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At least 577 records · Page 32

Transition Core Planning and Safety Analyses in Support of LEU Fuel Conversion of the University of Missouri Research Reactor (MURR)

The University of Missouri Research Reactor (MURR®) is one of six U.S. High Performance Research Reactors (USHPRR), including one critical facility, that is working with the National Nuclear Security Administration (NNSA) Office of Material Management and Minimization (M3) Reactor Conversion Program to convert from highly enriched uranium (HEU) to low-enriched uranium (LEU) fuel. The M3 Reactor Conversion USHPRR Project objectives include the development of LEU fuel element designs that will ensure safe reactor operations and to maintain the existing experimental performance of each facility. The work is being conducted through many inter-related activities being completed by four Project Pillars: Fuel Qualification (FQ), Fuel Fabrication (FF), Reactor Conversion (RC), and Cross Cutting (CC). A new type of LEU fuel based on an alloy of uranium-10 wt% molybdenum (U-10Mo) is expected to allow the conversion of those USHPRR, like MURR, requiring higher density fuels. The very-high-density LEU U-10Mo monolithic fuel is currently undergoing irradiation testing and post-irradiation examination under a planned and documented fuel qualification effort. The FQ Pillar will document fuel property and fuel performance data and qualify the fuel for use in these reactors. The FF Pillar is fabricating fuel for ongoing and future irradiation tests, as well as conducting fabrication demonstrations to validate or update preliminary fabrication assumptions. The FF Pillar is also working to develop and install commercial manufacturing capacity with the U-10Mo monolithic fuel to produce prototypic fuel. Working with the RC Pillar at Argonne, MURR has progressed through a preliminary fuel element design using preliminary data for the proposed monolithic alloy of U-10Mo. Analyses were completed in previous work that found for typical equilibrium operations with the preliminary LEU fuel element design, in conjunction with a power uprate to 12 MW and appropriate changes to the MURR Limiting safety system settings (LSSS), MURR will have adequate margins to safety for steady-state operations and postulated transient accidents and will have experimental performance in key locations that meets or exceeds current operations with HEU fuel. The purpose of this work is to develop a sequence of transition cycles that will enable MURR to transition from operation with the reactor core loaded with fresh LEU fuel elements only to typical equilibrium operations with mixed-burnup cores following conversion while meeting operational requirements on safety and experimental performance. It is expected that the use of fresh LEU fuel at conversion and subsequent low burnup of the LEU fuel elements that will initially be available for use following conversion will result in critical control blade positions that will substantially change the axial power distribution in the core and the neutron flux available in key experimental locations relative to equilibrium LEU operations. Given the constraints of MURR safety margins, operational practices, and production and research, a novel method has been developed to identify a transition sequence that minimizes the time MURR operates atypically compared to the current prototypic cycles using HEU fuel. The proposed transition sequence moves quickly to the same sort of equilibrium cycles for the LEU fuel that have already been evaluated in documented preliminary safety analyses. Although shifting the neutron flux peak to the lower half of the core during initial cycles with LEU at 12 MW reduces the experiment performance in some key locations relative to current HEU operations at 10 MW, all LEU cores provide an average performance that meets or exceeds that of HEU. An LEU cycle is reached that meets or exceeds the level of experimental performance predicted for current HEU and equilibrium LEU operations in more than 450 key locations identified by a reactor specialist at MURR by the 23rd cycle following conversion and that afterwards will enable MURR to consistently meet its experimental performance requirements. The proposed transition sequence only requires the fabrication of 34 fresh LEU elements in the first year of operation and does not exceed the anticipated availability of fresh elements that can be produced by the fuel fabricator. By the third year after conversion, 22 fresh LEU elements will be required each year, which is the same as expected for equilibrium LEU operations and the same as current operations with HEU fuel. The proposed transition sequence thus combines a relatively short time period before equilibrium burnup is achieved, a temporary increase of fuel elements needed annually relative to typical operations that are within the production capabilities of the fuel fabricator, and demonstrates comparable experimental performance of the LEU cores relative to current HEU operations. Further measures may be taken to reduce any initial experimental performance penalty even further, where possible, by repositioning certain experiments to leverage the increased performance in the lower axial experimental positions in the initial cycles following conversion or leaving the experiments in the irradiation facilities longer in order to achieve the required neutron fluence. This analysis may require refinement depending on the experimental facilities in use at the time of conversion. Nonetheless, the results presented here, including the experimental performance, core burnup, and critical control blade positions throughout the transition cycles, show that the proposed transition cycle fuel management patterns are consistent with what is expected and desired for MURR operation with LEU U-10Mo fuel. Detailed core power distributions from the neutronics models were also used to evaluate safety margins during steady-state operations for the selected transition cycles and the equilibrium LEU core. It is shown that there are adequate safety margins for both steady-state operations and postulated accident scenarios. For the steady-state operations with the preliminary LEU fuel element design the analysis predicts at least 2.49 MW margin to the onset of flow instability at the LSSS power of 15 MW. Considering the LSSS power is 125% of full license power, the margin to OFI is sufficient. In addition, the critical heat flux ratio at LSSS power is well above the requirement of CHFR > 2.0 from NUREG-1537 for all considered cases. For postulated transient accidents, the minimum margin to the fuel temperature safety limit is at least 109 °C. In summary, the proposed sequence of core loadings for MURR operations following conversion to LEU fuel and a power uprate to 12 MW provides sufficient safety margins for both steady-state operations and postulated transient accidents during a proposed sequence of transition cycles to equilibrium operations. Analysis has shown that there are some local experimental performance penalties during the initial cycles. Although there are local shifts in the experimental performance, on average all LEU cores at 12 MW have equal or higher performance than HEU at 10 MW. Temporary adjustments are being planned that will produce suitable experimental performance during these cycles. The results indicate that for the equilibrium LEU core the experimental performance exceeds that of current HEU operations in all key locations while also demonstrating sufficient safety margins.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Development of a new control rod drive mechanism design for the ISU AGN-201M reactor

