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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Double Paddle‐Wheel Enhanced Sodium Ion Conduction in an Antiperovskite Solid Electrolyte

Abstract Antiperovskite structure compounds (X 3 AB, where X is an alkali cation and A and B are anions) have the potential for highly correlated motion between the cation and a cluster anion on the A or B site. This so‐called “paddle‐wheel” mechanism may be the basis for enhanced cation mobility in solid electrolytes. Through combined experiments and modeling, the first instance of a double paddle‐wheel mechanism, leading to fast sodium ion conduction in the antiperovskite Na 3− x O 1− x (NH 2 ) x (BH 4 ), is shown. As the concentration of amide (NH 2 − ) cluster anions is increased, large positive deviations in ionic conductivity above that predicted from a vacancy diffusion model are observed. Using electrochemical impedance spectroscopy, powder X‐ray diffraction, synchrotron X‐ray diffraction, neutron diffraction, ab initio molecular dynamics simulations, and NMR, the cluster anion rotational dynamics are characterized and it is found that cation mobility is influenced by the rotation of both NH 2 − and BH 4 − species, resulting in sodium ion conductivity a factor of 10 2 higher at x = 1 than expected for the vacancy mechanism alone. Generalization of this phenomenon to other compounds could accelerate fast ion conductor exploration and design.

25 ENERGY STORAGE↗
DOE OSTI2024

HydraGNN_Predictive_GFM_2024 - Ensemble of predictive graph foundation models for ground state atomistic materials modeling

We provide the ensemble of fifteen pre-trained graph foundation models (GFMs) for atomistic materials modeling applications. Each one of the fifteen GFMs has been trained on five open-source datasets that (once aggregated) amount to over 154 million atomistic structures, which cover over two-thirds of the natural elements of the periodic table and that comprises a broad set of organic and inorganic compounds. This vast set of atomistic structures comprises ground state configurations that are dynamically stable (i.e., equilibrated structures with atomic forces approximately close to zero values) as well as dynamically unstable structures (i.e., non-equilibrium structures with non-negligible non-zero values of atomic forces). The ensemble of datasets aggregated does NOT include excited states. The datasets have been curated to remove atomistic structures with spectral norm of the force tensor above 100 eV/angstrom. Moreover, a linear term of the energy was computed for each dataset using a linear regression model that uses the chemical concentration of each natural element as regressor. The linear term predicted by the linear regression model has been subtracted from each original energy value to perform a re-alignment of the energy values across different electronic structures approximation theories performed to generate the diverse multi-source, multi-fidelity datasets. The folder "ADIOS_files" contains the set of pre-processed datasets in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used for the development and training of GFMs in this work. The "ADIOS_files" directory contains 6 sub-directories named as follows: - ANI1x-v3.bp - MPTrj-v3.bp - OC2020-20M-v3.bp - OC2020-v3.bp - OC2022-v3.bp - qm7x-v3.bp Each sub-directory contains the pre-processed datasets converted in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used to the development, training, and performance testing of the ensemble go predictive graph foundation models. Each GFM was developed using HydraGNN (https://github.com/ORNL/HydraGNN) as underlying graph neural network (GNN) architecture. The multi-task learning (MTL) capability of HydraGNN was used to simultaneously train the GFMs on labeled values for direct predictions of energy (a total system property of an atomistic structure that measures the chemical stability) and atomic forces (an atomic level property of an atomistic structure that measures the dynamical stability). The hyper parameters of the GFM have been tuned using scalable hyperparameter optimization (HPO) algorithms implemented in the software DeepHyper (https://github.com/deephyper/deephyper). The pre-training of each HPO trial was performed using distributed data parallelism (DDP) to scale the training across 128 compute nodes of the exascale OLCF supercomputer Frontier. Each HPO trial was trained only for 10 epochs and an early stopping was performed to avoid wasting significant computational resources on GNN architectures that were clearly underperforming. For each HPO trial, the 'omnistat' tool developed by (AMD Research - Advanced Micro Device) was used to measure the total energy consumption in kWh. The ensemble of GFMs was obtained by selecting the fifteen best performing HPO trials. Four models have been selected for their clear advantage in accuracy, and these are the GFMs with IDs 229, 156, 147, 260. Additional eleven models have been selected based on judicious balance between accuracy and energy consumption needed for training, and these are the GFMs with IDs 165, 78, 137, 1, 175, 171, 181, 67, 179, 167, 351. Each selected GFM of the ensemble was continued to cumulate a total of at most 30 epochs. In some cases, the total number of epochs actually performed was les than 30 due to two combined factors: (1) the size of the GFM (i.e., the number of model parameters to train) and (2) the total wall-clock time for which the computational resources could be allocated on OLCF-Frontier. The "Ensemble_of_models" directory contains 15 sub-directories named as follows: - gfm_0.229 - gfm_0.156 - gfm_0.147 - gfm_0.260 - gfm_0.165 - gfm_0.78 - gfm_0.137 - gfm_0.1 - gfm_0.175 - gfm_0.171 - gfm_0.181 - gfm_0.67 - gfm_0.179 - gfm_0.167 - gfm_0.351 Each one of these sub-directories refers to one of the fifteen HPO trials that have been selected to continue the pre-training with at most 30 epochs. With each sub-directory associated with a specific HPO trial, the following files can be found: - config.json: file for argument parsing to develop and train an HydraGNN architecture - gfm_0.ID_epoch_N.pk: file with model parameters for HPO ID trial after N epochs of training The ensemble of fifteen GFM architectures was used for (1) ensemble averaging to stabilize the predictions of energy and atomic forces after pre-training for post-processing analysis and (2) ensemble uncertainty quantification (UQ). The code used to develop, pre-train, and load the pre-trained models for post-processing analysis is available on the ORNL-GitHub at the following link: https://github.com/ORNL/HydraGNN/tree/Predictive_GFM_2024

