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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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NASA NTRS2005

Apex Reference Manual 3.0 Beta

Apex is a toolkit for constructing software that behaves intelligently and responsively in demanding task environments. Reflecting its origin at NASA where Apex continues to be developed, current applications include: a) Providing autonomous mission management and tactical control capabilities for unmanned aerial vehicles including an autonomous surveillance helicopter and a simulation prototype of an unmanned fixed-wing aircraft to be used for wildfire mapping; b) Simulating human air traffic controllers, pilots and astronauts to help predict how people might respond to changes in equipment or procedures; and c) Predicting the precise duration and sequence of routine human behaviors based on a human-computer interaction engineering technique called CPM-GOMS. Among Apex s components are a set of implemented reasoning services, such as those for reactive planning and temporal pattern recognition; a software architecture that embeds and integrates these services and allows additional reasoning elements to be added as extensions; a formal language for specifying agent knowledge; a simulation environment to facilitate prototyping and analysis; and Sherpa, a set of tools for visualizing autonomy logic and runtime behavior. In combination, these are meant to provide a flexible and usable framework for creating, testing, and deploying intelligent agent software. Overall, our goal in developing Apex is to lower economic barriers to developing intelligent software agents. New ideas about how to extend or modify the system are evaluated in terms of their impact in reducing the time, expertise, and inventiveness required to build and maintain applications. For example, potential enhancements to the AI reasoning capabilities in the system are reviewed not only for usefulness and distinctiveness, but also for their impact on the readability and general usability of Apex s behavior representation language (PDL) and on the transparency of resulting behavior. A second central part of our approach is to iteratively refine Apex based on lessons learned from as diverse a set of applications as possible. Many applications have been developed by users outside the core development team including engineers, researchers, and students. Usability is thus a central concern for every aspect of Apex visible to a user, including PDL, Sherpa, the Apex installation process, APIs, and user documentation. Apex users vary in their areas of expertise and in their familiarity with autonomy technology. Focusing on usability, a development philosophy summarized by the project motto "Usable Autonomy," has been important part of enabling diverse users to employ Apex successfully and to provide feedback needed to guide iterative, user-centered refinement.

Freed, Michael A.↗
NASA NTRSDate not supplied

Assessment of Long-term Trends in the Collection 4 Total Ozone Record from the Ozone Monitoring Instrument

Long-term changes in total ozone affect the amount of harmful UV radiation reaching Earth’s surface and reflect progress made towards recovery of stratospheric ozone. Satellite total ozone data are also used to estimate long-term trends in tropospheric ozone, a reactive and potent greenhouse gas, by subtracting the stratospheric column timeseries from that of total ozone. For these scientific applications, the long-term stability should be better than 1%. Left unchecked, instrument calibration drift can produce a trend of this magnitude or greater. NASA has produced nearly twenty years of total ozone data from the Ozone Monitoring Instrument (OMI) using the Total Ozone Mapping Spectrometer (TOMS) algorithm. The drift in the OMI instrument as monitored by ice radiance calibration has been relatively slow, but it has reached a level of ~3% over the mission lifetime. This drift was corrected in the recently released Collection 4 OMI calibrated radiances, updating the Collection 3 calibration released in 2006. We have reprocessed the OMI total ozone record using the Collection 4 calibration and updates to the TOMS algorithm. We summarize these changes and evaluate their impact by comparing to the previous Collection 3 OMI dataset, the Suomi NPP Ozone Mapping and Profiler Suite Nadir Mapper (OMPS-NM) and Solar Backscatter UV (SBUV) Merged Ozone Dataset (MOD) total ozone records and other independent satellite total ozone datasets. Climatological radiance residuals from OMI and OMPS-NM are calculated and compared to investigate differences in spectral calibration that can cause drifts in long-term total ozone trends. We also analyze the tropospheric ozone record produced using the Collection 4 OMI total ozone and stratospheric column ozone from MLS. Collection 3 OMI data processed with the TOMS algorithm show a positive drift relative to other satellite and ground-based data of 1-2 DU per decade. Initial results show that this drift is reduced in Collection 4 OMI, due to the updated OMI calibration. In this work we will quantify the improvements in Collection 4 OMI relative to independent data sources at both the ozone and radiance level

