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At least 253 records · Page 14

Increasing Iridium Oxide Activity for the Oxygen Evolution Reaction with Hafnium Modification

Synthesis and implementation of highly active, stable, and affordable electrocatalysts for the oxygen evolution reaction (OER) is a major challenge in developing energy efficient and economically viable energy conversion devices such as electrolyzers, rechargeable metal-air batteries, and regenerative fuel cells. The current benchmark electrocatalyst for OER is based on iridium oxide (IrO x ) due to its superior performance and excellent stability. However, large scale applications using IrO x are impractical due to its low abundance and high cost. In this work, we report a highly active hafnium-modified iridium oxide (IrHf x O y ) electrocatalyst for OER. The IrHf x O y electrocatalyst demonstrated ten times higher activity in alkaline conditions (pH = 11) and four times higher activity in acid conditions (pH = 1) than a IrO x electrocatalyst. The highest intrinsic mass activity of the IrHf x O y catalyst in acid conditions was calculated as 6950 A gIrO x -1 at an overpotential (η) of 0.3 V. Combined studies utilizing operando surface enhanced Raman spectroscopy (SERS) and DFT calculations revealed that the active sites for OER are the Ir-O species for both IrO x and IrHf x O y catalysts. The presence of Hf sites leads to more negative charge states on nearby O sites, and shortening the bond lengths of Ir-O, and lowering free energies for OER intermediates to accelerate the OER process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

EIC Hadron Beamline Vacuum Studies

Ninety percent of the EIC hadron ring vacuum chamber consists of cold-bore sections running through and interconnecting 4.55 K RHIC superconducting (SC) magnets. The EIC operating specification requires shorter bunches and 3x higher intensity beams which are not appropriate for the present RHIC stainless steel cold-bore beam tube. The intensity and emittance of the hadron beams will degrade due to interactions with residual gas or vacuum instabilities arising from the expected resistive-wall (RW) heating, electron clouds, and beam-induced desorption mechanisms. Without strategies to limit RW heating, major cryogenic system modifications are needed to prevent SC magnet quenches. The SC magnet cold-bore beam tubes will be equipped with a high RRR copper-clad stainless steel screen to significantly reduce RW heating and so the effect on the SC magnet cryogenic heat load and temperature. A thin amorphous carbon film applied to the beam-facing copper surface will suppress electron cloud formation. This paper discusses the vacuum requirements imposed by the EIC hadron beams and the plans to achieve the necessary vacuum and thermal stability that ensure acceptable beam quality and lifetime.

43 PARTICLE ACCELERATORS↗

Impact of New Physics on the JUNO-Long-Baseline Synergy in Neutrino Mass Ordering Determination

The determination of the neutrino mass ordering is one of the flagship goals in particle physics. A well-known and powerful synergy emerges when combining high-precision measurements of the effective atmospheric mass-squared splitting from electron antineutrino disappearance in reactor experiments with that from muon (anti)neutrino disappearance in accelerator-based long-baseline experiments. To fully exploit this synergy, percent-level precision in the atmospheric mass splitting is required-a target that JUNO is expected to achieve within a few months of data taking. This motivated the formulation of a mass ordering sum rule for neutrino disappearance channels, which shows that by combining data from T2K and NOvA with JUNO after one year of operation, the neutrino mass ordering can be determined at the $3σ$ confidence level. Since JUNO has recently started taking data, it is timely to ask whether this sum rule remains robust in the presence of new physics. We identify the necessary conditions for new physics to affect the sum rule and demonstrate that, in some cases, such effects could lead to an incorrect inference of the mass ordering. As concrete examples, we consider Scalar Non-Standard Interactions (SNSI) and neutrinos coupled to an ultralight scalar field. We find that, for SNSI, current constraints render any modification of the sum rule negligible, whereas in the latter case, the inference of the ordering requires caution. Nevertheless, these effects can be disentangled, illustrating how the sum rule can also be used to search for new physics.

