Results for “Rapid Process Design” — Page 8

DOE OSTI2024

IDAES-PSE 2.5.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost, most environmentally sustainable solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.5.0 Release Highlights Upcoming Changes IDAES will be switching to the new Pyomo solver interface in the next release. Whilst this will hopefully be a smooth transition for most users, there are a few important changes to be aware of. The new solver interface uses a different version of the IPOPT writer (“ipopt_v2”) and thus any custom configuration options you might have set for IPOPT will not carry over and will need to be reset. By default, the new Pyomo linear presolver will be activated with ipopt_v2. Whilst are working to identify any bugs in the presolver, it is possible that some edge cases will remain. IDAES will begin deploying a new set of scaling tools and APIs over the next few releases that make use of the new solver writers. The old scaling tools and APIs will remain for backward compatibility but will begin to be deprecated. New Models, Tools and Features New diagnostics check for near-parallel variables and constraints. New diagnostics tools for identifying causes of infeasibility in models. New example for creating a custom model of a liquid-liquid extractor unit operation. Bug Fixes Fixed bug in Gibbs reactor that caused it to appear to have additional spurious degrees of freedom. Fixed bug in the Modular Property Framework that would cause errors when trying to use phase-based material balances with phase equilibria. Fixed bug in Modular Properties Framework that caused errors when initializing models with non-vapor-liquid phase equilibria. Testing and Robustness Deployed the IDAES Diagnostics Toolbox to confirm that there are no structural or numerical issues in the core model libraries. Additional robustness tests for core model, and some associated improvements in the converge tester class. Fixed a number of issues that were causing unexpected warnings to be emitted during testing. Deprecations and Removals Removed examples for RIPE tool which has not been supported for a number of releases.

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DOE OSTI2024

IDAES-PSE 2.6.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.6.0 Release Highlights Upcoming Changes IDAES will be switching to the new Pyomo solver interface in the next release. Whilst this will hopefully be a smooth transition for most users, there are a few important changes to be aware of. The new solver interface uses a different version of the IPOPT writer (“ipopt_v2”) and thus any custom configuration options you might have set for IPOPT will not carry over and will need to be reset. By default, the new Pyomo linear presolver will be activated with ipopt_v2. Whilst are working to identify any bugs in the presolver, it is possible that some edge cases will remain. IDAES will begin deploying a new set of scaling tools and APIs over the next few releases that make use of the new solver writers. The old scaling tools and APIs will remain for backward compatibility but will begin to be deprecated. New Models, Tools and Features New Intersphinx extension automatically linking Jupyter notebook examples to project documentation New end-to-end diagnostics example demonstrated on a real problem New complementarity formulation for VLE with cubic equations of state, backward compatibility for old formulation New solver interface with presolve (ipopt_v2) in support of upcoming changes to the initialization and APIs methods, with default set to ipopt to maintain backwards compatibility; this will deprecate once all examples have been updated New forecaster and parameterized bidder methods within grid integration library Updated surrogates API and examples to support Keras 3, with backwards compatibility for older formats such as TensorFlow SavedModel (TFSM) Updated costing base dictionary to include the 2023 cost year index value Updated ProcessBlock to include information on the constructing block class Updated Flowsheet Visualizer to allow visualize() method to return value and functions Bug Fixes Fixed bug in the Modular Property Framework that would cause errors when trying to use phase-based material balances with phase equilibria. Fixed bug in Modular Properties Framework that caused errors when initializing models with non-vapor-liquid phase equilibria. Fixed typos flagged by June update to crate-ci/typos and removed DMF-related exceptions Minor corrections of units of measurement handling in power plant waste/transport costing expressions, control volume material holdup expressions, and BTX property package parameters Fixed throwing >7500 numpy deprecation warnings by replacing scalar value assignment with element extraction and item iteration calls Testing and Robustness Migrated slow tests (>10s) to integration, impacting test coverage but also yielding a nearly 30% decrease in local test runtime Pinned pint to avoid issues with older supported Python versions Pinned codecov versions to avoid tokenless upload behavior with latest version Bumped extensions to version 3.4.2 to allow pointing to non-standard install location Deprecations and Removals Python 3.8 is no longer supported. The supported Python versions are 3.9 through 3.12 The Data Management Framework (DMF) is no longer supported. Importing idaes.core.dmf will cause a deprecation warning to be displayed until the next release The SOFC Keras surrogates have been removed. The current version of the SOFC surrogate model in the examples repository is a PySMO Kriging model.

