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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Implementation of Genetic Algorithms to Optimize Metal–Organic Frameworks for CO 2 Capture

Metal-organic frameworks (MOFs) are promising materials for CO 2 capture with the potential to use less energy than current industrial CO 2 capture methods. MOFs are highly versatile sorbents, and there is an almost unlimited number of MOFs that could be synthesized. In this work, we used a genetic algorithm (GA) and grand canonical Monte Carlo (GCMC) simulations to efficiently search for high-performing MOFs for CO 2 capture. We analyzed the effects of important GA parameters, including the mutation probability, the number of MOFs per generation and the number of GA generations, on the GA performance. Here, we performed GCMC simulations on-the-fly during the GA procedure to determine the performance of proposed MOFs and optimized their structures using multiple objective functions across different topologies. The GA was able to determine top-performing MOFs balancing CO 2 selectivity versus working capacity and reduced the cost of molecular simulations by a factor of 25 versus brute-force screening of an entire database of structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2002

Trends in lignin modification: a comprehensive analysis of the effects of genetic manipulations/mutations on lignification and vascular integrity

A comprehensive assessment of lignin configuration in transgenic and mutant plants is long overdue. This review thus undertook the systematic analysis of trends manifested through genetic and mutational manipulations of the various steps associated with monolignol biosynthesis; this included consideration of the downstream effects on organized lignin assembly in the various cell types, on vascular function/integrity, and on plant growth and development. As previously noted for dirigent protein (homologs), distinct and sophisticated monolignol forming metabolic networks were operative in various cell types, tissues and organs, and form the cell-specific guaiacyl (G) and guaiacyl-syringyl (G-S) enriched lignin biopolymers, respectively. Regardless of cell type undergoing lignification, carbon allocation to the different monolignol pools is apparently determined by a combination of phenylalanine availability and cinnamate-4-hydroxylase/"p-coumarate-3-hydroxylase" (C4H/C3H) activities, as revealed by transcriptional and metabolic profiling. Downregulation of either phenylalanine ammonia lyase or cinnamate-4-hydroxylase thus predictably results in reduced lignin levels and impaired vascular integrity, as well as affecting related (phenylpropanoid-dependent) metabolism. Depletion of C3H activity also results in reduced lignin deposition, albeit with the latter being derived only from hydroxyphenyl (H) units, due to both the guaiacyl (G) and syringyl (S) pathways being blocked. Apparently the cells affected are unable to compensate for reduced G/S levels by increasing the amounts of H-components. The downstream metabolic networks for G-lignin enriched formation in both angiosperms and gymnosperms utilize specific cinnamoyl CoA O-methyltransferase (CCOMT), 4-coumarate:CoA ligase (4CL), cinnamoyl CoA reductase (CCR) and cinnamyl alcohol dehydrogenase (CAD) isoforms: however, these steps neither affect carbon allocation nor H/G designations, this being determined by C4H/C3H activities. Such enzymes thus fulfill subsidiary processing roles, with all (except CCOMT) apparently being bifunctional for both H and G substrates. Their severe downregulation does, however, predictably result in impaired monolignol biosynthesis, reduced lignin deposition/vascular integrity, (upstream) metabolite build-up and/or shunt pathway metabolism. There was no evidence for an alternative acid/ester O-methyltransferase (AEOMT) being involved in lignin biosynthesis.The G/S lignin pathway networks are operative in specific cell types in angiosperms and employ two additional biosynthetic steps to afford the corresponding S components, i.e. through introduction of an hydroxyl group at C-5 and its subsequent O-methylation. [These enzymes were originally