Alves, Gustavo F.S. [Fermilab; Northwestern U.; Sa↗

Electron Linear Accelerator Additive Manufacturing

Superconducting electron linear accelerators open up new opportunities for advanced materials processing. High energy electrons penetrate deeper within materials, increase the processing depth and rate and enables production of far-from-equilibrium materials and selective processing within a material surface and subsurface. With support from the Office of Naval Research, NASA, and DoE, Mainstream Engineering commissioned a superconducting linear electron accelerator to investigate advanced materials processing and additive manufacturing. The goal of Mainstream's Electron Beam Enabled Advanced Manufacturing (EBEAM) center is to develop unique, far-from-equilibrium materials and alleviate significant technological deficiencies. We will present results of irradiating various metals and their unique material properties. Monte Carlo simulations electron beam and sample interaction were used to optimize the processing parameters and study far-from-equilibrium processing conditions. Applications include stainless steel additive manufacturing for small modular nuclear reactors and dissimilar metal bonding of corrosion-resistant cladding for next-generation molten salt reactors.

36 MATERIALS SCIENCE↗

In Situ High-Temperature Ultrafast Electron Diffraction through Integrated Furnace and MEMS Platforms

Temperature fundamentally governs phase stability, defect evolution, and transport behavior in materials. Despite its central role, direct measurements of structural evolution at elevated temperatures on ultrafast timescales have remained limited. Here, we report the design, integration, and validation of 2 complementary in situ heating platforms that substantially extend the thermal operating range of ultrafast electron diffraction (UED). A compact furnace-type heating stage enables stable diffraction measurements from room temperature to 800 K with ±0.1 K stability under ultrahigh vacuum, achieved through multi-sensor feedback control, dual air-cooling channels, and a thermally isolated motion stage. In parallel, a microelectromechanical system (MEMS)-based heating platform provides rapid thermal response and access to extreme temperatures ≥1,373 K with ±0.1 K stability over hundreds-micrometer regions while supporting simultaneous electrical biasing for electrothermal coupling studies. Absolute temperature calibration is established using diffraction-based thermometry via aluminum lattice expansion and independently validated through in situ melting of bismuth thin films. UED measurements further reveal pronounced temperature-dependent nonequilibrium lattice dynamics in bismuth, including modifications to electron–phonon coupling and Debye–Waller behavior, as well as enhanced ultrafast diffuse scattering in aluminum at elevated temperatures. Together, these developments establish a practical framework for quantitative, time-resolved studies of temperature-driven kinetics and nonequilibrium structural dynamics under extreme thermal environments.

Bai, Qianqian [Chinese Academy of Sciences (CAS), ↗

Structure/Interface Coupling Effect for High-Voltage LiCoO 2 Cathodes

LiCoO 2 (LCO) is widely applied in today's rechargeable battery markets for consumer electronic devices. However, LCO operations at high voltage are hindered by accelerated structure degradation and electrode/electrolyte interface decomposition. To overcome these challenges, co-modified LCO (defined as CB-Mg-LCO) that couples pillar structures with interface shielding are successfully synthesized for achieving high-energy-density and structurally stable cathode material. Benefitting from the "Mg-pillar" effect, irreversible phase transitions are significantly suppressed and highly reversible Li + shuttling is enabled. Interestingly, bonding effects between the interfacial lattice oxygen of CB-Mg-LCO and amorphous Co x B y coating layer are found to elevate the formation energy of oxygen vacancies, thereby considerably mitigating lattice oxygen loss and inhibiting irreversible phase transformation. Meanwhile, interface shielding effects are also beneficial for mitigating parasitic electrode/electrolyte reactions, subsequent Co dissolution, and ultimately enable a robust electrode/electrolyte interface. As a result, the as-designed CB-Mg-LCO cathode achieves a high capacity and excellent cycle stability with 94.6% capacity retention at an extremely high cut-off voltage of 4.6 V. We report these findings provide new insights for cathode material modification methods, which serves to guide future cathode material design.

25 ENERGY STORAGE↗

National User Resource for Biological Accelerator Mass Spectrometry (Final Report)

