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At least 127 records · Page 7

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DOE OSTI2025

ThinCurr: An open-source 3D thin-wall eddy current modeling code for the analysis of large-scale systems of conducting structures

In this paper we present a new thin-wall eddy current modeling code, ThinCurr, for studying inductively-coupled currents in 3D conducting structures -- with primary application focused on the interaction between currents flowing in coils, plasma, and conducting structures of magnetically-confined plasma devices. The code utilizes a boundary finite element method on an unstructured, triangular grid to accurately capture device structures. The new code, part of the broader Open FUSION Toolkit, is open-source and designed for ease of use without sacrificing capability and speed through a combination of Python, Fortran, and C/C++ components. Scalability to large models is enabled through use of hierarchical off-diagonal low-rank compression of the inductance matrix, which is otherwise dense. Ease of handling large models of complicated geometry is further supported by automatic determination of supplemental elements through a greedy homology approach. Here, a detailed description of the numerical methods of the code and verification of the implementation of those methods using cross-code comparisons against the VALEN code and Ansys commercial analysis software is shown.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Bayesian Optimization for Anything (BOA): An open-source framework for accessible, user-friendly Bayesian optimization

We introduce Bayesian Optimization for Anything (BOA), a high-level Bayesian Optimization (BO) framework and model wrapping toolkit, which presents a novel approach to simplifying BO, with the goal of making it more accessible and user-friendly, particularly for those with limited expertise in the field. BOA addresses common barriers in implementing BO, focusing on ease of use, reducing the need for deep domain knowledge, and cutting down on extensive coding requirements. A notable feature of BOA is its language-agnostic architecture, which facilitates broader application in various fields and to a wider audience. We showcase BOA's application through three examples: a high-dimensional optimization with parameters of the SWAT+ watershed model, a highly parallelized optimization of this intrinsically non-parallel model, and a multi-objective optimization of the FETCH Tree-Crown Hydrodynamics model. Furthermore, these test cases illustrate BOA's effectiveness in addressing complex optimization challenges in diverse scenarios.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Shadow masks predictions in SPARC tokamak plasma-facing components using HEAT code and machine learning methods

Here, this work uses machine learning (ML) to complement HEAT (Heat flux Engineering Analysis Toolkit) by developing 3-D footprint surrogate models for fast and accurate heat load calculations in the divertor of the SPARC tokamak. The focus is on shadowed regions, or magnetic shadows, caused by the 3-D geometry of plasma-facing components (PFCs). ML classifiers are employed to create a surrogate model for HEAT generated shadow masks, predicting these shadow masks and divertor heat flux profiles based on a diverse range of equilibria and only the plasma current, safety factor(q95) at the edge, and magnetic flux angles as input parameters. The ultimate goal is to integrate the model for real-time control and future operational decisions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Origin of replication discovery for environmentally isolated Pantoea strain enables expression of heterologous proteins, pathways and products

Leveraging predicted origin sequences from a previously characterized groundwater plasmidome, we constructed a barcoded plasmid library to screen for previously unknown origins. Testing this library against a panel of representative bacterial strains led to the identification of 3 previously unknown origins that replicate in gram-negative bacteria not previously associated with these origin sequences. Experimental validation confirmed that a plasmid bearing origin 6911 as the sole origin could replicate with a copy number of 9 (±2) in Pantoea sp. MT58, a fast growing and metal tolerant, environmentally important bacterium. Plasmids based on this new origin were used to express the reporter protein GFP, and non-native metabolite pathways for the natural product indigoidine and the terpenoid compound isoprenol. Functional previously unknown origins of replication in such non-model organisms can expand the toolkit for genetic manipulations of both model and less-studied bacteria.

molecular biology↗

DOE OSTI2025

Enhancing 2D hydrodynamic flood models through machine learning and urban drainage integration