The Aerojet General Nucleonics (AGN) model 201-Modified, known as the AGN-201M reactor, plays an essential role in the educational and research activities at Idaho State University (ISU). The ISU AGN-201M's original Control Rod Drive Mechanism (CRDM) has been in operation for more than fifty years with no large-scale redesigns. The CRDM is required to eject the fuel rods within one second during a SCRAM event (also known as a 'reactor trip') and adjust the control rods' insertion speed, and keeps the rod insertion sequence correct. The existing control rod drive mechanisms meet these criteria but experience a few concerns due to aging. Concerns include complex maintenance and costly repairs for old electromechanical components, rod position feedback errors, and the impediment of the plate during a SCRAM due to binding of the lead screws of the existing mechanism. During a binding event, the drive mechanism becomes locked, preventing the control rod's magnetic plate from moving in or out under the reactor's normal and emergency operating conditions. Although, the binding has no effect on the ability of the rod to exit the core during the SCRAM. To counteract the concerns and issues with the current CRDM, a new design has been proposed using newer components and a simplified design. The new design utilizes more advanced electric and mechanical components that are commercially available. The new CRDM system is divided into four main aspects: (1) control rod movement design (motor, lead screw, guide rods), (2) control rod ejection (springs, electromagnet), (3) control rod position and feedback (position transducer, microswitches), and (4) material selection and structural analysis. The new design aims to reduce the overall complexity and probability of failure to improve the reactor's overall reliability. With proper material selection and improved structural design, the new drives are lighter with little to no change in structural integrity. The new control rod drive mechanism eliminates binding scenarios by using a single lead screw and implementing additional guide rods. An advanced linear position sensor and microswitches replace the existing and aging synchro system for accurate rod position feedback resulting in better reactivity control. The new design meets the reactor's operational limits by having an average reactivity insertion of 0.065% Δk/k per second, which corresponds to a total control rod insertion time of 19.23 s, while the control rod's ejection time remains less than one second during a SCRAM event. The new design ensures the reactor's long-term viability for educational and research activities by increasing the reliability and safety of operation for years to come.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

X-ray Free Electron Laser Accelerator Lattice Design Using Laser-Assisted Bunch Compression