36 MATERIALS SCIENCE↗
DOE OSTI2024

Systematic engineering for production of anti-aging sunscreen compound in Pseudomonas putida

Sunscreen has been used for thousands of years to protect skin from ultraviolet radiation. However, the use of modern commercial sunscreen containing oxybenzone, ZnO, and TiO 2 has raised concerns due to their negative effects on human health and the environment. In this study, we aim to establish an efficient microbial platform for production of shinorine, a UV light absorbing compound with anti-aging properties. First, we methodically selected an appropriate host for shinorine production by analyzing central carbon flux distribution data from prior studies alongside predictions from genome-scale metabolic models (GEMs). We enhanced shinorine productivity through CRISPRi-mediated downregulation and utilized shotgun proteomics to pinpoint potential competing pathways. Simultaneously, we improved the shinorine biosynthetic pathway by refining its design, optimizing promoter usage, and altering the strength of ribosome binding sites. Finally, we conducted amino acid feeding experiments under various conditions to identify the key limiting factors in shinorine production. The study combines meta-analysis of 13 C-metabolic flux analysis, GEMs, synthetic biology, CRISPRi-mediated gene downregulation, and omics analysis to improve shinorine production, demonstrating the potential of Pseudomonas putida KT2440 as platform for shinorine production.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Rationally Designed, Short-Acting RPE65 Inhibitors for Visual Cycle-Associated Retinopathies

Abstract The visual cycle is a metabolic pathway essential for visual function. The bisretinoid byproducts of this pathway can induce retinal toxicity, as occurs in Stargardt disease type 1 (STGD1). Emixustat, which inhibits bisretinoid production, is a visual cycle modulator (VCM) that targets RPE65. However, it causes visual impairment due to its unfavorable duration of action. Here, we report ester-containing analogs of emixustat that are susceptible to hydrolytic clearance and function as short-acting VCMs. We show that the esterase-mediated metabolism of these compounds can be tuned while maintaining high-affinity RPE65 targeting. Compounds 6 (EYE-002) and 7 (EYE-003) containing diethyl acetate and valproate esters, respectively, allowed faster recovery of visual cycle function compared to emixustat. These molecules protected against retinal degeneration in mouse models of photic retinopathy and STGD1. These data demonstrate that shorter attenuation of the visual cycle can therapeutically intervene in retinal diseases with fewer visual side effects compared to emixustat.