Two-dimensional hydrodynamic flood models are commonly employed for simulating flood extent and inundation depth. However, the influence of urban drainage network (UDN) is frequently overlooked in these models, potentially compromising their accuracy. Furthermore, the expensive computational costs and longer processing times make them challenging for large-scale hydrodynamic simulation. To address these challenges, this paper develops a machine learning (ML)-driven emulator for an open-source flood model, the Two-dimensional Runoff Inundation Toolkit for Operational Needs (TRITON). A TRITON-ML Emulator (TR-Emulator) that utilizes Convolutional Long Short-Term Memory is developed to capture the spatiotemporal features of flood events based on the outputs from TRITON. We further enhance the emulator by integrating UDN parameters (TR-UDN), such as the flow capacity of drainage pipes, pipe size, and pipe length, via an ML stacking technique to improve the water surface elevation (WSE) simulation. Hurricane Harvey 2017 in Houston, TX is used as the case study. We compare WSE results from TRITON, TR-Emulator, TR-UDN, and the United States Geological Survey (USGS) observations to evaluate the performance of these models. The results indicate that the TR-Emulator effectively replicates the WSE simulated by TRITON. Additionally, TR-UDN performs well in capturing WSE patterns and peak flows, aligning more closely with USGS observations, except in areas with milder slopes where conveyance discrepancies are observed. We further test the generalizability of our ML-based models using another smaller event. This paper shows that the TR-Emulator is effective for users and engineers to emulate a 2D hydrodynamic model, and the enhanced version of the TR-Emulator, TR-UDN, can be an efficient tool for predicting WSEs during urban flooding.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Development of a multi-layer canopy model for E3SM Land Model with support for heterogeneous computing

The vertical structure of vegetation canopies creates micro-climates. However, the land components of most Earth System Models, including the Energy Exascale Earth System Model (E3SM), typically neglect vertical canopy structure by using a single layer big-leaf representation to simulate water, CO 2 , and energy exchanges between the land and the atmosphere. In this study, we developed a Multi-Layer Canopy Model for the E3SM Land Model to resolve the micro-climate created by vegetation canopies. The model developed in this study re-implements the CLM-ml_v1 to support heterogeneous computing architectures consisting of CPUs and GPUs and includes three additional optimization-based stomatal conductance models. The use of Portable, Extensible Toolkit for Scientific Computation provides a speedup of 25–50 times on a GPU relative to a CPU. The numerical implementation of the model was verified against CLM-ml_v1 for a month-long simulation using data from the Ameriflux US-University of Michigan Biological Station site. Model structural uncertainty was explored by performing control simulations for five stomatal conductance models that exclude and include the control of plant hydrodynamics (PHD) on photosynthesis. The bias in simulated sensible and latent heat fluxes was lower when PHD was accounted for in the model. Additionally, six idealized simulations were performed to study the impact of three environmental variables (i.e. air temperature, atmospheric CO 2 , and soil moisture) on canopy processes (i.e. net CO 2 assimilation, leaf temperature, and leaf water potential). Increasing air temperature reduced net CO 2 assimilation and increased air temperature. Net CO 2 assimilation increased at higher atmospheric CO 2 , while decreasing soil moisture resulted in lower leaf water potential.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Conditional guide RNA deactivation by mRNA and small molecule triggers in Saccharomyces cerevisiae

CRISPR interference (CRISPRi) technologies have revolutionized bioengineering by providing precise tools for gene expression modulation, enabling targeted gene perturbation and metabolic pathway optimization. Despite these advances, achieving dynamic control over gene expression by CRISPR-based regulation remains a challenge due to its inherently static nature. Utilizing toehold-mediated strand displacement and ligand-responsive ribozymes (aptazymes), this study introduces switchable guide RNAs (gRNAs) that facilitate tunable gene expression mediated by mRNA or small molecule signals. We demonstrate complete silencing of gRNA via strategically designed 5’ or 3’ extensions that impede the gRNA spacer or the dCas9 handle, with subsequent restoration of function through sequestration or cleavage of the obstructive sequence. The resulting toehold-embedded or aptazyme-embedded gRNAs can be deactivated by specific signals, including two full-length translatable mRNAs and two small molecule triggers, thereby lifting CRISPRi repression on targeted genes. This modular approach allows for gRNA-based biocomputing through multi-layer or multi-input genetic logic gates in Saccharomyces cerevisiae . Offering a versatile strategy for post-CRISPR regulation in response to environmental signals or cellular states, this methodology expands the toolkit in eukaryotic systems for reversible control of gene expression.