We report the start-to-end modeling of our accelerator lattice design employing a laser-assisted bunch compression (LABC) scheme in an X-ray free electron laser (XFEL), using the proposed Matter-Radiation Interactions in Extremes (MaRIE) XFEL parameters. The accelerator lattice utilized a two-stage bunch compression scheme, with the first bunch compressor performing a conventional bulk compression enhancing the beam current from 20 A to 500 A, at 750 MeV. The second bunch compression was achieved by modulating the beam immediately downstream of the first bunch compressor by a laser with 1-μm wavelength in a laser modulator, accelerating the beam to the final energy of 12 GeV, and compressing the individual 1-μm periods of the modulated beam into a sequence of microbunches with 3-kA current spikes by the second bunch compressor. The LABC architecture presented had been developed based on the scheme of enhanced self-amplified spontaneous emission (ESASE), but operated in a disparate regime of parameters. Enabled by the novel technology of the cryogenic normal conducting radiofrequency photoinjector, we investigated an electron beam with ultra-low emittance at the starting point of the lattice design. Our work aimed at mitigating the well-known beam instabilities to preserve the beam emittance and suppress the energy spread growth.

43 PARTICLE ACCELERATORS↗

Improved high-throughput screening technique to rapidly isolate Chlamydomonas transformants expressing recombinant proteins

Abstract The single-celled eukaryotic green alga Chlamydomonas reinhardtii has long been a model system for developing genetic tools for algae, and is also considered a potential platform for the production of high-value recombinant proteins. Identifying transformants with high levels of recombinant protein expression has been a challenge in this organism, as random integration of transgenes into the nuclear genome leads to low frequency of cell lines with high gene expression. Here, we describe the design of an optimized vector for the expression of recombinant proteins in Chlamydomonas , that when transformed and screened using a dual antibiotic selection, followed by screening using fluorescence activated cell sorting (FACS), permits rapid identification and isolation of microalgal transformants with high expression of a recombinant protein. This process greatly reduces the time required for the screening process, and can produce large populations of recombinant algae transformants with between 60 and 100% of cells producing the recombinant protein of interest, in as little as 3 weeks, that can then be used for whole population sequencing or individual clone analysis. Utilizing this new vector and high-throughput screening (HTS) process resulted in an order of magnitude improvement over existing methods, which normally produced under 1% of algae transformants expressing the protein of interest. This process can be applied to other algal strains and recombinant proteins to enhance screening efficiency, thereby speeding up the discovery and development of algal-derived recombinant protein products. Key points • A protein expression vector using double-antibiotic resistance genes was designed • Double antibiotic selection causes fewer colonies with more positive for phenotype • Coupling the new vector with FACS improves microalgal screening efficiency > 60%

59 BASIC BIOLOGICAL SCIENCES↗

Beam dynamics in independent phased cavities

Linear accelerators containing the sequence of independently phased cavities with constant geometrical velocity along each structure are widely used in practice. The chain of cavities with identical cell lengths is utilized within a certain beam velocity range, with subsequent transformation to the next chain with higher cavity velocity. Design and analysis of beam dynamics in this type of accelerator are usually performed using numerical simulations. A full theoretical description of particle acceleration in an array of independent phased cavities has not been developed. In the present paper, we provide an analytical treatment of beam dynamics in such linacs employing Hamiltonian formalism. We begin our analysis with an examination of beam dynamics in an equivalent traveling wave of a single cavity, propagating within accelerating section with constant phase velocity. We then consider beam dynamics in arrays of cavities, utilizing an effective traveling wave propagating along with the whole accelerator with the velocity of synchronous (reference) particle. The analysis concluded with the determination of the matched beam conditions. Finally, we present a beam dynamics study in 805 MHz Coupled Cavity Linac of the LANSCE accelerator facility.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

High-throughput functional variant screens via in vivo production of single-stranded DNA

Significance We report a methodology for the pooled construction of mutants bearing precise genomic sequence variations and multiplex phenotypic characterization of these mutants using next-generation sequencing (NGS). Unlike existing techniques depending on CRISPR-Cas–directed genomic breaks for genome editing, this strategy instead uses single-stranded DNA produced by a retron element for recombineering. This enables libraries of millions of elements to be constructed and offers relaxed design constraints which permit natural DNA or random variation to be used as inputs.

