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At least 775 records · Page 43

Literature Review of Documented Persistent Secondary Uranium Sources at DOE LM Sites

The U.S. Department of Energy Office of Legacy Management (LM) has the responsibility to protect human health and the environment at 101 legacy uranium sites across the nation by implementing long-term surveillance and maintenance requirements. Included in these responsibilities is to provide for the safe and environmentally sound disposal, long-term stabilization, and control of uranium mill tailings in a manner that minimizes or eliminates radiation health hazards to the public at 21 Uranium Mill Tailings Radiation Control Act (UMTRCA) Title I sites; 6 UMTRCA Title II sites; and 9 Comprehensive Environmental Response, Compensation, and Liability Act/Resource Conservation and Recovery Act sites. These sites are former uranium mills (processing sites), or sites with wastes from processing sites encapsulated in engineered disposal cells (disposal sites), or sites where components of atomic weapons were manufactured. During site characterization, groundwater contamination was often discovered and evaluated or modeled for future movement with the inclusion of uranium sorption in the groundwater plume. Much of this original work did identify uranium processing wastes as the original contaminant source. However, more recent work has identified the existence and influence of persistent secondary uranium sources that may prevent uranium in groundwater from attenuating as quickly as initial evaluations or modeling indicated. By understanding these processes, better decisions can be made to choose the appropriate remediation and closure strategies, identify long-term surveillance and maintenance activities, and more accurately estimate life-cycle costs. The purpose of this report is to summarize the literature available on documented persistence secondary uranium sources at LM sites as part of the Applied Studies and Technology Persistent Secondary Contaminant Sources Project.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

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↗

Unconventional Catalytic Approaches to Ammonia Synthesis

Ammonia is a critically important industrial chemical and is largely responsible for sustaining the growing global population. To provide ammonia to underdeveloped regions and/or regions far from industrial production hubs, modular systems have been targeted and often involve unconventional production methodologies. These novel approaches for ammonia production can tap renewable resources at smaller scales located at the point of use, while decreasing the CO 2 footprint. Plasma-assisted catalysis and electrochemical ammonia synthesis have promise owing to their atmospheric pressure and low-temperature operation conditions and the ability to construct units at scales desired for modularization. Fundamental and applied studies are underway to assess these processes, although many unknowns remain. In this review, we discuss recent developments and opportunities for unconventional ammonia synthesis with a focus on plasma-stimulated systems.

42 ENGINEERING↗

A microscopic and crystallographic study of proton irradiated alloy 718

Solution annealing and age hardening are important processes for achieving good engineering and chemical properties of alloy 718. The composition of alloy 718 also plays an important role as it can affect both mechanical (γ”- and γ’-phase formation) and irradiation behaviors. Therefore, in this study five different sets of alloy 718 samples with two different chemical compositions were fabricated using different processing conditions and irradiated up to 4 dpa. Based on the effects of irradiation on the microstructural data of γ”- and γ’-phases, irradiation-induced dislocation statistics, and crystallographic data, it can be inferred that the samples processed at high solution annealing temperature (1093°C) behave better under irradiation compared to the samples processed at low solution annealing temperatures (945 and 1065°C).

36 MATERIALS SCIENCE↗

Mixed-Integer Linear Programming Formulation with Embedded Machine Learning Surrogates for the Design of Chemical Process Families

In previous work, we introduced process family design. The main idea is to design a platform of common elements, and, allowing us to capture additional cost savings, simultaneously design a family of processes, and reducing both engineering and deployment timelines. We formulate this as an optimization problem, specifically a nonlinear generalized disjunctive program (GDP). We have proposed two approaches for reformulating and solving this problem: one based on full-discretization of the design space and one that uses Machine Learning (ML) surrogates to replace the nonlinear process models. Using ML surrogates to predict required system costs and performance indicators allows us to reformulate the nonlinearities in the GDP generate an efficient MILP formulation. In this work, we apply the ML surrogate approach to two case studies. One case study involves designing a family of carbon capture systems to cover a set of different flue gas flow rates and inlet CO 2 concentrations, where we consider the absorber and stripper as common unit module types. The second case study focuses on a water-desalination process, where we design a family of these processes for a variety of salt concentrations and flow rates. In both of these case studies, we demonstrate a scalable optimization approach that enables the design of multiple processes simultaneously, reducing the time-to-market and overall costs by maximizing the cost savings due to both economies of scale and economies of numbers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Generalized Information Architecture for Managing Requirements in IBM's Rational DOORS® Application

