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At least 1,747 records · Page 97

AI-Based Protein Interaction Screening and Identification (AISID)

In this study, we presented an AISID method extending AlphaFold-Multimer’s success in structure prediction towards identifying specific protein interactions with an optimized AISIDscore. The method was tested to identify the binding proteins in 18 human TNFSF (Tumor Necrosis Factor superfamily) members for each of 27 human TNFRSF (TNF receptor superfamily) members. For each TNFRSF member, we ranked the AISIDscore among the 18 TNFSF members. The correct pairing resulted in the highest AISIDscore for 13 out of 24 TNFRSF members which have known interactions with TNFSF members. Out of the 33 correct pairing between TNFSF and TNFRSF members, 28 pairs could be found in the top five (including 25 pairs in the top three) seats in the AISIDscore ranking. Surprisingly, the specific interactions between TNFSF10 (TNF-related apoptosis-inducing ligand, TRAIL) and its decoy receptors DcR1 and DcR2 gave the highest AISIDscore in the list, while the structures of DcR1 and DcR2 are unknown. The data strongly suggests that AlphaFold-Multimer might be a useful computational screening tool to find novel specific protein bindings. This AISID method may have broad applications in protein biochemistry, extending the application of AlphaFold far beyond structure predictions.

59 BASIC BIOLOGICAL SCIENCES↗

Ultrathin Barrier InAlN/GaN Heterostructures for HEMTs

InAlN/AlN/GaN semiconductor heterostructures with a barrier thickness of 5–13 nm have been grown by metalorganic vapor phase epitaxy (MOVPE) on sapphire and SiC substrates. Optimization of GaN buffer and InAlN layers allows fabricating structures with sheet conductivity values below 210 Ohm/sq. High electron mobility transistors (HEMTs) fabricated from such structures show drain current value exceeding 1.25 A/mm with maximum transconductance of 450 mS/mm. Use of thin in situ Si{sub 3}N{sub 4} capping allows to fabricate and compare HEMT and MIS-HEMTs.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Advantages gained by Optimized ZIRLO and AXIOM PWR cladding materials

In support of industry's demands for higher performance cladding alloy materials, the Optimized ZIRLO alloy was developed as an evolutionary improvement of the ZIRLO alloy to obtain a significant improvement in corrosion performance and hydrogen pickup while maintaining the overall robust performance of ZIRLO alloy. Currently with operating experience in over 40 plants and burnup reaching over 70 GWd/MTU, a majority of the Westinghouse-fueled US PWR fleet, covering almost all Westinghouse fuel designs, has adopted full regions of Optimized ZIRLO cladding. Across all of these applications, Optimized ZIRLO cladding has demonstrated greatly improved corrosion performance and structural stability. These demonstrated improvements offer increased operational margin and flexibility, in support of industry trends toward increased core operating fuel duties and evolving regulatory requirements such as accident scenarios. Underpinning these benefits are the extensive post irradiation exam (PIE) data obtained from both pool-side and hot-cell exams for Optimized ZIRLO cladding. Building on the successes of Optimized ZIRLO cladding, and in recognition of increasingly challenging fuel management practices, and revised LOCA regulatory rules restricting cladding hydrogen content, AXIOM cladding is being rolled out for full lead test assembly irradiation. The AXIOM alloy, Westinghouse's next generation robust alloy targeting very high fuel duties, is designed to provide improved corrosion resistance, lower hydrogen pick-up, and lower creep and growth compared to current Westinghouse products. AXIOM cladding has been irradiated in a variety of reactors worldwide, including both commercial and test reactors. Extensive PIE data is available for various burnup levels, with leading rods approaching 75 GWd/MTU. The AXIOM composition was selected to ensure enhanced operating performance on multiple fronts, including the optimum combination of corrosion resistance and wear resistance, reduced hydrogen pick-up, improved dimensional stability, and robustness in aggressive coolant chemistry conditions. The present paper provides high burnup performance data, capturing the advantages gained by introducing Optimized ZIRLO and AXIOM alloy as PWR cladding materials. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Robust Optimization for the Day-Ahead Scheduling of Cascaded Hydroelectric Systems