59 BASIC BIOLOGICAL SCIENCES↗

Deterministic chaos in the self-assembly of β sheet nanotubes from an amphipathic oligopeptide

The self-assembly of designed peptides into filaments and other higher-order structures has been the focus of intense interest because of the potential for creating new biomaterials and biomedical devices. These peptide assemblies have also been used as models for understanding biological processes, such as the pathological formation of amyloid. Here we investigate the assembly of an octapeptide sequence, Ac-FKFEFKFE-NH2, motivated by prior studies that demonstrated that this amphipathic beta strand peptide self-assembled into fibrils and biocompatible hydrogels. Using high-resolution cryoelectron microscopy (cryo-EM), we are able to determine the atomic structure for two different coexisting forms of the fibrils, containing four and five beta sandwich protofilaments, respectively. Surprisingly, the inner walls in both forms are parallel beta sheets, while the outer walls are antiparallel beta sheets. Our results demonstrate the chaotic nature of peptide self-assembly and illustrate the importance of cryo-EM structural analysis to understand the complex phase behavior of these materials at near-atomic resolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hierarchical semi-Markov models with duration-aware dynamics for activity sequences

Residential electricity demand at granular scales is driven by what people do and for how long. Accurately forecasting this demand for applications like microgrid management and demand response therefore requires generative models for activities that can produce realistic daily activity sequences, capturing both the timing and duration of human behavior. This paper develops a generative model of human activity sequences using nationally representative time-use diaries at a 10-min resolution. We use this model to quantify which demographic factors are most critical for improving predictive performance. We propose a hierarchical semi-Markov framework that addresses two key modeling challenges. First, a time-inhomogeneous Markov router learns the patterns of “which activity comes next.” Second, a semi-Markov hazard component explicitly models activity durations, capturing “how long” activities realistically last. To ensure statistical stability when data are sparse, the model pools information across related demographic groups and time blocks. The entire framework is trained and evaluated using survey design weights to ensure our findings are representative of the U.S. population. On a held-out test set, we demonstrate that explicitly modeling durations with the hazard component provides a substantial and statistically significant improvement over purely Markovian models. Furthermore, our analysis reveals a clear hierarchy of demographic factors: Sex, Day-Type, and Household Size provide the largest predictive gains, while Region and Season, though important for energy calculations, contribute little to predicting the activity sequence itself. The result is an interpretable and robust generator of synthetic activity traces, providing a high-fidelity foundation for downstream energy systems modeling.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Design of Broadly Cross-Reactive M Protein–Based Group A Streptococcal Vaccines

Group A streptococcal infections are a significant cause of global morbidity and mortality. A leading vaccine candidate is the surface M protein, a major virulence determinant and protective Ag. An obstacle to the development of M protein–based vaccines is the >200 different M types defined by the N-terminal sequences that contain protective epitopes. Despite sequence variability, M proteins share coiled-coil structural motifs that bind host proteins required for virulence. In this study, we exploit this potential Achilles heel of conserved structure to predict cross-reactive M peptides that could serve as broadly protective vaccine Ags. Combining sequences with structural predictions, six heterologous M peptides in a sequence-related cluster were predicted to elicit cross-reactive Abs with the remaining five nonvaccine M types in the cluster. The six-valent vaccine elicited Abs in rabbits that reacted with all 11 M peptides in the cluster and functional opsonic Abs against vaccine and nonvaccine M types in the cluster. We next immunized mice with four sequence-unrelated M peptides predicted to contain different coiled-coil propensities and tested the antisera for cross-reactivity against 41 heterologous M peptides. Based on these results, we developed an improved algorithm to select cross-reactive peptide pairs using additional parameters of coiled-coil length and propensity. The revised algorithm accurately predicted cross-reactive Ab binding, improving the Matthews correlation coefficient from 0.42 to 0.74. These results form the basis for selecting the minimum number of N-terminal M peptides to include in potentially broadly efficacious multivalent vaccines that could impact the overall global burden of group A streptococcal diseases.