classified as ferulate-5-hydroxylase (F5H) and caffeate O-methyltransferase (COMT), respectively.] As before, neither step has apparently any role in carbon allocation to the pathway; hence their individual downregulation/manipulation, respectively, gives either a G enriched lignin or formation of the well-known S-deficient bm3 "lignin" mutant, with cell walls of impaired vascular integrity. In the latter case, COMT downregulation/mutation apparently results in utilization of the isoelectronic 5-hydroxyconiferyl alcohol species albeit in an unsuccessful attempt to form G-S lignin proper. However, there is apparently no effect on overall G content, thereby indicating that deposition of both G and S moieties in the G/S lignin forming cells are kept spatially, and presumably temporally, fully separate. Downregulation/mutation of further downstream steps in the G/S network [i.e. utilizing 4CL, CCR and CAD isoforms] gives predictable effects in terms of their subsidiary processing roles: while severe downregulation of 4CL gave phenotypes with impaired vascular integrity due to reduced monolignol supply, there was no evidence in support of increased growth and/or enhanced cellulose biosynthesis. CCR and CAD downregulation/mutations also established that a depletion in monolignol supply reduced both lignin contents supply reduced both lignin contents and vascular integrity, with a concomitant shift towards (upstream) metabolite build-up and/or shunting.The extraordinary claims of involvement of surrogate monomers (2-methoxybenzaldehyde, feruloyl tyramine, vanillic acid, etc.) in lignification were fully disproven and put to rest, with the investigators themselves having largely retracted former claims. Furthermore analysis of the well-known bm1 mutation, a presumed CAD disrupted system, apparently revealed that both G and S lignin components were reduced. This seems to imply that there is no monolignol specific dehydrogenase, such as the recently described sinapyl alcohol dehydrogenase (SAD) for sinapyl alcohol formation. Nevertheless, different CAD isoforms of differing homology seem to be operative in different lignifying cell types, thereby giving the G-enriched and G/S-enriched lignin biopolymers, respectively. For the G-lignin forming network, however, the CAD isoform is apparently catalytically less efficient with all three monolignols than that additionally associated with the corresponding G/S lignin forming network(s), which can more efficiently use all three monolignols. However, since CAD does not determine either H, G, or S designation, it again serves in a subsidiary role-albeit using different isoforms for different cell wall developmental and cell wall type responses.The results from this analysis contrasts further with speculations of some early investigators, who had viewed lignin assembly as resulting from non-specific oxidative coupling of monolignols and subsequent random polymerization. At that time, though, the study of the complex biological (biochemical) process of lignin assembly had begun without any of the (bio)chemical tools to either address or answer the questions posed as to how its formation might actually occur. Today, by contrast, there is growing recognition of both sophisticated and differential control of monolignol biosynthetic networks in different cell types, which serve to underscore the fact that complexity of assembly need not be confused any further with random formation. Moreover, this analysis revealed another factor which continues to cloud interpretations of lignin downregulation/mutational analyses, namely the serious technical problems associated with all aspects of lignin characterization, whether for lignin quantification, isolation of lignin-enriched preparations and/or in determining monomeric compositions. For example, in the latter analyses, some 50-90% of the lignin components still cannot be detected using current methodologies, e.g. by thioacidolysis cleavage and nitrobenzene oxidative cleavage. This deficiency in lignin characterization thus represents one of the major hurdles remaining in delineating how lignin assembly (in distinct cell types) and their configuration actually occurs.