Uncertain electricity prices resulting from the re-structuring of electricity market have brought new opportu-nities and challenges for hydroelectric producers. This paper presents a data-driven robust optimization approach for the day-ahead scheduling of cascaded hydroelectric systems (CHS) with electricity price uncertainty. In this paper, a minimum volume enclosing ellipsoid (MVEE) is adopted to construct an ellipsoidal uncertainty set that fully identifies and exploits the historical characteristics data. Here, a second-order conic optimization formulation of the robust counterpart is derived for efficient computation. A real-world case study is conducted to demonstrate the capability of the proposed optimization approach compared with the traditional robust optimization approach.

13 HYDRO ENERGY↗

Local Chemical Clustering Enabled Ultrahigh Capacitive Energy Storage in Pb-Free Relaxors

Designing Pb-free relaxors with both a high capacitive energy density (W rec ) and high storage efficiency (η) remains a remarkable challenge for cutting-edge pulsed power technologies. Local compositional heterogeneity is crucial for achieving complex polar structure in solid solution relaxors, but its role in optimizing energy storage properties is often overlooked. Here, in this paper, we report that an exceptionally high W rec of 15.2 J cm –3 along with an ultrahigh η of 91% can be achieved through designing local chemical clustering in Bi 0.5 Na 0.5 TiO 3 –BaTiO 3 -based relaxors. A three-dimensional atomistic model derived from neutron/X-ray total scattering combined with reverse Monte Carlo method reveals the presence of subnanometer scale clustering of Bi, Na, and Ba, which host differentiated polar displacements, and confirming the prediction by density functional theory calculations. This leads to a polar state with small polar clusters and strong length and direction fluctuations in unit-cell polar vectors, thus manifesting improved high-field polarizability, steadily reduced hysteresis, and high breakdown strength macroscopically. The favorable polar structure features also result in a unique field-increased η, excellent stability, and superior discharge capacity. Our work demonstrates that the hidden local chemical order exerts a significant impact on the polarization characteristic of relaxors, and can be exploited for accessing superior energy storage performance.

25 ENERGY STORAGE↗

The role of pressure in inverse design for assembly

Isotropic pairwise interactions that promote the self-assembly of complex particle morphologies have been discovered by inverse design strategies derived from the molecular coarse-graining literature. While such approaches provide an avenue to reproduce structural correlations, thermodynamic quantities such as the pressure have typically not been considered in self-assembly applications. In this work, we demonstrate that relative entropy optimization can be used to discover potentials that self-assemble into targeted cluster morphologies with a prescribed pressure when the iterative simulations are performed in the isothermal-isobaric ensemble. The benefits of this approach are twofold. First, the structure and the thermodynamics associated with the optimized interaction can be controlled simultaneously. Second, by varying the pressure in the optimization, a family of interparticle potentials that all self-assemble the same structure can be systematically discovered, allowing for a deeper understanding of self-assembly of a given target structure and providing multiple assembly routes for its realization. Selecting an appropriate simulation ensemble to control the thermodynamic properties of interest is a general design strategy that could also be used to discover interaction potentials that self-assemble structures having, for example, a specified chemical potential.

74 ATOMIC AND MOLECULAR PHYSICS↗

A Computational Framework to design 3D stiffness gradient acoustic metamaterials for impedance matching