When a requirements engineering effort fails to meet expectations, often times the requirements management tool is blamed. Working with numerous project teams at Sandia National Laboratories over the last fifteen years has shown us that the tool is rarely the culprit; usually it is the lack of a viable information architecture with well-designed processes to support requirements engineering. This document illustrates design concepts with rationale, as well as a proven information architecture to structure and manage information in support of requirements engineering activities for any size or type of project. This generalized information architecture is specific to IBM's Rational DOORS (Dynamic Object Oriented Requirements System) software application, which is the requirements management tool in Sandia's CEE (Common Engineering Environment). This generalized information architecture can be used as presented or as a foundation for designing a tailored information architecture for project-specific needs. It may also be tailored for another software tool.

Aragon, Kathryn Mary↗

Butyric acid: Applications and recent advances in its bioproduction

Butyric acid is an important C4 organic acid with broad applications. It is currently produced by chemosynthesis from petroleum-based feedstocks. However, the fermentative production of butyric acid from renewable feedstocks has received growing attention because of consumer demand for green products and natural ingredients in foods, pharmaceuticals, animal feed supplements, and cosmetics. In this review, strategies for improving microbial butyric acid production, including strain engineering and novel fermentation process development are discussed and compared regarding product yield, titer, purity and productivity. Future perspectives on strain and process improvements for butyric acid production are also discussed.

59 BASIC BIOLOGICAL SCIENCES↗

Fuel element design and analysis for potential LEU conversion of the Advanced Test Reactor

This study provides a summary of the status of the design process for a low-enrichment replacement for the high-enrichment fuel that has historically been used in the Advanced Test Reactor (ATR) at Idaho National Laboratory. Under current long-term Department of Energy policy, the ATR will be converted to operate using low-enrichment fuel by 2030. To this end, an engineering evaluation and design process has been underway for more than ten years. Initially performed as a series of scoping studies for different design options, the last five years have seen a transition to a formal Safety-in-Design approach to the design and safety evaluation process. This paper focuses on such efforts in progress since 2012 to identify pre-conceptual and conceptual design candidates for ATR conversion. The Enhanced LEU Fuel (ELF) design is selected as the most promising conceptual design. Analyses and trade-off studies performed that led to that selection are described. Analysis of certain aspects of core performance for an ELF-fueled core relative to the current high-enrichment fuel show that only small and manageable changes to core operations will be necessary to support conversion of ATR to low-enrichment fuel.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Success Path Method: Conformance with Safety Management Systems

All industrial facilities deal with safety hazards such as equipment failures, chemical and toxic releases, and fires and explosions just to name a few. A disciplined framework for managing the integrity of operating systems and processes that handle hazardous substances by applying good design principles, engineering, and operating practices is called process safety. The goal of such framewoks is to prevent the release of energy or material that could cause harm to people or damage to equipment and/or environment. Process safety covers all aspects of facility operation also including design, maintenance, and human and organizational factors that could possibly have effect on process safety. As it will be seen from the discussion below, process safety is just one of the pieces of the much bigger matter, a safety culture. Many industries have long recognized the importance of safety culture in their day-to-day operation. Although the definition of safety culture can slightly differ from organization to organization, in general, a safety culture is how things are done to demonstrate a commitment to safety by everyone involved. An organization acquires safety culture over time as the product of individual and group values, actions, and behaviors toward overall safety. It is important to note that safety culture should not be viewed as some static state that an organization wants to reach. It is more like a constantly evolving level of “how things are done when nobody is watching.” Safety culture is an inherent characteristic of an organization, it is always present, but the level can range on a continuum from undesirable to desirable or more commonly used, from negative to positive. An example for an undesirable, negative safety culture would be a company in which accidents resulting in harm (physical and/or emotional) of its employees, equipment or surrounding environment and community occur frequently. At the other end of the spectrum would be a company in which such accidents are rare or do not occur at all (desired or positive safety culture). Every company/industry exists somewhere within this spectrum.

