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DOE OSTI2025

Joint cosmological fits to DESI-DR1 full-shape clustering and weak gravitational lensing in configuration space

We present a joint $3\times2$-pt cosmological analysis of auto- and cross-correlations between the Dark Energy Spectroscopic Instrument Data Release 1 (DESI-DR1) Bright Galaxy Survey (BGS) and Luminous Red Galaxy (LRG) samples and overlapping shear measurements from the KiDS-1000, DES-Y3 and HSC-Y3 weak lensing surveys. We perform our analysis in configuration space and, in addition to the cosmic shear correlation functions for each weak lensing dataset, we fit the tangential shear of the weak lensing source galaxies around DESI lens galaxies. Finally, we make use of the anisotropic BGS and LRG clustering information by fitting the full shape of the two-point correlation function multipoles measured over the full DESI-DR1 footprint, presenting the first full-shape analysis of DESI measurements in configuration space. We find that the addition of weak lensing information serves to improve, with respect to the clustering-only case, the measurements of the power spectrum amplitude parameters $\ln(10^{10}A_{\rm{s}})$ and $σ_{12}$ by $15\%$ and $36\%$, respectively. It also improves measurements of the linear bias of the lens galaxies by $15-20\%$, depending on the tracer. Our results show excellent consistency, regardless of the weak lensing survey considered, and are furthermore consistent with a companion analysis that fits $3\times2$-pt correlations including DESI projected clustering measurements, as well as the results published by the weak lensing collaborations themselves. Our measured values for weak lensing amplitude are $S_{8}^{\mathrm{DESI\times HSC}}=0.787\pm0.020$, $S_{8}^{\mathrm{DESI\times DES}}=0.791\pm0.016$, $S_{8}^{\mathrm{DESI\times KiDS}}=0.771\pm0.017$, which are $1.9σ-2.9σ$ below the $S_8$ value preferred by Planck. Finally, our clustering-only results are in good agreement with the Fourier space full-shape analysis of all DESI tracers.

Semenaite, A. [Swinburne U., Ctr. Astrophys. Super↗

DOE OSTI2026

Long-Range Fit: A Software Package for the Representation and Study of Long-Range Molecular Interactions

Describing intermolecular forces is fundamental to modeling and predicting the behavior of molecular systems. In particular, long-range molecular interactions─with electrostatic, induction, and dispersion as the main components─play a critical role, especially for low-temperature and low-density regimes. Long-range interactions are often described through perturbation theory, representing the electronic charge distribution via a multipolar series of the moments and polarizability tensors corresponding to each molecule. However, while the theory is well established, obtaining the resulting analytical expressions (and their practical implementation) constitutes a highly complex and system-dependent task. To address this challenge, we developed long-range-fit (LRF), an interactive and user-friendly software package designed to automate the generation and fitting of long-range interaction terms for arbitrary molecules in nondegenerate (ground or excited) electronic states. We have derived and implemented all terms up to 15th order, without approximations, via a spherical tensor representation, with symmetry adaptation to all molecular point-group symmetries. The resulting potential energy surface is compatible with most representations of the close interaction region.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

WUS324: Multiscale Full Waveform Inversion Approaching Convergence Improves Waveform Fits While Imaging Seismic Structure of the Western United States

Abstract We report a new model of radially anisotropic crustal and upper mantle structure of the western United States (WUS324) obtained from full waveform inversion of earthquake data. We ran three multiscale inversion stages beyond model WUS256 (Rodgers et al., 2022, https://doi.org/10.1029/2022jb024549 ) allowing them to approach convergence to fit a larger data set to a shorter minimum period of 16 s. WUS324 is based on 324 total iterations from its starting model, significantly more (16 times) than previous studies. Waveform misfit reductions are 66%–70% for both the inversion data and an independent validation data set providing confidence in the predictive power of the model. WUS324 provides much better fits and reveals shear wavespeed, v S , structure of this large region with more detail than previous waveform tomography models. We show representative images demonstrating the resolution of diverse seismic structure across this highly heterogeneous region including oceanic lithosphere, subducting slabs and continental magmatism.