Review, Academic↗
NASA NTRS1999

Genetic ablation of root cap cells in Arabidopsis

The root cap is increasingly appreciated as a complex and dynamic plant organ. Root caps sense and transmit environmental signals, synthesize and secrete small molecules and macromolecules, and in some species shed metabolically active cells. However, it is not known whether root caps are essential for normal shoot and root development. We report the identification of a root cap-specific promoter and describe its use to genetically ablate root caps by directing root cap-specific expression of a diphtheria toxin A-chain gene. Transgenic toxin-expressing plants are viable and have normal aerial parts but agravitropic roots, implying loss of root cap function. Several cell layers are missing from the transgenic root caps, and the remaining cells are abnormal. Although the radial organization of the roots is normal in toxin-expressing plants, the root tips have fewer cytoplasmically dense cells than do wild-type root tips, suggesting that root meristematic activity is lower in transgenic than in wild-type plants. The roots of transgenic plants have more lateral roots and these are, in turn, more highly branched than those of wild-type plants. Thus, root cap ablation alters root architecture both by inhibiting root meristematic activity and by stimulating lateral root initiation. These observations imply that the root caps contain essential components of the signaling system that determines root architecture.

Non-NASA Center↗
DOE OSTI2025

Genetically Controlled Iron Oxide Biomineralization in Encapsulin Nanocompartments for Magnetic Manipulation of a Mammalian Cell Line

Magnetic nanoparticles have proven invaluable for biomechanical investigations due to their ability to exert localized forces. However, cellular delivery of exogenous magnetic agents often results in endosomal entrapment, thereby limiting their utility for manipulating subcellular structures. This study characterizes and exploits fully genetically controlled biomineralization of iron-oxide cores inside encapsulin nanocompartments to enable magnetic-activated cell sorting (MACS) and magnetic cell manipulation. The fraction of MACS-retained cells showed substantial overexpression of encapsulins and exhibited both para- and ferrimagnetic responses with magnetic moments of 10 -15 A m 2 per cell, comparable to standard exogenous labels for MACS. Electron microscopy revealed that MACS-retained cells contained densely packed agglomerates of ≈30 nm iron oxide cores consisting of ultrafine quasicrystalline ordered nuclei within an amorphous matrix of iron, oxygen, and phosphorus. Scanning transmission X-ray microscopy, X-ray absorption spectroscopy, and Raman microspectroscopy confirmed that the iron-oxide species are consistent with ferric oxide (Fe 2 O 3 ). In addition, the encapsulin-overexpressing MACS-retained cells can be manipulated by a magnetic needle and regrown in patterns determined by magnetic gradients. This study demonstrates that the formation of quasicrystalline iron oxide with mixed para/ferrimagnetic behavior in the cytosol of mammalian cells enables magnetic manipulation without the delivery of exogenous agents.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Optimization of the FRIB beam dump: a hybrid genetic algorithm and reinforcement learning approach

The operational envelope of high-power-density systems, such as particle accelerators and advanced nuclear energy systems, is critically constrained by the need to manage extreme thermal loads. To address this, we present a novel hybrid optimization framework combining a genetic algorithm (GA) with a soft actor-critic (SAC) deep reinforcement learning agent. This framework was applied to a practical high-heat-flux problem: redesigning the beam dump at the Facility for Rare Isotope Beams (FRIB) for a power upgrade from 20 kW to 50 kW. The resulting design, validated by three-dimensional conjugate heat transfer simulations, suppresses hazardous hot spots and yields a markedly more uniform temperature distribution. This provides a robust operating margin, increasing the average power-handling capability by 72% relative to the current design, demonstrating the framework’s potential to solve complex thermal management challenges in both accelerator technology and advanced nuclear systems.

Accelerator↗
DOE OSTI2025

Developing a robust strength model using physically-informed genetic programming

The strength of materials is influenced by a range of external conditions, such as temperature and deformation rate. Consequently, materials that demonstrate substantial variations in their mechanical behavior due to fluctuations in temperature and strain rate require complex strength models to accurately predict material performance in real-world applications. To predict such complex behavior, a robust and flexible strength model is necessary. In this work, we utilize genetic programming-based symbolic regression (GPSR) to develop data-driven strength models that accurately represent the measured stress–strain responses of tin across a wide range of strain, strain rate and temperature regimes. The GPSR models are constrained by physically-informed conditions, which leads to significant improvement in extrapolation. The best model is integrated into a multi-physics code to perform Taylor impact simulations, validating the model’s accuracy and robustness. In conclusion, the model predictions showed excellent agreement with experimental results, particularly when compared to predictions using traditional strength models.

Genetic programming↗
DOE OSTI2026

Optimizing pressurized-water reactor equilibrium cycle using a novel loading pattern encoding and rule-based genetic crossover operators