The National User Resource for Biological Accelerator Mass Spectrometry (User Resource) will provide isotopic analysis (primarily radiocarbon or 14C) by accelerator mass spectrometry (AMS) for NIH- funded researchers across the United States and will be the only User Resource of its type in the United States. The User Resource will provide measurement capability and expertise to a research community that requires highly sensitive, quantitative isotope analyses. Since commissioning a new accelerator mass spectrometer in June 2014, we have measured over 4000 samples a year for collaborators and service users. The User Resource will enable us to continue to meet these research needs, as well as provide for new users whose research programs would benefit from AMS as a measurement tool. The User Resource’s forte will be ultra-high sensitivity quantitation of radiocarbon and selected other radioisotopes for research studies where isotopes are required. Radioisotope labeling studies have been and will continue to be an important tool for addressing many complex biomedical science problems. AMS is a specialized and unique type of mass spectrometry that provides absolute quantitation of radiocarbon and other relevant radioisotopes with extreme sensitivity, having limits of detection in real samples on the order of a few attomol/mg of sample at measurement precisions of ~3%. It is the only instrumental method capable of quantifying radioisotope-labeled agents routinely in real-world samples with such precision and sensitivity. The sensitivity of AMS allows for the quantification of radiolabeled metabolites in extremely complex matrices of cells and organisms at very low concentrations and in small samples. AMS allows studies to be conducted without perturbing metabolism leading to more relevant quantification of metabolic rates and pathways. In addition, it enables quantification of pharmacokinetic and metabolic properties of toxicants at environmentally relevant concentrations in model systems as well as the ability to quantify pharmacokinetics and other molecular endpoints directly in humans. Such quantitative assessments can 1) improve risk assessment for toxicants, 2) address safety and efficacy considerations for therapeutic entities, 3) deepen understanding of xenobiotic and intermediary metabolism, 4) help understand the interactions between critical molecular pathways, and 5) improve efforts to model and predict various metabolic and biological states. These capabilities have been applied in a number of areas including research in carcinogenesis, toxicology, nutrition, pharmacology/drug development and basic biological science. As a NIGMS National Resource the National User Resource for Biological Accelerator Mass Spectrometry will help NIH funded scientists achieve a deeper understanding of the etiology of human health concerns by (1) enabling the quantification of pharmacokinetics and other molecular endpoints directly in humans; (2) offering the ability to conduct quantitative studies using biologics such as proteins or lipids, and thereby reducing the amount of radioisotope usage in biomedical labs; and (3) enabling more relevant studies of metabolic pathways in health and disease through the use of much lower, more biologically-relevant, concentrations of metabolic substrates in cells and intact organisms. Such studies support NIGMS’s basic biomedical research areas that contribute to the understanding of fundamental cellular and physiological principles and enable research supported by the Biophysics, Biomedical Technology, and Computational Biosciences (BBCB); Genetics and Molecular, Cellular, and Developmental Biology (GMCDB); Pharmacology, Physiology, Biological Chemistry (PPBC) and Training, Workforce Development, and Diversity (TWD) Divisions. Over the next five years, our goals are to: 1. Improve the efficiency of operation for AMS measurements through installation of new interfaces to our AMS systems, technical modifications to improve gas accepting ion source efficiency and upgrading our data analysis software for improved ease of use and data reporting. 2. Increase the accessibility and visibility of ultra-sensitive 14C measurements for the biomedical research community by training of new investigators and expanding our national user base. 3. Provide high throughput, ultra-sensitive 14C analysis for the NIGMS and NIH user community.

47 OTHER INSTRUMENTATION↗

Assessment of MQXF Quench Heater Insulation Strength and Test of Modified Design

The HL-LHC interaction region magnet triplets (Q1,Q2, and Q3) will be composed of superconducting Nb 3 Sn quadrupoles. The MQXF quadrupole protection system is based on CLIQ (Coupling-Loss Induced Quench system) and outer layer quench heaters. Furthermore, this paper reports a summary of quench heaters to coil high voltage tests performed on MQXF short and long coils in air after fabrication, and in air and He gas after magnet training. Breakdown voltage values demonstrate good margin with respect to the Electrical design criteria for the HL-LHC inner triplet mag-nets. A modification in the quench heater installation-with an extra layer of fiber glass between the coil and the quench heater trace-has been proposed and tested in a mirror magnet to further increase electrical margins. Results demonstrated improvements of high voltage margin at the expense of a clear increase of hot spot temperature.The baseline heater to coil insulation was assessed to be able to guarantee safe operation for the Nb 3 Sn quadrupole magnets for the interaction regions of HL-LHC.

43 PARTICLE ACCELERATORS↗

Record of Decision: H - LEBT Design Modifications

The LAMP Conceptual Design (LCD) is described in the LAMP Conceptual Design Report. The proposed new configuration of the LAMP H - LEBT encompasses multiple changes to the LCD. The new configuration makes use of a single H - source to supply beam to all LANSCE user stations except IPF; this eliminates one of the H - sources in the LCD, and the associated pulsed merger magnet the use of two such sources required. The source current from the sole H - source is gated on a macropulse-by-macropulse basis using techniques demonstrated at SNS (Spallation Neutron Source), specifically, changes to the RF plasma drive power. A pulsed electrode system is used to match the beam into the LEBT transport line, variable on a macropulse-by-macropulse basis to match the source beam current.

