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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Engineering PHL7 for Improved Poly(Ethylene Terephthalate) Depolymerization via Rational Design and Directed Evolution

Enzymatic depolymerization of poly(ethylene terephthalate) (PET) has emerged as a promising approach for polyester recycling, and, to date, many natural and engineered PET hydrolase enzymes have been reported. For industrial use, PET hydrolases must achieve high depolymerization extent and exhibit excellent thermostability. Here, we engineered a natural PET hydrolase, Polyester Hydrolase Leipzig #7 (PHL7), through rational design and directed evolution using a high-throughput screening platform. Four new enzymes were engineered with enhanced properties compared with the parent enzyme, wild-type PHL7 (PHL7-WT), and other benchmark PET hydrolases, under the tested conditions. In bioreactors, the exemplary engineered enzyme, PHL7-Jemez, exhibited improved ability to depolymerize amorphous PET film compared with PHL7-WT at 2.9% and 20% substrate loadings, with 37% and 270% higher hydrolysis, respectively, after 48 h. This study develops several state-of-the-art PET hydrolases and demonstrates a directed evolution platform to engineer high-performance enzymes, which can accelerate enzyme discovery toward improved biocatalytic recycling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

JOINT APPOINTEE: Evolution of ferroelectric properties in SmxBi1-xFeO3 via automated Piezoresponse Force Microscopy across combinatorial spread libraries

Combinatorial spread libraries offer a innovative approach to explore the evolution of material properties over broad concentration, temperature, and growth parameter spaces. However, traditional limitation of this approach is the requirement for the read-out of functional properties across the library. Here we develop automated Piezoresponse Force Microscopy (PFM) for the exploration of combinatorial spread libraries and demonstrate its application in the SmxBi1-xFeO3 system with the ferroelectric-antiferroelectric morphotropic phase boundary. This approach relies on the synergy of the quantitative nature of PFM and the implementation of automated experiments that allow PFM-based sampling over macroscopic samples. The concentration dependence of pertinent ferroelectric parameters has been determined and used to develop the mathematical framework based on Ginzburg-Landau theory describing the evolution of these properties across the concentration space. We pose that a combination of automated scanning probe microscope and combinatorial spread library approach will emerge as an efficient research paradigm to close the characterization gap in the high-throughput materials discovery. We make the data sets open to the community and hope that this will stimulate other efforts to interpret and understand the physics of these systems.

Automated Microscopy, Combinatorial Library, Ferro↗
DOE OSTI2025

Faceted NiO(111) nanosheets: morphological and catalytic evolution for the oxygen evolution reaction

The renaissance of the energy system through the use of green hydrogen by water electrolysis lies behind the development of abundant, active, and scalable catalysts for the oxygen evolution reaction (OER). A fundumental understanding of the surface properties for these materials is of vital importance in producing viable heterogenous catalysts. In this feature article, we summarize several years of collaborative work on a uniquely faceted NiO(111) nanosheet possessing hexagonal holes with a focus on understanding how the evolution of the catalyst surface and bulk composition effects OER performance. The importance of surface faceting, morphological evolution, and metal combination by different doping strategies are all analyzed and summarized to further improve the material's performance. Furthermore, microwave and supercritical synthesis processes are utilized to understand how varying wet-chemical techniques effect the formation of the NiO(111) nanosheet and activity of the material. We discuss our chosen strategies and the difficulties encountered with optimizing a catalyst surface for the OER.

08 HYDROGEN↗
DOE OSTI2025

Evolution at the Edge: Real-Time Evolution for Neuromorphic Engine Control

Neuromorphic computing systems are attractive for real-time control at the edge because of their low power operation, real-time processing capabilities and their potential ability to do online learning. In this work, we describe an approach for performing real-time evolution of spiking neural networks for neuromorphic systems at the edge called Neuromorphic Optimization using Dynamic Evolutionary Systems or NODES. We apply this approach to real-time combustion engine control and develop an engine-specific hardware platform for NODES called FireBox. We demonstrate how the real-time evolution approach works in simulation and the performance of networks trained in simulation on the physical engine.