AS↗

DOE OSTI2024

IDAES-PSE 2.7.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.7.0 Release Highlights New features: AutoScaler and CustomScalerBase classes: Such tools are the core of the new scaling framework being implemented in IDAES. Wider adoption of scaling tools among users will result in quicker and more robust model solutions. Scaler for equilibrium reactor and saponification properties: These scaler models are examples to follow for how to use the new scaling tools. ONNX Surrogate support from Optimization & Machine Learning Toolkit (OMLT): ONNX is an open standard format to save and load ML/AI models that is widely supported by all major frameworks. This capability makes it easier for IDAES users to create surrogate models and use them without having to support each framework individually. 1D Membrane Model for CO2 Capture and Utilization: Supports ongoing efforts for modeling and optimizing polymer membrane processes for CO2 capture and conversion into formic acid. StreamScaler unit model: Unrelated to the CustomScalerBase, this unit model allows a stream’s extensive variables to be scaled by a fixed factor. This allows streams being processed by multiple units in parallel to be scaled down to unit scale and scaled back up to process scale. Bug fixes or improvements: Scaling, EoS, Diagnostics tool, Modular Properties, tests & documentation Deprecations: Old Cubic EoS

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DOE OSTI2025

IDAES-PSE 2.8.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications.

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DOE OSTI2022

Reimagining Codesign for Advanced Scientific Computing: Report for the ASCR Workshop on Reimagining Codesign

In March 2021, the U.S. Department of Energy’s Advanced Scientific Computing Research program convened the Workshop on Reimagining Codesign. The workshop, also known as ReCoDe, was organized around discussions on eight topic areas: (1) codesign for traditional high-performance computing workloads; (2) codesign of memory/storage systems; (3) codesign of machine learning, neuromorphic, quantum, and other non-von Neumann accelerators; (4) codesign for edge computing and processing at experimental instruments; (5) codesign for security and privacy; (6) hardware design tools and open-source hardware for high-productivity codesign; (7) tools, software stack, and programming languages for high-productivity codesign; and (8) quantitative tools and data collection for modeling and simulation for codesign. The panels identified four Priority Research Directions from these deliberations: (1) breakthrough computing capabilities with targeted heterogeneity and rapid design; (2) software and applications that embrace radical architecture diversity; (3) engineered security and integrity, from transistors to applications; and (4) design with data-rich processes.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Multi-physics Topology OPtimization and Additive Manufacturing for High-temperature Heat Exchangers

This research significantly advances the understanding of high-temperature heat exchanger design through an integrated approach that combines topology optimization (TO), triply periodic minimal surface (TPMS) structures, additive manufacturing (AM) and thermohydraulic testing. Each of these components contributes uniquely to a unified, high-performance design, fabrication and testing workflow. Topology optimization serves as the foundation of the design methodology by providing a systematic way to determine the most effective material layout for separating hot and cold fluids while maximizing thermal performance. The researchers introduced a novel three-material optimization framework using two density fields to represent hot fluid, cold fluid, and solid domains. This approach enables automated discovery of optimal shapes and flow paths that cannot be intuitively designed, especially under constraints imposed by manufacturing technologies. Furthermore, constraints such as minimal wall thickness and overhang angles were embedded into the optimization process, ensuring that resulting designs are not only thermally efficient but also manufacturable using modern additive techniques. In parallel, the study delves into the use of Gyroid-based TPMS geometries for constructing the core of the heat exchanger. TPMS structures are known for their high surface area, excellent fluid mixing capabilities, and minimal pressure drop characteristics. The researchers applied a data-driven modeling framework using Heteroscedastic Sparse Gaussian Process Regression (HSGPR) combined with genetic algorithms. This allowed for the rapid evaluation and optimization of key geometric parameters such as frequency, iso-value, and phase shift. The result was a set of Gyroid structures tailored for high heat transfer and low flow resistance, demonstrating clear improvements over conventional straight-channel designs. After the designing process, additive manufacturing played a critical role by turning these highly complex, optimized geometries into physical components. Utilizing Laser Powder Bed Fusion (LPBF) with Haynes 282, the study demonstrated the feasibility of fabricating these heat exchangers at high precision. Post-processing methods, including dilation-erosion operations, were applied to ensure local features adhered to self-supporting constraints. The fabricated structures were then subjected to thermohydraulic testing under conditions representative of supercritical CO 2 Brayton cycles, validating the predicted performance and confirming the viability of the full design-to-fabrication pipeline. Finally, thermohydraulic testing across the above studies served as a crucial experimental validation of advanced heat exchanger. Under consistent high-temperature and high-pressure conditions using supercritical CO 2 , the testing demonstrated that both TO and Gyroid-based TPMS designs significantly outperformed conventional straight-channel HXs. The TO design achieved a 115% increase in UA and NTU and a 27.6% boost in gravimetric power density, while the data-driven optimized Gyroid design delivered a 166% increase in UA and NTU and improved effectiveness from 68.7% to 86.1%. These results validate the simulation models, confirm the manufacturability of complex geometries under AM constraints, and provide key insights into design-performance trade-offs, thereby advancing the development of high-efficiency, compact heat exchangers for extreme environments.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Multifunctional optical correlator for picosecond ultraviolet laser pulse measurement