Acoustic waves play a crucial role in various applications, including medical imaging, non-destructive testing, and sonar systems. One of the significant challenges in these applications is impedance matching, which is essential for minimizing reflections and maximizing the transfer of acoustic energy between different media. Acoustic metamaterials offer a promising solution to this challenge. In addition to impedance control, gradient stiffness can enhance structural efficiency and enable spatial control of wave propagation, making it a valuable feature in acoustic metamaterial design. In this pa- per, we present our developed computational method to design 3D stiffness gradient acoustic metamaterials for impedance matching. The key steps in our approach include generating initial designs using a periodic covariance function to provide unit cells that are both periodic on the boundaries and randomly formed inside the unit cell. Furthermore, we integrated manufacturing constraints into the design process, ensuring that the structures are interconnected for fabrication. We propose two computational optimization algorithms: GenUnit, based on a non-dominated sorting genetic algorithm (NSGA-II), and MLMatch, which leverages differentiable machine learning. The two approaches are not separate contributions but complementary com- ponents of a unified framework. GenUnit requires no training data and directly interfaces with physics-based simulations, making it highly accurate but slower for large-scale exploration. In contrast, MLMatch is data-hungry during training but, once trained, enables near-instantaneous inference and broad design-space coverage. Together, they form a hybrid strategy: ML- Match rapidly explores the global design space, and GenUnit provides local refinement with high-fidelity accuracy. This balance between training cost, inference time, and precision is the motivation for including both methods in the same study. We applied this dual-algorithm framework to generate two metallic-based metamaterial designs that match the acoustic impedance of water while exhibiting a controlled gradient in stiffness (from stiff to soft). The stiffness gradient is particularly advantageous in applications where one side of the structure must interface with soft or sensitive surfaces, such as human tissue or delicate components. Here, this work paves the way for improved materials in various acoustic applications, particularly in ultrasound devices, by providing better impedance.

Metamaterial↗

Automation and control of laser wakefield accelerators using Bayesian optimization

Laser wakefield accelerators promise to revolutionize many areas of accelerator science. However, one of the greatest challenges to their widespread adoption is the difficulty in control and optimization of the accelerator outputs due to coupling between input parameters and the dynamic evolution of the accelerating structure. Here, we use machine learning techniques to automate a 100 MeV-scale accelerator, which optimized its outputs by simultaneously varying up to six parameters including the spectral and spatial phase of the laser and the plasma density and length. Most notably, the model built by the algorithm enabled optimization of the laser evolution that might otherwise have been missed in single-variable scans. Subtle tuning of the laser pulse shape caused an 80% increase in electron beam charge, despite the pulse length changing by just 1%.

43 PARTICLE ACCELERATORS↗

Comparing Synthetic Routes and Thermal Characteristics of Alternate APO Variants

Low density, high-strength, temperature-resistant foams see widespread application in the aerospace and weapons fields due to their excellent qualities as structural supports. In these demanding environments, the most common formulation is a three-phase syntactic foam containing APOCure-601, BMI, and carbon or glass microballoons. Of these, APOCure-601 and BMI form the polymer resin amino-poly(oxadiazole) bismaleimide (APO-BMI), also known as Legacy APO or S-1,2-Ethyl-APO. In manufacturing this foam, the selective laser sintering (SLS) additive manufacturing technique is quickly gaining prominence, over more traditional injection molding since SLS allows for 3D printing of materials and reduces overall cost and waste production. That said, SLS also requires a narrow window between the melt and cure temperatures for a successful print. SLS printing of APO-BMI is therefore difficult since the compound possesses a broad window between its melting and curing temperatures, and also requires several post-cure steps or complete polymerization. This work explores synthesis optimization and thermal characteristics for variant Apo-BMI structures by observing the effect that alternative heteroatoms in the APO linkages, geometries 0f the BMI groups, and bridge structure identities impart on the resultant material. Synthetic methods for these altered structures were established in batch, with some others further converted to continuous flow chemistry, a method that produces materials in a continuous stream and is highly reproducible and readily scaled. Additionally, each structural change significantly altered the melt and cure properties for each APO variant, which is advantageous for SLS manufacturing.

