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At least 1,045 records · Page 58

Bacterial Membranes Are More Perturbed by the Asymmetric Versus Symmetric Loading of Amphiphilic Molecules

Characterizing the biophysical properties of bacterial membranes is critical for understanding the protective nature of the microbial envelope, interaction of biological membranes with exogenous materials, and designing new antibacterial agents. Presented here are molecular dynamics simulations for two cationic quaternary ammonium compounds, and the anionic and nonionic form of a fatty acid molecule interacting with a Staphylococcus aureus bacterial inner membrane. The effect of the tested materials on the properties of the model membranes are evaluated with respect to various structural properties such as the lateral pressure profile, lipid tail order parameter, and the bilayer’s electrostatic potential. Conducting asymmetric loading of molecules in only one leaflet, it was observed that anionic and cationic amphiphiles have a large impact on the Staphylococcus aureus membrane’s electrostatic potential and lateral pressure profile as compared to a symmetric distribution. Nonintuitively, we find that the cationic and anionic molecules induce a similar change in the electrostatic potential, which points to the complexity of membrane interfaces, and how asymmetry can induce biophysical consequences. Finally, we link changes in membrane structure to the rate of electroporation for the membranes, and again find a crucial impact of introducing asymmetry to the system. Understanding these physical mechanisms provides critical insights and viable pathways for the rational design of membrane-active molecules, where controlling the localization is key.

59 BASIC BIOLOGICAL SCIENCES↗

Fabrication and Testing of Complex Silicon Carbide Composite Structures

The ability to fabricate larger complex silicon carbide composites is an enabling technology for advanced reactors. Processing techniques to make complex SiC/SiC structures must be versatile enough to facilitate fabrication of both very large components (>1 m), as well as very small feature sizes (<1 mm), minimize the amount of machining required to complete the final part, and must also provide composite material with similar performance to bulk properties previously established for planar SiC/SiC composite material. This paper presents results on fabrication of complex silicon carbide structures and targeted testing aimed specifically at understanding how complex features impact composite performance. Silicon carbide (SiC) and silicon carbide matrix, silicon carbide fiber-reinforced composites (SiC/SiC) are a strong candidate for cladding and core structure used in advanced reactor concepts such as General Atomics' (GA) Energy Multiplier Module (EM{sup 2}) as well as accident tolerant fuel (ATF) in LWRs. SiC retains its strength up to very high temperatures, is stable under irradiation, and shows favorable neutronics and oxidation resistance compared to alloy alternatives. However, unlike metals, SiC cannot be easily machined, formed or welded to make the more complex core components needed to fully realize the benefits of advanced high temperature reactors. TEP processing provides an appealing route to achieving SiC/SiC composite structures with enhanced feature complexity. This is a critical development in the maturation of SiC/SiC for in-core structural materials in advanced reactors. This processing route provides an avenue to make large, dense, complex structures. Experiments have shown retention of strength and pseudo-ductility with hole spacing as small as 4 mm with potential for still smaller feature spacing. The results indicate that feature spacing is not limited by processing effects, but instead by the fiber architecture. The lower limit of feature spacing will likely have implications on potential core loading limits in advanced nuclear reactors utilizing SiC/SiC. (authors)

36 MATERIALS SCIENCE↗

Multiphysics Modeling of Microreactors with NEAMS codes, and Validation Based on KRUSTY Reactivity Insertion