Collection 4 OMI Total Ozone↗
DOE OSTI2026

The Role of Cooperative Interactions Among Surfaces, Solvents, and Reactive Intermediates on Catalysis at Liquid–Solid Interfaces (Final Report DE-SC0020224)

This project established quantitative links between inner‑sphere chemistry (active metal identity, coordination, and zeolite topology) and outer‑sphere organization (solvent identity, hydrogen‑bond networks, and pore condensation) that govern rates, activation barriers, and selectivities for alkene epoxidation and epoxide ring‑opening at solid–liquid and quasi‑liquid–solid interfaces. We deconvoluted contributions from covalent interactions at active sites and noncovalent, solvent‑mediated interactions within pores by pairing well‑defined metal substituted zeolites with controlled solvent environments. We then mapped those contributions onto measurable kinetics (ΔH‡, ΔS‡), adsorption thermodynamics (ITC), and in situ spectroscopy. The transferrable outcomes include a set of design rules that include the following understandings. First, tune silanol ((SiOH)x) density and pore topology to organize solvent networks that selectively stabilize transition states. Second, exploit activity‑coefficient‑normalized rates and adsorption– barrier correlations to diagnose when solvent reorganization rather than surface chemistry limits performance. Third, use partial pore condensation (e.g., acetonitrile, water but also generalizable to other solvents) to elicit liquid‑like stabilization effects even in nominally vapor‑phase reactors. Collectively, these results provide strategies to increase epoxidation rates, improve oxidant utilization (i.e., selectivities), and steer regioselectivity in zeolite‑based catalytic processes relevant to sustainable oxidation chemistry. These outcomes should be transferable to other classes of reactions that proceed in microporous materials and under confinement provided by organized solvents (e.g., electrochemical double layers).

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

Capacity Fade of Graphite/NMC811: Influence of Particle Morphology, Electrolyte, and Charge Voltage

LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) is an important Li-ion battery cathode material; however, there is a tradeoff between delivered capacity and capacity retention. As the charge potential increases the capacity rises but at the expense of capacity retention. The decrease in capacity retention has been ascribed to several factors including particle cracking, surface reconstruction, transition metal dissolution, and electrolyte reactivity. The present study compares 4.1 and 4.3 V charging limits in commercially relevant graphite/NMC811 pouch cells for single crystal (SC) and polycrystalline (PC) NMC811 with ethylene carbonate (EC)-containing or EC-free electrolytes. The electrochemistry is rationalized through analysis of electrochemical impedance spectroscopy, positive electrode X-ray photoelectron spectroscopy, soft X-ray absorption spectroscopy, X-ray diffraction, and negative electrode mapping by X-ray fluorescence. Graphite/SC-NMC811 cells show high-capacity retention at 4.1 V but exhibit degradation at 4.3 V charging potentials. The EC-free electrolyte cells led to higher capacity fade, especially when charged to 4.3 V. Cathode dissolution and deposition on the negative electrode from PC-NMC811 cells was higher than for samples from SC-NMC811 cells. This study reveals the impact of material type, charge voltage, and electrolyte composition on the reactions at the positive electrode, their influence on the negative electrode, and evolution with cycle number.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Multiple Mechanisms Mapped in Aryl Alkyl Ether Cleavage via Aqueous Electrocatalytic Hydrogenation over Skeletal Nickel