43 PARTICLE ACCELERATORS↗

The price of a large electron Yukawa modification

The theoretical implications of an electron Yukawa modification are considered in the context of a possible Higgs pole run at FCC-ee, aimed at bounding this coupling. We start from an effective field theory viewpoint, considering the impact of renormalisation group effects on related observables and also examining assumptions on the broader UV flavour structure. We then give an overview of the landscape of simplified models, investigating phenomenological constraints arising at higher orders. A short discussion of fine-tuning is also included.

Anomalous Higgs Couplings↗

Ultrafast renormalization of the magnetic continuum in the proximal Kitaev quantum spin liquid H 3 LiIr 2 O 6 by tr-RIXS [Invited]

We present the first circularly polarized non-resonant pump time-resolved resonant inelastic X-ray scattering (tr-RIXS) experiment in H 3 LiIr 2 O 6 , an iridium-based Kitaev system. Our calculations and experimental results are consistent with the modification of the low-energy magnetic excitations in H 3 LiIr 2 O 6 only during illumination by the laser pulse. We discuss these results in a cooperative framework between the Floquet engineering of the exchange interactions and the dynamic renormalization of electron-electron correlations. However, the penetration length mismatch between the X-ray probe and laser pump and the intrinsic complexity of Kitaev magnets prevents us from unequivocally extracting towards which ground state H 3 LiIr 2 O 6 is driven. We outline possible solutions to these challenges for light-driven stabilization and observation of the Kitaev quantum spin liquid limit by RIXS.

Kim, Jungho [Argonne National Laboratory (ANL), Ar↗

Resonant Slow Extraction Simulation using Bmad

Simulations of slow extraction and transport of charged particle beams from synchrotrons requires careful modeling and experimentation. In this paper, we outline how the Bmad modeling software was adapted and developed to run third-integer resonant extraction simulations of beams at Brookhaven National Laboratory’s Booster synchrotron. Further, we show experimental comparisons of the slowly extracted beams transferred to the NASA Space Radiation Laboratory (NSRL) transport line. In this process, beam passes through a stripping foil element at the extraction point, which, along with stripping remaining electrons from the beam ions, acts as a scatterer to modify the phase space, moving to a more Gaussian-like distribution. This modification to the beam helps generate a uniform beam at the beam line’s target location; which is necessary for the variety of experiments performed at the facility. During this work, beam energy loss and multiple scattering by foil routines were built in conjunction with the Bmad code developers and are now integrated into the software.

43 PARTICLE ACCELERATORS↗

Development of the IES Plug-and-Play Framework

This report discusses the status of the flexible plug-and-play framework development currently ongoing that aims to integrate Modelica/Dymola with the Risk Analysis and Virtual ENvironment (RAVEN) software in terms of both Functional Mock-Up Interface (FMI)/Functional Mock-Up Unit (FMU) construction and repository structures that aim to ease the sharing and simulation of complex dynamic models. This report aims to provide an overview of all the performed activities resolving around the deployment of methods, software infrastructures, guidelines and workflow for the construction and usage of models, encapsulated using the FMI/FMU protocols and standards. In particular, the report is organized in three main macro-subjects, which are connected to each other: - FMI/FMU adaptors for modelica models - HYBRID repository new structure and open-source deployment - RAVEN FMI/FMU exporting capabilities and Artificial Intelligence (AI)-based analysis acceleration. The first part of the report discusses the FMI/FMU adaptors that have been created within the HYBRID repository to allow users to quickly export models, such as FMUs. Several examples are shown that highlight the step-by-step process of converting an existing Modelica model into an FMU for use within the Dymola platform. Simulation results demonstrate that, while minor differences may occur, the overall control, trends, and solution integrity are maintained between standard Modelica simulation and FMU simulation results. However, it is worth noting that, for small systems, the FMU results have a slower simulation time than the Modelica only simulation. Using this process, a company can provide models that contain proprietary information to entities without disclosing any of the information about the model that could be considered business sensitive. Such an ability would allow institutions to bypass the necessity of “whitewashing” data. In the second part of the report, the new structure of the HYBRID repository is discussed with a major focus on the series of updates that has been completed. These updates include the addition of Modelica system-level regression tests and software quality assurance documentation that ensure that modifications to the Modelica models do not alter system-level model results. The third and final part of the report aims to report the work that has been performed for the deployment of methods and workflows for the construction of RAVEN AI-based models compliant with the FMI/FMU standard. Such development represents the key for the deployment of the concept of “Flexible ecosystem” since it allows for the replacement of high-fidelity modelica models (or any other FMI/FMU compliant model) with RAVEN generated AI surrogate models. Overall, extensive work has been completed on developing FMUs and FMIs from existing models, understanding the requirements and limitations of FMUs, and open-sourcing the HYBRID repository with an integrated regression system.