The NEAMS Multiphysics Applications team continues to assess code usability and functionality for microreactor design and safety analyses, while demonstrating that NEAMS tools capture both steady-state and transient behavior across distinct microreactor concepts. In FY2025, the team advanced full-core, high-fidelity, multiphysics models that solve more complex problems and strengthen verification/validation for several microreactor systems: heat-pipe microreactor (HPMR), gas-cooled microreactor (GCMR), and the KRUSTY experiment. These models employ the MOOSE MultiApp/Transfers architecture with Griffin for neutronics, BISON for heat conduction/thermomechanics, Sockeye for heat pipes, SAM/THM for coolant channels and loops, and SWIFT for hydride behavior, with meshes generated via the MOOSE Reactor Module. The graphite models available in the Grizzly code were also investigated for future analyses. For the HPMR, a Na-HPMR variant was constructed to align with recently validated heat-pipe experiments and Sockeye’s LCVF capability, enabling mechanistic heat-pipe transients and startup modeling. The Na-HPMR will serve as the primary model for HPMR investigations in upcoming tasks. The load-following and single heat-pipe failure scenarios (Griffin/BISON/Sockeye), which were previously modeled for the K-HPMR, were replicated for the Na-HPMR, showing strong negative temperature feedback and highly localized thermal effects, respectively, while the startup case captured vapor-front progression and heat-removal activation. Solid mechanics was added to the previously built K-HPMR full-core model in BISON, showing minimal impact on steady-state reactivity yet enabling stress-field predictions that prepare the path for full-core TRISO performance analyses. For the GCMR, automated steady-state and four transient scenarios were executed using Griffin/BISON/SAM/SWIFT. Results confirm robust inherent safety: power collapses promptly in loss-of-cooling events, the inlet-temperature drop settles to a new equilibrium, and a single-channel blockage yields only a ~30 K local fuel-temperature rise with <0.4% power decrease. SWIFT-predicted hydrogen redistribution affects reactivity during both steady-state and transient conditions, underscoring its importance. A Brayton-cycle balance of plant (BOP) model in SAM/THM demonstrated stable startup behavior, and xenon-driven reactivity during load following was analyzed. To improve TRISO-compact temperature fidelity, a fast multiscale Heat Source Decomposition (HSD) treatment was implemented. Against heterogeneous benchmarks, HSD reduces underprediction of kernel temperatures and lowers predicted peak powers in reactivity-insertion transients compared to previous homogenized models. KRUSTY warm-critical validation progressed from FY2024 baselines: the 15Ȼ insertion shows excellent agreement in peak power (~2% high) and temperature trends, and the 30Ȼ case was automated via a feedback controller that maintained power near 3 kW for ~150 s with close agreement to data. The successful modeling of the warm critical tests has laid a strong foundation for simulating more complex nuclear system tests in the years ahead. Throughout FY2025, developer feedback was provided (e.g., MOOSE batch mesh generation, distributed pre-split meshes, Griffin sweeper on displaced meshes), several new models were contributed to the Virtual Test Bed, and an OECD-NEA WPRS multiphysics benchmark based on the HPMR was initiated to enable broader cross-comparison and best-practice development with the nuclear community at large.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

The GPU-enabled divide-expand-consolidate RI-MP2 method (DEC-RI-MP2)

We report porting of the Divide-Expand-Consolidate Resolution of the Identity second-order Møller–Plesset perturbation (DEC-RI-MP2) method to the graphic processing units (GPUs) using OpenACC compiler directives. It is shown that the OpenACC compiler directives implementation efficiently accelerates the rate-determining step of the DEC-RI-MP2 method with minor implementation effort. Moreover, the GPU acceleration results in a better load balance and thus in an overall scaling improvement of the DEC algorithm. The resulting cross-platform hybrid MPI/OpenMP/OpenACC implementation has scalable and portable performance on heterogeneous HPC architectures. The GPU-enabled code was benchmarked using a reduced version of the S12L test set of Stefan Grimme (Grimme, Chem. Eur. J. 2012, 18, 9955) consisting of supramolecular complexes up to 158 atoms and 4292 contracted basis functions (cc-pVTZ). The test set results demonstrate the general applicability of the DEC-RI-MP2 method showing results consistent with the DEC-RI-MP2 introductory paper (Baudin et al., J. Chem. Phys. 2016, 144, 054102) on molecules of complicated electronic structures. © 2016 Wiley Periodicals, Inc.

