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At least 937 records · Page 52

Engineering Assembly Kinetics and Line Roughness in Solvent Vapor-Annealed Block Copolymer/Homopolymer Blends

Block copolymer (BCP) directed self-assembly (DSA) is a promising route to enhance lithography resolution by multiplying nanopattern density and reducing feature roughness. Eliminating kinetically trapped self-assembly defects requires fast self-assembly. However, acceleration strategies like solvent vapor annealing or homopolymer blending broaden domain interfaces, implying a trade-off in increased feature roughness. In this work, we experimentally investigate this apparent dilemma between self-assembly kinetics and line roughness for solvent vapor-annealed thin films of a lamellar poly(styrene-block-2-vinylpyridine) (PS-b-P2VP) BCP blended with PS and P2VP homopolymers. Binary blends with PS or P2VP homopolymers and ternary blends incorporating both in equal weight fractions were solvent vapor annealed using acetone, a near-neutral solvent for PS and P2VP, followed by P2VP-selective vapor-phase infiltration with alumina (AlOx) and polymer etching. Binary blends with P2VP exhibit a modest kinetic enhancement but also higher line-edge and -width roughness due to the increased frequency of P2VP protrusions and bridge defects in the alumina line patterns. In contrast, binary blends with PS self-assemble noticeably faster, while domain asymmetry from the added PS homopolymer reduces roughness by curbing the number of alumina protrusions and bridge defects. Ternary blends maintain DSA line patterns across a wider composition window and, at higher homopolymer loadings, reduce roughness at length scales near the lamellar period, consistent with a reduced impact of intradomain compositional fluctuations. These findings provide important insights for codesigning blend compositions and process flows to achieve high-resolution, defect free patterns with minimal roughness through BCP DSA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-throughput oxygen chemical potential engineering of perovskite oxides for chemical looping applications

Chemical looping (CL) represents a versatile, emerging strategy for sustainable chemical and energy conversion. Designing metal oxide oxygen carriers with suitable redox properties remains one of the most critical challenges to CL due to the considerably different thermodynamic property requirements for different applications. Here, taking SrFeO 3–δ as a base-structure, this study seeks to rationally substitute its A- and/or B-site cations to tailor the equilibrium oxygen partial pressure over 20 orders of magnitude. 2401 Sr x A 1–x Fe y B 1–y O 3–δ perovskite-phase structures were investigated using high-throughput density functional theory (DFT) and 227, 273 high-entropy perovskites were screened via machine learning (ML). This significantly expands the materials design space. While most of the compositions predicted are new and nonobvious, 19 previously reported oxygen carriers, with excellent redox properties, were correctly identified by the algorithm. Moreover, we experimentally demonstrated 15 new oxygen carriers with superior redox performance. These results support the effectiveness of the high-throughput approaches for accelerated materials discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Surface Engineering Strategy to Synthesize Bicomponent Carbons for Rechargeable Zinc-Air Batteries

Atomic Fe-N x moieties and nanosized FeCo species anchored on carbons have each been demonstrated to be among the most effective active components for oxygen reduction and evolution reactions (ORR/OER), respectively in rechargeable zinc -air batteries (ZABs). However, incorporating both of these components in a single catalyst presents a great challenge due to the trade-off in formation between them during hightemperature preparation. Herein, we integrate them into a bicomponent carbon through a surface engineering strategy. In this process, K 3 [Fe(CN) 6 ] is engineered on the surface of a precursor mixture consisting of polyaniline-coated graphene oxide and ZIF-67. This is followed by pyrolysis to produce the bicomponent carbon catalyst of FeCo nanoparticles modified carbon polyhedron (for accelerating the OER), supported on atomically dispersed Fe -N -doped carbon nanosheet (for boosting the ORR). The catalyst exhibits a small potential gap of 0.69 V for OER/ORR. In situ Raman spectroscopy demonstrates that spinel FeCo oxides may be responsible for OER. The use of this catalyst in ZABs achieves high power densities of 225 mW cm -2 in aqueous electrolyte and 164 mW cm -2 in solid-state electrolyte. Additionally, a small and stable voltage gap of 0.712 V at 10 mA cm -2 is maintained after 1035 discharge -charge cycles demonstrating the great application potential in energy devices.

