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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

Probing substrate water access through the O1 channel of Photosystem II by single site mutations and membrane inlet mass spectrometry

Abstract Light-driven water oxidation by photosystem II sustains life on Earth by providing the electrons and protons for the reduction of CO 2 to carbohydrates and the molecular oxygen we breathe. The inorganic core of the oxygen evolving complex is made of the earth-abundant elements manganese, calcium and oxygen (Mn 4 CaO 5 cluster), and is situated in a binding pocket that is connected to the aqueous surrounding via water-filled channels that allow water intake and proton egress. Recent serial crystallography and infrared spectroscopy studies performed with PSII isolated fromThermosynechococcus vestitus(T. vestitus) support that one of these channels, the O1 channel, facilitates water access to the Mn 4 CaO 5 cluster during its S 2 →S 3 and S 3 →S 4 →S 0 state transitions, while a subsequent CryoEM study concluded that this channel is blocked in the cyanobacteriumSynechocystis sp.PCC 6803, questioning the role of the O1 channel in water delivery. Employing site-directed mutagenesis we modified the two O1 channel bottleneck residues D1-E329 and CP43-V410 (T. vestitusnumbering) and probed water access and substrate exchange via time resolved membrane inlet mass spectrometry. Our data demonstrates that water reaches the Mn 4 CaO 5 cluster via the O1 channel in both wildtype and mutant PSII. In addition, the detailed analysis provides functional insight into the intricate protein-water-cofactor network near the Mn 4 CaO 5 cluster that includes the pentameric, near planar ‘water wheel’ of the O1 channel.

Plant Sciences↗

Challenges and Opportunities in the Enzymatic Recycling of Nylons

Enzymatic depolymerization has the potential to contribute to nylon waste recycling. However, the implementation of a viable industrial process still lags far behind progress in enzymatic polyester recycling. Here we review the current biocatalytic nylon recycling landscape, highlighting biochemical, structural, and materials science barriers that currently limit depolymerization extents. We detail efforts to identify, engineer, and characterize new nylon depolymerases, where currently even the best biocatalysts rarely exceed ~1 wt% conversion of solid polymer to products. Based on our analyses, we suggest that limited substrate accessibility due to substrate crystallinity and hydrogen bonding, rather than intrinsic enzyme inefficiency or instability, is the primary bottleneck to enhanced depolymerization. Guided by successes in polyester enzymatic recycling, we outline a research roadmap combining nylonase engineering with polymer pretreatment, chemo-enzymatic cascades, and process analyses to accelerate development of viable enzymatic nylon recycling processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coordination-Induced Weakening of N–H Bonds Driven by Bimetallic Cooperativity in Zr/Co Compounds

The bond dissociation free energy (BDFE) of the element-hydrogen bonds of protic substrates have been found to decrease upon metal coordination. Herein, an early/late heterobimetallic complex is used to examine the impact on the BDFE N−H when the substrate binding site and the redox-active site are two different metals that are spatially separated. A tris- (phosphinoamide) framework is used to link a d 0 ZrIV center with an accessible substrate binding site to a coordinatively saturated redox-active Co center, which serves as an appended electron reservoir. A series of aniline, amido, and imido Zr/Co model compounds were synthesized starting from the Zr IV /Co −I aniline adduct PhH 2 N−Zr(MesNP i Pr 2 ) 3 CoCN t Bu (2). 2,4,6-tristert- butylphenoxyl radical ( t Bu 3 ArO • ) was used to abstract one or two H atoms and produce the amido and imido complexes PhHNZr( MesNP i Pr 2 ) 3 CoCN t Bu (3) and PhN≡Zr(MesNP i Pr 2 ) 3 CoCNtBu (4), respectively. Using open-circuit potential measurements, the BDFE N−H within 2 and 3 were determined to be 37 kcal/mol (2) and 55 kcal/mol (3). Cyclic voltammetry measurements were conducted to determine the Co I/0 and Co 0/−I redox potentials. The pK a s were then estimated using the Bordwell equation to provide further insight into the thermochemical aspects of the observed proton coupled electron transfer (PCET) reactions.