Chemistry↗

Wire arc additive manufactured A36 steel performance for marine renewable energy systems

Additive manufacturing has established itself to be advantageous beyond small-scale prototyping, now supporting full-scale production of components for a variety of applications. Despite its integration across industries, marine renewable energy technology is one largely untapped application with potential to bolster clean energy production on the global scale. Wave energy converters (WEC) are one specific facet within this realm that could benefit from AM. As such, wire arc additive manufacturing (WAAM) has been identified as a practical method to produce larger scale marine energy components by leveraging cost-effective and readily available A36 steel feedstock material. The flexibility associated with WAAM can benefit production of WEC by producing more complex structural geometries that are challenging to produce traditionally. Additionally, for large components where fine details are less critical, the high deposition rate of WAAM in comparison to traditional wrought techniques could reduce build times by an order of magnitude. In this context of building and supporting WEC, which experience harsh marine environments, an understanding of performance under large loads and corrosive environments must be understood. Hence, WAAM and wrought A36 steel tensile samples were manufactured, and mechanical properties compared under both dry and corroded conditions. Here, the unique microstructure created via the WAAM process was found to directly correlate to the increased ultimate tensile and yield strength compared to the wrought condition. Static corrosion testing in a simulated saltwater environment in parallel with electrochemical testing highlighted an outperformance of corroded WAAM A36 steel than wrought, despite having a slighter higher corrosion rate. Ultimately, this study shows how marine energy systems may benefit from additive manufacturing components and provides a foundation for future applications of WAAM A36 steel.

36 MATERIALS SCIENCE↗

Carbon clusters formed from shocked benzene

Abstract Benzene (C 6 H 6 ), while stable under ambient conditions, can become chemically reactive at high pressures and temperatures, such as under shock loading conditions. Here, we report in situ x-ray diffraction and small angle x-ray scattering measurements of liquid benzene shocked to 55 GPa, capturing the morphology and crystalline structure of the shock-driven reaction products at nanosecond timescales. The shock-driven chemical reactions in benzene observed using coherent XFEL x-rays were a complex mixture of products composed of carbon and hydrocarbon allotropes. In contrast to the conventional description of diamond, methane and hydrogen formation, our present results indicate that benzene’s shock-driven reaction products consist of layered sheet-like hydrocarbon structures and nanosized carbon clusters with mixed sp 2 - sp 3 hybridized bonding. Implications of these findings range from guiding shock synthesis of novel compounds to the fundamentals of carbon transport in planetary physics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Investigating deformation and mesoscale void creation in HMX based composites using tomography based grain scale FEM

The microstructure of plastic bonded explosives (PBXs) significantly affects their macroscale mechanical characteristics. Imaging and modeling of the mesoscale constituents allows for a detailed examination of the deformation of mechanically loaded PBXs. In this study, a pair of explosive HMX crystals were bound with an HTPB based polymer binder and imaged using micro Computed Tomography ($µ$CT). Delamination of the polymer binder from the crystals was induced via macro-scale application of a tensile load. Cohesive parameters for simulation of the crystal/binder interface were determined by comparing numerical and experimental results of the delamination of this bi-crystal system. Simulations showed macro-scale plastic behavior is accommodated through both crystal-binder delamination and plastic deformation of the binder itself. Imaging and simulation of this bi-crystal system demonstrated the complex interplay of material constitutive behavior and grain-scale geometry. Successful parameterization of this relatively simple mechanical system is a step toward a better understanding void nucleation in similarly composed polycrystalline composites.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Advanced Cell-Level Control for Extending Electric Vehicle Battery Pack Lifetime

A cell-level control approach for electric vehicle battery packs is presented that enhances traditional battery balancing goals to not only provide cell balancing but also achieve significant pack lifetime extension. These goals are achieved by applying a new life-prognostic based control algorithm that biases individual cells differently based on their state of charge, capacity and internal resistance. The proposed life control approach reduces growth in capacity mismatch typically seen in large battery packs over life while optimizing usable energy of the pack. The result is a longer lifetime of the overall pack and a more homogeneous distribution of cell capacities at the end of the first life for vehicle applications. Active cell balancing circuits and associated algorithms are used to accomplish the cell-level life extension objectives. This paper presents details of the cell-level control approach, selection and design of the active balancing system, and low-complexity state-of-charge, capacity, and series-resistance estimation algorithms. A laboratory prototype is used to demonstrate the proposed control approach. The prototype consists of twenty-one 25 Ah Panasonic lithium-Ion NMC battery cells from a commercial electric vehicle and an integrated BMS/DC-DC system that provides 750 W to the vehicle low voltage auxiliary loads.