42 ENGINEERING↗

Insights into the Morphology and Kinetics of Growth of Silver Metal–Organic Nanotubes

The kinetics of the formation of novel porous metal organic nanotubes, [Ag2(4,4 -(1,4-(xylene)diyl)bis- (1,2,4-triazole) (NO3)2] NMP, was investigated by means of ex-situ time-resolved small-angle X-ray scattering (SAXS) and scanning electron microscopy (SEM). The SAXS results were modeled using the Gualtieri model, which decouples the nucleation and growth processes giving additional insight into the crystal formation mechanism. The results show that the semirigid 4,4 -(1,4-(xylene)diyl)bis(1,2,4-triazole) ligand (L) binds with silver ions, adopting a seesaw geometry to form a polydisperse isotropic framework immediately after mixing the ligands and metal ions. In addition, the SEM imaging demonstrates that the microcrystals grow anisotropically, with nucleation along the edge of the 3D aggregate. These combined data demonstrate that the growth of this MONT occurs in two steps: a rapid formation of an isotropic porous structure immediately after mixing the reactant, which then develops anisotropically as the aggregates of nanorods grow in a preferred direction. The anisotropic growth of the crystal is autocatalytic and determined by the rate of nucleation of new growth sites on the crystals. Moreover, the results of this analysis elucidate, for the rst time, the exact order of the competing processes that occur in the synthesis of these MONTs, showing that their anisotropic growth occurs on the initial 3D aggregate and appears to be directed by the interplay between the surface energies that exist during the MONT formation process. This insight is crucial to the use of crystal engineering to guide the crystal formation processes in MONTs to targeted structures, properties, and applications.

36 MATERIALS SCIENCE↗

A Hybrid Heavy-Duty Diesel Power System for Off-Road Applications - Concept Definition

A multi-year Power System R&D project was initiated with the objective of developing an off-road hybrid heavy-duty concept diesel engine with front end accessory drive-integrated energy storage. This off-road hybrid engine system is expected to deliver 15-20% reduction in fuel consumption over current Tier 4 Final-based diesel engines and consists of a downsized heavy-duty diesel engine containing advanced combustion technologies, capable of elevated peak cylinder pressures and thermal efficiencies, exhaust waste heat recovery via SuperTurbo™ turbocompounding, and hybrid energy recovery through both mechanical (high speed flywheel) and electrical systems. The first year of this project focused on the definition of the hybrid elements using extensive dynamic system simulation over transient work cycles, with hybrid supervisory controls development focusing on energy recovery and transient load assist, in Caterpillar’s DYNASTY™ software environment. Three key off-road applications were the focus of the hybrid concept definition with an aim of understanding the system’s modular capability for the diverse off-road heavy-duty market. Core engine performance 1D and 3D simulations isolated the efficiency contributions from the downsized engine, turbocompounding, and in-cylinder thermal barrier coatings. A fuel consumption improvement range of 14 to 24% was predicted, resulting in successful project progression to the design and experimental validation phase. Furthermore, an overview of the experimental engine and hybrid system status concludes the discussion along with the multi-year project’s next steps.