42 ENGINEERING↗

Development of the IES Plug-and-Play Framework

This report discusses the status of the flexible plug-and-play framework development currently ongoing that aims to integrate Modelica/Dymola with the Risk Analysis and Virtual ENvironment (RAVEN) software in terms of both Functional Mock-Up Interface (FMI)/Functional Mock-Up Unit (FMU) construction and repository structures that aim to ease the sharing and simulation of complex dynamic models. This report aims to provide an overview of all the performed activities resolving around the deployment of methods, software infrastructures, guidelines and workflow for the construction and usage of models, encapsulated using the FMI/FMU protocols and standards. In particular, the report is organized in three main macro-subjects, which are connected to each other: - FMI/FMU adaptors for modelica models - HYBRID repository new structure and open-source deployment - RAVEN FMI/FMU exporting capabilities and Artificial Intelligence (AI)-based analysis acceleration. The first part of the report discusses the FMI/FMU adaptors that have been created within the HYBRID repository to allow users to quickly export models, such as FMUs. Several examples are shown that highlight the step-by-step process of converting an existing Modelica model into an FMU for use within the Dymola platform. Simulation results demonstrate that, while minor differences may occur, the overall control, trends, and solution integrity are maintained between standard Modelica simulation and FMU simulation results. However, it is worth noting that, for small systems, the FMU results have a slower simulation time than the Modelica only simulation. Using this process, a company can provide models that contain proprietary information to entities without disclosing any of the information about the model that could be considered business sensitive. Such an ability would allow institutions to bypass the necessity of “whitewashing” data. In the second part of the report, the new structure of the HYBRID repository is discussed with a major focus on the series of updates that has been completed. These updates include the addition of Modelica system-level regression tests and software quality assurance documentation that ensure that modifications to the Modelica models do not alter system-level model results. The third and final part of the report aims to report the work that has been performed for the deployment of methods and workflows for the construction of RAVEN AI-based models compliant with the FMI/FMU standard. Such development represents the key for the deployment of the concept of “Flexible ecosystem” since it allows for the replacement of high-fidelity modelica models (or any other FMI/FMU compliant model) with RAVEN generated AI surrogate models. Overall, extensive work has been completed on developing FMUs and FMIs from existing models, understanding the requirements and limitations of FMUs, and open-sourcing the HYBRID repository with an integrated regression system.

14 SOLAR ENERGY↗

A novel, steerable, low-energy proton source for detector characterization

We report on the conversion of the Manitoba II mass spectrometer into a versatile low-energy proton beam facility. This infrastructure is adaptable to any detector-under-test (DUT), and has proven itself effective with the characterization of silicon detectors used in subatomic beyond-the-Standard-Model (BSM) searches, namely the Nab experiment. A pencil beam of mono-energetic protons can be produced in a range from 25 keV to 35 keV, achieving a beam current of ~1 x 10 -18 A. Electrostatic steering plates were constructed to direct the Gaussian-profile proton beam over a 117 mm diameter area-of-interest with full-width at half-maxima (FWHM) ranging from 0.6 mm to 1.26 mm. This work discusses the modifications and subsequent tests to confirm the beam specifications met the demands of the aforementioned detectors.