25 ENERGY STORAGE↗

CRADA Final Report: Weld Predictor App

Welding is an important manufacturing process used in a broad range of industries and market sectors, including automotive, aerospace, heavy manufacturing, medical, and defense. During welded fabrication, high localized heat input and subsequent rapid cooling result in the creation of residual stresses and distortion. These residual stresses can significantly affect the fatigue resistance, cracking behavior, and load-carrying capacity of welded structures during service. Further, additional fitting and tacking time is often required to fit distorted subassemblies together, resulting in non-value added cost. Using trial-and-error methods to determine which welding parameters, welding sequences, and fixture designs will most effectively reduce distortion is a time-consuming and expensive process. For complex structures with many welds, this approach can take several months. For this reason, efficient and accurate methods of mitigating distortion are in-demand across all industries where welding is used. Analytical and computational methods and commercial software tools have been developed to predict welding-induced residual stresses and distortion. Welding process parameters, fixtures, and tooling can be optimized to reduce the HAZ softening and minimize weld residual stress and distortion, improving performance and reducing design, fabrication and testing costs. However, weld modeling technology tools are currently accessible only to engineers and designers with a background in finite element analysis (FEA) who work with large manufacturers, research institutes, and universities with access to high-performance computing (HPC) resources. Small and medium enterprises (SMEs) in the US do not typically have the human and computational resources needed to adopt and utilize weld modeling technology. To allow an engineer with no background in FEA and SMEs to gain access to this important design tool, EWI and the Ohio Supercomputer Center (OSC) developed the online weld application software tool “WeldPredictor” ( https://eweldpredictor.ewi.org ). About 1400 users have tested this application. This project marked the beginning of development on the next version of WeldPredictor that addresses many outstanding features of the original, including 3D models, allow more material hardening laws, model material phase transformation, and uses open source finite element solvers to quickly solve problems (as opposed to expensive commercial tools).

42 ENGINEERING↗

A Parametric, Data-Driven, Non-Intrusive Reduced-Order Model Framework for Crystal Plasticity Simulations of Voids

The influence of the internal structure at micrometer length scales on the deformation of polycrystalline materials can be effectively captured using crystal plasticity finite element methods (CPFEM). However, the complexity and nonlinearity of the deformation equations CPFEM solves demand significant computational power and resources to achieve accurate predictions, limiting its broader application. To address this challenge, we have identified a reduced-order representation of the complex data in order to establish a computationally efficient reduced-order models (ROM) and drastically reduce the computational expense of CPFEM. Specifically, in this work, we developed a parametric, data-driven, and non-intrusive ROM framework for CPFEM using proper orthogonal decomposition (POD) and sparse variational Gaussian process (SVGP) regression for single-crystal microstructures under tensile loading conditions. The developed protocol enables one to compress field into a latent/low-dimensional space described by principal component analysis (PCA) via the singular value decomposition (SVD) algorithm. As a result, the high-dimensional data are reduced to a significantly smaller amount of dimensions with POD bases and POD coefficients. Furthermore, we deployed an ensemble of SVGPs—extended from the classical Gaussian process (GP) regression for scalability and handling big data—in a massively parallel manner to train and predict latent POD coefficients using known POD bases from a set of previously obtained simulations results. Lastly, using the predicted POD coefficients, we reconstructed the full-field results and showed reasonable agreement compared with the true values obtained from running CPFEM. The developed framework is validated with a set of CPFEM simulations of a single embedded void in single-crystal aluminum alloy. While the framework is broadly applicable, this work specifically focuses on single-crystal microstructures, a single load case (e.g., tensile), and a specific void geometry (spherical).

Anisotropy↗

Additive manufacturing of strong silica sand structures enabled by polyethyleneimine binder

Abstract Binder Jet Additive Manufacturing (BJAM) is a versatile AM technique that can form parts from a variety of powdered materials including metals, ceramics, and polymers. BJAM utilizes inkjet printing to selectively bind these powder particles together to form complex geometries. Adoption of BJAM has been limited due to its inability to form strong green parts using conventional binders. We report the discovery of a versatile polyethyleneimine (PEI) binder for silica sand that doubled the flexural strength of parts to 6.28 MPa compared with that of the conventional binder, making it stronger than unreinforced concrete (~4.5 MPa) in flexural loading. Furthermore, we demonstrate that PEI in the printed parts can be reacted with ethyl cyanoacrylate through a secondary infiltration, resulting in an increase in flexural strength to 52.7 MPa. The strong printed parts coupled with the ability for sacrificial washout presents potential to revolutionize AM in various applications including construction and tooling.

