as a part of the Watershed Function Scientific Focus Area (SFA) located in the Upper Colorado River Basin. The data were collected in order to investigate the role of hyporheic exchange and other river corridor processes on riverine export of solutes. Data includes samples from two intra-meander zones: Meander C, in the Pumphouse vicinity, and Meander Z, just upstream of the confluence with Brush Creek. Floodplain piezometers installed along two transects across Meander C (MCP and MCB wells) and Meander Z (MZA and MZB wells) were sampled on daily to weekly time scales during summer-fall 2019. Some river water grab samples are also included. Data includes in-field measurements (pH, electrical conductivity [EC], oxidation reduction potential [ORP], dissolved oxygen [DO], and groundwater level) along with laboratory measurements (dissolved inorganic carbon [DIC], dissolved organic carbon [DOC], metals and major cations, anions [chloride, sulfate, nitrate], and dissolved ammonium). Files are included in this dataset include: sample locations and depths in both a kmz file which can be opened in Google Earth and a csv file, aqueous geochemistry data in a csv files for Meander C and Meander Z, and analytical detection limits in a csv file. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Data from: "Towards CONUS-Wide ML-Augmented Conceptually-Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics"

This data package was generated to support the manuscript “Towards CONUS-Wide Machine Learning-Augmented Conceptually Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics.” It provides input files, model outputs, plotting data, scripts, notebooks, and documentation used to develop, evaluate, and reproduce Mass-Conserving Perceptron (MCP)-based hydrologic modeling experiments across 513 selected Catchment Attributes and Meteorology for Large-sample Studies in the United States (CAMELS-US) basins. The files are organized by modeling component and analysis purpose, including rainfall–runoff experiments, snow module experiments, coupled hydrologic-snow experiments, Long Short-Term Memory (LSTM) benchmark results, model skill metrics, initialization and epoch records, cell-state normalization files, Akaike Information Criterion (AIC)-based model comparison files, and data used to generate manuscript figures. Tabular files can be opened using standard spreadsheet software or Python/R data-analysis tools. Python scripts, Jupyter notebooks, and selected MATLAB scripts are included for model execution, postprocessing, plotting, and statistical analysis. Quality assurance and quality control were conducted through the source-data selection and modeling workflow. Meteorological forcing, streamflow, and static catchment attributes were derived from the CAMELS-US dataset, and snow water equivalent data were derived from the University of Arizona (UA) Snow Water Equivalent dataset. Selected basins and time periods were screened during the associated research workflow to avoid missing observations or poor-quality cases. Static geospatial features were processed primarily using Quantum Geographic Information System (QGIS) and Geospatial Data Abstraction Library (GDAL) workflows. Additional details are provided in the associated manuscript and documentation.

ESS-DIVE CSV File Formatting Guidelines Reporting ↗
DOE OSTI2026

ORCHID: Orchestrated Retrieval-Augmented Classification of High-Risk Property with Intelligent Decision-Making

High-Risk Property (HRP) classification is critical at U.S. Department of Energy (DOE) sites, where inventories include sensitive and often dual-use equipment. Compliance must track evolving rules designated by various export control policies to make transparent and auditable decisions. Traditional expert-only workflows are time-consuming, backlog-prone, and struggle to keep pace with shifting regulatory boundaries. We propose ORCHID, a modular agentic framework for HRP classification that pairs retrieval-augmented generation (RAG) with human oversight to produce policy based outputs that can be audited. Small cooperating agents—retrieval, description refiner, classifier, validator, and feedback logger—coordinate via agent-to-agent messaging and invoke tools through the Model Context Protocol (MCP) for model-agnostic on-premise operation. The interface follows an "Item to Evidence to Decision" loop with step-by-step reasoning, on-policy citations, and append-only audit bundles (run-cards, prompts, evidence). In preliminary tests on real HRP cases, ORCHID improves accuracy and traceability over a non-agentic baseline while deferring uncertain items to Subject Matter Experts (SMEs). The demonstration shows single item submission, grounded citations, SME feedback capture, and exportable audit artifacts—illustrating a practical path to trustworthy LLM assistance in sensitive DOE compliance workflows.