An, Jia-Xing↗

Optimization of Desalination Systems with Detailed Water Chemistry through Integration of Reaktoro in WaterTAP

Chemistry predictions are critical for an accurate estimation of performance and costs in desalination process models, which allows for the estimation of the value of new technologies and the viability of treating new water sources. Herein, we present how an implicit function formulation can be used to integrate the chemical modeling package, Reaktoro, into the techno-economic assessment and modeling platform, WaterTAP. This approach resolves the critical issues of integrating large-scale thermodynamic models and databases into equation-oriented process models while allowing more flexibility relative to previously presented surrogate-based methods. We describe how this integration into Pyomo and WaterTAP models is implemented and used through the open-source package Reaktoro-PSE . We first validate this integration approach by performing optimization on a previously presented desalination treatment train with softening and acid addition as the pretreatment steps. Then, to demonstrate the value of this approach, we extend the cost-optimization problem to include the simultaneous addition of lime and soda ash for softening, and HCl and H 2 SO 4 in the acidification steps. Finally, we were able to confirm the previously established results that were obtained by using surrogate models and demonstrate that the implicit function approach enables exploration of different feedwater compositions and a larger number of chemicals and their combinations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accelerated Deterministic Phonon Transport With Consistent Material Temperature and Intensities

Abstract We present a method for deterministically solving the frequency and temperature dependent phonon radiative transport (PRT) equation in the single-mode relaxation time (SMRT) approximation in the self-adjoint angular flux (SAAF) form. To handle the nonlinear coupling between the phonon intensities and the material temperature, we apply a linearization approach that is similar to one in thermal radiative transport. This procedure leads to the PRT equation with pseudo-scattering. The method presented includes acceleration of both the inner pseudo-scattering source iterations and outer temperature iteration with a gray diffusion synthetic acceleration (DSA) and Anderson acceleration, respectively. We use the finite-element method to discretize the PRT equation in space and the method of discrete ordinates (SN) for angular discretization. The proposed method is verified by a gray method of manufactured solutions problem and demonstrated on a problem using temperature and direction dependent multigroup data from lithium aluminate (LiAlO2). The iterative performance of the acceleration method in each test is then compared to the unaccelerated method.

Engineering↗

NREL Innovations Help Drive Wind Industry Transformation [Fact Sheet]

For nearly 30 years, NREL has helped the wind turbine industry through design and research innovations. The comprehensive capabilities of the National Wind Technology Center (NWTC), ranging from specialized computer simulation tools to unique test facilities, has been used to design, develop, and deploy several generations of advanced wind energy technology.

17 WIND ENERGY↗

Fatigue Performance of High-Strength Pipeline Steels and Their Welds in Hydrogen Gas Service

Objectives of the project include: Enable the use of high strength steel hydrogen pipelines, as significant cost savings can result by implementing high strength steels as compared to lower strength pipes. Demonstrate that girth welds in high-strength steel pipe exhibit fatigue performance similar to lower-strength steels in high-pressure hydrogen gas. Identify pathways for developing high-strength pipeline steels by establishing the relationship between microstructure constituents and hydrogen-accelerated fatigue crack growth (HA-FCG)

08 HYDROGEN↗

Basic Research Needs for Inverse Methods for Complex Systems under Uncertainty

Inverse problems, which aim to infer unknown properties of a system using experimental and observational data, are central to addressing many of the U.S. Department of Energy’s (DOE) most critical scientific and engineering challenges. Accurate, computationally efficient, and data-efficient solutions to inverse problems are essential for advancing DOE mission-critical science drivers, including analyzing data from large-scale experimental facilities, optimizing fusion reactor performance, accelerating materials discovery, enhancing geophysical imaging, improving wildfire predictions, and enabling autonomous systems and digital twins. However, these problems are becoming increasingly complex, often involving nonlinear, highdimensional, and interconnected systems and models that span multiple physics and scales, while relying on data with varying quantity, quality, and information content. Compounding these challenges is the uncertainty inherent in DOE-relevant systems, where errors in inputs, noise in data, incompleteness of data, and discrepancies between models and reality constrain the accuracy and precision of solutions. At the same time, the convergence of recent scientific computing trends—scientific machine learning, artificial intelligence, and computing advances such as exascale computing—is creating unprecedented opportunities for tackling these challenges. The cross-cutting nature of inverse problems, combined with their growing complexity and rapidly evolving data and algorithmic demands, strongly motivates the formulation of a prioritized research agenda to maximize their capabilities and impact. In response to this need, DOE’s Advanced Scientific Computing Research (ASCR) program in the Office of Science convened the Workshop on Basic Research Needs for Inverse Problems for Complex Systems Under Uncertainty in June 2025. This workshop brought together experts across disciplines to identify grand challenges and major opportunities in the field. Through collaborative discussions, the workshop defined transformative research directions aimed at addressing the mathematical, statistical, and computational challenges posed by inverse problems under uncertainty. As a result of these efforts, four priority research directions (PRDs) were identified to guide future research and development in this area. These PRDs, summarized below, represent a roadmap for advancing the foundational science and mathematics of inverse problems, enabling robust, scalable, and uncertainty-aware solutions that are critical for DOE applications.