36 MATERIALS SCIENCE↗

Low Carbon Technology Strategies: Secondary School

This document includes steps that building owners and operators can implement to achieve smart, healthy, and low-carbon secondary schools within their existing building portfolios. Secondary schools often include complex heating and cooling systems or packaged rooftop units and can include specialty equipment for gymnasiums, pools, and buses.

analytics↗

NREL Project CloudZero

The National Renewable Energy Laboratory's (NREL's) CloudZero project is evaluating the ability to reliably and securely manage complex energy systems from the cloud, identifying major technical and regulatory barriers to cloud adoption, suggesting new security controls and best practices for cloud applications, and empowering industry to embrace the cloud, where appropriate.

cloud↗

Field validation of dynamic mechanical torque measurements using fiber-optic strain sensors for geared wind turbines

Abstract Accurate knowledge of the mechanical loads of wind turbine gearboxes has become essential in modern, highly loaded gearbox designs, as maintaining or even improving gearbox reliability with increasing torque density demands is proving to be challenging. Unfortunately, the traditional method of measuring dynamic mechanical torque using strain gauges placed on the outer surface of a rotating shaft and transmitting the resulting signal is unsuitable for serial deployment due to technical and economic constraints. An alternative method based on fiber-optic strain sensors placed on the stationary outer surface of the gearbox ring gear has been proposed. Like shaft torsion, the radial deformation of the ring gear is proportionate to the rotor torque. Placing the sensors on a stationary component is a cost-effective alternative for serial implementation because the need for complex and expensive data transfer via wireless transmission or a slip ring is eliminated. In this paper, we present the results of an extensive field experiment conducted to evaluate the torque measurement accuracy of this novel sensing solution installed on the gearbox of a Gamesa G97 2-MW wind turbine at the National Renewable Energy Laboratory’s Flatirons Campus. Torque measurements derived from fiber-optic strain sensors placed on the ring gear of the planetary stage are compared to conventional torque measurements from strain gauges placed on the main shaft. Two different torque estimation data processing methods were evaluated, with the method based on operational deflection shapes providing the most accurate results with an average normalized root mean square error below 0.7% for a load revolution distribution analysis. The effect of operating conditions on the torque estimate was also investigated, and the third planet-passing operational deflection shape was found to be the least sensitive to nontorque load-related effects. The fiber-optic strain sensors’ successful operation during the complete test campaign has demonstrated a robust and accurate solution for fleet-wide enhanced gearbox remaining useful life estimation.

17 WIND ENERGY↗

Field Validation of Dynamic Mechanical Torque Measurements for Geared Wind Turbines

Accurate knowledge of the mechanical loads of wind turbine gearboxes has become essential in modern, highly loaded gearbox designs, as maintaining or even improving gearbox reliability with increasing torque density demands is proving to be challenging. Unfortunately, the traditional method of measuring dynamic mechanical torque using strain gauges placed on the outer surface of a rotating shaft and transmitting the resulting signal is unsuitable for serial deployment due to technical and economic constraints. An alternative method based on fiber-optic strain sensors placed on the stationary outer surface of the gearbox ring gear has been proposed. Like shaft torsion, the radial deformation of the ring gear is proportionate to the rotor torque. Placing the sensors on a stationary component is a cost-effective alternative for serial implementation because the need for complex and expensive data transfer via wireless transmission or a slip ring is eliminated. In this paper, we present the results of an extensive field experiment conducted to evaluate the torque measurement accuracy of this novel sensing solution installed on the gearbox of a Gamesa G97 2-MW wind turbine at the National Renewable Energy Laboratory's Flatirons Campus. Torque measurements derived from fiber-optic strain sensors placed on the ring gear of the planetary stage are compared to conventional torque measurements from strain gauges placed on the main shaft. Two different torque estimation data processing methods were evaluated, with the method based on operational deflection shapes providing the most accurate results with an average normalized root mean square error below 0.7% for a load revolution distribution analysis. The effect of operating conditions on the torque estimate was also investigated, and the third planet-passing operational deflection shape was found to be the least sensitive to nontorque load-related effects. The fiber-optic strain sensors' successful operation during the complete test campaign has demonstrated a robust and accurate solution for fleet-wide enhanced gearbox remaining useful life estimation.