58 GEOSCIENCES↗

DOE OSTI2025

The effects of continuum fitting on Lyman-α forest correlations

Correlations of fluctuations of the flux in Lyman-α forests of high-redshift quasars have been observed by the Baryonic Acoustic Oscillation Spectroscopy Survey (BOSS) and the Dark Energy Spectroscopy Instrument (DESI) survey where they have revealed the effects of baryon acoustic oscillations (BAO). In order to fit the correlation functions to a physical model and thereby constrain cosmological parameters, it is necessary to take into account the effects of fitting the observed spectra to a template about which the fluctuations are measured. In this paper we use mock spectra to test the distortion matrix technique that has been used since the final BOSS data release to appropriately distort the models. We show that while percent-level effects on the derived forest bias parameters may be present, the technique works sufficiently well that the determination of the BAO peak position is not affected at the percent level. We introduce modifications in the technique used by DESI that were not in the original applications and suggest further possibilities for improvements.

Lyman alpha forest↗

DOE OSTI2025

Precision Local Burnup Assessment Through Dynamic Peak Fitting in Atom Probe Tomography for Depleted, Enriched, and Irradiated Metallic and Ceramic Fuels

Abstract Burnup estimation in nuclear fuels is vital for evaluating fuel performance, transportation, and safe fuel storage. Accurate assessments of burnup from service period and spent fuels involve tracking the consumption of fissile isotopes of uranium (U) offering a direct insight into energy changes within the fuels especially for thermal spectrum reactors. In current approach, mass spectroscopic technique in atom probe tomography (APT) is utilized for accurate quantification of U isotopes. Quantification of U peaks in mass spectrum is performed on asymmetric shapes due to delayed signals, known as thermal tails, particularly for poorly conducting samples analyzed in laser mode. In this study, we introduce a novel quantification tool for isotopic analysis from APT datasets by developing a fitting algorithm based on shapes of the peaks. A MATLAB-based dynamic peak fitting toolbox is developed and designed to adapt to various peak shapes, ensuring accurate quantification of U isotopes. The effectiveness of this approach is demonstrated in standard Ni-Cr sample, depleted and enriched U samples, and U-based fuels with different burnup levels. The viability of this approach for isotopic quantification is demonstrated on both metallic and ceramic fuels.

Burnup↗

DOE OSTI2024

Reevaluation of XPS Pt 4f peak fitting: Ti 3s plasmon peak interference and Pt metallic peak asymmetry in Pt@TiO2 system

The structural, electronic, and electrochemical properties of noble metals supported on transition metal oxides, such as Pt nanoparticles (NPs) supported on TiO2 (Pt@TiO2), have been extensively studied for their relevance to energy technologies, including photocatalysis, electrocatalysis, and electrochemical energy conversion. As the need to lower the amount of Pt and other noble metals used in energy conversion systems becomes urgent, it is essential to accurately quantify the loading of these metals and electronic density redistribution between them and their supports. X-ray photoelectron spectroscopy (XPS) is widely used for the identification and quantification of chemical species. In particular, fitting of the Pt 4f spectra for Pt@TiO2 is frequently performed to determine the chemical environment and oxidation state of Pt, which strongly affect the physical behavior and catalytic performance of this system. Here, we show that neglecting contributions due to the Pt surroundings and the asymmetry of the Pt metal peak in the line shape fitting can lead to severe mischaracterization of the oxidation state of Pt. We quantify the effects of background contributions that stem from the TiO2 support and discuss how factoring in the strong asymmetry of Pt 4f doublets, which stems from the shake-up type processes, affects the interpretation of Pt 4f XPS line shape.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

AK112: Full Waveform Inversion Tomography of Alaska Improves Waveform Fits While Imaging Crustal, Mantle, and Slab Structure

We report a full waveform inversion tomography model of Alaska and the surrounding regions, inferring radially anisotropic shear and isotropic compressional wavespeeds by fitting complete waveforms from 120 regional earthquakes. Our multiscale approach inverted time–frequency phase misfits (maximum period of 100 s), starting with a minimum period of 40 s and ending at 20 s in 7 stages and 112 total iterations. The model (AK112) was evaluated by computing the misfits for 36 independent validation events. We find that misfit reductions were large and equal (∼55%) for both the inversion and validation data sets, providing confidence in the model. AK112 also provides much better waveform fits compared to other reported models for the region, including an isotropic version of itself, highlighting the importance of anisotropy. The model resolves known crustal, upper mantle, and slab structure to depths of 100 km with new detail: sedimentary basins in the Alaskan Shelf, Cook Inlet, and Colville basins, among others; discontinuous lithospheric structure across major terrane boundaries; and subducting slab geometry and back‐arc volcanic sources. In addition to tectonic interpretations, the model enables full waveform simulations for long‐period earthquake ground motions and source characterization (e.g., moment tensor and finite‐fault inversion).