Maldonado Puente, Bryan [ORNL] (ORCID:000000033880↗
DOE OSTI2026

Data for Engineering and Evolution of Yarrowia lipolytica for Producing Lipids from Lignocellulosic Hydrolysates

Yarrowia lipolytica , an oleaginous yeast, shows promise for industrial fermentation due to its robust acetyl-CoA flux and well-developed genetic engineering tools. However, its lack of an active xylose metabolism restricts the conversion of cellulosic sugars to valuable products. To address this, metabolic engineering, and adaptive laboratory evolution (ALE) were applied to the Y. lipolytica PO1f strain, resulting in an efficient xylose-assimilating strain (XEV). Whole-genome sequencing (WGS) of the XEV followed by reverse engineering revealed that the amplification of the heterologous oxidoreductase pathway and a mutation in the GTPase-activating protein gene (YALI0B12100g) might be the primary reasons for improved xylose assimilation in the XEV strain. When a sorghum hydrolysate was used, the XEV strain showed superior xylose consumption and lipid production compared to its parental strain (X123). This study advances our understanding of xylose metabolism in Y. lipolytica and proposes effective metabolic engineering strategies for optimizing lignocellulosic hydrolysates.

Hydrolysate↗
DOE OSTI2025

UO2 microstructural evolutions induced by Ni, Mo, and W dopants for intentional forensics

The concept of tagging nuclear fuel with a chemical barcode to enable forensics analysis across the nuclear fuel cycle is an area of active investigation, particularly to ensure fabrication viability without disrupting current fuel performance. This study explored the feasibility of using Ni, Mo, and W isotopic double-spikes as dopants in UO2 fuel from the perspective of fuel fabrication. Doped UO2 pellets were produced using conventional fuel fabrication processes, including powder mixing, sieving, pressing, and sintering in a reductive atmosphere. Two composition levels, 100 and 1000 ppm, were evaluated for each dopant element with isotopic double-spike configurations. For the Ni system, additional dopant concentrations of 250 and 500 ppm were produced with nonperturbed isotopic ratios. The results demonstrated that successful incorporation of Ni, Mo, and W double-spikes into UO2 pellets occurred with minimal shift in final density or dopant loss during pellet fabrication. Isotopic analysis confirmed the presence of the double-spike signature even when diluted with natural isotopic material in ratio of 1:5 in the fabrication process. Microstructural examinations revealed different impacts on grain size compared with undoped UO2. This study showed that Ni incorporation up to ∼500 ppm promoted moderate grain growth, whereas the Mo and W systems caused grain size reduction at all concentrations. Changes in the UO2 lattice parameter as a function of composition were detected exclusively for Ni up to 500 ppm, indicating that the Ni solid solution was the main factor for the observed grain growth. Insoluble (Mo and W) or supersaturated (Ni > 500 ppm) conditions produced grain size reduction. The Ni-doped pellets in the solution range resulted in a final microstructure within fuel specifications, demonstrating its potential benefits of employing complex dopant systems for potential nuclear forensic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Data for Transposon Signatures of Allopolyploid Genome Evolution

Hybridization brings together chromosome sets from two or more distinct progenitor species. Genome duplication associated with hybridization, or allopolyploidy, allows these chromosome sets to persist as distinct subgenomes during subsequent meioses. Here, we present a general method for identifying the subgenomes of a polyploid based on shared ancestry as revealed by the genomic distribution of repetitive elements that were active in the progenitors. This subgenome-enriched transposable element signal is intrinsic to the polyploid, allowing broader applicability than other approaches that depend on the availability of sequenced diploid relatives. We develop the statistical basis of the method, demonstrate its applicability in the well-studied cases of tobacco, cotton, and Brassica napus, and apply it to several cases: allotetraploid cyprinids, allohexaploid false flax, and allooctoploid strawberry. These analyses provide insight into the origins of these polyploids, revise the subgenome identities of strawberry, and provide perspective on subgenome dominance in higher polyploids.