17 WIND ENERGY↗

Spatial distribution of organic functional groups supported on mesoporous silica nanoparticles (2): a study by 1 H triple-quantum fast-MAS solid-state NMR

The distribution of organic functional groups attached to the surface of mesoporous silica nanoparticles (MSNs) via co-condensation was scrutinized using 1D and 2D 1 H solid-state NMR, including the triple-quantum/single-quantum (TQ/SQ) homonuclear correlation technique. The excellent sensitivity of 1 H NMR and high resolution provided by fast magic angle spinning (MAS) allowed us to study surfaces with very low concentrations of aminopropyl functional groups. The sequential process, in which the injection of tetraethyl orthosilicate (TEOS) into the aqueous mother liquor was followed by dropwise addition of the organosilane precursor, resulted in deployment of organic groups on the surface, which were highly clustered even in a sample with a very low loading of ~0.1 mmol g -1 . The underlying mechanism responsible for clustering could involve fast aggregation of the aminopropyltrimethoxysilane (APTMS) precursor within the liquid phase, and/or co-condensation of the silica-bound molecules. Understanding the deposition process and the resulting topology of surface functionalities with atomic-scale resolution, can help to develop novel approaches to the synthesis of complex inorganic–organic hybrid materials.

36 MATERIALS SCIENCE↗

Fluid-structure interactions in compressible cavity flows

Experiments were performed to understand the complex fluid-structure interactions that occur during aircraft internal store carriage. A cylindrical store was installed in a rectangular cavity having a length-to-depth ratio of 3.33 and a length-to-width ratio of 1. The Mach number ranged from 0.6 to 2.5 and the incoming boundary layer was turbulent. Fast-response pressure measurements provided aeroacoustic loading in the cavity, while triaxial accelerometers provided simultaneous store response. Despite occupying only 6% of the cavity volume, the store significantly altered the cavity acoustics. The store responded to the cavity flow at its natural structural frequencies, and it exhibited a directionally dependent response to cavity resonance. Specifically, cavity tones excited the store in the streamwise and wall-normal directions consistently, whereas a spanwise response was observed only occasionally. Also, the streamwise and wall-normal responses were attributed to the longitudinal pressure waves and shear layer vortices known to occur during cavity resonance. Although the spanwise response to cavity tones was limited, broadband pressure fluctuations resulted in significant spanwise accelerations at store natural frequencies. As a result, the largest vibrations occurred when a cavity tone matched a structural natural frequency, although energy was transferred more efficiently to natural frequencies having predominantly streamwise and wall-normal motions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Impact of soil model complexity on the long-term thermal performance prediction of a new shallow bore ground heat exchanger

Shallow bore ground heat exchangers have been investigated in recent years because they have the potential to reduce the initial cost of the ground source heat pump system. Correctly modeling the transient heat transfer between the ground heat exchanger and the surrounding soil is essential for predicting a ground heat exchanger's performance. Simplification of the soil model could increase computation speed but sacrifice accuracy. This study investigates the impact of the soil model complexity on the annual performance prediction of a new shallow bore ground heat exchanger, the underground thermal battery (UTB). A simple 1D soil model and a more detailed 2D soil model were implemented, and they were validated against a 3D soil model. Overall, the resulting predictions of the UTB’s response from the 1D and 2D models to a given thermal load in different climates were compared. The results show that the root mean square differences between the hourly temperatures of the UTB during a year predicted using the two soil models range from 1.17°C to 3.39°C. As a result, the difference in the annual power consumption of the heat pump was between 0.7% and 3.4%. Furthermore, the dimensions of the UTB affected its performance, and a longer UTB was less sensitive to the soil models.

42 ENGINEERING↗