Fundamental neutron physics↗

Advanced Simulation and Computing: ASC FY24 Implementation Plan

The DOE National Nuclear Security Administration (NNSA) Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, security, and reliability of the U.S. nuclear stockpile. The SSP incorporates nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. The suite of data analyzed comes from activities including previous nuclear tests, stockpile surveillance, experimental research, and development and engineering programs. This integrated national program requires the continued use of experimental facilities and the computational capabilities to support the SSP missions. These component parts, in addition to an appropriately scaled production capability, enable NNSA to support stockpile requirements. The ultimate goal of the SSP, and thus of the Advanced Simulation and Computing (ASC) program, is to ensure that the U.S. maintains a safe, secure, and effective strategic deterrent. The ASC program is a cornerstone of the SSP, providing simulation capabilities and computational resources to support the annual stockpile assessment and certification process, study advanced nuclear weapons design and manufacturing processes, analyze accident scenarios and weapons aging, and provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This work requires a balance of resources, including technical staff, hardware, simulation software, and computer science solutions. The ASC program focuses on increasing the predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The Program continues to improve its unique tools for understanding and solving progressively more difficult stockpile problems (sufficient resolution, dimensionality, and scientific details), and quantifying critical margins and uncertainties. Resolving each issue requires increasingly difficult analyses because the aging process has progressively moved the stockpile further from the original test base. While the focus remains on the U.S. nuclear weapons program, where possible, the Program also enables the use of high-performance computing (HPC) and simulation tools to address broader national security needs, such as foreign nuclear weapon assessments and nuclear counterterrorism. The 2022 Nuclear Posture Review (NPR) calls for NNSA to “deliver a modern, adaptive nuclear security enterprise based on an integrated strategy for risk management, production-based resilience, science and technology innovation, and workforce initiatives.” Furthermore, “NNSA will establish a Science and Technology Innovation Initiative to accelerate the integration of science and technology (S&T) throughout its activities.” Executing this strategy necessitates the continued emphasis on developing and sustaining high-quality scientific and engineering staff, as well as supporting computational and experimental capabilities. These components constitute the foundation of the nuclear weapons program. The continued success of the SSP and LEPs is predicated upon the ability to credibly certify the stockpile, without a return to underground nuclear tests (UGTs). Shortly after the nuclear test moratorium entered into force in 1992, the Accelerated Strategic Computing Initiative (ASCI) was established to provide an extensive simulation capability to underpin stockpile certification. While computing and simulation have always been essential to the success of the nuclear weapons program, the program goal of ASCI was to execute NNSA’s vision of using these tools in support of the stockpile stewardship mission. The ASCI program was essential to the successful demonstration of the SSP, providing critical nuclear weapons simulation and modeling capabilities. ASCI officially evolved into the ASC program in fiscal year (FY) 2005, but the mission remains essentially the same: provide the simulation and computational capabilities that underpin the ability to maintain a safe, secure, effective nuclear weapon stockpile, without returning to underground nuclear testing. The capabilities that the ASC program provides at the national laboratories play a vital role in the nuclear security enterprise and are necessary for fulfilling the stockpile stewardship and life extension requirements outlined for NNSA. The Program develops modern simulation tools that provide insights into stockpile aging issues, provide the computational and simulation tools that enable designers and analysts to certify the current stockpile and life-extended nuclear weapons, and inform the decision-making process when any modifications in nuclear warheads or the associated manufacturing processes are deemed necessary. Furthermore, ASC is enhancing the predictive simulation capabilities that are essential to evaluate weapons effects, design experiments, and ensure test readiness. The ASC program continues to improve its unique tools to solve stockpile problems— with a focus on sufficient resolution, dimensionality, and scientific detail—to enable Quantification of Margins and Uncertainties (QMU) and to resolve the increasingly difficult analyses needed for stockpile stewardship. The needs of the Stockpile Management and Production Modernization programs (formerly Directed Stockpile Work) also drive the requirements for simulation and computational resources. These requirements include planned LEPs, stockpile support activities, and mitigation efforts against the potential for technical surprise. All of the weapons within the current stockpile are in some stage of the life extension process. The simulation and computational capabilities are crucial for successful execution of these life extensions and for ensuring NNSA can certify these life-extended weapons without conducting a UGT.