Genomics↗
DOE OSTI2025

Warm-phase microphysical evolution in large-eddy simulations of tropical cumulus congestus: evaluating drop size distribution evolution using polarimetry retrievals, in situ measurements, and a thermal-based framework

Owing to uncertainties in convective microphysics processes, improving parameterizations in Earth system models (ESMs) can benefit from observationally constrained cases suitable for scaling between cloud-resolving models and ESMs. We propose a benchmark large-eddy simulation (LES) cumulus congestus case study from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP 2 Ex) for evaluating and improving ESMs in single-column model (SCM) mode. We seek observational constraints using novel polarimetric retrievals and in situ cloud microphysics measurements. Simulations using bulk and bin microphysics initialized with observed aerosol profiles are compared to cloud-top retrievals of cloud droplet effective radius (R eff ), effective variance (ν eff ), and number concentration (N d ) from the airborne Research Scanning Polarimeter (RSP). Both schemes reproduce characteristics of cloud-top N d and R eff that increase and decrease with altitude, respectively. Cloud-top N d is low-biased relative to RSP retrievals in both schemes, potentially due to limitations in both simulations and retrieval assumptions. Cloud-top R eff is low-biased in the bulk scheme but reasonably reproduced by the bin scheme. Profiles of N d and R eff are sensitive to the collision–coalescence process and the vertical variation in aerosol size distribution. Comparison of simulated and in situ droplet size distributions (DSDs) shows that, to first order, integrated moments are always sensitive to sizes < ~ 30 µm and can also be sensitive to larger sizes if the DSDs are sufficiently broad, with implications for the assumed maximum observed size retrieved by the RSP. The bin scheme captures the observed extended tail of the DSD, while the bulk scheme is unable to due to parametric constraints. Differences in expected relationships between in situ measurements of cloud cores and cloud-top retrievals by RSP demonstrate difficulty in constraining well the case presented herein. Finally, a thermal-tracking framework demonstrates that the dilution of N d throughout a thermal's lifetime is heavily determined by collision–coalescence and the height-varying aerosol distribution and that, in the absence of these, the impact of entrainment on diluting N d is largely offset by secondary activation. Implications for evaluating warm-phase convective microphysics schemes in ESMs and translating results for use on global, space-based polarimetry platforms are discussed.

Stanford, McKenna Wallace [Columbia Univ., New Yor↗
DOE OSTI2025

Asymptotic errors in adiabatic evolution

The adiabatic theorem in quantum mechanics implies that if a system is in a discrete eigenstate of a Hamiltonian and the Hamiltonian evolves in time arbitrarily slowly, the system will remain in the corresponding eigenstate of the evolved Hamiltonian. Understanding corrections to the adiabatic result that arise when the evolution of the Hamiltonian is slow—but not arbitrarily slow—has become increasingly important, especially since adiabatic evolution has been proposed as a method of state preparation in quantum computing. Here, this paper identifies two regimes, an adiabatic regime in which corrections are generically small and can depend on details of the evolution throughout the path, and a hyperadiabatic regime in which the error is given by a form similar to an asymptotic expansion in the inverse of the evolution time with the coefficients depending principally on the behavior at the endpoints. However, the error in this hyperadiabatic regime is neither given by a true asymptotic series nor solely dependent on the endpoints: the coefficients combine the contributions from both endpoints, with relative phase factors that depend on the average spectral gaps along the trajectory, multiplied by the evolution time. The central result of this paper is to identify a quantity, referred to as the typical error, which is obtained by appropriately averaging the error over evolution times that are small compared to the evolution time itself. This typical error is characterized by an asymptotic series and depends solely on the endpoints of the evolution, remaining independent of the details of the intermediate evolution.

adiabatic approximation↗
DOE OSTI2024

Quantification of the Crack Evolution Process by Extracting Relevant Signal Components from Wave Propagation and Diffusive Transport Front Measurements