A compact optical correlator system that measures both the autocorrelation between two infrared (IR) lights and the cross-correlation between an IR and an ultraviolet (UV) light using a single nonlinear optical crystal has been designed and experimentally demonstrated. The rapid scanning of optical delay line, switching between auto and cross-correlations, crystal angle tuning, and data acquisition and processing are all computer controlled. Pulse widths of an IR light from a mode-locked laser are measured by the correlator and the results are compared with a direct measurement using a high-speed photodetector system. The correlator has been used to study the parameter dependence of the pulse width of a macropulse UV laser designed for laser-assisted hydrogen ion (H-) beam stripping for the Spallation Neutron Source at Oak Ridge National Laboratory.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2015

Rapid Computer Aided Ligand Design and Screening of Precious Metal Extractants from TRUEX Raffinate with Experimental Validation

Rhodium is the most extensively used metal in catalytic applications; it occurs in mixed ores with platinum group metals (PGMs) in the earth’s crust in low concentrations (0.4 - 10 ppb). It is resistant to aerial oxidation and insoluble in all acids, including aqua regia, making classical purification methods time-consuming and inefficient. To ensure adequate purity, several precipitation and dissolution steps are necessary during separation. Low abundance, high demand, and extensive processing make rhodium the most expensive of all PGMs. From alternative sources, rhodium is also produced in sufficient quantities (0.47 kg per ton initial heavy metal (tIHM)) during the fission of U-235 in nuclear reactors along with other PGMs (i.e., Ag, Pd, Ru). A typical power water reactor operating with UO 2 fuel after cooling can generate PGMs in quantities greater than found in the earth’s crust (0.5-2 kg/tIHM). This currently untapped supply of PGMs has the potential to yield $5,000-30,000/tIHM. It is estimated that by the year 2030, the amount of rhodium generated in reactors could exceed natural reserves. Typical SNF processing removes the heavier lanthanides and actinides and can leave PGMs at ambient temperatures in aqueous acidic (Cl⁻ or NO 3 ⁻; pH < 1) solutions at various activities. While the retrieval of these precious metals from SNF would minimize waste generation and improve resource utilization, it has been difficult to achieve thus far. Two general strategies have been utilized to extract Rh(III) from chloride media: ion pairing and coordination complexation. Ion pairing mechanisms have been studied primarily with the tertiary and quaternary amines. Additionally, mixed mechanism extractions have been observed in which ion pairing is the initial mechanism, and longer extraction equilibrium time generated coordination complexes. Very few coordination complexation extraction ligands have been studied. This project approached this problem through the design of a software program that uses state-of-the-art computational combinatorial chemistry, and is developed and validated with experimental data acquisition; the resulting tool allows for rapid design and screening of new ligands for the extraction of precious metals from SNF. This document describes the software that has been produced, ligands that have been designed, and fundamental new understandings of the extraction process of Rh(III) as a function of solution phase conditions (pH, nature of acid, etc.).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Melt-Spun PAN Precursor for Cost-Effective Carbon Fibers in High Pressure Compressed Gas Tankage