This work presents an extended multi-batch approach applied in shuffling scheme optimization for equilibrium cycle for pressurized water reactors using Genetic Algorithms (GAs). A new ruled based GA crossover operator called Inherited Location and Batch (ILB) was introduced to enhance offsprings reproduction efficiency specialized for equilibrium cycle optimization problem. This approach was implemented within the Plant ReLoad Optimization (PRLO) framework and validated using a generic reactor model based on the AP1000 design, with core parameters calculated via the CASMO/SIMULATE software package. The ILB approach is then applied for both single and multi-objective problems in maximizing cycle length and core average exposure while minimizing the average enrichment of the 57 fresh fuel assemblies (FAs) per cycle. The optimal solutions are selected based on their dominance to the objectives from all feasible solutions. This research identified three optimal solutions satisfied safety constraints: The first solution minimizes feed enrichment costs with a cycle length of 338.8 days and core exposure of 25.39 MWd/MT; the second solution extends cycle length to 361.2 days, with the highest core exposure of 26.84 MWd/MT, using 3.75 wt% average fuel enrichment; the third solution balances both objectives with a cycle length of 349.6 days, core exposure of 25.82 MWd/MT with a slight enrichment increase compared to the first solution. Collectively, these findings underscore the efficiency and effectiveness of the proposed approach in achieving practical multi-objective optimal equilibrium cycle designs using GAs optimizer.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Adsorption Hysteresis Under Control: Tuning Host–Guest Interactions via a Genetic Algorithm

Mesoporous adsorbent materials offer a large volumetric capacity; however, cyclic adsorption/desorption processes in these systems often suffer from hysteresis and may require a significant pressure swing to access this capacity. To mitigate hysteresis, a proposed strategy is to include nucleation sites on the walls of the mesoporous material to facilitate droplet and bubble formation, lowering the free energy barriers to the respective phase transitions. It is unclear, however, what combination of adsorbate− adsorbent interactions and spatial patterning would be beneficial for a given application, considering that improvements to some sorption properties may come at the expense of other attributes. To understand these interconnected observables, we examine two model systems, planar-slit and cylindrical pores with tunable interaction sites, using GPU-accelerated transition matrix Monte Carlo simulations. The simulations provide a free energy map of the pressure−adsorption space in a matter of minutes, which we use to track adsorption isotherm characteristics as a function of adsorbent properties. We then leverage the rapid acquisition of simulation data to construct a genetic algorithm to iteratively modify interaction sites of the slit-pore wall to minimize the hysteresis of this system without sacrificing uptake. We find that the adsorption branch of the isotherm is easily modulated via the average host−guest interaction strength, but desorption is only adjustable if there is a suitable bubble nucleation site. Within the context of a slit-pore system, we identify relative interaction strengths and patch sizes required to gain control over both branches of the hysteresis loop.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Multi-Objective Optimization of Uranium Target Assembly–3: A Comparison of Genetic and Traditional Methods

Commonly produced as a byproduct of uranium fission, 99 Mo is a key medical isotope that is in high demand in the United States. An international goal is to switch from medical isotope production technologies that require highly enriched uranium to medical isotope production technologies that require only low-enriched uranium. Niowave Inc. is contributing to this goal by developing an accelerator-driven subcritical assembly called the Uranium Target Assembly (UTA). This work compares the performance of Dakota’s Multi-Objective Genetic Algorithm (MOGA) against traditional sensitivity analysis in the neutronic optimization of the UTA-3 system. The design objectives are k-eigenvalue (k eff ) and natural uranium fission power, which are directly correlated with the amount of 99 Mo produced. Dakota:MOGA did not perform as well as human engineering ingenuity in optimization studies with high numbers of input parameters, such as fuel rod type selection and fuel rod placement. However, Dakota:MOGA did outperform traditional sensitivity analysis in optimization studies with fewer than 20 parameters and revealed the degree to which each parameter influences the optimal design space for k eff and natural uranium fission power (to a lesser extent). As the design model became more complex in the final stage of design, the computational resources required to calculate the design objective values in the Monte Carlo N-Particle transport code from selected input parameter combinations limited Dakota:MOGA’s performance, and, unfortunately, human intervention was required to discern the optimal design space. In conclusion, future work will attempt to reduce computational resource constraints by incorporating areduced-order neutronics model into the optimization cycle.