Wave propagation and diffusive transport phenomena in a geological rock sample undergoing crack evolution process are expected to interact with the mechanical discontinuities in the medium. The measurements of the signals associated with these phenomena can be used to assess and monitor the crack-driven micromechanical alterations in the rock. Different wave/diffusion phenomena, such as sonic propagation, pressure diffusion, and acoustic emission (AE), are sensitive to different elements of the mechanical discontinuities generated during the evolution of the crack clusters from initiation to coalescence. Sonic propagation, AE, and pressure diffusion monitoring have the potential to map the crack evolution because the transmitter-receiver arrays can be designed, arranged and tuned to (1) achieve maximum recovery of the scattered waveforms and travel times, (2) capture the later arrivals and multiple reflections, and (3) illuminate large rock volume. However, the structural/topological complexities of the mechanical discontinuities, complex distribution of the stress fields, complex mechanical alterations in media, and fluid redistribution in the crack system pose serious challenges for the detection and modeling of the crack evolution process (from here on, we will use the term ‘crack evolution process’ to mean that the crack evolution occurred under shallow crustal conditions). For purposes of accurately accounting such complexities and heterogeneities in the absence of reliable physical laws, simulation methods, and signal processing techniques, my early-career research proposal will develop and apply novel data-driven machine learning methods to: (1) extract signal components relevant to the various phases of crack evolution and (2) generate a 2D visual map of the crack evolution process.

58 GEOSCIENCES↗
DOE OSTI2024

Cosmic quenching and scaling laws for the evolution of supermassive black holes and host galaxies

ABSTRACT Observations suggest a co-evolution of supermassive black holes (SMBHs) and host galaxies. In this paper, we consider the mass and energy flow in a near-equilibrium bulge suffused by gases of varying temperatures. By assuming the rate of energy flow independent of the distance r from the bulge center and the local virial equilibrium for permeated gases on scale r, a key parameter $\varepsilon _b$ was identified that quantifies the mass and energy flow in gases and the efficiency of gas cooling (or the "specific" cooling rate per unit mass), and thus regulates the co-evolution of both SMBHs and hosts. With the help of Illustris simulations and observations, we determined the redshift variation $\varepsilon _b\propto (1+z)^{5/2}$. A higher $\varepsilon _b$ in the early Universe means a higher specific cooling rate that allows rapid evolution of SMBHs and hosts. This simple theory, characterized by a single parameter $\varepsilon _b$, provides the dominant mean cosmic evolution of SMBHs and hosts. All other transient phenomena may only contribute to the dispersion around this mean evolution. Based on this theory and relevant assumptions, scaling laws involving $\varepsilon _b$ were identified for the evolution of SMBHs and hosts. For host galaxies, the mass–size relation $M_b\propto \varepsilon _b^{2/3}r_b^{5/3}G^{-1}$, the dispersion–size relation $\sigma _b^2\propto (\varepsilon _b r_b)^{2/3}\propto (1+z)$, or the mass–dispersion relation $M_b\propto \varepsilon _b^{-1}G^{-1}\sigma _b^5$ were identified, where $r_b\propto (1+z)^{-1}$ is the bulge size. For SMBHs, three evolution phases were found involving an initial rapid growth stage with a rising luminosity $L_B\propto (\varepsilon _b M_{\rm BH})^{4/5}$, a transition stage with a declining $L_B\propto \varepsilon _b^2 M_{\rm BH} \propto (1+z)^5$, and a dormant stage with $L_B\propto (\varepsilon _b M_{\rm BH})^{4/3}$. Our results suggest a rapid initial super-Eddington growth in a short period with a new redshift-dependent luminosity limit $L_X\propto\varepsilon _b^{4/5}M_{\rm BH}^{4/5}G^{-1/5}c$, in contrast to the Eddington limit. Analytical solutions were formulated for the BH mass function $\Phi _{\rm BH}$, active galactic nucleus (AGN) mass function $\Phi _{\rm AGN}$, and duty cycle U that predict $\Phi _L\propto L^{-1/5}$ for the faint-end luminosity function, $\Phi _{\rm AGN}\propto M^{-1/5}$ for small-mass-end AGN mass function $\Phi _L$, and $U\propto M^{-1/5}$ at high redshift.