60 APPLIED LIFE SCIENCES↗

A scalable design of experiments framework for optimal sensor placement

Here, we present a scalable design of an experiments framework for sensor placement in systems described by partial differential equations (PDEs). In particular, we aim to compute optimal sensor locations by minimizing the uncertainty of parameters estimated from Bayesian inverse problems and where the system. The resulting problem is a computationally intractable mixed-integer nonlinear program constrained by PDEs. We approach this problem with two heuristics used in compressed sensing and optimal control literature: a sparsity-inducing approach and a sum-up rounding approach. We also investigate metrics to guide the design of experiments (the total flow variance and the A-optimal design criterion) and analyze the effect of different noise structures (white and colored). Using an application in natural gas pipelines, we conclude that the sum-up rounding approach approach gives the best results and produces shrinking gaps with increasing mesh resolution. We also observe that convergence for the white noise measurement error case is slower than for the colored noise case. For A-optimal design, the solution is close to a uniform distribution of sensors along the pipeline while for the flow variance design the distribution is unstructured.

42 ENGINEERING↗

Precipitation hardening of laser powder bed fusion Ti-6Al-4V

Here, the laser powder bed fusion (PBF-L) additive manufacturing (AM) community has dedicated significant efforts into process optimization and control for defect-free Ti-6Al-4V. As defects become less of an issue for PBF-L Ti-6Al-4V, the processing-structure-properties (PSP) relationships between AM microstructures can now be explored to optimize mechanical properties. Lower temperature aging treatments around 550 °C in wrought Ti-6A-4V have been historically understood to precipitation harden the α phase with an ordered, hexagonal close packed (HCP) α 2 phase. The α 2 phase existed as nanoscale Ti 3 Al precipitates coherent with the parent α phase. The goal of the present investigation was to implement a vacuum heat treatment of 545 °C for 100 hours on PBF-L Ti-6Al-4V. This vacuum heat treatment took place after an initial hot isostatic pressure (HIP) treatment that decomposed the as-built, martensitic microstructure. The vacuum aging successfully produced nanoscale precipitates of α 2 phase within α-laths, confirmed via atom probe tomography (APT). Microstructural-length scale and quasi-static mechanical properties were investigated by nanoindentation and uniaxial tensile tests of miniaturized test specimens. Given the sensitivity of Ti-6Al-4V mechanical properties to small changes in chemistry, all test specimens originated from the same build. The α 2 precipitation resulted in significantly harder α-laths (≈ 2 GPa) as measured via nanoindentation, as well as a relative yield and ultimate tensile strength increase of 60 MPa and 38 MPa, respectively. Analysis of Variance (ANOVA) of the datasets revealed no statistical differences in total elongation between the HIPed and HIPed + aged specimens, indicative of the aging treatment producing a net benefit of strength with no loss in ductility.

36 MATERIALS SCIENCE↗

Design and Analysis Progress of ITER Diagnostic Equatorial Port #09

ITER is the world's largest fusion device currently under construction in the South of France with >50 diagnostic systems to be installed inside the port plugs (PPs), the interspace (IS), or the port cell region of various diagnostic ports. The plasma facing diagnostic first wall (DFW) and its supporting diagnostic shield modules (DSM) are designed to protect front-end diagnostics from plasma neutron and plasma radiation, while providing apertures for diagnostic access to the plasma. The design of ITER port plug structures including the DFW and the DSM is largely driven by the electromagnetic loads included on the PP structural components during plasma major disruptions and the vertical displacement events (VDEs). Unlike DFW and DSM, the design of diagnostic system, however, is likely driven by the steady-state thermal loads from plasma volumetric and surface heating and the dynamic response of the in-port components attached to the port-specific DSM or closure plate under transient loads induced on the vacuum vessel and the port extension during asymmetric VDEs. Three tenant diagnostic systems are integrated into the equatorial port 09. The toroidal interferometer/polarimeter, or TIP system, is installed in the left drawer (DSM3, left looking from plasma) for measuring the plasma density so to control the fuel input. The electron cyclotron emission (ECE) system is installed in the middle drawer (DSM2) to provide the high spatial and temporal resolution measurements of electron temperature evolution and the electron thermal transport inferences. The visible/infrared wide angle viewing system is installed in the right drawer (DSM1) to provide visible and infrared viewing and temperature data of the first wall for its protection in support of machine operation. The port plug integration design and multiphysics analyses are performed following port integration requirements including the weight limit (45 tones total), shut down dose rate limits, the cooling/heating and structural integrity validation. Mass distribution for TIP and ECE DSMs has been optimized to minimize the total weight by a new design of the boron carbide shielding pocket. Furthermore, the lightened DSM maintains its front-end load distribution and the structural stiffness with minimum impact to the DFW so to better protect on-board diagnostics; while still provides sufficient front-end stiffness for its structural integrity as well as the diagnostics function requirements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Revealing meso-structure dynamics in additive manufacturing of energy storage via operando coherent X-ray scattering