The objective of this program was to synthesize melt-spinnable polyacrylonitrile (PAN) precursor that will lead to carbon fiber 25% less expensive than carbon fiber produced from conventional PAN precursor when produced in large volumes. The carbon fiber produced from this precursor needs to achieve ≥ 700 ksi tensile strength with this cost reduction to replace the incumbent fiber. In this program, the technology for producing precursor and then converted carbon fiber (CF) capable of meeting the 700 ksi target was to be demonstrated at a small scale in tows, containing ≥ 100 filaments. If this program moved on to a “Phase 2”, the processes would be scaled up to produce and test Type IV compressed gas storage tanks capable of meeting the 700-bar ultimate targeted FOA performance level. Precursor fiber production typically contributes a large fraction (~50%) to finished CF manufactured cost. Presently, all high strength CFs are manufactured from solution spun PAN precursor, accomplished at low temperatures using large amounts of environmentally unfriendly solvents that impart major impact to line speed and costs involved with handling and reclaiming the solvents and associated “waste streams” required in spinning and extracting those solvents. PAN melt spinning was demonstrated by the company BASF in CF precursor production and used in production of some other acrylic fibers, but significant production challenges remain for meeting the established CF metrics. Melt spinning requires use of plasticizers to suppress the melt temperature of the predominantly PAN formulation to a point sufficiently below the temperature of significant cross-linking. Fortunately, BASF and this team’s earlier work had demonstrated acrylic formulations melt spun with combinations of plasticizing solvents at much lower solvent levels. This project team made significant progress in understanding technical issues and identifying formulation pathways in earlier work in this area where >250ksi strength was achieved. The goal of this program was to pursue a more comprehensive approach with a larger, more diverse team having greater equipment design and overall production capabilities to push rapidly beyond the science to resolve remaining “engineering” issues associated with establishing stable, continuous processes for precursor fiber leading to enhanced, cost-effective CF and composite tank production.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Manufacturing Supply Chain Development for Modular Solar-Thermochemical Conversion Platform - CRADA 387 (Final Report)

Modular chemical process intensification (MCPI) is an emerging field where chemical processing is performed using small-scale modular equipment instead of conventional large centralized chemical plants. Conventional chemical plants benefit from economies of scale that encourage scale-up to ever larger plants. A goal of MCPI is to develop technology that intensifies processing so that equipment can be dramatically smaller and integrated into modular systems. Scale-up occurs by adding more modules in parallel rather than making the equipment larger. A key concept is that equipment and modules can ultimately be cheaper by leveraging economies of mass production, analogous to the automotive industry, in manufacturing the equipment. This project made significant progress toward this outcome by meeting the RAPID institute metric to reduce equipment cost by 20% for each doubling in manufacturing volume. The MCPI application was thermochemical technology that is being commercialized by STARS Technology Corporation, one of the CRADA partners. The technology converts solar and renewable power to chemical energy to produce renewable hydrogen, fuels, and chemicals. The benefit to the public is reduction in greenhouse gases that are contributing to climate change. The project transitioned the steam methane reforming (SMR) reactor from conventional fabrication methods to additive manufacturing (AM) direct metal laser sintering (DMLS) process. This is projected to reduce the cost of making a reactor by 58% when producing 100 reactors per year. Innovations in the DMLS process produced a patented design that reduces reactor weight by 60%. Reductions in material costs and processing time extend the DMLS advantage to higher production volumes. The new design promises to be 38% cheaper than the conventional processes at 1000 units per year. The resulting 87% reduction in the steam methane reforming (SMR) module cost in scaling from current costs meets the RAPID metric. The project was successful in producing and testing the first ever additively manufactured SMR reactors. A reactor achieved over 82% efficiency in converting electric power to chemical energy, which is a world record for an inductively heated SMR. The project has contributed to the design and assembly of a first demonstration plant that is headed to a hydrogen bus filling station in Thousand Palms, CA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Integrating Emerging Polymer Chemistries for the Advancement of Recyclable, Biodegradable, and Biocompatible Electronics