Pharmacology & Pharmacy↗
DOE OSTI2026

Continental-scale integration of soil metagenomes and organic matter chemistry reveals ubiquitous microbial capacity for chemically-recalcitrant carbon decomposition

Soil organic matter (SOM) decomposition by microorganisms is a major uncertainty in predicting terrestrial carbon–atmosphere feedbacks, partly because we lack understanding of the microbial diversity involved in depolymerizing different carbon pools across environmental gradients. We address this gap using a continental-scale dataset pairing shotgun metagenomes with high-resolution SOM chemistry, assembling 0.76 Tbp of prokaryotic MAGs (828 genomes) and identifying 66,727 SOM molecules from 47 standardized U.S. soil cores selected using respiration rates from 106 soils. Integrating these datasets reveals widespread microbial potential for depolymerizing chemically-recalcitrant SOM previously considered stable. We uncover complementary metabolic specialization between genera affiliated with two abundant bacterial orders, Rhizobiales and Chthoniobacterales, and an archaeal order, Nitrososphaerales. This metabolic partitioning is consistent across soil depths and activity levels, suggesting coordinated decomposition of complex SOM through distinct but complementary biochemical strategies. The metabolic potential for depolymerization of chemically-recalcitrant compounds is supported by the abundance of these molecules across the soils, as indicated by Fourier-Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR-MS), and by flux balance analysis of metabolic models. Our results show that a substantial portion of ostensibly stable SOM remains vulnerable to microbial decomposition, a mechanism not captured in current Earth System Models.

Song, Young C. [Pacific Northwest National Laborat↗
DOE OSTI2025

Exploring a New Regime of Molecular Orbital Physics in 4⁢d Cluster Magnets with Resonant Inelastic X-Ray Scattering

Molecular orbital systems with clusters of heavy transition metal (TM) ions are one of the most important classes of model materials for studying the interplay between local physics and effects of itinerancy. Despite a large number of candidates identified in the family of 4⁢d TM materials, an understanding of their physics from competing microscopic energy scales is still missing. Here, we bridge this gap by reporting the first resonant inelastic x-ray scattering (RIXS) measurement on a well-known series of Ru cluster magnets with a 6⁢H-perovskite structure Ba 3 ⁢M⁢Ru 2 ⁢O 9 (M 3+ = In 3+ , Y 3+ , La 3+ ) comprised of Ru dimers. In addition to providing a microscopic explanation for their anomalous magnetic properties, our RIXS measurements combined with theoretical modeling uncover a new regime of molecular orbital physics where the combined effect of large hopping and small spin-orbit coupling results in highly fragile electronic states in the Ru-dimer compounds directly manifested as an abrupt change in the RIXS spectrum accompanying a tiny change in the local structure tuned by the M-site ion. This unique combination of energy scales found only in the 4⁢d but not the 5⁢d cluster magnets highlights the value of these materials as a new platform for studying quantum phase transition involving molecular orbitals.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Using in situ UO 2 bicrystal sintering to understand grain boundary dislocation nucleation kinetics and creep

Capillary evolution at bicrystal UO 2 grain boundaries is characterized using in situ transmission electron microscopy. The discontinuous nature of the densification process, both particle rotation and axial strain, along with the large activation stress for densification support a hypothesis that grain boundary strain in UO 2 follows nucleation rate limited kinetics at low to intermediate stresses, that is, less than ≈ 10 8 PA. Further, the temperature dependence of the average activation stress for sintering agrees well with analysis of bulk sintering data and creep data reported within the literature when analyzed in the context of a grain boundary dislocation nucleation rate limited kinetic model.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Simulated Evaluation of Powder Flowability Through a Partially Obstructed Consumable in Blown Powder Directed Energy Deposition Systems