Aptazyme↗

DOE OSTI2027

Conceptual design of highly-constrained splitters for the FFA@CEBAF energy upgrade study

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab is investigating a significant energy upgrade utilizing Fixed-Field Alternating-gradient (FFA) recirculating arcs. This upgrade requires the design of complex horizontal beam splitters to manage up to six concurrent beam passes. This paper presents the conceptual design of these splitters, which are subject to severe physical constraints imposed by the existing accelerator tunnel and multifaceted beam dynamics requirements for matching into the permanent-magnet FFA arcs. The design methodology, centered on multi-pass simulations in the Bmad toolkit, is detailed from the initial geometric layout through the advanced optics matching. Key results include a robust geometric arrangement that fits within the spatial boundaries and the development of multiple, flexible optics matching solutions. Furthermore, the design integrates a viable scheme for extracting high-energy beams for the experimental halls, a critical operational requirement. This work establishes a comprehensive and viable conceptual design, forming a baseline for future engineering and performance optimization studies.

Bodenstein, R.M. [Thomas Jefferson National Accele↗

DOE OSTI2026

59 Co(p,X) spallation reaction cross sections for 250 MeV to 2 GeV protons

Cobalt is an advantageous target for probing the physics of nuclear spallation, because it is a naturally mono-isotopic element ( 59 Co), and its per-nucleon binding energy (BE/A = 8.768 MeV) is near the maximum value for all nuclei. We measured nuclear spallation cross sections for the 59 Co(p,X) reaction at five kinetic energies ranging from 250 MeV to 2 GeV. Cross sections for the production of 58 Co, 57 Co, 57 Mn, 56 Co, 56 Mn, 56 Cr, 55 Fe, 53 Fe, 54 Mn, 52 Mn, 51 Cr, 49 Cr, 48 V, 47 Sc, 46 Sc, 44 Sc, and 44 Scm are reported. Where comparable data exist in the EXFOR reaction database, we find that our measured cross sections generally agree. In many cases, we provide data for reactions or energies not currently reported in EXFOR. Our cross sections also provide evidence for the presence of α-clusters within the 59 Co nucleus, a surprising result given the asymmetry in Z (27) and N (32) for this nucleus. Finally, we use our measurements to evaluate the accuracy of spallation cross section simulations from GEANT4-based radiation transport toolkit, performed with the INCLXX-, Bertini-, and Binary-ion-cascade (BIC) based physics lists. This benchmarking activity revealed that the simulations overestimated the cross sections by a factor of ∼2–4 on average, and that the INCL-XX physics list provides the most reliable results. This evaluation informs the selection of the GEANT4 physics lists used for the analysis of data from NASA’s Psyche mission, which will measure γ rays and neutrons resulting from spallation reactions occurring on the surface of an asteroid whose surface is thought to be rich in iron-nickel metal.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

A nonhydrostatic formulation for MPAS-Ocean

The Model for Prediction Across Scales-Ocean (MPAS-Ocean) is an open-source, global ocean model and is one component of a family of climate models within the MPAS framework, including atmosphere, sea-ice, and land-ice models. Here, in this work, a new formulation for the ocean model is presented that solves the nonhydrostatic, incompressible Boussinesq equations on an unstructured, staggered, z-level grid. The introduction of this nonhydrostatic capability is necessary for the resolution of internal wave dynamics and large eddy simulations. Compared to the standard, hydrostatic formulation, a nonhydrostatic pressure solver and a vertical momentum equation are added, where the PETSc (Portable Extensible Toolkit for Scientific Computation) library is used for the inversion of a large sparse system for the nonhydrostatic pressure. Numerical results on a stratified seiche, internal solitary wave, overflow and lock-exchange test cases are presented, and the parallel efficiency of the code is evaluated using up to 1024 processors.