Abstract Through advances in molecular design, understanding of processing parameters, and development of non‐traditional device fabrication techniques, the field of wearable and implantable skin‐inspired devices is rapidly growing interest in the consumer market. Like previous technological advances, economic growth and efficiency is anticipated, as these devices will enable an augmented level of interaction between humans and the environment. However, the parallel growing electronic waste that is yet to be addressed has already left an adverse impact on the environment and human health. Looking forward, it is imperative to develop both human‐ and environmentally‐friendly electronics, which are contingent on emerging recyclable, biodegradable, and biocompatible polymer technologies. This review provides definitions for recyclable, biodegradable, and biocompatible polymers based on reported literature, an overview of the analytical techniques used to characterize mechanical and chemical property changes, and standard policies for real‐life applications. Then, various strategies in designing the next‐generation of polymers to be recyclable, biodegradable, or biocompatible with enhanced functionalities relative to traditional or commercial polymers are discussed. Finally, electronics that exhibit an element of recyclability, biodegradability, or biocompatibility with new molecular design are highlighted with the anticipation of integrating emerging polymer chemistries into future electronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Accelerated Fuel Qualification of Fast Modular Reactor Fuel in a Thermal Reactor: Modeling and Simulation Paired with Irradiation Testing

The accelerated fuel qualification (AFQ) methodology is applied by simulating accelerated fuel tests of the General Atomics Electromagnetic Systems’ fuel system for its 44-MW(electric) gas-cooled, fast-spectrum fast modular reactor (FMR). This fuel is comprised of UO 2 pellets in SiGA® cladding, a silicon carbide ceramic matrix composite. Fast reactors, like the FMR, offer many benefits, including high fuel utilization and flexibility, but may require a lengthy material design process if tests are performed using fast neutron irradiation alone. A thermal neutron irradiation can instead be used to rapidly test how well key components of the current material models extend to high burnup. Thermal neutrons produce a different radial power distribution within the pin than fast neutrons. However, the temperature and burnup values for the two neutron types are comparable, and the differences between the simulated fuel responses are relatively small, demonstrating the weak sensitivity of the physics-based fuel model calculations on the neutron type and the irradiation rate. Furthermore, the deformation of the SiGA cladding saturates after about 1 displacement per atom for both neutron spectra. In an accelerated fuel test, the irradiation time required to reach the target fuel burnup can be reduced by a factor of 3 by using a small rodlet with a 45% smaller pellet diameter while maintaining the same linear power. Therefore, the time for data collection up to high burnup can be significantly reduced while maintaining the same temperature profile, which largely determines the material response. Tests of fuel rodlets of standard and compact size will be carried out in the Idaho National Laboratory’s Advanced Test Reactor (ATR), including full size and compact rodlets with varying gap sizes. By applying physics-based mechanistic modeling and simulation in accordance with the AFQ methodology, this type of compact rodlet testing in a thermal test reactor captures the necessary phenomena to test fuel material models up to high burnup and to simulate the expected impact of fast neutron radiation on the fuel in FMR operations. Finally, this approach to testing fast reactor fuels in existing thermal test reactors, paired with advanced physics-based mechanistic modeling and simulation, is expected to be applicable to a range of advanced fuels and will decrease the overall fuel qualification timeframe from decades to years.