Bond dissociation free energy↗

Decoding substrate specificity determining factors in glycosyltransferase-B enzymes – insights from machine learning models

Substrate specificity is an essential characteristic of any enzyme's function and an understanding of the factors that determine this specificity is crucial for enzyme engineering. Unlike the structure of an enzyme which is directly impacted by its sequence, substrate specificity as an enzyme attribute involves a rather indirect relationship with sequence as it also depends on structural aspects that dictate substrate accessibility and active site dynamics. In this study, we explore the performance of classifier-based machine learning models trained on curated sequence and structural data for a class of glycosyltransferases (GTs), namely GT-Bs, to understand their substrate specificity determining factors. GTs enable the transfer of sugar moieties to other biomolecules such as oligosaccharides or proteins and are found in all kingdoms of life. In plants, GTs participate in the biosynthesis of plant cell wall biopolymers (e.g.: hemicelluloses and pectins) and are an integral part of the enzymatic machinery that enables the storage of carbon and energy as plant biomass. To elucidate the substrate specificity of uncharacterized GT-Bs, we constructed multi-label machine learning models (Support Vector Classifier, K-Nearest Neighbors, Gaussian Naïve-Bayes, Random Forest) that incorporate both sequence and structural features. These models achieve good predictive accuracies on test datasets. However, despite our use of structural information, we highlight that there is further scope for improvement in training these models to draw interpretable relationships between sequence, structure and substrate specificity determining motifs in GT-Bs.

97 MATHEMATICS AND COMPUTING↗

Isolation of a Terminal Cobalt Nitride in a Metal–Organic Framework

Transition metal nitrides are reactive intermediates in biological and industrial processes. Chemists have synthesized molecular model complexes of such reactive species to understand their function and electronic requirements for new applications. However, molecular chemistry can suffer from intra- and intermolecular decomposition pathways, which preclude further discovery of unknown reactive species. Metal-organic frameworks offer an opportunity for creating long-lived forms of such species with the vacuum of the pore suppressing degradation while simultaneously enabling substrate access for controlled reactivity studies. Here, in this study, we report the characterization of an elusive terminal cobalt nitride species generated through photolysis or thermolysis of a site-isolated cobalt azide within the evacuated metal-organic framework CoN 3 -MFU-4l. The first crystal structure of such a species is presented, with vibrational, X-ray absorption, and electron paramagnetic resonance spectroscopies providing further direct evidence for its formation while elucidating its electronic structure. The system additionally enables subsequent reactivity studies with selected substrates, revealing a unique ambiphilic behavior for a metal nitride species.

Börgel, Jonas [University of California, Berkeley,↗

Volatile traits expand the microbial playbook

Microbial metabolic functions are increasingly conceptualized as fitness-regulating traits. However, volatile compounds (the volatilome), despite their key roles in metabolism and ecology, are often overlooked in trait-based frameworks. We propose that volatile traits not only reflect ecological strategies but also shape them by mediating responses to selection pressures. Their volatility affects diffusion, substrate access, and interactions across space, conferring selective advantages as resources or waste products. We outline approaches to incorporate volatile traits into predictive models to improve understanding of microbial selection and community dynamics. Furthermore, this integration enables a more holistic view of microbial life by accounting for the ecological and evolutionary consequences of volatile-mediated processes.

54 ENVIRONMENTAL SCIENCES↗

Thermostable Enzyme Variants in the Lower Mevalonate Pathway Improve Isoprenoid Production by Cell-Free Biocatalysis

Cell-free biocatalysis is a rapidly evolving field with great potential for sustainably producing valuable chemicals. Some challenges in cell-free biocatalysis include reaction longevity, enzyme stability, and the cost of the biocatalysts. Here, the challenge of enzyme instability was addressed by employing thermophilic enzymes to improve the productivity of the lower mevalonate pathway, using limonene as an example isoprenoid product. The Classical mesophilic mevalonate pathway was compared to a newly assembled set of thermophilic enzymes comprising the Archaea I mevalonate pathway. The thermophilic pathway enzymes were thermostable to at least 60 °C and exhibited a 6× longer operating lifetime at 22 °C. Thus, despite lower initial activity rates at ambient temperature, the thermophilic pathway was longer-lived and resulted in a more productive cell-free reaction overall, achieving 1.7× higher yield of limonene compared to using enzymes from mesophiles. Moreover, the thermostable pathway retained activity for longer with the challenge of solvent exposure, namely, ethanol and isoprenol, which broadens the scope of accessible substrates and/or products in cell-free reactions employing this pathway. Altogether, we showed significant improvement in the stability and productivity of the lower mevalonate pathway, which will enable more efficient cell-free biosynthesis of isoprenoid products. This represents a valuable strategy to increase the robustness of cell-free systems by carefully sourcing biocatalysts from thermophilic organisms, which have proven to be resilient to challenges unique to cell-free reaction systems.