33 ADVANCED PROPULSION SYSTEMS↗

Project DarkStar: Vision for LLNL in 2030

DarkStar was a Strategic Initiative (FY2021-FY2024) to investigate applications of Artificial Intelligence (AI) and Machine Learning (ML) to scientific problems of complex hydrodynamics, shockwave physics and energetic materials. The research focused on physics and engineering design as a process that can be tremendously accelerated through merging AI with advanced physics simulation on exascale-class platforms, and to experimentally validate this revolutionary new approach through dynamic materials campaigns. A central thread of scientific inquiry was in the application of AI to enable human understanding of how to control hydrodynamic instability (which has impacts to areas such as inertial confinement fusion) via engineering features and time-dependent sources. Motivated by an unfinished line of research started by Dr. Johnny von Neumann, AI-enabled simulation approaches were developed that allowed DarkStar researchers to uncover several ground-breaking discoveries regarding hydrodynamic instability, including how to completely suppress Richtmyer-Meshkov instability (RMI). These S&T discoveries, along with other advances, have shown the way for an entirely new approach to time-dependent problems known as inverse design – the idea that complex systems can be developed directly from a final state that is to be achieved and resolve the initial design via satisfying several constraints simultaneously via AI/ML. Through experimental campaigns conducted across a wide range of facilities in the NNSA complex (the High Explosive Application Facility at LLNL, the Dynamic Compression Sector/Advanced Photon Source at Argonne National Lab, and Special Technologies Laboratory at MSTS) the radical new AI/ML approach to engineering complex material dynamics was verified, establishing a new field of study within the realm of shock physics. As advanced manufacturing capabilities continue to develop, the great importance of inverse design as a means to apply that technology effectively for NNSA missions will feature prominently over this decade. DarkStar has positioned NNSA as a world-leader in this newly emerging cross-disciplinary area of AI methods for advanced physics simulation and pioneered multiple novel approaches that have enabled the broader scientific community. By allowing us to see past the horizon, to 2030 and beyond, DarkStar has illuminated the vast potential of AI/ML to impact a wide range of new national security missions and, consequently, multiple areas of further research have already emerged across the NNSA and DOD complex.

42 ENGINEERING↗

Accelerating Manufacturing of Powder-Processed Strong, Lightweight and Thermally Stable Bulk Nanocrystalline Al Alloys via Engineered Interface States

The overarching goal of this program is to develop an integrated materials by design framework enabling a simple, scalable, and efficient manufacturing route for thermally stable nanocrystalline Al-based alloys with high specific strength over a range of service temperatures. The central scientific principle underpinning this program is the elucidation, and ultimately implementation in novel alloy design, of unique interfacial structures and chemistries driven by segregation in multi-component systems that give rise to unprecedented processability and properties. This program targeted nanocrystalline Al-based ternary alloys produced by mechanical alloying of powders followed by compaction and sintering with hot pressing, which are inherently scalable and inexpensive manufacturing routes, but when applied to nanocrystalline alloys are usually plagued by low density and/or poor retention of the intended nanostructures during processing. This program successfully demonstrated manufacturing of a bulk (>1 cm 3 ) nanocrystalline Al-based alloy with a combination of thermal stability, high temperature strength retention, and specific strength that exceeds the current-state-of-the-art of Al alloys. It is anticipated that the greatest technological impact will occur by demonstration of rapid and scalable manufacturing of bulk nanocrystalline Al alloys with exceptional thermal stability and mechanical performance, thus enabling increased energy efficiency in high performance power generation systems via: (i) replacement of existing components with lightweight Al-based alloys and (ii) increasing operating temperatures with property retention. The program focused on the development of a simple and efficient manufacturing route for thermally stable nanocrystalline Al-based alloys with high specific strength over a range of service temperatures. The program is expected to have direct impact on scalable and economic manufacturing of bulk nanocrystalline alloys. This program profited from the recent discovery by the project team of segregation-driven amorphous intergranular films in nanocrystalline metallic alloys that can be kinetically frozen-in at sub-solidus temperatures. These interfacial states (also known as amorphous complexions) comprise a large fraction of the total material in nanocrystalline alloys and are responsible for two beneficial characteristics that anchor the proposed work: (1) activated sintering leading to high density and (2) retained nanostructures leading to high strengths that approach a substantial fraction of the theoretical limit. More specifically, these engineered interfaces led to a three-fold benefit: (i) high-throughput materials processing with low energy budget and cost, (ii) exceptional thermal stability, and (iii) high specific strength at both room temperature and intermediate temperatures experienced during service.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Reverse engineering nuclear properties from rare earth abundances in the r process