Abstract In the interest of continued industrialization of metal additive manufacturing in modern production environments, cost is often referenced as a primary deterrent to new adopters. Conventional economic models for additive systems, processes, and supply chains often focus on specific process applications with little generalizability, or they neglect significant costs associated with production such as machine maintenance and consumable part replacement. Compounding the latter issue are substantial knowledge gaps in consumable part wear characterization for additive and other convergent manufacturing systems. In coaxial blown powder directed energy deposition systems, gas atomized metal powder is wasted during material deposition at a rate that is partly dependent on present wear phenomena in a consumable nozzle housed in the cladding head assembly. The price and lead time required to replace the nozzle incentivizes its reuse even when visibly worn. Often this initiates a process quality decline in the form of underbuilt geometry and internal defects due to losses in powder catchment efficiency. While depositing H13 steel using a hybrid manufacturing machine tool equipped with such a deposition system, a unique partial clog with a bridge-like structure formed at the consumable nozzle exit when supporting argon gas flows failed mid-process. To further understand coaxial multi-phase powder flow in the event of support gas failure, a computational fluid dynamics simulation is tailored to relevant process parameters, H13 powder material profile, and machine operator observations collected after the incident. The resulting differences in powder flow compared to control gas flow parameters is presented and discussed. The powder flowability and performance of the clogged nozzle is then assessed by using an optical profilometer to extract the profile of the clog and recreate the clog geometry within the simulation environment. In past work this simulation has been experimentally validated for a 316L steel powder material profile and used specifically for analyzing powder stream geometry and catchment efficiency. After the initial powder flow characterization, the clog is removed, and the nozzle is reprofiled. After removing the obstructing clog, the newly unobstructed nozzle geometry, the original off the shelf nozzle geometry, and additional nozzle profiles exploring different consumable refurbishment strategies are reevaluated in the simulation. Powder catchment efficiency for all variant nozzle geometries and relevant flow variables are compared and discussed, along with potential mitigation strategies for optimizing powder flowability with worn consumables. This work expands on the known morphology of blown powder obstructions and wear defects present in consumable coaxial nozzles while discussing pragmatic simulation driven responses to unanticipated subsystem failure in hybrid manufacturing machining platforms.

DeWitte, Lisa↗
DOE OSTI2026

Data from a four-day long microcosm experiment addressing the destabilization of artificial mineral-associated organic matter by model root exudates embedded in a soil matrix from the Rocky Mountain Biological Laboratory (Gothic, CO, USA), 2019

This dataset provides data collected during a four-day long laboratory soil microcosm experiment testing the efficacy of root exudate-driven mineral-associated organic matter destabilization. This dataset contains four data files in comma-separate values (*.csv). The files provide the metadata and the experimental results on microbial respiration, MAOM-derived respiration, and sequential mineral-extractions. This data was used to produce the figures in Bölscher et al., 2026. The results of the experiment can be found in the open access article Bölscher et al., 2026 (https://doi.org/10.1016/j.soilbio.2026.110276). Abstract: Mineral-associated organic matter (MAOM) is often considered stable, but root exudates can destabilize MAOM via various pathways. Theory and model system studies suggest that direct MAOM destabilization by strong ligands, like oxalic acid, or reducing agents, like catechol, is more effective than indirect, microbial-mediated MAOM destabilization, stimulated by less reactive compounds like glucose. Here, we demonstrate that the presence of a soil matrix alters the efficacy of exudate-driven MAOM destabilization pathways. Glucose and catechol destabilized significantly greater amounts of MAOM from ferrihydrite and aluminum hydroxide (Al (OH)3) embedded in a soil matrix than oxalic acid. Our findings indicate that indirect, microbial-mediated MAOM destabilization may play a larger role than direct MAOM destabilization in soil environments.

Destabilization↗
DOE OSTI2021

Developing Multi-Gene CRISPRa/I Programs to Accelerate DBTL Cycles in ABF Hosts Engineered for Chemical Production (CRADA 468)