09 BIOMASS FUELS↗

Correlating Protein Dynamics and Catalytic Activity of a Model Hydrogenase Using Paramagnetic and Biological Nuclear Magnetic Resonance Spectroscopy

Rational catalyst design remains a significant challenge, with electronic structure, steric, and electrostatic effects known to contribute to activity. Recently, dynamics has been recognized as another factor that impacts catalysis, though identifying and predicting these effects has remained out of reach. Nickel-substituted rubredoxin (NiRd), a protein-based mimic of a hydrogenase enzyme, serves as a model catalytic system in which dynamics can be systematically investigated with respect to activity. While over 30 secondary-sphere mutants of NiRd have been shown to be catalytically active, no significant correlation was observed between the rates and catalytic overpotential or electronic structure, prompting questions about the protein-derived factors that modulate activity. Here, in this work, NMR spectroscopy was used to investigate the roles of substrate accessibility, protein dynamics, and protein stability in controlling catalysis. Significant paramagnetic effects from the nickel center (S = 1) isolate the methylene proton resonances of the metal-coordinating cysteine residues. The sensitivity of resonance positions and linewidths to local environment offers an opportunity to study dynamical molecular changes around the metal center with high resolution. Machine learning algorithms were employed to identify correlations between the catalytic activity and the paramagnetic NMR spectra. These analyses revealed spectroscopic features of specific cysteine protons that report on catalytic overpotential and increased turnover rates, which are further supported by the results obtained using high-field NMR techniques. Collectively, these studies indicate the potential for multifrequency NMR techniques to resolve key contributors to catalytic activity and highlight the importance of local and outer-sphere dynamics.

Protein Engineering↗

Structure-guided functional suppression of AML-associated DNMT3A hotspot mutations

DNA methyltransferases DNMT3A- and DNMT3B-mediated DNA methylation critically regulate epigenomic and transcriptomic patterning during development. The hotspot DNMT3A mutations at the site of Arg822 (R882) promote polymerization, leading to aberrant DNA methylation that may contribute to the pathogenesis of acute myeloid leukemia (AML). However, the molecular basis underlying the mutation-induced functional misregulation of DNMT3A remains unclear. Here, we report the crystal structures of the DNMT3A methyltransferase domain, revealing a molecular basis for its oligomerization behavior distinct to DNMT3B, and the enhanced intermolecular contacts caused by the R882H or R882C mutation. Our biochemical, cellular, and genomic DNA methylation analyses demonstrate that introducing the DNMT3B-converting mutations inhibits the R882H-/R882C-triggered DNMT3A polymerization and enhances substrate access, thereby eliminating the dominant-negative effect of the DNMT3A R882 mutations in cells. Together, this study provides mechanistic insights into DNMT3A R882 mutations-triggered aberrant oligomerization and DNA hypomethylation in AML, with important implications in cancer therapy.

59 BASIC BIOLOGICAL SCIENCES↗

Model scripts associated with “Revisiting controls on hyporheic respiration with knowledge-guided machine learning at continental scale”

NOTE: The manuscript associated with this data package is currently in review. The data/scripts may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final scripts and additional metadata. This data package is associated with the publication “Revisiting controls on hyporheic respiration with knowledge-guided machine learning at continental scale” submitted to Environmental Science & Technology (Zheng et al. 2026). The project combines mechanistic process modeling with knowledge-guided machine learning (KGML) to evaluate how organic matter chemistry, microbial biomass, and physical substrate accessibility regulate realized respiration rates across river corridors. All data used in this paper have been previously published and can be accessed at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1729719 (Goldman et al., 2020). This data package contains 3 R-markdown (Rmd) preprocessing scripts for the previously published data and subsequent modelling workflows. The full workflow with input and output data can be found in the associated GitHub repository at https://github.com/jianqiuz/KGML-WHONDRS.