The bulk of the rare earth elements are believed to be synthesized in the rapid neutron capture process or r process of nucleosynthesis. The solar r-process residuals show a small peak in the rare earths around $A\sim 160$, which is proposed to be formed dynamically during the end phase of the r process by a pileup of material. This abundance feature is of particular importance as it is sensitive to both the nuclear physics inputs and the astrophysical conditions of the main r process. Here, we explore the formation of the rare earth peak from the perspective of an inverse problem, using Monte Carlo studies of nuclear masses to investigate the unknown nuclear properties required to best match rare earth abundance sector of the solar isotopic residuals. When nuclear masses are changed, we recalculate the relevant β-decay properties and neutron capture rates in the rare earth region. The feedback provided by this observational constraint allows for the reverse engineering of nuclear properties far from stability where no experimental information exists. We investigate a range of astrophysical conditions with this method and show how these lead to different predictions in the nuclear properties influential to the formation of the rare earth peak. Finally, we conclude that targeted experimental campaigns in this region will help to resolve the type of conditions responsible for the production of the rare earth nuclei, and will provide new insights into the longstanding problem of the astrophysical site(s) of the r process.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Upscaling ab-initio chemistry models to non-equilibrium flow simulations

Thermochemical nonequilibrium is generated by hypersonic cruise vehicles, high speed combustion and detonations. Nonequilibrium interactions affect reaction rates and energy transfer that are critical for many engineering applications. Ab-initio potential energy surfaces can be used in quasi-classical trajectory (QCT) calculations to calculate state-specific dissociation rates and cross sections, as well as state-to-state energy exchange rates and cross sections. These rates and cross sections are needed for simulating such nonequilibrium flows. However, there are two main challenges in extending QCT calculations to modeling all chemical processes found in typical engineering flowfields. First, ab-initio surfaces for many collision partners are not available and when available their fidelity is not quantified. Second, state-to-state cross section datasets are typically on the order of 1000 4, , and are too large to be efficiently implemented in engineering simulations. This work focuses on O 2 +O interactions because of prevalence of oxygen in many engineering application; however, all of the models developed here may be applied to other diatom-atom interactions and can be extended to other diatom-diatom combinations. It is shown in this work that at temperatures between 2,500 and 20,000K, state-specific cross sections are not highly sensitive to potentials and a Morse additive pairwise (MAP) potential is proposed for modeling collisions for which ab-initio potentials are not available. Next, this work suggests an approach to model state-to-state cross sections based on maximum entropy considerations. The calculated cross sections are fit to a new model with just 8 parameters, which can be easily scaled up to flow simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Integrated Flue Gas Purification and Latent Heat Recovery for Pressurized Oxy-Combustion (Final Scientific/Technical Report)