(galaxies:) quasars: supermassive black holes↗
DOE OSTI2026

Climate change drives convergent evolution of root traits on Sky Island climate relicts

Roots are essential to the strategies plants use to survive in variable environments, yet we know little of how they vary within species. Experimental conditions demonstrate that intraspecific plant root traits respond strongly to variation in the environment; however, it is unclear when these responses can be characterized as evolution in response to selective pressures of climate change over many generations. Sky Islands are model, natural climate relict ecosystems to examine climate-change driven evolution. Utilizing a common garden with replicate genotypes of Populus angustifolia (Narrowleaf cottonwood) from six Sky Island (SI) populations and nine adjacent Mountain Chain (MC) populations across three genetic provenances, we hypothesized that SI root traits have diverged due to historical isolation in warmer, drier climates. When grown in common conditions, populations originating on SI’s showed convergent evolution across three distinct genetic provenances, which was characterized by 44.16% decreased total root length, 42.64% decreased average root volume, 43.31% decreased root surface area, and significantly less root trait variation, relative to adjacent mountain chains. Convergent evolution of root traits from trees originating on SI’s is correlated with changes in mean annual precipitation and potential evapotranspiration in the field over the past ~ 125 years. These results demonstrate a consistent pattern in root trait evolution at the landscape scale and the role of climate on the evolution of root traits in a genetic and geographic context relevant to climate change.

Convergent evolution↗
DOE OSTI2026

The landscape of regulatory element evolution in a C4 perennial grass

Gene regulatory evolution is a well-known source of phenotypic diversity and adaptive evolution. Although cis-regulatory elements (CREs) play a vital role in gene expression evolution, the molecular evolution of CREs remains mostly unknown due to the difficulty in identifying and characterizing these functional elements. Comparative genomic analyses of noncoding DNA can be leveraged to identify conserved noncoding sequences (CNS), many of which may harbor functional CREs conserved by purifying selection. However, purely computational inference of CREs from putative CNS can be erroneous due to the complex genomic architecture in plants. One promising experimental approach to identify CREs is by profiling accessible chromatin regions (ACRs) that are often associated with the location of CREs. In this study, we use comparative genomics along with the profiling of ACRs to study the molecular evolution of putative functional noncoding regulatory regions in Panicoid grasses. We identified sets of CNS that varied in relationship to the degree of evolutionary divergence among the studied taxa, including identifying core-Panicoid-CNS. We augmented this analysis by profiling ACRs in Panicum hallii ecotypes using ATAC-seq. ACRs had low SNP density at the summit, harbored a high frequency of core-Panicoid-CNS, and were enriched with expression QTL. These data help to annotate the P. hallii genome for putative functional elements and suggest that a large proportion of these ACRs are evolving under purifying selection. Turnover in CNS and ACR between ecotypes of P. hallii identifies a small set of putatively divergent CREs that may underlie differences in gene regulation between genotypes from inland and coastal habitats. In summary, we profiled ACRs in Panicoid grasses and integrated this data with our putative CNS prediction framework, which provides unique insight into patterns of polymorphism and divergence in CREs in C4 perennial grasses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Factors Influencing Gas Evolution from High‐Nickel Layered Oxide Cathodes in Lithium‐Based Batteries

Abstract Gas evolution from high‐nickel layered oxide cathodes (>90% Ni) remains a major issue for their practical application. Gaseous species, such as CO 2 , O 2 , and CO, that are evolved at high states of charge (SOC) worsen the overall safety of batteries, as pressure build‐up within the cell may lead to cell rupture. Since these gasses are produced during cathode degradation, tracking the formation of gasses is also important in diagnosing cathode failure. Online electrochemical mass spectrometry (OEMS) is a powerful in situ technique to study gas evolution from the cathode during high‐voltage charge. However, the differences in the OEMS experimental setups between different groups make it challenging to compare results between groups. In this perspective, the various factors that influence gas evolution based on the OEMS results collected in this group are presented. The focus is on the conditions that lead to gas release, with a particular emphasis on reactive oxygen formation and subsequent chemical reactions with the electrolyte. Promising strategies, such as electrolytes, compositional tuning, and surface coatings that are effective at suppressing gas evolution from the cathode are highlighted. Critical insights into mitigating cathode degradation and gas evolution are provided to guide the development of safer, high‐energy batteries.