Rodgers, Arthur [Lawrence Livermore National Labor↗

DOE OSTI2024

Rejection Sampling with Autodifferentiation -- Case study: Fitting a Hadronization Model

We present an autodifferentiable rejection sampling algorithm termed Rejection Sampling with Autodifferentiation (RSA). In conjunction with reweighting, we show that RSA can be used for efficient parameter estimation and model exploration. Additionally, this approach facilitates the use of unbinned machine-learning-based observables, allowing for more precise, data-driven fits. To showcase these capabilities, we apply an RSA-based parameter fit to a simplified hadronization model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

The track-length extension fitting algorithm for energy measurement of interacting particles in liquid argon TPCs and its performance with ProtoDUNE-SP data

This paper introduces a novel track-length extension fitting algorithm for measuring the kinetic energies of inelastically interacting particles in liquid argon time projection chambers (LArTPCs). The algorithm finds the most probable offset in track length for a track-like object by comparing the measured ionization density as a function of position with a theoretical prediction of the energy loss as a function of the energy, including models of electron recombination and detector response. The algorithm can be used to measure the energies of particles that interact before they stop, such as charged pions that are absorbed by argon nuclei. The algorithm's energy measurement resolutions and fractional biases are presented as functions of particle kinetic energy and number of track hits using samples of stopping secondary charged pions in data collected by the ProtoDUNE-SP detector, and also in a detailed simulation. Additional studies describe the impact of the dE/dx model on energy measurement performance. The method described in this paper to characterize the energy measurement performance can be repeated in any LArTPC experiment using stopping secondary charged pions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Bacterial fitness for plant colonization is influenced by plant growth substrate

Despite advances in our understanding of bacterial plant colonization, the extent to which growth substrate influences the molecular mechanisms enabling bacteria to efficiently colonize plants remains poorly understood. To address this, we used randomly barcoded transposon mutagenesis sequencing (RB-TnSeq) in Paraburkholderia graminis OAS925, an efficient rhizosphere colonizer, and Brachypodium distachyon grown in six different substrates. Of the 382 rhizosphere colonization genes that we identified in OAS925, 348 genes (91.1%) are dependent on the growth substrate evaluated, and 34 genes (8.9%) are shared across all the substrates. Both the core and substrate-dependent colonization genes are from multiple functional categories, demonstrating the multifaceted and major impact that plant growth substrate has on bacterial colonization. The identified colonization genes and their varied importance across plant growth substrates could not be readily explained by differences in root exudate profiles, suggesting that the substrate environment itself plays an outsized role in the ability of a bacterium to colonize the rhizosphere. Our data confirm that bacterial fitness for plant colonization is strongly influenced by plant growth substrate type and highlights the importance of taking this parameter into consideration when engineering bacterial strains for improved host colonization.

Paraburkholderia↗

DOE OSTI2024

Tailoring Microbial Fitness Through Computational Steering and CRISPRi-Driven Robustness Regulation

The widespread application of genetically modified microorganisms (GMMs) across diverse sectors underscores the pressing need for robust strategies to mitigate the risks associated with their potential uncontrolled escape. This study merges computational modeling with CRISPR interference (CRISPRi) to refine GMM metabolic robustness. Utilizing ensemble modeling, we achieved high-throughput in silico screening for enzymatic targets susceptible to expression alterations. Translating these insights, we developed functional CRISPRi, boosting fitness control via multiplexed gene knockdown. Our method, enhanced by an insulator-improved gRNA structure and an off-switch circuit controlling a compact Cas12m, resulted in rationally engineered strains with escape frequencies below National Institutes of Health standards. The effectiveness of this approach was confirmed under various conditions, showcasing its ability for secure GMM management. This research underscores the resilience of microbial metabolism, strategically modifying key nodes to halt growth without provoking significant resistance, thereby enabling more reliable and precise GMM control. A record of this paper's transparent peer review process is included in the supplemental information.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Speeding Up Hartree–Fock in JuliaChem with Density Fitting

In this work, the density fitting (DF) approximation is added to the restricted Hartree–Fock (RHF) implementation in the JuliaChem computational chemistry code. Utilizing a DF algorithm that uses symmetry and integral screening, a significant reduction in time to compute the Fock matrix is achieved. The symmetry and screening DF-RHF techniques were adapted to be performed on graphics processing units (GPUs), which are well suited to perform the matrix multiplications that comprise the bulk of the Fock build time in DF-RHF. The JuliaChem DF-RHF GPU algorithm employs a novel approach that automatically switches between two DF-RHF algorithms depending on the number of basis functions in the calculation. The JuliaChem GPU DF-RHF implementation demonstrates up to 2× speedup for Fock build times compared to the existing best-in-class GPU DF-RHF implementation by operating directly on screened intermediate matrices. Due to the high portability of the Julia language code, the JuliaChem CPU and GPU DF-RHF implementations could be benchmarked on a variety of CPU and GPU architectures from multiple hardware vendors.