3D Poisson equation↗

DOE OSTI2025

A nonhydrostatic formulation for MPAS-Ocean

3D Poisson equation↗

DOE OSTI2024

DRiFT current mode, trigger settings and flexible detector specifications applied to scintillator arrays

MCNP radiation transport output is post-processed by DRiFT, a Detector Response Function Toolkit to simulate detailed nuclear instrumentation response. DRiFT can be used to assess the performance and potential limitations of scintillator, gas, and semiconductor detectors under a variety of simulated conditions not easily achievable in a laboratory setting. This work describes new updates in DRiFT for scintillator simulations which focus on the capability to simulate scintillators in current mode, an expansion of trigger options, and the ability to customize individual detector properties in a simulation. These improvements are designed to facilitate the ability to model large arrays of scintillator detectors with higher fidelity than was previously possible and are demonstrated in three examples. The first shows the difference between operating DRiFT in current and pulse mode. In the second example, which is intended to demonstrate deviations in individual detector performance, each detector has properties (PMT gain, optical transport, scintillation yield, etc.) that vary between detectors and are specified in DRiFT. A final example examines how DRiFT could be used to optimize digitizer settings in high rate measurements with split signals using the new common trigger option.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2025

Groundwater flowpath characteristics drive variability in per- and polyfluoroalkyl substances (PFAS) loading across a stream-wetland system

Groundwater dependent ecosystems in areas with industrial and military land use are at risk of direct exposure to a wide range of contaminants, including PFAS chemicals. Glaciated terrain often has mixed high and low permeability sediments coupled with groundwater flow-through lake features. These hydrogeologic attributes create highly complex ‘source to seep’ dynamics that make spatiotemporal contaminant transport patterns difficult to predict. We investigated one such system in detail using a suite of heat-tracing and chemical methods. Numerous (n=57) preferential groundwater discharge zones (vertical flux rates ranging 0.2 to 3.2 m/d) were identified across the upper Quashnet River stream-wetland system in Mashpee, MA, USA, adjacent to an Air Force Base with several known PFAS source areas. Surface-water and groundwater samples were collected and analyzed (n=145) for precursors and terminal PFAS compounds between March and September 2022. Samples were collected at identified seeps along the Quashnet River (n=59), from wells upgradient from the stream-wetland system (n= 44), from contributing flow-through kettle lakes (n=8), and at multiple locations along the Quashnet River (n=34). Samples from seeps and wells had measured PFAS concentrations ranging from non-detect to approximate 3,500 ng/L (mean= 1,650 ng/L), and a range of deuterium excess values (3.2 to 15.9 per mil) indicative of varying degrees of groundwater-lake interaction prior to emergence at the discharge zones. Groundwater-lake interaction along flowpaths that sourced the sampled seeps was farther supported by significant correlations (p < 0.01) between deuterium excess and %PFAS precursors, and between %PFAS precursors and multiple terminal PFAS compounds (e.g., PFPeS, PFBS, PFHxS). However, some sampled seeps contributing groundwater to the stream-wetland system had much higher total PFAS concentrations (>1000 ng/L) than the upgradient kettle lakes, despite showing lake (evaporative) isotopic signatures, indicating the potential for groundwater flowpath convergence at wetland discharge zones and the influence of lakebed PFAS precursor reactions. PFAS compounds and water isotopic composition at sampled multilevel groundwater wells, rivers, lakes, and seeps suggest that a complex mixture of source groundwater and flowpath characteristics are responsible for diverse observed PFAS mixtures at preferential discharge zones across the stream-wetland system. Further, total PFAS loading patterns to the Quashnet River via groundwater discharge remained remarkably similar from winter to summer to fall conditions, despite a regional dry period in late summer 2022 with the upper river channel completely drying. This work addresses gaps in the existing PFAS literature by demonstrating the importance of subsurface fate and transport on PFAS compound concentrations in controlling contaminant mass loading in preferential groundwater discharge zones and presents a transferrable field toolkit for efficient characterization of spatially preferential PFAS transport dynamics.