We present here detailed mechanistic studies of electrocatalytic hydrogenation (ECH) in aqueous solution over skeletal nickel cathodes to probe the various paths of reductive catalytic C–O bond cleavage among functionalized aryl ethers relevant to energy science. Heterogeneous catalytic hydrogenolysis of aryl ethers is important both in hydrodeoxygenation of fossil fuels and in upgrading of lignin from biomass. The presence or absence of simple functionalities such as carbonyl, hydroxyl, methyl, or methoxyl groups is known to cause dramatic shifts in reactivity and cleavage selectivity between sp3 C–O and sp2 C–O bonds. Specifically, reported hydrogenolysis studies with Ni and other catalysts have hinted at different cleavage mechanisms for the C–O ether bonds in α-keto and α-hydroxy β-O-4 type aryl ether linkages of lignin. Our new rate, selectivity, and isotopic labeling results from ECH reactions confirm that these aryl ethers undergo C–O cleavage via distinct paths. For the simple 2-phenoxy-1-phenylethane or its alcohol congener, 2-phenoxy-1-phenylethanol, the benzylic site is activated via Ni C–H insertion, followed by beta elimination of the phenoxide leaving group. But in the case of the ketone, 2-phenoxyacetophenone, the polarized carbonyl π system apparently binds directly with the electron rich Ni cathode surface without breaking the aromaticity of the neighboring phenyl ring, leading to rapid cleavage. Substituent steric and electronic perturbations across a broad range of β-O-4 type ethers create a hierarchy of cleavage rates that supports these mechanistic ideas while offering guidance to allow rational design of the catalytic method. Furthermore, on the basis of the new insights, the usage of cosolvent acetone is shown to enable control of product selectivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

RIC Advanced Sensors & Controls FWP: Novel Sensors for Boilers

Overview and brief project update on 3 tasks within the RIC Advanced Sensors & Controls FWP with direct applications to coal fired boiler temperature sensing. Task 32, Field demonstration of distributed temperature measurement with optical fiber for fossil energy power generation applications. Task 47, In-situ temperature measurements via reactive particles. Task 48, Ultrafast laser measurements for power generation environments.

coal boilers↗
NASA NTRS1987

The effect of sulfur and zirconium Co-doping on the oxidation of NiCrAl

The adhesion behavior of Al2O3 scales formed on NiCrAl+Zr alloys was examined as a function of both sulfur and zirconium doping levels. In general, very high levels of zirconium were required to counteract the detrimental effects of sulfur. A sulfur-zirconium adherence map was constructed, as determined from the oxidation and spalling behavior in 1100 C cyclic tests. For low sulfur alloys, the amount of zirconium required for adherence at any given sulfur level can be described by Zr greater than 600 S sup 0.2 (in ppma). These results underscore the importance of sulfur to adhesion mechanisms and suggests that sulfur gettering is a first order effect of reactive element additions to MCrAl alloys.

Smialek, James L.↗
DOE OSTI2025

Experimental Investigation of Air-Fuel Equivalence Ratio Effects on Advanced Dual-fuel Diesel/Ammonia Combustion on a Single-Cylinder Medium-Duty Diesel Engine at High Load

Ammonia (NH3) has gathered a lot of interest as a low-lifecycle-carbon fuel in sectors with high weight and distance requirements, such as shipping. The International Maritime Organization (IMO) mandates a 70-80% greenhouse gas (GHG) reduction by 2040, which is only possible with advanced engine technologies and fuels like NH3. Prior research studies at the US Department of Energy’s Oak Ridge National Laboratory have shown strong performance with NH3 under dual-fuel mode using conventional diesel combustion (CDC) manifold air pressure (MAP) settings. Diesel airflow was initially used to simplify retrofitting (no turbocharger modification), which resulted in air-fuel equivalence ratios (λ) greater than 1.5. To characterize potential improvements in dual-fuel NH3 combustion performance at richer in-cylinder conditions, a global λ sweep using a diesel pilot ignition (DPI) strategy with diesel fuel injected near top-dead center (TDC) and a reactivity-controlled compression ignition (RCCI) injection strategy with diesel fuel injected earlier during the compression stroke were compared. The experiments were conducted at 1200 RPM and 12.6 bar (75% load), and λ was varied by decreasing the commanded air flow to the engine at greater than 90% ammonia energy substitution (AES) level. A diesel injection timing sweep was conducted for both the combustion modes at fixed λ, and the timing with the lowest engine-out N2O emissions was identified. The results indicated an optimal balance between CO2, eq and thermal efficiency benefits for both DPI and RCCI injection strategy cases compared to CDC at a λ of 1.4. The indicated N-based emissions exhibited a strong correlation to the ratio of CA5–50 and ignition delay for DPI, but no apparent trend emerged for the RCCI injection strategy at the tested boundary conditions.