Pressurized oxy-combustion has been identified by DOE as a transformational technology for coal power with carbon capture due to the advantages that are realized when the combustion process is pressurized. The staged pressurized oxy-combustion (SPOC) process is particularly attractive as the efficiency of the process is almost 6 percentage points greater than that of first generation oxy-combustion. A critical component of the SPOC process, and potentially other pressurized combustion processes, is the Direct Contact Cooler (DCC) where the latent heat of the flue gas moisture is recovery to improve plant efficiency while simultaneously removing SO x and NO x from the flue gas, so that the FGD and de-NO x processes can be eliminated, and the cost of electricity minimized. The objective of this R&D effort was to advance the TRL of the DCC technology, which included performance testing at a 100 kW scale to validate the process and obtain key engineering data for scale-up. A collateral objective was to study the gas- and liquid-phase kinetics, and the development of a systematic chemical mechanism validated by experimental data. Experiments in a bench-scale stirred reactor provided an updated understanding of the liquid chemistry and the effects of temperature and pH. This information was used to develop a reduced reaction mechanism, which was subsequently incorporated in an ASPENbased process model, to allow for evaluation of the DCC at full scale. A small-pilot DCC column was designed, constructed and tested using simulated flue gas at the pressurized oxy-combustion test facility at Washington University in St. Louis. In the majority of tests, the SO 2 capture approached 100%, making the NO x capture the primary metric of capture efficiency. An NO x capture efficiency of 90% was achieved when the gas residence time was 95 seconds, demonstrating that high capture rates can be attained with reasonable reactor size. At higher temperatures (up to 200°C inlet gas temperature) the total NO x scrubbing efficiency was reduced by approximately 10% (compared to room temp.) and this was attributed to a reduced NO oxidation rate. A significant amount of SO 2 was present in the gas outlet (10%) only when the temperature was high and the N:S ratio was low (N/S < 1), which highlights the necessity of controlling the NOx concentration in the flue gas for complete sulfur scrubbing. After incorporated our optimized chemical mechanism into an ASPEN process model, various full-scale configurations of the DCC were evaluate, and the results indicate that the proposed DCC can accomplish its intended goals at full scale and at a modest size. Thus, the results of this project indicate that the DCC is a promising technology for recovery of the latent heat of the moisture in the flue gas while simultaneously scrubbing the nitrogen and sulfur oxides, thus enabling pressurized oxy-combustion, in general, and the SPOC process, in particular.

01 COAL, LIGNITE, AND PEAT↗

Achieving high rate performance in hybrid pristine-recycled cathodes using model-informed electrode designs

Direct recycling lithium-ion battery cathodes, a process that retains the engineered oxide structures from end-of-life materials, presents a cost-effective and energy-efficient alternative to other battery recycling methods. However, while direct-recycled cathodes have demonstrated performance comparable to that of pristine materials at low cycling rates, their high-rate performance remains uncertain. Morphology changes in cathode particles, a main mode of degradation, directly impact rate performance by limiting surface kinetics and solid-phase diffusion. If direct recycling processes do not sufficiently restore pristine-like morphologies, the recycled materials may retain structural defects that hinder high-rate performance. The present work uses a physics-based pseudo-2D model to simulate hybrid electrodes with pristine and artificially “aged/recycled” NMC materials to investigate potential impacts of incorporating performance-limited aged cathode materials into cells. The study highlights how differences in transport and kinetic properties can influence rate capabilities in mixed electrodes — particularly in high-loading cells in high-demand applications. However, model results also reveal a possible mitigation strategy via dual-layer electrode architectures with lower-performing materials positioned near the current collector. Simulations of 4.0 mAh cm −2 cells cycled at 4C using a dual-layer architecture provided approximately 5%–30% more capacity in constant-current protocols compared to homogeneously blended electrode architectures with the same loadings and mixed-material compositions. These findings highlight the importance of strategic electrode design in minimizing potential performance losses and facilitating the integration of recycled materials into high-performance batteries, advancing sustainable and cost-effective battery manufacturing.

25 ENERGY STORAGE↗

ICME Guided Development of Advanced Cast Aluminum Alloys for Automotive Engine Applications (ADAPA)

Project Objectives: To develop a new class of advanced, cost competitive aluminum casting alloys providing a 25% improvement in component strength relative to components made with A319 or A356 alloys using sand and semi-permanent casting processes for high-performance engine applications. To demonstrate the power of Integrated Computational Materials Engineering (ICME) tools for accelerating the development of new materials and processing techniques, as well as to identify the gaps in ICME capabilities. To develop comprehensive cost models to ensure that components manufactured with these new alloys do not exceed 110% of the cost using incumbents alloys A319 or A356. To develop a technology transfer and commercialization plan for deployment of these new alloys in automotive engine applications. The key targets and baseline are shown in the table below.

36 MATERIALS SCIENCE↗