60 APPLIED LIFE SCIENCES↗

A novel triple power cycle featuring a gas turbine cycle with supercritical carbon dioxide and organic Rankine cycles: Thermoeconomic analysis and optimization

In this study, a novel triple power cycle is proposed where waste heat from a gas turbine cycle is utilized to drive a supercritical carbon dioxide (s-CO 2 ) recompression cycle and a recuperative organic Rankine cycle (ORC) in sequence. A detailed thermoeconomic model is developed and implemented in MATLAB to evaluate the performance of the proposed cycle under different operating conditions. Optimization using a particle swarm optimization (PSO) algorithm is performed to minimize the levelized cost of electricity (LCOE) and determine the optimum design conditions of the cycle. The optimization results show that for a 100 MW cycle, the overall thermal efficiency and LCOE are 0.521 and $\$52.819$/MWh, respectively. The turbine inlet temperature of the gas turbine and s-CO 2 cycles are found as the most influential parameters on the thermoeconomic performance of the triple cycle. The proposed triple cycle shows an excellent waste energy recovery potential and superiority over a very thermodynamically efficient cycle from the literature, which included a gas turbine topping cycle and a complex cascade s-CO 2 power cycle used a bottoming cycle. As a result, the proposed triple cycle shows up to 0.9% points higher efficiency while it has fewer heat exchangers and turbomachinery than the cycle from the literature.

30 DIRECT ENERGY CONVERSION↗

Polarity-Tolerant Chloride Binding in Foldamer Capsules by Programmed Solvent-Exclusion

Persistent anion binding in a wide range of solution environments is a key challenge that continues to motivate and demand new strategies in synthetic receptor design. Though strong binding in low-polarity solvents has become routine, our ability to maintain high affinities in high-polarity solvents has not yet reached the standard set by nature. Anions are bound and transported regularly in aqueous environments by proteins that use secondary and tertiary structure to isolate anion binding sites from water. Inspired by this principle of solvent exclusion, we created a sequence-defined foldameric capsule whose global minimum conformation displays a helical folded state and is preorganized for 1:1 anion complexation. The high stability of the folded geometry and its ability to exclude solvent were supported by solid-state and solution phase studies. This capsule then withstood a 4-fold increase in solvent dielectric constant (εr) from dichloromethane (9) to acetonitrile (36) while maintaining a high and solvent-independent affinity of 10 5 M –1 ; ΔG ~ 28 kJ mol –1 . This behavior is unusual. More typical of solvent-dependent behavior, Cl – affinities were seen to plummet in control compounds, such as aryl-triazole macrocycles and pentads, with their solvent-exposed binding cavities susceptible to dielectric screening. Finally, dimethyl sulfoxide denatures the foldamer by putative solvent binding, which then lowers the foldamer’s Cl – affinity to normal levels. Furthermore, the design of this capsule demonstrates a new prototype for the development of potent receptors that can operate in polar solvents and has the potential to help manage hydrophilic anions present in the hydrosphere and biosphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Decoding the protein–ligand interactions using parallel graph neural networks

Abstract Protein–ligand interactions (PLIs) are essential for biochemical functionality and their identification is crucial for estimating biophysical properties for rational therapeutic design. Currently, experimental characterization of these properties is the most accurate method, however, this is very time-consuming and labor-intensive. A number of computational methods have been developed in this context but most of the existing PLI prediction heavily depends on 2D protein sequence data. Here, we present a novel parallel graph neural network (GNN) to integrate knowledge representation and reasoning for PLI prediction to perform deep learning guided by expert knowledge and informed by 3D structural data. We develop two distinct GNN architectures: $$\hbox {GNN}_{\mathrm{F}}$$ GNN F is the base implementation that employs distinct featurization to enhance domain-awareness, while $$\hbox {GNN}_{\mathrm{P}}$$ GNN P is a novel implementation that can predict with no prior knowledge of the intermolecular interactions. The comprehensive evaluation demonstrated that GNN can successfully capture the binary interactions between ligand and protein’s 3D structure with 0.979 test accuracy for $$\hbox {GNN}_{\mathrm{F}}$$ GNN F and 0.958 for $$\hbox {GNN}_{\mathrm{P}}$$ GNN P for predicting activity of a protein–ligand complex. These models are further adapted for regression tasks to predict experimental binding affinities and $$\hbox {pIC}_{\mathrm{50}}$$ pIC 50 crucial for compound’s potency and efficacy. We achieve a Pearson correlation coefficient of 0.66 and 0.65 on experimental affinity and 0.50 and 0.51 on $$\hbox {pIC}_{\mathrm{50}}$$ pIC 50 with $$\hbox {GNN}_{\mathrm{F}}$$ GNN F and $$\hbox {GNN}_{\mathrm{P}}$$ GNN P , respectively, outperforming similar 2D sequence based models. Our method can serve as an interpretable and explainable artificial intelligence (AI) tool for predicted activity, potency, and biophysical properties of lead candidates. To this end, we show the utility of $$\hbox {GNN}_{\mathrm{P}}$$ GNN P on SARS-Cov-2 protein targets by screening a large compound library and comparing the prediction with the experimentally measured data.