Advanced test reactor (ATR)↗

DOE OSTI2013

A Cask Processing Enclosure for the TRU Waste Processing Center - 13408

This paper will discuss the key elements considered in the design, construction, and use of an enclosure system built for the TRU Waste Processing Center (TWPC). The TWPC system is used for the repackaging and volume reduction of items contaminated with radioactive material, hazardous waste and mixed waste. The modular structural steel frame and stainless steel skin was designed for rapid field erection by the use of interchangeable self-framing panel sections to allow assembly of a sectioned containment building and for ease of field mobility. The structure was installed on a concrete floor inside of an outer containment building. The major sections included an Outer Cask Airlock, Inner Cask Airlock, Cask Process Area, and Personnel Airlocks. Casks in overpacks containing transuranic waste are brought in via an inter-site transporter. The overpack lid is removed and the cask/overpack is transferred into the Outer Cask Airlock. A contamination cover is installed on the overpack body and the Outer Cask Airlock is closed. The cask/overpack is transferred into the Inner Cask Airlock on a cask bogie and the Inner Cask Airlock is closed. The cask lid is removed and the cask is transferred into the Cask Process Area where it is placed on a cask tilting station. Once the Cask Processing Area is closed, the cask tilt station is activated and wastes are removed, size reduced, then sorted and re-packaged into drums and standard waste boxes through bag ports. The modular system was designed and built as a 'Fast Track' project at IP Systems in Broomfield Colorado and then installed and is currently in use at the DOE TWPC located near Oak Ridge, Tennessee. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Building a Computational and Experimental Rapid Response Pipeline to Counter the Coronavirus Disease 2019 Outbreak and Emerging Biothreats

The COVID-19 pandemic underscored the promise of monoclonal antibody-based prophylactic and therapeutic drugs, especially where protective candidates can be rapidly identified or developed for emerging biothreats and escape variants. Current cutting-edge technologies for this purpose still rely on pathogen-exposed convalescent volunteers and a large screening effort to find a proverbial needle in a haystack. Computational design of protective antibodies based on pre-existing templates skips those requirements and allows for greater control over the breadth and target epitope, while also co-optimizing for potency and developability or other biophysical characteristics. We approached this problem by building and expanding an in vitro experimental rapid antibody production and characterization pipeline to support development of an autonomous, closed loop, active learning software system based on structural simulation and ground truth experimental data to design and evaluate antibody antigen interactions. Starting from early in the pandemic, we targeted SARS-CoV-2, the causative agent of COVID-19, by re-purposing neutralizing antibodies against SARS-CoV-1 that had been identified in the wake of that outbreak in the early 2000’s. We successfully re-targeted three different anti-SARS-CoV-1 antibodies to neutralize SARS-CoV-2 in vitro, where the antibodies were generated externally and tested through conventional binding and neutralization assays internally or with collaborators. As antibodies were identified from the blood of humans infected with SARS-CoV-2, we shifted to collaborate with academic partners to develop improved versions of their human-derived antibodies. This work reached its most important stage in rapid response to the emergence of the Omicron variant of concern (VOC) in late 2021. In a matter of weeks, enabled by on demand innovation to our screening pipeline, we computationally designed and experimentally characterized derivative antibodies of COV2-2130, one of two antibodies from Vanderbilt that form the basis of the AstraZeneca Evusheld prophylactic drug product. This drug product suffers a serious loss of efficacy against Omicron BA.1 and BA.1.1, the first Omicron strains. Due to tight integration of computational design and experimental evaluation, we were able to identify a pair of designs with potent neutralization of the main targets Omicron BA.1 and BA.1.1; but also the earlier Delta variant, and subsequent Omicron strains including BA.2, BA.4, BA.5, and BA.2.75, demonstrating that our multi-target design process can, by its nature, produce robust antibody designs that strictly improve over the parental antibody. These results, recognized by a 2022 Director’s Science and Technology award, have enabled the follow-on GUIDE program, to commence in FY23. While earlier design campaigns were substantially outsourced, we have engineered better and faster processes internally to better compliment, calibrate, and speed computational designs. As part of the follow-on GUIDE program, we will stand up a rapid and high-throughput antibody production and characterization facility staffed with the expertise and capabilities to foster our current collaboration across PLS and ENG as well as other partnerships toward computational design of biologics.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

A New Design Consideration for Bidirectional Resonant Converters

This paper introduces innovative design considerations for a bidirectional resonant converter, optimized for Electric Vehicle (EV) charging and vehicle-togrid (V2G) applications. By eliminating the need for complex voltage or current gain functions, the proposed design greatly simplifies the development process, making it more accessible for manufacturers and system integrators. This approach not only reduces engineering time and resource investment but also accelerates time-to-market, giving stakeholders a competitive edge in rapidly expanding EV infrastructure markets. In addition, the streamlined design ensures soft switching at maximum output power, leading to higher efficiency and improved durability, which translates to lower operating costs and a longer service life for EV charging equipment. These benefits provide a clear pathway to more cost-effective, scalable, and sustainable EV charging and V2G solutions, enhancing value for stakeholders by facilitating smoother integration into the grid and supporting energy resilience. To validate the benefits, a 60 kW bidirectional charger with a flexible input range of 700−900VDC and an output range of 400−1250VDC was developed, underscoring the design's adaptability and potential for large-scale implementation.