97 MATHEMATICS AND COMPUTING↗

Advanced Computing Annual Report 2025 [Slides]

In Fiscal Year (FY) 2025, the National Laboratory of the Rockies (NLR) continued to advance computing as a cornerstone of energy innovation, expanding the Kestrel high-performance computing (HPC) system to 56 peak petaflops. This growth strengthened Kestrel's role as a national asset for applied energy research, enabling larger, more complex simulations and accelerating the integration of artificial intelligence (AI) methods across the laboratory's computing portfolio. In FY 2025, AI was a component of most projects running on Kestrel, underscoring its central role in modern energy science and engineering. Kestrel supported a broad and diverse set of 507 modeling and simulation projects, engaging 855 researchers across the U.S. Department of Energy's (DOE's) Office of Critical Minerals and Energy Innovation (CMEI) portfolio and other offices, as well as partners from industry, academia, and utilities. These efforts span critical materials discovery, energy systems modeling, grid modernization, advanced manufacturing, and other areas essential to strengthening U.S. energy security and competitiveness. Together, these collaborations produced 708 technical outputs, including 293 peer-reviewed publications, reflecting both the depth and impact of the science enabled by NLR's computing capabilities. This year's report highlights the growing importance and benefit of AI throughout NLR's research programs and features work by early career researchers who are helping shape the future of computing-enabled energy innovation. Explore these sections and the many project successes captured in the pages that follow.

97 MATHEMATICS AND COMPUTING↗

Progress on the development of new correlations under the framework of the IAEA Coordinated Research Programme on heat transfer in SCWR's

This paper begins with an introduction designed to provide researchers who are new to field of heat transfer to fluids at supercritical pressure with a brief picture of early developments, and to set the scene for the review of work on the development of new correlations for such fluids under the framework of the IAEA CRP. These are needed because of the active consideration now being given to water-cooled nuclear reactors operating at pressures above the critical value. Work on the development of a trans-critical look-up table aimed at covering the region near the critical point is outlined. A very large heat transfer databank has been compiled and subjected to a thorough screening process. It covers a wide range of conditions and has been used for the assessment of the performance of a number of empirical equations. A detailed error analysis was carried out for the most promising ones and an examination of parametric trends was made. A new correlation is described which has been specifically designed to combine simplicity of structure, explicit connection with physically-based phenomena whilst being able to cover both normal and deteriorated heat transfer conditions. It avoids direct dependence of heat transfer coefficient on wall temperature. The performance of this correlation was evaluated using the data set of Herkenrath et al for water at supercritical pressure. Results from a recent experimental study of heat transfer to carbon dioxide at supercritical pressure under conditions of mixed convection have been used to develop a set of equations to describe the general behaviour observed. Comparisons are made between the performance of a number of equations and the data from the carbon dioxide experiments and also some for water. Finally, the development is outlined of physically-based, semi-empirical models aimed at extending an empirical equation for variable property forced convection heat transfer to fluids at supercritical pressure to account for influences of buoyancy and flow acceleration. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Presentation: Reactor Containment Passive Safety Analysis: Steam Condensation in Presence of Non-condensable Gas Scaled Experiment and Modeling