Das, Sanjay [ORNL] (ORCID:0009000542591915)↗
DOE OSTI2026

Conversational Grid Storage: Bridging Rucio and LLMs with Model Context Protocol

Experiments at Fermilab use Rucio to handle datasets that can be up to exabyte scale. However, navigating through Rucio’s syntax-heavy Command Line Interface (CLI) is a major workflow obstruction for researchers who just want to check quotas, track data identifiers (DIDs), or locate data sets. This project introduces a natural language interface. By building a containerized Model Context Protocol (MCP) server, an AI agent is created that translates plain English queries into data operations.

Akella, Kashyap [Fermilab; Illinois U., Urbana (ma↗
DOE OSTI2025

ADEPT: A Pedagogical Framework for Integrating Agentic AI with Deterministic Scientific Workflows

The integration of Large Language Models (LLMs) into scientific research promises to accelerate discovery, yet a significant gap remains between the dynamic reasoning of Artificial Intelligence (AI) agents and the static, deterministic nature of canonical scientific workflows. This paper introduces ADEPT (Agentic Discovery and Exploration Platform for Tools), a reference architecture and pedagogical framework explicitly designed to bridge this gap. ADEPT's primary mission is to provide a transparent, "glass-box" environment where researchers and engineers can learn to effectively wrap established scientific software (e.g., BLAST, Nextflow pipelines) and compose it into reliable, agent-driven workflows. We describe its modular, multi-server architecture, which leverages the Model Context Protocol (MCP) for tool serving, LangGraph for robust agentic orchestration, and a secure nsjail-based sandbox for safe code execution. By prioritizing architectural clarity, safety, and modularity, ADEPT serves as an extensible blueprint for building trustworthy AI-augmented systems and fosters the collaborative development necessary to responsibly employ agentic AI for science. We provide practical examples of how to adapt and extend this framework, highlighting its utility in workforce development and AI-readiness capabilities across research and development projects.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

HRPPD photosensors for RICH detectors with a high resolution timing capability

Recently, a new version of DC-coupled High Rate Picosecond Photodetectors (DC-HRPPDs) substantially re-designed for use at the Electron-Ion Collider (EIC) has been developed. A first batch of seven “EIC HRPPDs” was manufactured in early 2024. These HRPPDs are DC-coupled photosensors based on Micro-Channel Plates (MCPs) that have an active area of 104 mm by 104 mm, 32 × 32 direct readout pixel array at a pitch of 3.25 mm, peak quantum efficiency in excess of 30%, exceptionally low dark count rates and timing resolution of 15–20 ps for a single photon detection. As such, these photosensors are very well suited for Ring Imaging CHerenkov (RICH) detectors that can additionally provide high resolution timing capability, especially in a configuration where a detected charged particle passes through the sensor window, which produces a localized flash containing a few dozens of Cherenkov photons in it.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Evaluation of the absolute single-photon detection efficiency of HRPPD

Pixelated High Rate Picosecond Photon Detectors (HRPPDs) by Incom Inc. are promising photosensors for use in Ring Imaging CHerenkov (RICH) detectors, where a high gain, sub-mm position resolution and sub-100ps timing resolution are required in a single photon mode. Quantum Efficiency (QE) has been measured for the first batch of EIC HRPPDs both by Incom and EIC research groups at Jefferson Lab and Brookhaven Lab, with peak values at ∼365 nm typically exceeding 30%. Furthermore, in this study, we present a first direct measurement of Photon Detection Efficiency being equal to (17.1 ± 0.1 [stat] ± 0.3 [sys])% at 398.6 nm, for a pixel near the center of HRPPD, in a photoelectron pulse counting mode using a picosecond diode laser. HRPPD QE at the same spot and at the same wavelength was evaluated to be (24.4 ± 0.1 [stat] ± 0.3 [sys])%, leading to a Collection Efficiency estimate of (70.3 ± 1.6)%, which is consistent with the expectations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Studies of LAPPD and HRPPD photodetectors for Cherenkov imaging applications

HRPPDs are the baseline single-photon sensors for a classic proximity-focusing RICH (pfRICH) counter, one of the Cherenkov radiation-based PID subsystems of the ePIC detector at the EIC. We report SPE time resolution of 87 ps rms for an LAPPD unit detecting Cherenkov photons in a quartz lens at a CERN PS test beam (2022). We also present the degradation and partial recovery of gain and relative efficiency of an LAPPD unit as a function of the B-field strength (up to 1.5 T) and angular orientation, measured with vertical dipole magnets at CERN (2023–2024). Finally, we report preliminary results of an accelerated ageing study performed on an HRPPD unit in Trieste laboratory (2025).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