Biogeochemistry↗

Heterogeneous Integration of Flipped Oxide Heterostructure Membranes for Nanoelectronics

Freestanding complex oxide membranes enable the release and transfer of epitaxial films, offering new design freedoms for next‐generation electronics. While the LaAlO 3 /SrTiO 3 (LAO/STO) heterostructure exhibits remarkable tunable conductivity at its interface, the active interface remains buried beneath the substrate, limiting access to this functionality. Here, we demonstrate how the LAO/STO heterostructure, in membrane form, can be flipped and precisely positioned on silicon and other platforms using polymer‐free micromanipulation. The transferred membranes preserve atomically smooth surfaces, high crystallinity, and key electronic properties. Through the 44‐nm insulating STO layer, ultra‐low‐voltage electron‐beam lithography (ULV‐EBL) writes conductive nanostructures at the now‐accessible STO/LAO interface, offering the potential to function as programmable local gates that modulate charge carriers in the underlying silicon. The platform establishes a general strategy for integrating complex oxide heterostructures with semiconductors, quantum materials, and flexible substrates, enabling new architectures for reprogrammable nanoelectronic devices.

36 MATERIALS SCIENCE↗

Crystal structures of Salmonella enterica FraB deglycase reveal a conformational heterodimer with remarkable structural plasticity at the active site

Abstract Thefralocus ofSalmonella entericaencodes five genes for metabolism of fructose‐asparagine, an Amadori product formed by condensation of asparagine with glucose. In the last step of this pathway, the FraB deglycase cleaves 6‐phospho‐fructose‐aspartate into glucose‐6‐phosphate and aspartate. In homology models, FraB forms a homodimer with two equivalent active sites located at the dimer interface. E214 and H230, two invariant residues essential for catalysis, project into each active site cleft from opposing subunits of the dimer. Here, we have determined six crystal structures of FraB, three of a variant containing an N‐terminal His 6 tag and two mutations needed for crystallization (hereafter referred to as WT′), two with additional mutations to active site residues (E214A and P232A), and one of a variant with C‐terminal residues 313–325 deleted. Surprisingly, in the WT′ FraB structure, the two catalytic residues, E214 (general base) and H230 (general acid), are positioned ~22 Å apart. In the E214A and C‐terminus‐truncated FraB variants, however, a conformational change in the E214‐residing helix brings E214 and H230* to ~7 Å (* indicates residue from the second protomer that creates the inter‐subunit catalytic center). The loop bearing H230 also exhibits significant variation, ranging from being completely disordered to adopting open or closed states, with the nearby P232* residue being eithercisortrans. The C‐terminal residues 313–325 form a flexible “C‐tail” that can be fully disordered, bind in the active site to block access of substrate, or angle across the active site to wrap across the other subunit of the dimer and potentially close over substrate. Collectively, these structures reveal that FraB is a conformational heterodimer with two chemically identical subunits that are constrained to adopt different structures as they come together for catalysis. This plasticity likely involves correlated opening and closure of the two active sites for their respective binding and release of substrates and ligands.

Biochemistry & Molecular Biology↗

Optimizing semi-hydrogenation of unsaturated hydrocarbons by electrolyte engineering approach

Electrochemical hydrogenation of unsaturated hydrocarbons, when powered by renewables, represents a unique opportunity to substitute current energy-intensive synthetic routes. Modulation of adsorption energies of the organic substrate and key intermediates of the reaction is critical for fine tuning of the yield, selectivity and kinetics of the reaction. Interestingly, mounting evidence exists regarding the role of electrolyte composition in the outcome of semi-hydrogenation reactions. Nevertheless, electrolyte optimization is a complex task, owing to its hybrid nature. Indeed, it is composed of water serving as a proton source, an organic solvent necessary to dissolve the organic substrate and a conducting salt. Herein, we demonstrate that varying conducting salt and organic solvent has a dramatic impact on the outcomes of semi-hydrogenation of alkynes. By varying salt and water concentrations, we demonstrate that water does not serve as a proton source, and instead addition of an acid is necessary. While increasing the acid concentration increases the yield of the reaction, at too large concentrations the hydrogen evolution reaction becomes predominant. Furthermore, by combining electrochemical measurements with spectroscopic techniques including Fourier transform infrared (FTIR) spectroscopy and small angle X-ray spectroscopy (SAXS), we demonstrate that the electrolyte solvation structure dramatically impacts the yield of the reaction. Organic solvents weakly interacting with water, including acetonitrile, form aqueous nanoheterogeneities that prevent the organic substrate from accessing the catalyst interface and thus lead to limited yields. Instead, solvents such as dimethylformamide form homogeneous mixtures with which all reactants can access the interface, leading to yields greater than 80% for optimized compositions.