This study presents steam condensation scaled experiments and semi-empirical models in presence of nitrogen--a noncondensable gas (NCG), simulating air in the reactor containment--to support water-cooled small modular reactors (SMRs) passive containment cooling system (PCCS) design and analysis. Previous experimental studies on PCCS are focused on fixed and smaller tube (mostly 2-in.) geometries and specific test condition variations, bringing challenges with geometric scaling and mismatching with SMR prototypic design. To address these challenges, this study presents steam condensation test dataset obtained from three scaled test sections of 1-, 2-, and 4-in.-diameter steam condensers with an annular/jacket cooling of 2-, 3-, and 6 in.-diameter tubes, respectively. Test data were collected for steam ranges from 58 to 63 kg/hr., and NCG flow of 4.4 to 13.3 kg/hr. Annular cooling water flow was varied to obtain required testing conditions of saturated steam inlet and fully condensed outlet. Axial temperature test data of bulk cooling water, steam and condensate were collected by thermocouples for three test sections and various steam-NCG mixing/testing conditions. A standard data reduction method was adopted--utilizing iterative and nodalized mass and heat transfer calculation to estimate axial local heat fluxes, heat transfer coefficients (HTCs), condensation rates, film thickness, and Nusselt number. Based on the obtained dataset semi-empirical model results--a ratio of experimental and Nusselt's theoretical HTC are presented. Such results and findings are supportive of developing scaled-up testing facility, to enable model validations and accelerate next generation of reactors development and deployment.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Effects of Electron Irradiation on Candidate Materials for Target Window in Accelerator-Driven Mo-99 Production

Room-temperature (RT) axial tensile tests were conducted in 2018 and 2021 with flat, sub-sized, dog-boned samples of non-irradiated and irradiated Inconel 718 and irradiated beryllium (Be). The sample gauge length was 7.62 mm. Tensile properties of interest are the engineering yield stress (YS), ultimate tensile stress (UTS), uniform elongation (UE) and total elongation (TE). The electron dose of the 2021 samples was ≈2 times the dose of samples tested in 2018. Relative dose rates of 0, 1 (2018), and 2 (2021) are assigned to these samples. The 2021 electron-irradiated Be samples were brittle with a low failure stress of 338±64 MPa based on two samples. The failures occurred in the gauge section. The 2018 results for electron-irradiated Be indicated a slight decrease in ductility and strength for the one electron-irradiated sample that failed in the gauge section.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

IBC’s 23rd Antibody Engineering and 10th Antibody Therapeutics Conferences and the Annual Meeting of The Antibody Society: December 2–6, 2012, San Diego, CA

Now in its 23rd and 10th years, respectively, the Antibody Engineering and Antibody Therapeutics conferences are the Annual Meeting of The Antibody Society. The scientific program covers the full spectrum of challenges in antibody research and development from basic science through clinical development. In this preview article of the conferences, the chairs provide their thoughts on sessions that will allow participants to track emerging trends in (1) the development of next-generation immunomodulatory antibodies; (2) the complexity of the environment in which antibodies must function; (3) antibody-targeted central nervous system (CNS) therapies that cross the blood brain barrier; (4) the extension of antibody half-life for improved efficacy and pharmacokinetics (PK)/pharmacodynamics (PD); and (5) the application of next generation DNA sequencing to accelerate antibody research. A pre-conference workshop on Sunday, December 2, 2012 will update participants on recent intellectual property (IP) law changes that affect antibody research, including biosimilar legislation, the America Invents Act and recent court cases. Keynote presentations will be given by Andreas Plückthun (University of Zürich), who will speak on engineering receptor ligands with powerful cellular responses; Gregory Friberg (Amgen Inc.), who will provide clinical updates of bispecific antibodies; James D. Marks (University of California, San Francisco), who will discuss a systems approach to generating tumor targeting antibodies; Dario Neri (Swiss Federal Institute of Technology Zürich), who will speak about delivering immune modulators at the sites of disease; William M. Pardridge (University of California, Los Angeles), who will discuss delivery across the blood-brain barrier; and Peter Senter (Seattle Genetics, Inc.), who will present his vision for the future of antibody-drug conjugates.

59 BASIC BIOLOGICAL SCIENCES↗

Evaluating WRF-Chem aerosol indirect effects in Southeast Pacific marine stratocumulus during VOCALS-REx