59 BASIC BIOLOGICAL SCIENCES↗

RNA nanotechnology to build a dodecahedral genome of single-stranded RNA virus

The quest for artificial RNA viral complexes with authentic structure while being non-replicative is on its way for the development of viral vaccines. RNA viruses contain capsid proteins that interact with the genome during morphogenesis. The sequence and properties of the protein and genome determine the structure of the virus. For example, the Pariacoto virus ssRNA genome assembles into a dodecahedron. Virus-inspired nanotechnology has progressed remarkably due to the unique structural and functional properties of viruses, which can inspire the design of novel nanomaterials. RNA is a programmable biopolymer able to self-assemble sophisticated 3D structures with rich functionalities. RNA dodecahedrons mimicking the Pariacoto virus quasi-icosahedral genome structures were constructed from both native and 2'-F modified RNA oligos. The RNA dodecahedron easily self-assembled using the stable pRNA three-way junction of bacteriophage phi29 as building blocks. The RNA dodecahedron cage was further characterized by cryo-electron microscopy and atomic force microscopy, confirming the spontaneous and homogenous formation of the RNA cage. The reported RNA dodecahedron cage will likely provide further studies on the mechanisms of interaction of the capsid protein with the viral genome while providing a template for further construction of the viral RNA scaffold to add capsid proteins for the assembly of the viral nucleocapsid as a model. Understanding the self-assembly and RNA folding of this RNA cage may offer new insights into the 3D organization of viral RNA genomes. Finally, the reported RNA cage also has the potential to be explored as a novel virus-inspired nanocarrier.

59 BASIC BIOLOGICAL SCIENCES↗

Genesis: A Compiler Framework for Hamiltonian Simulation on Hybrid CV-DV Quantum Computers

We introduce Genesis, the first compiler designed to support Hamiltonian Simulation on hybrid continuous-variable (CV) and discrete-variable (DV) quantum computing systems. Genesis is a two-level compilation system. At the first level, it decomposes an input Hamiltonian into basis gates using the native instruction set of the target hybrid CV-DV quantum computer. At the second level, it tackles the mapping and routing of qumodes/qubits to implement long-range interactions for the gates decomposed from the first level. Rather than a typical implementation that relies on SWAP primitives similar to qubit-based (or DV-only) systems, we propose an integrated design of connectivity-aware gate synthesis and beamsplitter SWAP insertion tailored for hybrid CV-DV systems. We also introduce an OpenQASM-like domain-specific language (DSL) named CVDV-QASM to represent Hamiltonian in terms of Pauli-exponentials and basic gate sequences from the hybrid CVDV gate set. Genesis has successfully compiled several important Hamiltonians, including the Bose-Hubbard model, Z2−Higgs model, Hubbard-Holstein model, Heisenberg model and Electron-vibration coupling Hamiltonians, which are critical in domains like quantum field theory, condensed matter physics, and quantum chemistry. Our implementation is available at Genesis-CVDV-Compiler https://github.com/ruadapt/Genesis-CVDV-Compiler

Chen, Henry↗

Mirostructure Characterization of Friction Consolidated Copper-Nickel using a Machine Learning Approach: Developing Process to Microstructure Associations