Bacterial metabolism is comprised of large and complex gene networks that can produce valuable chemical products. Sophisticated organism engineering efforts are required to optimize production of high-value compounds from these networks. In principle, synthetic multi-gene transcriptional programs could be constructed to reengineer these networks for efficient industrial chemical production. In practice, however, our incomplete ability to understand and model the underlying networks, combined with our limited ability to predictably control the expression of multiple genes makes achieving this goal difficult. To overcome these challenges, we will combine new CRISPR-Cas multi-gene expression programs with computational modeling, machine learning, and multi-omics data to enhance the efficacy of design-build-test-learn (DBTL) cycles. For industrially promising microorganisms in early stages of development, creating technologies for rapidly engineering complex multi-gene programs could be transformative for accelerating data- and model-driven strain design. New CRISPR-Cas tools allow programmable gene activation (CRISPRa) or repression (CRISPRi) at multiple genes simultaneously, using the catalytically inactive Cas9 protein (dCas9) with guide RNAs that recognize DNA targets through predictable Watson-Crick base pairing. To enable accelerated DBTL cycles, we will combine these technologies with advanced Agile BioFoundry (ABF) capabilities for multi-omics data collection and machine learning. We will demonstrate the immediate applicability of these tools by rapidly improving the production of an industrial aromatic in multiple ABF organisms. We recently identified and optimized new transcriptional activators that can be linked to programmable CRISPR-Cas DNA binding domains to activate gene expression in E. coli. We can now use these CRISPRa tools as generalizable trans-acting regulators for combinatorial multi-gene expression tuning that can be easily transferred to new pathways and networks without additional genome engineering. We anticipate these tools will also transfer to new hosts. We have recently found that CRISPRa systems developed in E. coli can be readily ported to Pseudomonas putida, suggesting that multi-gene CRISPRa/i programs for diverse ABF organisms may be within reach.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Characterizing the Defense Hierarchy of Populus trichocarpa

The U.S. Departments of Energy and Agriculture are developing bioenergy crops as a sustainable alternative to traditional fossil fuels. Plant disease threatens this effort by inhibiting the efficient production of plant feedstocks for bioenergy. In particular, biotrophic Melampsora leaf rust pathogens can increase morbidity in Populus trichocarpa and its hybrids (aka poplars), the primary woody feedstocks for bioenergy. Controlling rust disease in plantations is thus critical to the success of the poplar bioenergy program. Current efforts to control rust disease focus on plant genetic resistance. However, with novel pathogenic variation generated by the global movement of pathogens and their hybridization, it is increasingly clear that controlling rust disease in a long-lived plant like Populus depends on our ability to understand and manage not only genes for rust resistance, but also short-lived plant microorganisms that contribute to defense against rust (aka “defense mutualists”). Our proposed research thus seeks to develop an integrative, hierarchical model of P. trichocarpa defense that integrates genetic resistance and defense mutualists. Our overarching hypothesis is that defense against Melampsora rust is biologically degenerate, with major and minor plant resistance genes, plant defense compounds, and defense mutualists within the microbiome each contributing to rust resistance under different circumstances. The specific aims of our study will test the placement of each of these factors in the defense hierarchy. Ultimately, it is our hope that disease management strategies harnessing both resistance genes and naturally occurring defense mutualists of P. trichocarpa, and an appreciation of the ecological circumstances in which each is effective, will maximize plant resistance and productivity while minimizing impacts on the surrounding ecological landscape.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Structure-Aware Unsupervised, Transformational Machine Learning for Drug Discovery (DTRA Basic Research Final Report)

The major goal of this project is to develop machine learning (ML) methods to enable improved predictive power on real drug discovery for novel targets. More specifically, we planned to demonstrate the capability and effectiveness of ML tools utilizing unlabeled large-volume protein-ligand datasets. We investigated multiple pre-training approaches for 3D protein-ligand structure-based foundation models, without relying on experimental binding data. We also addressed scenarios in which crystal structures are unavailable or binding data are limited. We also planned to develop a complete pipeline to screen novel compounds as well as to demonstrate the capability and effectiveness of the developed methods by testing on a realistic drug discovery task such as SARS-CoV-2. While the major goals and milestones remain consistent with the original proposal, certain technical details have been adjusted, based on the experimental results and related outcomes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Experimental Comparison of Elastomeric Materials for Hydraulic Seal Durability under Reciprocating Conditions