Asa, Erdem [ORNL] (ORCID:0000000190884812)↗

DOE OSTI2020

High-throughput experimentation for microstructural design in additively manufactured 316L stainless steel

In the present study, a combination of high-throughput (HT) and low-throughput (LT) techniques was used to rapidly determine the processing window and generate processing maps for Selective Laser Melting (SLM) of 316L stainless steel. The HT method includes the fabrication of hundreds of hex nut-shaped specimens, each processed with a unique combination of laser power, scanning speed, and hatch spacing. An easily removable scaffolding permitted rapid sample extraction from the base plate, thus saving machining cost and time. Hardness and immersion density measurements were used for HT characterization to identify a processing window for maximum strength and density. Within the defined processing window, a low-throughput (LT) microstructural interrogation of specimens were performed. The microstructural analysis included quantification at various length scales (i.e., grains size and morphology, texture, primary dendrite arm spacing, and melt pool geometry analysis). Microstructure-based processing maps as a function of volumetric energy density were generated. The combination of HT and LT methods produced a predictive relationship between hardness and primary dendrite arm spacing using a Hall-Petch relationship. A model is proposed to explain the dependence of microstructure on the melt pool geometry. Here, the HT method can be applied for the microstructural design of SLM-fabricated components in other alloys.

316L stainless steel↗

DOE OSTI2016

Directed self-assembly of block copolymer films on atomically-thin graphene chemical patterns

Directed self-assembly of block copolymers is a scalable method to fabricate well-ordered patterns over the wafer scale with feature sizes below the resolution of conventional lithography. Typically, lithographically-defined prepatterns with varying chemical contrast are used to rationally guide the assembly of block copolymers. The directed self-assembly to obtain accurate registration and alignment is largely influenced by the assembly kinetics. Furthermore, a considerably broad processing window is favored for industrial manufacturing. Using an atomically-thin layer of graphene on germanium, after two simple processing steps, we create a novel chemical pattern to direct the assembly of polystyreneblock-poly(methyl methacrylate). Faster assembly kinetics are observed on graphene/germanium chemical patterns than on conventional chemical patterns based on polymer mats and brushes. This new chemical pattern allows for assembly on a wide range of guiding periods and along designed 90° bending structures. We also achieve density multiplication by a factor of 10, greatly enhancing the pattern resolution. Lastly, the rapid assembly kinetics, minimal topography, and broad processing window demonstrate the advantages of inorganic chemical patterns composed of hard surfaces.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Safeguards Modeling for Advanced Nuclear Facility Design.

Future nuclear fuel cycle facilities will see a significant benefit from considering materials accountancy requirements early in the design process. The Material Protection, Accounting, and Control Technologies (MPACT) working group is demonstrating Safeguards and Security by Design (SSBD) for a notional electrochemical reprocessing facility as part of a 2020 Milestone. The idea behind SSBD is to consider regulatory requirements early in the design process to provide more optimized systems and avoid costly retrofits later in the design process. Safeguards modeling, using single analyst tools, allows the designer to efficiently consider materials accountancy approaches that meet regulatory requirements. However, safeguards modeling also allows the facility designer to go beyond current regulations and work toward accountancy designs with rapid response and lower thresholds for detection of anomalies. This type of modeling enables new safeguards approaches and may inform future regulatory changes. The Separation and Safeguards Performance Model (SSPM) has been used for materials accountancy system design and analysis. This paper steps through the process of designing a Material Control and Accountancy (MC&A) system, presents the baseline system design for an electrochemical reprocessing facility, and provides performance metrics from the modeling analysis. The most critical measurements in the electrochemical facility are the spent fuel input, electrorefiner salt, and U/TRU product output measurements. Finally, material loss scenario analysis found that measurement uncertainties (relative standard deviations) for Pu would need to be at 1% (random and systematic error components) or better in order to meet domestic detection goals or as high as 3% in order to meet international detection goals, based on a 100 metric ton per year plant size.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