We evaluate a regional-scale simulation with the WRF-Chem model for the VAMOS (Variability of the American Monsoon Systems) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx), which sampled the Southeast Pacific's persistent stratocumulus deck. Evaluation of VOCALS-REx ship-based and aircraft observations focuses on analyzing how aerosol loading affects marine boundary layer (MBL) dynamics and cloud microphysics. We compare local time series and campaign averaged longitudinal gradients, and highlight differences in model simulations with (W) and without wet (NW) deposition processes. The higher aerosol loadings in the NW case produce considerable changes in MBL dynamics and cloud microphysics, in accordance with the established conceptual model of aerosol indirect effects. These include increase in cloud albedo, increase in MBL and cloud heights, drizzle suppression, increase in liquid water content, and increase in cloud lifetime. Moreover, better statistical representation of aerosol mass and number concentration improves model fidelity in reproducing observed spatial and temporal variability in cloud properties, including top and base height, droplet concentration, water content, rain rate, optical depth (COD) and liquid water path (LWP). Together, these help to quantify confidence in WRF-Chem's modeled aerosol-cloud interactions, while identifying structural and parametric uncertainties including: irreversibility in rain wet removal; overestimation of marine DMS and sea salt emissions and accelerated aqueous sulfate conversion. Our findings suggest that WRF-Chem simulates marine cloud-aerosol interactions at a level sufficient for applications in forecasting weather and air quality and studying aerosol climate forcing, including the reliability required for policy analysis and geo-engineering applications.

54 ENVIRONMENTAL SCIENCES↗

DevOps Pragmatic Practices and Potential Perils in Scientific Software Development

The DevOps movement, which aims to accelerate the continuous delivery of high-quality software, has taken a leading role in reshaping the software industry. Likewise, there is growing interest in applying DevOps tools and practices in the domains of computational science and engineering (CSE) to meet the ever-growing demand for scalable simulation and analysis. Translating insights from industry to research computing, however, remains an ongoing challenge; DevOps for science and engineering demands adaptation and innovation in those tools and practices. There is a need to better understand the challenges faced by DevOps practitioners in CSE contexts in bridging this divide. To that end, we conducted a participatory action research study to collect and analyze the experiences of DevOps practitioners at a major US national laboratory through the use of storytelling techniques. We share lessons learned and present opportunities for future investigation into DevOps practice in the CSE domain.

97 MATHEMATICS AND COMPUTING↗

Californium purification and electrodeposition

The staff at the Radiochemical Engineering Development Center, located at Oak Ridge National Laboratory, produced a 6.3 ± 0.4 GBq (1.7 ± 0.1 Ci) 252 Cf source for the Californium Rare Isotope Breeder Upgrade (CARIBU) project at Argonne National Laboratory’s Argonne Tandem Linac Accelerator System. The source was produced by electrodeposition of a 252 Cf sample onto a stainless steel substrate, which required material free from excess mass for efficient deposition. The resulting deposition was the largest reported 252 Cf electrodeposition source ever produced. Several different chromatographic purification methods were investigated to determine which would be most effective for final purification of the feed material used for the CARIBU source. The separation of lanthanides from the Cf was of special concern. Furthermore, the separation, using 145 Sm, 153 Gd, and 249 Cf as tracers, was investigated using BioRad AG 50X8 in α-hydroxyisobutyric acid, Eichrom LN resin in both HNO 3 and HCl, and Eichrom TEVA resin in NH 4 SCN. The TEVA NH 4 SCN system was found to completely separate 145 Sm and 153 Gd from 249 Cf and was adopted into the purification process used in purifying the 252 Cf.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

A high throughput assay to detect enzymatic polyethylene oxidation

Biological plastics deconstruction and upcycling have emerged as sustainable alternatives to traditional recycling technologies for plastics waste. The discovery and engineering of efficient thermostable poly(ethylene terephthalate) (PET) hydrolases have made biological PET recycling possible at scale; however, enzymes for non-PET plastics, which account for approximately 70% of all plastics produced, remain largely undiscovered. To accelerate the discovery of such enzymes, we develop a high-throughput screen to detect initial polymer oxidation, specifically that of the C-H bond to an aldehyde. We test 4-hydrazino-7-nitro-2,1,3-benxoxadiozole hydrazine (NBD-H), which reacts with generated aldehydes to form a fluorescent hydrazone on plasma oxidized low-density polyethylene (LDPE) films. Hydrazone generation correlated well with the area of aldehyde peaks as measured by Fourier Transform Infrared Spectroscopy (FTIR) (R2 = 0.92). Moreover, we demonstrate that the probe reliably identifies LDPE-active dye decolorizing peroxidases (DyPs) that generate aldehydes on LDPE films (1.7 – 3.0 fold change relative to background), serving as an effective screen as demonstrated by receiver operating characteristic area under the curve of 0.95. Furthermore, this assay offers an LDPE oxidation screening platform that can be readily parallelized and automated for accelerated discovery of enzymes involved in polyolefin deconstruction.

biocatalysis↗