Friction consolidation (FC) is a solid phase processing approach where discrete material forms such as powders, chips, nuggets, etc. are densified via shear deformation. The precursors are placed in a billet container and brought in contact with a rotating tool that applying the desirable amount of normal force. Under the combined action of the rotation and normal pressure, the discrete precursor is consolidated through porosity reduction and shear deformation. FC is increasingly being studied as an attractive approach to manufacturing fully dense parts from powder forms owing to its ability to mix, alloy and consolidate difficult-to-process precursors in minimal number of process steps. Material consolidation and deformation in shear consolidation processes have been studied extensively previously for different material combinations previously. However, despite the extensive research in this area, understanding of the mechanistic processes in pore consolidation, deformation-induced mixing and material solubility during FC is still evolving. Material development using solid phase processing approaches such as FC is often performed based on research experience/education, which can be biased. Conventional analysis and simulation tools in this area tend to be successful only when material thermodynamic pathways and microstructural evolution sequences resulting from processing are clearly defined or known. They are not as effective for emerging advanced manufacturing technologies where material evolution pathways are not well established. The ability to predict optimal process parameters based on material chemistry and bulk properties is essential to accelerate materials design and processing, as are an understanding of the relevant structure-processing-property relationships. These structure-processing-property-performance relationships are at the core of materials science research. Microstructure characterization provides the link to these four core areas, often through visualizing material microstructure using imaging techniques. However, linking microstructure image data (i.e., micrographs) to variables of interest (e.g., processing parameters, material chemistry) in a reproducible, generalizable, and quantitative manner is a significant challenge. Typically, quantitatively linking image data to processing history relies on significant domain knowledge and manual or subject matter expert (SME)-heuristic based image analysis. Such an approach to image analysis has the potential to be biased, inefficient, and difficult to replicate.

36 MATERIALS SCIENCE↗

Evaluation of Potential In Vitro Recombination Events in Codon Deoptimized FMDV Strains

Codon deoptimization (CD) has been recently used as a possible strategy to derive foot-and-mouth disease (FMD) live-attenuated vaccine (LAV) candidates containing DIVA markers. However, reversion to virulence, or loss of DIVA, from possible recombination with wild-type (WT) strains has yet to be analyzed. An in vitro assay was developed to quantitate the levels of recombination between WT and a prospective A24-P2P3 partially deoptimized LAV candidate. By using two genetically engineered non-infectious RNA templates, we demonstrate that recombination can occur within non-deoptimized viral genomic regions (i.e., 3'end of P3 region). The sequencing of single plaque recombinants revealed a variety of genome compositions, including full-length WT sequences at the consensus level and deoptimized sequences at the sub-consensus/consensus level within the 3'end of the P3 region. Notably, after further passage, two recombinants that contained deoptimized sequences evolved to WT. Overall, recombinants featuring large stretches of CD or DIVA markers were less fit than WT viruses. Our results indicate that the developed assay is a powerful tool to evaluate the recombination of FMDV genomes in vitro and should contribute to the improved design of FMDV codon deoptimized LAV candidates.

59 BASIC BIOLOGICAL SCIENCES↗

Exploring the binding properties and activities of ancestral expansins

Bacterial expansins are non-lytic proteins capable of loosening cellulose networks, offering promising applications in agriculture, biotechnology, and material science. Their ability to disrupt noncovalent interactions in biopolymer matrices such as cellulose and chitin positions them as valuable tools for upgrading abundant natural materials. However, their industrial use remains limited due to their relatively low wall-loosening activity compared to plant expansins. To address this limitation, we applied Ancestral Sequence Resurrection (ASR) to reconstruct and characterize ancient variants of the Bacillus subtilis expansin BsEXLX1. ASR is a powerful evolutionary tool that enables the inference and synthesis of ancestral proteins, allowing researchers to explore functional traits that may have been lost over time. This approach not only provides insights into protein evolution but also facilitates the design of proteins with enhanced properties, such as improved substrate affinity or structural stability. In this study, we combined biochemical and biophysical assays to evaluate the activity and binding behavior of ancestral expansins. Our results reveal that ancestral variants exhibit increased cellulose affinity, reduced binding to acidic polysaccharides, and greater salt resistance. Furthermore, these traits enhance their wall-loosening activity and demonstrate the utility of ASR in engineering surface-active proteins for industrial applications, particularly in biomass processing and cellulose modification.

09 BIOMASS FUELS↗