97 MATHEMATICS AND COMPUTING↗

Interpretable machine learning-guided design of Fe-based soft magnetic alloys

Here, we present a machine learning (ML) guided approach to predict saturation magnetization (𝑀 S ) and coercivity (𝐻 C ) in Fe-rich soft magnetic alloys, particularly Fe-Si-B systems. ML models trained on experimental data reveal that increasing Si and B content reduces 𝑀 S from 1.81 T (DFT ≈ 2.04 T) to ≈1.54 T (DFT ≈ 1.56T) in Fe-Si-B, which is attributed to decreased magnetic density and structural modifications. Experimental validation of ML predicted magnetic saturation on Fe-1Si-1B (2.09 T), Fe-5Si-5B (2.01 T), and Fe-10Si-10B (1.54 T) alloy compositions further supports our findings. These trends are consistent with density functional theory predictions, which link increased electronic disorder and band broadening to lower 𝑀 S values. Experimental validation on selected alloys confirms the predictive accuracy of the ML model, with good agreement across compositions. Beyond predictive accuracy, detailed uncertainty quantification and model interpretability including through feature importance and partial dependence analysis reveal that 𝑀 S is governed by a nonlinear interplay between Fe content and early transition metal ratios, while 𝐻 C is more sensitive to processing conditions such as ribbon thickness and thermal treatment windows. The ML framework was further applied to Fe-Si-B/Cr/Cu/Zr/Nb alloys in a pseudoquaternary compositional space, which shows comparable magnetic properties to NANOMET (Fe 84.8 ⁢Si 0.5 ⁢B 9.4 ⁢Cu 0.8⁢ P 3.5 ⁢C 1 ), FINEMET (Fe 73.5 ⁢Si 13.5 ⁢B 9 Cu 1 ⁢Nb 3 ), NANOPERM (Fe 88 ⁢Zr 7⁢ B 4 ⁢Cu 1 ), and HITPERM (Fe 44 ⁢Co 44 ⁢Zr 7⁢ B 4 ⁢Cu 1 . Our findings demonstrate the potential of the ML framework for accelerated search of high-performance soft magnetic materials.

density functional theory↗

Systems Engineering of Rhodococcus opacus to Enable Production of Drop-in Fuels from Lignocellulose

Production of drop-in fuels from lignocellulose using Rhodococcus opacus PD630 (hereafter R. opacus) is a challenging goal. During the grant period we have pushed the field forward significantly in several areas of research. Towards the end goal of accelerating the adoption of R. opacus in biofuel production, during the grant period we have expanded the phenotypic characterization of R. opacus grown in single aromatic (model lignocellulosic) compounds or their mixtures, modeling the growth conditions in lignocellulosic biomass. Harnessing the power of adaptive evolution, we produced evolved R. opacus isolates with superior lignin valorization capabilities and identified differentially expressed genes and pathways after adaptation. We used next generation multi-omic techniques such as genomic, transcriptomic, and metabolomic analyses, to identify the catabolic pathways used by R. opacus to degrade aromatic compounds and funnel these degradation products into central metabolism, as well as the aromatic transport genes required for increased tolerance and utilization. Taking this information one step further, we identified endogenous transcription factors and regulatory mechanisms important for degradation of five model aromatic compounds. To accurately estimate R. opacus growth and consumption on model lignin compounds we pioneered the use of novel extraction procedures prior to GC-MS analysis. Alongside 13 C-metabolic flux analysis, we have elucidated the metabolic routes preferred by Rhodococcus opacus during aromatic compound degradation. Finally, we used in tandem lipidomics and high-resolution mass spectrometry to identify the modulation of mycolic acids and phospholipid membrane composition modification as a strategy for aromatic tolerance in R. opacus. Being a non-model organism, R. opacus lacks the breadth of tools and technical foundation which drive biofuel research in more well-understood microbes such as Escherichia coli. To reduce this burden for use, we designed and produced new tools for genomic manipulation and engineering in R. opacus. These engineering breakthroughs support efficient genomic editing, enabling gene overexpression, repression, and genetic alteration. Using these tools, we have generated synthetically engineered strains with increased lipogenesis and growth, both positive traits required for increased lignin valorization. Optimizing engineered strains for biofuel production from lignocellulose requires extremely sophisticated synthetic rewiring of metabolism. To facilitate systems-level reorganization of metabolism in R. opacus, we created a genome-scale model that accurately predicts metabolic flux and growth rates on the aromatic compound phenol. Lignin requires extensive pre-treatment before biological degradation by R. opacus. Towards an eventual goal of degrading real-world lignin, we developed new depolymerization processes to generate lignin breakdown products (LBP). We optimized LBP storage and composition analysis techniques, enabling accurate prediction of specific LBP compound integration into cell wall components. Overall, through the work funded by this grant we generated 20 manuscripts (17 published, 3 in review/preparation), methods for increased accuracy in metabolomics of aromatic compounds, multiple genetic tools for altering the R. opacus genome, genome scale models for predicting flux through metabolic pathways, as well as multi-omic data for community use. The work funded by this grant has increased the knowledge of aromatic degradation in bacteria and advanced our efforts to optimize R. opacus for lignin valorization.

09 BIOMASS FUELS↗