Chemistry↗
DOE OSTI2026

The quantum evolutions of the diffractive transverse-momentum dependent gluon distribution

Using the Colour Glass Condensate description of electron-nucleus collisions at high energy, we study the diffractive production of a pair of jets with transverse momenta much larger than the nuclear saturation momentum Q s . At leading order in the QCD coupling, the di-jet cross-section exhibits transverse-momentum dependent (TMD) factorisation, with a gluon diffractive TMD distribution (DTMD) which is controlled by gluon saturation and describes the transverse-momentum imbalance between the produced jets. The next-to-leading corrections generate the various quantum evolutions of the diffractive gluon distribution. We focus on the Collins-Soper-Sterman (CSS) evolution which describes the change in the gluon DTMD when increasing the “hard scale” (the typical transverse momentum of the di-jets). We consider two different representations for this equation, one in transverse-momentum space, the other one in transverse-coordinate space. They are not fully equivalent with each other (despite being related by a Fourier transform) because of the respective boundary conditions. These conditions encode the essential physics of gluon saturation together with the effects of two other types of quantum evolution: the BK/JIMWLK evolution over the rapidity gap (“inside the Pomeron”) and the DGLAP evolution outside the rapidity gap (“within the diffractive system”). We demonstrate that, due to gluon saturation, one can compute both the boundary conditions and the CSS solutions mostly from first principles, without the need for a non-perturbative Sudakov. We numerically find a good agreement between the CSS solutions in the two aforementioned representations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Coupled cluster and dislocation dynamics modeling of microstructure evolution in irradiated materials

We develop here a coupled cluster and dislocation dynamics framework to study the microstructure evolution of irradiated materials. The framework not only accounts for the three dimensional diffusion of radiation-generated clusters, but also their interaction with dislocation networks and the resultant climb motion of discrete dislocations within finite crystals. The framework is solved with a superposition solution scheme, and is applied to investigate the evolution of the irradiation-induced dislocation loops in zirconium (Zr), considering the effects of various bias factors including the diffusion anisotropy difference (DAD) of interstitials and interstitial clusters, the dislocation bias of defects to discrete dislocation segments, and the production bias of defects from the radiation cascade. We find that the DAD is the most critical factor influencing the kinetics of the loop evolution in Zr, while the recombination/interaction of mobile defects can induce a strong spatial dependence of the loop evolution together with the DAD. Here, the method is also adopted to study the evolution of interstitial $\langle$a$\rangle$ and vacancy $\langle$c$\rangle$ dislocation loop ensembles consistent with the microstructure observed during irradiation-induced growth of Zr. Our findings not only reveal the spatial dependence of the size and ellipticity of the dislocation loops, but also suggest a limit on the anisotropy factor of interstitials to reproduce the co-growth of $\langle$a$\rangle$ and $\langle$c$\rangle$ loops in zirconium, in good agreement with experimental observations and other simulation results.

Bias factors↗
DOE OSTI2024

Coupled neutronics, thermochemistry, corrosion modeling and sensitivity analyses for isotopic evolution in molten salt reactors

This study presents a computational methodology for analyzing isotopic evolution and associated uncertainties in molten salt reactors (MSRs), focusing on both fluoride- and chloride-based fuel salts. The primary goal is to enhance the understanding of isotopic behavior in MSRs and provide data to support future experimental efforts. The methodology integrates transport-coupled depletion calculations using OpenMC, equilibrium thermodynamics modeling with Thermochimica, and a corrosion model. Sensitivity analyses are performed to evaluate the impact of power density, air ingress, and humidity content on isotopic evolution in MSR concepts. This study examines representative F- and Cl-based MSR designs, highlighting the dominant influence of power density on isotopic composition, which significantly affects isotope production and depletion rates, accounting for approximately 76% of the observed variance in element concentration. Air ingress and humidity content also affect the redox potential, solubility of heavier elements, and corrosion rates, thereby altering the expected isotopic evolution in the reactor. On average, air ingress accounts for around 17% of the variance in element concentrations, while humidity explains the remaining 7%. These variances differ significantly from element to element, depending on the element’s role in depletion, redox potential evolution, and galvanic corrosion. The findings indicate that power density, air ingress, and humidity content are all critical factors for optimizing reactor design and operational strategies. Furthermore, the study provides expected ranges for key impurities in the fuel salt, which are crucial for guiding future experimental studies and refining MSR designs. Finally, this study demonstrates the importance of modeling depletion coupled with the evolution of redox potential and chemical interactions in MSR fuel salts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