3D printing is an emerging technology for the fabrication of energy storage devices, offering advantages over traditional manufacturing methods. However, optimization and design of such devices requires an understanding of the meso-structure formation during the 3D printing process. This study utilizes operando coherent X-ray scattering, X-ray Photon Correlation Spectroscopy (XPCS), to study the spatiotemporally-resolved far-from-equilibrium dynamics during direct ink writing 3D printing. Here, Lithium Titanate (LTO) based ink is prepared and rheologically tested for its shear-thinning properties. Two-time intensity-intensity functions are calculated to be used in subsequent quantitative analysis, which allows for an overall characterization of the dynamics, description of an initial fast decorrelation and identification of sudden rearrangements of subdomains of the sample. The results show the dynamics to be anisotropic, spatiotemporally heterogenous and marked by distinct rearrangement events, all of which impact the electrochemical performance of energy storage devices. The studied 3D printing ink is used to fabricate electrodes which are then electrochemically tested, showing good performance in cycling and retaining structural integrity. This work furthers the understanding of the far-from-equilibrium material dynamics during 3D printing, giving quantitative characterization of this process, and highlights aspects of structure formation relevant to the electrochemical performance of the resultant energy storage device.

36 MATERIALS SCIENCE↗

Adjoint-optimized nanoscale light extractor for nitrogen-vacancy centers in diamond

Abstract We designed a nanoscale light extractor (NLE) for the efficient outcoupling and beaming of broadband light emitted by shallow, negatively charged nitrogen-vacancy (NV) centers in bulk diamond. The NLE consists of a patterned silicon layer on diamond and requires no etching of the diamond surface. Our design process is based on adjoint optimization using broadband time-domain simulations and yields structures that are inherently robust to positioning and fabrication errors. Our NLE functions like a transmission antenna for the NV center, enhancing the optical power extracted from an NV center positioned 10 nm below the diamond surface by a factor of more than 35, and beaming the light into a ±30° cone in the far field. This approach to light extraction can be readily adapted to other solid-state color centers.

42 ENGINEERING↗

Optimization of Advanced Steels for Cyclic Operation through an Integration of Material Testing, Modeling and Novel Component Test Validation

The efforts in this project were focused in three primary objectives, provided below: • To develop the needed microstructural processing and performance relationships and associated material models for specific constituents in fabricated weldments (such as the parent material, heat affected zone regions and weld metal), • Apply these metallurgical relationships through modeling of a welded pressure bearing power plant component subjected to cyclic operational conditions under both mechanical and thermal loading, and • Validate the model through novel structural feature and component tests. An attempt was made to optimize the heat treatment schedule to reduce or eliminate the presence of boron nitride (BN) in the matrix of the Grade 92 material. BN has been shown to be a primary nucleation source for creep damage. Proper evaluation of material behavior, and as assessed in this research, included the influence of geometric notches (such as those from poor fabrication or design) and metallurgical notches (such as weldments or poorly processed parent material). Better practice methodologies were implemented in the theoretical design of a high-temperature, critical component for cyclic operation. It was demonstrated that vessel testing can be reliably performed and provides a critical link between standard testing, structural assessment and validation. While the goal of an improved Grade 92 steel was not achieved in this project, there is considerable value in applying the documented testing and assessment methodologies to assess material and/or component behavior. This is especially true for materials and/or designs which are expected to be subjected to flexible operating modes. Design of a cycling state of the art thick wall steam header for long term operation with a state of the art ferritic steel was a task in this project. Implementation of that task showed how many factors including plant operating mode, creep strength, creep ductility, fatigue strength, and resistance to crack growth should be considered and evaluated to properly design high temperature components for long term service (200,000 operating hours or more) in a modern Fossil energy power plant. The current ASME non-nuclear boiler design code does not mandate this level of complex analysis nor does it provide all the metallurgical and mechanical properties data needed to perform this kind of design analysis.