Contaminant transport↗

DOE OSTI2026

Development, optimization, and application of an episomal plasmid system for Rhodotorula toruloides

Rhodotorula toruloides is an emerging oleaginous yeast with strong potential as a microbial cell factory for the production of acetyl-CoA-derived bioproducts. However, engineering of this organism has been limited by the absence of a functional episomal plasmid system, a foundational genetic tool for rapid gene expression, pathway testing, and CRISPR-based genome engineering. Here, we report the first episomal plasmid system for R. toruloides . Through systematic screening of candidate autonomously replicating sequences (ARSs) from diverse sources, we identified multiple functional ARS elements and selected C63F4, a fragment derived from Contig 63 of R. toruloides CBS14, because of its stable performance. The resulting pC63F4 plasmid was maintained episomally, supported GFP reporter expression, exhibited a copy number of 2.39 ± 0.13, and showed good stability during long term cultivation. To overcome poor transformation efficiency, we developed a Cre- loxP -mediated in vivo re-circularization strategy that enabled reliable delivery of the episomal plasmid. Using this improved system, we demonstrated functional episomal expression of metabolic engineering genes and multi-gene pathways for the production of triacetic acid lactone, fatty alcohols, and limonene. Finally, we leveraged this platform to establish a redesigned CRISPR system that enables seamless genome editing in R. toruloides for the first time, while also simplifying marker recycling. Together, this work establishes a long-needed episomal plasmid platform and associated CRISPR toolkit that will accelerate metabolic engineering, synthetic biology, and fundamental studies in R. toruloides .

CRISPR-Cas9↗

DOE OSTI2025

On the effectiveness of neural operators at zero-shot weather downscaling

Machine-learning (ML) methods have shown great potential for weather downscaling. These data-driven approaches provide a more efficient alternative for producing high-resolution weather datasets and forecasts compared to physics-based numerical simulations. Neural operators, which learn solution operators for a family of partial differential equations, have shown great success in scientific ML applications involving physics-driven datasets. Neural operators are grid-resolution-invariant and are often evaluated on higher grid resolutions than they are trained on, i.e., zero-shot super-resolution. Given their promising zero-shot super-resolution performance on dynamical systems emulation, we present a critical investigation of their zero-shot weather downscaling capabilities, which is when models are tasked with producing high-resolution outputs using higher upsampling factors than are seen during training. To this end, we create two realistic downscaling experiments with challenging upsampling factors (e.g., 8x and 15x) across data from different simulations: the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) and the Wind Integration National Dataset Toolkit. While neural operator-based downscaling models perform better than interpolation and a simple convolutional baseline, we show the surprising performance of an approach that combines a powerful transformer-based model with parameter-free interpolation at zero-shot weather downscaling. We find that this Swin-Transformer-based approach mostly outperforms models with neural operator layers in terms of average error metrics, whereas an Enhanced Super-Resolution Generative Adversarial Network-based approach is better than most models in terms of capturing the physics of the ground truth data. We suggest their use in future work as strong baselines.

17 WIND ENERGY↗

DOE OSTI2025

First-Principles Statistical Mechanics Study of Magnetic Fluctuations and Order–Disorder in the Spinel LiNi 0.5 Mn 1.5 O 4 Cathode