Hayes, John J. [Ames Laboratory, and Iowa State Un↗

DOE OSTI2025

Fitness For Service Assessment of a Corroded Heat Exchanger

Within the Fermi National Accelerator complex, there exist various water systems that support accelerator operations. One of these systems is extremely vital to the operation of the machine; that is the cooling system. The cooling system consists of nine relatively large heat exchangers that take untreated pond water and use it to cool the process fluid that further cools machine components. Over the 30 years these heat exchangers have been in operation, they have undergone significant material loss on the channels. This material loss, due to various forms of corrosion such as galvanic and microbiologically influenced corrosion (MIC) and possibly others, has deteriorated more than 80% of the nominal wall thickness of some of the exchangers and placed them in a questionable state. ASME FFS-1 (API 579) has been applied to address the condition of the heat exchangers due to their noncompliance with the governing code, BPVC Sec. VIII Div. 1. The assessments encompassed ASME FFS-1 parts 4: General Metal Loss and 9: Crack Like Flaw using level 1, 2, and 3 analysis techniques based on inspection data obtained by API 510 inspections. Level 1 and 2 assessments were deemed unfit for the corroded regions due to their location relative to a major structural discontinuity (channel to tube-sheet joint), so a level 3 analysis was conducted according to ASME Sec. VIII Div. 2 (design by analysis) rules for pressure vessels. Supplemental information included pond water tests to determine an accurate future corrosion allowance due to lacking inspection history. A leak before break (LBB) route was chosen to evaluate the possibility of leaking prior to the onset of failure. The analysis of one heat exchanger shows that the possibility the channel will develop a pinhole leak over 2.5 more years of operation should not be overlooked, but burst was unlikely from operation. The use of fracture mechanics show, that if a through-wall crack were to develop, it would not propagate further than the channel geometry and cause a leak not greater than 35 GPM. Using ASME Section XI Code Case N-705-1, allowing us to operate with a leak until the next outage given certain operating conditions and developing a leak mitigation procedure, this heat exchanger is deemed fit-for-service.

Humenik, Alex [Fermilab]↗

DOE OSTI2025

Methods in PES-Learn: Direct-Fit Machine Learning of Born–Oppenheimer Potential Energy Surfaces

The release of PES-L EARN version 1.0 as an open-source software package for the automatic construction of machine learning models of semi-global molecular potential energy surfaces (PESs) is presented. Improvements to PES-L EARN ’s interoperability are stressed with new Python API that simplifies workflows for PES construction via interaction with QCSchema input and output infrastructure. In addition, a new machine learning method is introduced to PES-L EARN : kernel ridge regression (KRR). The capabilities of KRR are emphasized with examination of select semi-global PESs. All machine learning methods available in PES-L EARN are benchmarked with benzene and ethanol datasets from the rMD17 database to illustrate PES-L EARN ’s performance ability. Fitting performance and timings are assessed for both systems. Finally, the ability to predict gradients with neural network models is presented and benchmarked with ethanol and benzene. PES-L EARN is an active project and welcomes community suggestions and contributions.

kernel ridge regression↗

DOE OSTI2026

Ab Initio Many Body Quantum Embedding and Local Correlation in Crystalline Materials using Interpolative Separable Density Fitting

We present an efficient implementation of ab initio many-body quantum embedding and local correlation methods for infinite periodic systems through translational symmetry adapted interpolative separable density fitting, an approach which reduces the scaling of the calculations to only linear with the number of k-points. Employing this methodology, we compute correlated ground-state coupled cluster energies within density matrix embedding and local natural orbital correlation frameworks for both weakly and strongly correlated solids, using up to 1000 k-points. By extrapolating the local correlation domains and k-point sampling we further obtain estimates of the full coupled cluster with singles, doubles, and perturbative triples ground-state energies in the thermodynamic limit.