Zhang, Rongyu↗

Microbial responses to long-term warming differ across soil microenvironments

Soil carbon loss is likely to increase due to climate warming, but microbiomes and microenvironments may dampen this effect. In a 30-year warming experiment, physical protection within soil aggregates affected the thermal responses of soil microbiomes and carbon dynamics. In this study, we combined metagenomic analysis with physical characterization of soil aggregates to explore mechanisms by which microbial communities respond to climate warming across different soil microenvironments. Long-term warming decreased the relative abundances of genes involved in degrading labile compounds (e.g. cellulose), but increased those genes involved in degrading recalcitrant compounds (e.g. lignin) across aggregate sizes. These changes were observed in most phyla of bacteria, especially for Acidobacteria, Actinobacteria, Bacteroidetes, Chloroflexi, and Planctomycetes. Microbial community composition was considerably altered by warming, leading to declined diversity for bacteria and fungi but not for archaea. Microbial functional genes, diversity, and community composition differed between macroaggregates and microaggregates, indicating the essential role of physical protection in controlling microbial community dynamics. Our findings suggest that microbes have the capacity to employ various strategies to acclimate or adapt to climate change (e.g. warming, heat stress) by shifting functional gene abundances and community structures in varying microenvironments, as regulated by soil physical protection.

59 BASIC BIOLOGICAL SCIENCES↗

Understanding the Effects of Ash Content on Various Pretreatment Technologies for the Bioconversion of Corn Stover

Here, the study aimed to examine the effects of adding biomass ash on the biochemical processes involved in fermentable sugar production. Corn stover was pretreated using several methods—hot water, dilute acid, alkaline, γ-valerolactone, and ionic liquid methods, each examined with ash loadings of 7.18% and 21.07%. The findings demonstrated that increased ash content adversely affected both pretreatment and enzymatic hydrolysis. Specifically, the total sugar yield was 3 to 16% lower at the higher ash content across all pretreatment methods, and up to 4.01% lower during enzymatic hydrolysis. For acidic pretreatment, the sugar yield decreased as ash content increased. In contrast, ash content had a lesser impact on alkaline pretreatment compared to acidic pretreatment. For example, using corn stover with an ash content as high as 22.65% resulted in only a 2.90% decrease in total sugar yield compared to corn stover without added ash. Further, the primary reasons for the reduced sugar yield in higher ash biomass during acidic pretreatments were likely the neutralizing effect of the ash and decreased acid access to the substrates. During enzymatic hydrolysis, ash reduced the sugar yield by limiting enzyme access to cellulose.

09 BIOMASS FUELS↗

Distinguishing isotropic and anisotropic signals for X-ray total scattering using machine learning

Understanding structure–property relationships is essential for advancing technologies based on thin films. X-ray pair distribution function (PDF) analysis can access relevant atomic structure details spanning local-, mid- and long-range structure. While X-ray PDF has been adapted for thin films on amorphous substrates, measurements on single-crystal substrates are necessary to accurately determine structure origins for some thin film materials, especially those for which the substrate changes the accessible structure and properties. However, when measuring films on single-crystal substrates, high-intensity anisotropic Bragg spots saturate 2D detector images, overshadowing the thin films' isotropic scattering signal. This renders previous data processing methods for films on amorphous substrates unsuitable for films on single-crystal substrates. To address this measurement need, we developed IsoDAT2D, an innovative data processing approach using unsupervised machine learning algorithms. The program combines dimensionality reduction and clustering algorithms to separate thin film and single-crystal substrate X-ray scattering signals. We use SimDAT2D , a program we developed to generate simulated thin film data, to validate IsoDAT2D . Here we also use IsoDAT2D to isolate X-ray total scattering signal from a thin film on a single-crystal substrate. The resulting PDF data are compared with similar data processed using previous methods, especially substrate subtraction for single-crystal and amorphous substrates. PDF data from IsoDAT2D -identified X-ray total scattering data are significantly better than from single-crystal substrate subtraction, but not as reliable as PDF data from amorphous substrate subtraction. With IsoDAT2D , there are new opportunities to expand PDF to a wider variety of thin films, including those on single-crystal substrates, with which new structure–property relationships can be elucidated to enable fundamental understanding and technological advances.