While significant magnetic interactions exist in lithium transition metal oxides, commonly used as Li-ion cathodes, the interplay between magnetic couplings, disorder, and redox processes remains poorly understood. In this work, we focus on the high-voltage spinel LiNi 0.5 Mn 1.5 O 4 (LNMO) cathode as a model system on which to apply a computational framework that uses first principles-based statistical mechanics methods to predict the finite temperature magnetic properties of materials and provide insights into the complex interplay between magnetic and chemical degrees of freedom. Density functional theory calculations on multiple distinct Ni–Mn orderings within the LNMO system, including the ordered ground-state structure (space group P4332), reveal a preference for a ferrimagnetic arrangement of the Ni and Mn sublattices due to strong antiferromagnetic superexchange interactions between neighboring Mn 4+ and Ni 2+ ions and ferromagnetic Mn–Mn and Ni–Ni couplings, as revealed by magnetic cluster expansions. These results are consistent with qualitative predictions using the Goodenough-Kanamori-Anderson rules. Simulations of the finite temperature magnetic properties of LNMO are conducted using Metropolis Monte Carlo. We find that a “semiclassical” Monte Carlo sampling method based on the Heisenberg Hamiltonian accurately predicts experimental magnetic transition temperatures observed in magnetometry measurements. This study highlights the importance of a robust computational toolkit that accurately captures the complex chemomagnetic interactions and predicts finite temperature magnetic behavior to help analyze experimental magnetic and magnetic resonance spectroscopy data acquired ex situ and operando.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Structural Propensities in Cs2MBiX6 (M=Na, Ag; X=Cl, Br) Bismuth Halide Double Perovskites

A previously unreported low-temperature phase transition in the bismuth halide double perovskite Cs2AgBiCl6 is reported, thereby establishing trends in the structural ground state across Cs2NaBiCl6, Cs2AgBiCl6, and Cs2AgBiBr6. Using the combined toolkit of variable-temperature synchrotron X-ray and neutron powder diffraction, Raman spectroscopy, and density-functional theory–based electronic structure modeling, we demonstrate a cubic Fm¯3m → tetragonal I4/m transition upon cooling with distinct onset temperatures. Neutron powder diffraction refinements permit the unambiguously assignment of the low-temperature phase of Cs2NaBiCl6 to I4/m, correcting prior reports of an I4/mmm ground state. Cs2AgBiCl6 is also found to transforms to a structure crystallizing in the I4/m space group at low temperatures. Temperaturedependent Raman data and density-functional theory-based modeling capture the softening and freezing of out-of-phase octahedral-tilt modes and quantify relative instabilities. Solid-state nuclear magnetic resonance spectroscopy at room temperature completes the characterization and helps underpin the subtle differences in covalency across the compounds. Trends in the phase transition temperature Ts and tilt magnitudes emerge from coupled effects of halide identity, M(I)–site bonding character, and a mismatch between interatomic distances. These results establish the structure– dynamics–bonding framework for tuning tilt-driven instabilities in halide double perovskites.

Tian, Haowen↗

DOE OSTI2025

Improved Treatment of 1–4 Interactions in Force Fields for Molecular Dynamics Simulations

Traditional force fields commonly use a combination of bonded torsional terms and empirically scaled nonbonded interactions to capture 1-4 energies and forces of atoms separated by three bonds in a molecule. While this approach can yield accurate torsional energy barriers, it often leads to inaccurate forces and erroneous geometries and creates an interdependence between dihedral terms and nonbonded interactions, complicating parametrization and reducing transferability. Here, in this paper, we demonstrate that 1-4 interactions can be accurately modeled using only bonded coupling terms, eliminating the need for arbitrarily scaled nonbonded interactions altogether. Furthermore, by leveraging the automated parametrization capabilities of the Q-Force toolkit, we efficiently determine the necessary coupling terms without the need for manual adjustment. Our approach is first validated on a range of small molecule systems, encompassing both flexible and rigid structures, and shows a significant improvement in force field accuracy, obtaining subkcal/mol mean absolute error for every molecule tested. We further extend the bonded-only model for 1-4 interactions to Amber ff14sb, CHARMM36, and OPLS-AA force fields to reproduce ab initio gas and implicit solvent ϕ,ψ surfaces of alanine dipeptide.

Abdullah, Aalim S. [University of California, Berk↗