Chemical Physics (physics.chem-ph)↗

DOE OSTI2025

A Diazo Linker Ligand Promotes Flexibility and Induced Fit Binding in a Microporous Copper Coordination Network

Abstract Flexible organic linkers represent an intuitive and effective strategy to design flexible metal–organic materials. We report herein a systematic study concerning the effect of varying the central bond of mixed pyridyl‐benzoate linkers, L, upon the flexibility of three isostructuralkddtopology microporous coordination networks (CNs) of formula ML 2 :X‐kdd‐1‐Cu,1= L = (E)‐4‐(pyridin‐4‐yldiazenyl)benzoate;X‐kdd‐2‐Cu,2= L = (E)‐4‐(2‐(pyridin‐4‐yl)vinyl)benzoate; the previously reportedX‐kdd‐3‐Cu,3= L = 4‐(pyridin‐4‐ylethynyl)benzoate. As revealed by single crystal x‐ray diffraction (SCXRD) and gas sorption studies,X‐kdd‐1‐Cu, exhibited gate‐opening during CO 2 and hydrocarbon (C2 and C8) sorption experiments whereas the other two CNs did not. Insight into these phase transformations was gained from in situ variable‐pressure and variable temperature powder X‐ray diffraction (PXRD), SCXRD, and modeling. Rotation of ligand1around the diazo bond, torsion angle changes between phenyl and carboxylate moieties, and deformation of the Cu‐based rod building blocks enabled activatedX‐kdd‐1‐Cuto form new phases with C8 isomers and CH 2 Cl 2 , CH 2 Cl 2 inducing contraction of the activated phase. Computational studies suggest that1enables flexibility thanks to its lower barrier of deformation versus2or3. This study teaches that diazo moieties could offer a general strategy to enhance the flexibility of CNs.

Chemistry↗

DOE OSTI2025

The efficacy and ecological impact of mercury sorbents on the physiology and reproductive fitness of Daphnia magna

Environmental mercury (Hg) contamination threatens ecosystems due to its bioaccumulation and toxicity. Effective and sustainable remediation strategies are essential, with carbon-based sorbents like biochar (BC) and activated carbon (AC) gaining attention for their high adsorption capacity and cost-effectiveness. However, their ecological impacts remain poorly understood. This study evaluates the Hg removal efficacy and ecological effects of three sorbents—BC, granular AC (GAC), and AC fiber (ACF)—in a flow-through column system with and without Hg additions. We tested Hg removal at two concentrations (1 and 4 µg/L Hg) and assessed chronic exposure effects on a sentinel and sensitive freshwater organism, Daphnia magna, over 30 days of exposure to the columns’ effluent. GAC removed 100 % of Hg, while BC and ACF achieved 99 % removal. The ACF + 4 µg/L Hg effluent induced 70 % lethality in D. magna after nearly three weeks of exposure, while the GAC effluent significantly reduced fecundity, even in the absence of Hg exposure. In contrast, the BC effluent enhanced reproductive output, likely due to inputs of carbon and nitrogen in the effluent. These findings highlight the need to balance Hg removal efficacy with ecological safety, emphasizing the importance of considering both remediation effectiveness and potential environmental impacts.

Activated carbon↗

DOE OSTI2025

Simulations of Heat Transfer Using Tight-Fitting Twisted Tape Inserts for First Wall Cooling in Molten Salt Breeder Blankets

One of the major components in fusion energy systems is the fusion blanket, which has a vacuum vessel to contain the plasma. As part of the fusion blanket/vacuum vessel, the first wall and plasma-facing components require sufficient cooling to prevent material degradation during operation from the superheated plasma. Most fusion blanket concepts involve first wall and divertor coolant channels with heat transfer enhancements (HTEs) that are intended to withstand the incident high heat fluxes of 1 to 5 MW/m 2 . Twisted tape inserts are a proposed HTE that have been investigated previously for first wall cooling and monoblock divertor cooling channels and in other nonfusion heat transfer components. By inserting twisted tapes into straight pipes, the amount of turbulence in the system can be increased at lower Reynolds numbers by swirling the flow. This results in better heat transfer characteristics with marginal increases in frictional pressure losses. In particular, simulations of high-Prandtl-number fluids such as the proposed molten salt FLiBe in twisted tapes, which is prototypic to liquid immersion blankets, have not been previously explored. Here, in this study, we simulate various Prandtl numbers in pipes with twisted tape inserts using large eddy simulations to determine the effects of increasing Prandtl numbers on heat transfer performance. The quantities of particular interest are the Nusselt number and the friction factor, which were recovered using data reduction techniques to determine impacts on heat transfer and pressure losses. This work serves as a starting point for determining the feasibility of twisted tape inserts for liquid immersion blanket concepts.

LES↗