36 MATERIALS SCIENCE↗

Structural and Mechanistic Advances in the Chemistry of Methyl-Coenzyme M Reductase (MCR)

Methane represents 34% of U.S. energy consumption and is a major greenhouse gas related to the global carbon cycle and energy production. However, current industrial practices significantly increase atmospheric methane levels, necessitating a deeper understanding of its biosynthesis and oxidation. Methyl-coenzyme M reductase (MCR) is central to biological methane metabolism, catalyzing the final step of methanogenesis and the first step in anaerobic methane oxidation. It is also a key target for strategies to capture and transform methane into value-added chemicals.The active site of MCR is a buried Ni-based cofactor only accessible by the substrates via a 50 Å long tunnel. Although the Ni(I) state is required to initiate catalysis, capturing this state remains a challenge for the current structural techniques. Recent advances in structural biology using X-ray Free-Electron Laser serial crystallography have provided insights into MCR's inactive Ni(II) state at room temperature and show promise for capturing its active Ni(I) form.Our team has established several critical aspects of the MCR mechanism using a combination of experimental and computational studies. MCR uses CH 3 -SCoM and CoBSH as substrates, producing methane and a disulfide product CoMSSCoB. Kinetic analysis showed that productive substrate binding requires CH 3 -SCoM to bind first, inducing conformational changes that optimize the active site for subsequent CoBSH binding. Following substrate binding, four proposed methane production/oxidation mechanisms were examined, establishing whether the reaction proceeds through an organometallic methyl-nickel(III), methyl anion ion, or methyl radical intermediate. Experimental measurements using CoBSH analogs successfully slowed the reaction, allowing for mechanistic insight that demonstrated the methyl radical pathway, where the initial interactions involve homolytic cleavage of the methyl-sulfur bond, generating a methyl radical that quickly abstracts the thiol hydrogen atom of CoBSH to form methane. Computational studies further confirmed that, compared to other mechanisms, the methyl radical mechanism is thermodynamically more favorable and accessible under physiological conditions.Spectroscopic and computational studies challenged the conventional understanding of substrate binding in MCR by proposing an alternative positioning of CH 3 -SCoM and CoMSSCoB in the active site pocket. The research suggested that CH 3 -SCoM (substrate) and CoMSSCoB (product) bind via their sulfonate groups to the Ni(I) center of cofactor F 430 . This binding allows for the reaction without substrate reorganization in the pocket but would require a long-range electron transfer. Altogether, the work summarized in this review reflects our current understanding of the enzyme's catalytic mechanism and structural dynamics. This is essential for developing efficient methane conversion technologies that could mitigate its environmental impact while harnessing energy-storage properties.

03 NATURAL GAS↗

Optical memory development. Volume 3: The membrane light value page composer

The feasibility of producing a page composer for optical memory systems using thin, deformable, membrane-mirror elements as light valves was investigated. The electromechanical and optical performances of such elements were determined both analytically and experimentally. It was found that fast switching (approximately 10 microseconds), high-contrast (10 or greater), fatigue-free operation over missions of cycles, and efficient utilization of input light could be obtained with membrane light valves. Several arrays of 64 elements were made on substrates with feedthroughs, allowing access to individual elements from the backside of the substrate. Single light valves on such arrays were successfully operated with the transistors designed and produced for selection and storage at each bit location. This simulated the operation of a prototype page composer with semiconductor chips beam-lead bonded to the back of the substrate.

Cosentino, L. S.↗