Accelerator-driven systems↗
DOE OSTI2025

Genetic programming for the nuclear many-body problem: a guide

Genetic Programming (GP) is an evolutionary algorithm that generates computer programs, or mathematical expressions, to solve complex problems. In this Guide, we demonstrate how to use GP to develop surrogate models to mitigate the computational costs of modeling atomic nuclei with ever increasing complexity. The computational burden escalates when uncertainty quantification is pursued, or when observables must be globally computed for thousands of nuclei. By studying three models in which the mean field depends on the total particle density self-consistently, we show that by constructing reduced order models supported by GP one can speed up many-body computations by several orders of magnitude with a negligible loss in accuracy.

dimensionality reduction↗
DOE OSTI2025

Decoding crops one cell at a time: from cell atlases to single-cell genetics

Understanding the mechanisms underlying key agricultural traits remains a central challenge in crop research, but recent advances in technologies are providing powerful tools to address this issue. Among these, single-cell and spatial transcriptomics have revealed tissue heterogeneity and spatial organization, offering unique insights into cellular gene expression dynamics and the coordinated activity of multiple cell types. These approaches help uncover how specific cell types contribute to agricultural traits and refine candidate loci lists through integration with trait-associated loci. Additionally, single-cell and spatial transcriptomics have the potential to serve as cell-level readout platforms integrating cellular perturbations, enabling high-throughput discovery of causal relationships between genotype and gene expression at the cellular level in plants. Successful implementation will accelerate the identification of key genetic variants for crop improvement. Furthermore we review lessons learned from application of single-cell screening in mammalian cells, highlight major technical and biological barriers to its use in plants, and outline potential strategies to overcome these challenges. Together, the widespread application and integration of single-cell and spatial transcriptomics with other technologies enable not only the descriptive cataloging of cell states but also the causal interrogation of sequence functions and regulatory networks at cell type resolution, ultimately advancing gene function studies and accelerating crop improvement.

Cellular heterogeneity↗
DOE OSTI2025

Targeted genetic manipulation and yeast-like evolutionary genomics in the green alga Auxenochlorella

Auxenochlorella spp. are diploid oleaginous green algae whose streamlined genomes can be readily manipulated by homologous recombination, making them highly amenable to discovery research and bioengineering. Vegetatively diploid organisms experience specific evolutionary phenomena, including allodiploid hybridization, mitotic recombination, loss-of-heterozygosity, and aneuploidy; however, studies of these forces have largely focused on yeasts. Here, we present a telomere-to-telomere phased diploid genome assembly of Auxenochlorella UTEX 250-A (haploid length 22 Mb) and introduce a genetic toolkit for site-specific manipulation of the nuclear genome in multiple strains, featuring several selectable markers, inducible promoters, and fluorescent reporters for protein localization. UTEX 250-A is an allodiploid hybrid of Auxenochlorella protothecoides and Auxenochlorella symbiontica, two species differentiated by extensive chromosomal rearrangements. UTEX 250-A haplotypes are a mosaic of each parental species following mitotic recombination, and two chromosomes are trisomic. Loss-of-heterozygosity events are pervasive across Auxenochlorella and can evolve rapidly in the laboratory. High-quality structural annotation yielded ∼7,500 genes per haplotype. Auxenochlorella have experienced gene family loss and reduction, including core photosynthesis genes, and exhibit periodic adenine and cytosine methylation at promoters and gene bodies, respectively. Approximately 10% of genes, especially those involved in DNA repair and sex, overlap antisense long noncoding RNAs, which may participate in a regulatory mechanism. We demonstrate the utility of Auxenochlorella for fundamental research by knockout of a chlorophyll biosynthesis enzyme, and confirm one trisomy by allele-specific transformation. These results demonstrate the generality of several evolutionary forces associated with vegetative diploidy and provide a foundation for the use of Auxenochlorella as a reference organism.