20 FOSSIL-FUELED POWER PLANTS↗

Modular Processing of Flare Gas for Carbon Nanoproducts

This project demonstrated the technical viability and economic promise of a modular system for converting flared natural gas into valuable carbon nanoproducts (CNPs) through catalytic chemical vapor deposition (CVD). All major project milestones were successfully completed, including reactor design and commissioning, catalyst development, process optimization, technoeconomic analysis, and application testing in concrete systems. The overarching goal was to create a scalable, field-deployable process that valorizes stranded methane by producing high-value carbon materials for use in cementitious composites. At the lab scale, the team designed and built a fluidized bed reactor optimized for use with silica fume-supported nickel catalysts synthesized via atomic layer deposition (ALD). A statistically designed sintering study enabled precise tuning of nickel nanoparticle size, identifying the influence of oxygen partial pressure, time, and temperature on catalyst morphology and performance. These insights allowed the team to target catalyst conditions that maximize carbon nanofilament growth. Subsequent CVD experiments achieved up to 31.8 wt% carbon deposition under optimized conditions, with TEM confirming the presence of nanofilament structures and sustained hydrogen evolution during reaction. Reactor upgrades and empirical fluidization studies supported the development of reliable, repeatable experimental protocols. The modular pilot-scale skid reactor was fully constructed, instrumented, and commissioned. Capable of operating at 675–800°C and pressures up to 290 psig, the system was designed for continuous operation at a carbon production rate of 1 kg/hr. Initial demonstration runs confirmed solids handling, thermal control, and system leak-tightness, although a critical reactor component (the downfeed tube) was inadvertently omitted during final assembly. This omission limited gas–solid contact and prevented meaningful carbon deposition during pilot-scale CVD runs. Nonetheless, the system operated safely under design conditions, and the root cause of performance limitations was clearly identified. Complementary work on UHPC formulations demonstrated that small additions of carbon nanoproducts, including those derived from flare gas, can significantly enhance mechanical performance while preserving workability. A comprehensive study of CNF dispersion techniques and mix design optimization led to a clear protocol for integrating these nanomaterials into concrete. Incorporation of CNPs improved flexural toughness and reduced porosity, supporting their use in high-performance infrastructure applications. A technoeconomic analysis (TEA) confirmed that this process can produce CNP-loaded catalyst material at a levelized cost below $\$$7/kg across a range of catalyst loadings and reaction yields. With estimated market values for the carbon composite product ranging from $\$$14 to over $\$$60/kg, and the ability to blend CNPs into concrete at sub-percent levels with less than 10% added cost, the system presents a compelling economic case. While additional engineering work is needed to optimize fluidization and heat transfer at scale, this project establishes a strong foundation for commercial development. The process is not only technically sound but also economically promising, representing a viable pathway for flare gas mitigation through modular carbon nanomaterial production.

03 NATURAL GAS↗

Optimal periodic frequency combs for high-efficiency optical quantum memory based on rare-earth ion crystals

The possibility of enhancing the quantum efficiency of photon echo broadband quantum memory in rare-earth-ion-doped crystals with a frequency comb structure of optical transition inhomogeneous broadening is studied. We have found the optimal parameters of the frequency combs for implementing the pre-assigned quantum efficiency in the chosen spectral range of the optical transitions of rare-earth ions with real parameters. The obtained results allow the conditions to be formulated for increasing the efficiency of broadband quantum memory. The possibilities of experimental implementation of such memory are also discussed. (paper)

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