Wave Energy Converters (WECs) rely on hydraulic Power Take-Off (PTO) systems to transform the kinetic energy of ocean waves into electricity, where hydraulic seals play a critical role in preventing fluid leakage and ensuring watertight operation under harsh marine conditions. However, seal degradation due to wear, fatigue, and corrosion remains a key challenge limiting system reliability and increasing maintenance costs. In this study, the tribological performance of elastomeric materials for hydraulic sealing applications that are based on commercial polyurethane and custom-compounded Ethylene Propylene Diene Monomer (EPDM) is investigated. Using a CSM tribometer, reciprocating wear tests were conducted in accordance with ASTM G133 under dry sliding conditions, with normal loads ranging from 3 to 10 N, and sliding speeds of 10 to 30 mm/s. Coefficient of friction (COF), specific wear rate, and worn surface morphology are evaluated to understand how load, velocity, and material composition affect seal durability. Improved wear stability and high Shore A hardness (93–94) were demonstrated by the commercial thermoplastic polyurethane (Duralast 4203 and 4758). EPDM-based compounds showed different filler-dependent behaviors, formulations filled with carbon black (E3) had the lowest wear rate (1.45 × 10?4 mm³ N?¹ m?¹) and increased load-bearing capacity, while samples modified with silica and plasticizer (E4, E5) had better conformability and damping but less hardness. Compounded EPDMs showed wider deformation zones because of their lower modulus and filler-matrix interfacial fluctuations, while commercial grades exhibited shallower wear scars (= 380 µm), according to optical profilometry. The Archard model-based lifetime estimation showed that, under 10 N and 30 mm/s, operational endurance ranged from 3.1 to 6.2 years. Because of its low wear rate and steady interfacial behavior, E3 had the longest anticipated life. For medium-load hydraulic sealing applications, these results demonstrate the possibility of customized EPDM formulations as affordable substitutes for commercial polyurethanes. They also offer a quantitative foundation for material selection and lifespan prediction.

Durability↗
DOE OSTI2021

Characterizing the contribution of bioaerosols diversity from complex aerosol particle samples.

Current global change scenarios expect to significantly increase the contribution of pollen to the total organic aerosol budget. In addition, pollen can burst into smaller fragments that are highly efficient as cloud condensation nuclei. However, current climate models still do not incorporate the effects of these particles due to detection and quantification challenges in complex aerosol mixtures. Chemical biomarkers (i.e. fructose) have commonly been used to trace pollen but this approximation can generate false positive results given the large number of shared compounds between different bioaerosols. A previous pilot EMSL experiment performed on pure pollen samples suggested that using a set of metabolites as a fingerprint of bioaerosols could serve to substantially increase detection accuracy over single biomarker approaches. In this proposal we developed novel bioinformatic strategies to characterize and quantify complex pollen mixtures present in the atmosphere. For that, we used diverse machine learning algorithms to analyze metabolic fingerprints from complex mixtures of different pollen acquired with high-resolution mass spectrometry (Orbitrap Q-Exactive). Our preliminary results demonstrated the potential to accurately discern and identify at specific relative abundances different pollen species in complex mixtures. Our research will lead to a significant advancement in the atmospheric chemistry and provide much needed data to improve the accuracy of climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Controls on Soil Organic Matter Degradation and Subsequent Greenhouse Gas Emissions Across a Permafrost Thaw Gradient in Northern Sweden

Warming-induced permafrost thaw could enhance microbial decomposition of previously stored soil organic matter (SOM) to carbon dioxide (CO 2 ) and methane (CH 4 ), one of the most significant potential feedbacks from terrestrial ecosystems to the atmosphere in a changing climate. The environmental parameters regulating microbe-organic matter interactions and greenhouse gas (GHG) emissions in northern permafrost peatlands are however still largely unknown. The objective of this work is to understand controls on SOM degradation and its impact on porewater GHG concentrations across the Stordalen Mire, a thawing peat plateau in Northern Sweden. Here, we applied high-resolution mass spectrometry to characterize SOM molecular composition in peat soil samples from the active layers of a Sphagnum-dominated bog and rich fen sites in the Mire. Microbe-organic matter interactions and porewater GHG concentrations across the thaw gradient were controlled by aboveground vegetation and soil pH. An increasingly high abundance of reduced organic compounds experiencing greater humification rates due to enhanced microbial activity were observed with increasing thaw, in parallel with higher CH 4 and CO 2 porewater concentrations. Bog SOM however contained more Sphagnum-derived phenolics, simple carbohydrates, and organic- acids. The low degradation of bog SOM by microbial communities, the enhanced SOM transformation by potentially abiotic mechanisms, and the accumulation of simple carbohydrates in the bog sites could be attributed in part to the low pH conditions of the system associated with Sphagnum mosses. We show that Gibbs free energy of C half reactions based on C oxidation state for OM can be used as a quantifiable measure for OM decomposability and quality to enhance current biogeochemical models to predict C decomposition rates. We found a direct association between OM chemical diversity and δ 13 C-CH 4 in peat porewater; where higher substrate diversity was positively correlated with enriched δ 13 C-CH 4 in fen sites. Oxidized sulfur-containing compounds, produced by Sphagnum, were further hypothesized to control GHG emissions by acting as electron acceptors for a sulfate-reducing electron transport chain, inhibiting methanogenesis in peat bogs. These results suggest that warming-induced permafrost thaw might increase organic matter lability, in subset of sites that become wetlands, and shift biogeochemical processes toward faster decomposition with an increasing proportion of carbon released as CH 4 .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Accurate Prediction of pKb in Amines: Validation of the CAM-B3LYP/6-311+G(d,p)/SMD Model