CHL27↗
DOE OSTI2025

Direct structural retrieval from gas-phase ultrafast diffraction data using a genetic algorithm

Ultrafast scattering techniques such as ultrafast electron diffraction and ultrafast x-ray diffraction have been utilized to elucidate the structural dynamics, reaction intermediates, and final products in molecular reactions following photoexcitation. The time-dependent structures are typically not directly retrieved from the experimental data, but they rely on comparison with calculations. The genetic algorithm (GA), a global optimization strategy, can be used to retrieve the molecular structures directly from diffraction patterns without any theoretical input. However, the robustness of the GA with respect to real experimental conditions such as a limited momentum transfer range, noise, and artifacts has not been studied in detail. In this work, we characterize the performance of the GA with simulated data that mimic realistic experimental conditions. We have developed and implemented a variant of the GA specific to diffraction measurements which performs better in the presence of imperfect data compared to the standard implementation of the GA. We demonstrate this method with both synthetic data and experimental ultrafast electron diffraction data on the UV-induced photodissociation of trifluoroiodomethane (C⁢F 3⁡ I) molecules.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

Synthetic overlapping genes stabilize genetic systems

Overlapping genes—wherein two different proteins are translated from alternative reading frames of the same DNA sequence—provide a means to stabilize an engineered gene by directly linking its evolutionary fate with that of an overlapping gene. However, creating overlapping gene pairs is challenging, as it requires redesigning both protein products to accommodate overlap constraints. Here, we present a new “overlapping, alternate-frame insertion” (OAFI) method for creating synthetic overlapping genes by inserting an “inner” gene, encoded in an alternate frame, into a flexible region of an “outer” gene. Using OAFI, we create new overlapping gene pairs of genetic reporters and bacterial toxins within an antibiotic resistance gene. We show that both the inner and outer genes retain function despite redesign, with translation of the inner gene influenced by its overlap position in the outer gene. Importantly, we show that, despite these inner gene sequences not contributing to outer gene function, selection for the outer gene alters the permitted inactivating mutations in the inner gene, and that overlapping toxins can restrict horizontal gene transfer of the antibiotic resistance gene. Overall, OAFI offers a versatile tool for synthetic biology, expanding the applications of overlapping genes in gene stabilization and biocontainment.

Biological and medical sciences↗
DOE OSTI2025

Data for "Viral Delivery of Recombinases Activates Heritable Genetic Switches in Plants"

Viral vectors provide an increasingly versatile platform for transformation-free reagent delivery to plants. RNA viral vectors can be used to induce gene silencing, overexpress proteins, or introduce gene editing reagents; however, they are often constrained by carrying capacity or restricted tropism in germline cells. Site-specific recombinases that catalyze precise genetic rearrangements are powerful tools for genome engineering that vary in size and, potentially, efficacy in plants. In this work, we show that viral vectors based on tobacco rattle virus (TRV) deliver and stably express four recombinases ranging in size from ∼0.6 to ∼1.5 kb and achieve simultaneous marker removal and reporter activation through targeted excision in transgenic Nicotiana benthamiana lines. TRV vectors with Cre, FLP, CinH, and Integrase13 efficiently mediated recombination in infected somatic tissue and led to heritable modifications at high frequency. An excision-activated Ruby reporter enabled simple and high-resolution tracing of infected cell lineages without the need for molecular genotyping. Together, our experiments broaden the scope of viral recombinase delivery and offer insights into infection dynamics that may be useful in developing future viral vectors.

gene editing↗
DOE OSTI2025

Efficient genetic code expansion tools enable in vivo study of lysine acetylation in non-model bacteria

Recent proteomic advancements have revealed widespread Nε-lysine acetylation in pathways governing pathogenicity, metabolism, and antibiotic resistance in bacteria. The spontaneous, non-specific nature of this modification in prokaryotes obscures its biological role, necessitating prokaryotic specific in vivo interrogation systems. Genetic Code Expansion (GCE) offers a powerful method to investigate the roles and regulation dynamics of acetyl-lysine in vivo with the precise incorporation of a suite of non-canonical amino acids, including acetyl-lysine analogs. However, its use has been largely restricted to E. coli strains due to challenges associated with implementation and optimization of the technology in more diverse bacterial strains. Here, we present a bacterial host-agnostic, readily optimizable GCE platform designed to site-specifically incorporate non-canonical amino acids into target proteins within living bacteria. We further demonstrate the versatility of this technology by showcasing, for the first time, the successful incorporation of acetyl-lysine in a non- E. coli bacterium.

59 BASIC BIOLOGICAL SCIENCES↗