Amines play several key roles in chemistry and biology and are involved in numerous industrial processes, often with significant economic impacts. Recently, amines are also garnering interest as catalysts for polymer synthesis and for CO 2 fixation, incentivizing the need to rapidly design and screen new amino compounds. Hence, developing reliable methods to predict their physicochemical properties, e.g., the base dissociation constant (pKb), is pivotal. Here, a density functional theory (DFT)-based approach was employed to compute the pKb of substituted amines, exploring the impact of several key parameters, including (i) the number of explicit water molecules at the reaction center, (ii) the van der Waals (vdW) surface, and (iii) solvent polarizability. In previous work, it was determined that including two explicit water molecules at the reaction center resulted in highly accurate pKb estimates for primary amines. Here, we find that including a third water molecule at the reaction center is essential for accurate pKb for secondary and tertiary amines. The revised methodology was then applied to a wider selection of amines, obtaining a minimum average error (MAE) < 0.4. In conclusion, this result represents an extension of our “easy-to-use method,” a simple and direct DFT approach exploiting CAM-B3LYP/SMD/6-311G+(d,p) to compute pKb without post facto modifications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Estimation of the NiCu Cycle Strength and Its Impact on Type I X-Ray Bursts

Abstract Type I X-ray bursts (XRBs) are powered by thermonuclear burning on proton-rich unstable nuclides. The construction of burst models with accurate knowledge of nuclear physics is required to properly interpret burst observations. Numerous studies that have investigated the sensitivities of burst models to nuclear inputs have commonly extracted the strength of the NiCu cycle in the rp process, determined by the 59 Cu( p , α ) 56 Ni and 59 Cu( p , γ ) 60 Zn thermonuclear reaction rates, as critical in the determination of reaction flow in the burst. In this study, the strength of the cycle at the XRB temperature range was estimated based on published experimental data. The nuclear properties of the compound nucleus 60 Zn were evaluated for the 59 Cu( p , α ) 56 Ni and 59 Cu( p , γ ) 60 Zn reaction rate calculations. Monte Carlo rate calculations were conducted to include the large uncertainties of nuclear properties in the calculations. In the current work, a weak NiCu cycle is expected, whereas the rates adopted by the previous studies suggest a strong NiCu cycle. Model simulations were performed with the new rates to assess the impact on Type I XRBs. The results show that the estimated cycle strength does not strongly influence the model predictions of the burst light curve or synthesized abundances.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

On the Electride Nature of Na–hP4

Early quantum mechanical models suggested that pressure drives solids towards free-electron metal behavior where the ions are locked into simple close-packed structures. The prediction and subsequent discovery of high-pressure electrides (HPEs), compounds assuming open structures where the valence electrons are localized in interstitial voids, required a paradigm shift. Our quantum chemical calculations on the iconic insulating Na-hP4 HPE show that increasing density causes a 3s→3pd electronic transition due to Pauli repulsion between the 1s2s and 3s states, and orthogonality of the 3pd states to the core. The large lobes of the resulting Na-pd hybrid orbitals point towards the center of an 11-membered penta-capped trigonal prism and overlap constructively, forming multicentered bonds, which are responsible for the emergence of the interstitial charge localization in Na-hP4. As a result, these multicentered bonds facilitate the increased density of this phase, which is key for its stabilization under pressure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