Tyrewala, Daanish [ORNL] (ORCID:0000000208599324)↗
DOE OSTI2023

Creation of Synthetic Electric Grids (SPP/MISO) Supporting PERFORM (Final Report)

Over the course of the project, two “realistic but not real” synthetic transmission-level grid models over the SPP-MISO and ERCOT footprints were created to provide more realistic data and increase the reliability and resiliency of the grids under a variety of scenarios. The synthetic ERCOT transmission grid is compatible with the distribution grid developed in collaboration with NREL. All generators are based on the EIA 860 data and a column with EIA plant code and Gen ID is added to generators of both grids so that they can be easily mapped. The improvements are also made to electric grids including N-1 contingencies with some remedial actions, improving the transmission lines to avoid lines in lakes, including an HVDC line to the SPP-MISO case, providing several generator parameters and their temporal constraints that were not included in EIA 860 form, generators’ cost curves, load offer curves, adding phase shifters and tap changers with impedance correction tables, adding reactive power control and partitioning the grids into active and reactive reserve zones and determine different types of the required reserve for each zone. Hourly load time series at the bus level were generated to create scenarios for solving power flow in different loading conditions. Weather measurement information and the models of renewable generators are used to directly include the impact of weather on the grids. Based on a variety of load and weather conditions the grids are improved to accommodate different conditions. The ERCOT 7k-bus grids were also modeled for the year 2030 with predicted improvements in renewable resources. The renewable generation model was also improved with historic weather data included. The impact of electric vehicles on the ERCOT grid is also modeled.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1988

The effect of sulfur and zirconium co-doping on the oxidation of NiCrAl

The adhesion behavior of Al2O3 scales formed on NiCrAl+Zr alloys was examined as a function of both sulfur and zirconium doping levels. In general, very high levels of zirconium were required to counteract the detrimental effects of sulfur. A sulfur-zirconium adherence map was constructed, as determined from the oxidation and spalling behavior in 1100 C cyclic tests. For low sulfur alloys (less than 500 ppma), the amount of zirconium required for adherence at any given sulfur level can be described by Zr greater than 600 S(0.2) (in ppma). These results underscore the importance of sulfur to adhesion mechanisms and suggest that sulfur gettering is a first order effect of reactive element additions to MCrAl alloys.

Smialek, James L.↗
DOE OSTI2023

Multifidelity Neural Network Formulations for Prediction of Reactive Molecular Potential Energy Surfaces

Here, this paper focuses on the development of multifidelity modeling approaches using neural network surrogates, where training data arising from multiple model forms and resolutions are integrated to predict high-fidelity response quantities of interest at lower cost. We focus on the context of quantum chemistry and the integration of information from multiple levels of theory. Important foundations include the use of symmetry function-based atomic energy vector constructions as feature vectors for representing structures across families of molecules and single-fidelity neural network training capabilities that learn the relationships needed to map feature vectors to potential energy predictions. These foundations are embedded within several multifidelity topologies that decompose the high-fidelity mapping into model-based components, including sequential formulations that admit a general nonlinear mapping across fidelities and discrepancy-based formulations that presume an additive decomposition. Methodologies are first explored and demonstrated on a pair of simple analytical test problems and then deployed for potential energy prediction for C 5 H 5 using B2PLYP-D3/6-311++G(d,p) for high-fidelity simulation data and Hartree–Fock 6-31G for low-fidelity data. For the common case of limited access to high-fidelity data, our computational results demonstrate that multifidelity neural network potential energy surface constructions achieve roughly an order of magnitude improvement, either in terms of test error reduction for equivalent total simulation cost or reduction in total cost for equivalent error.

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

Organic matter concentration and composition of experimentally burned open air and muffle furnace vegetation chars across differing burn severity and feedstock types from Pacific Northwest, USA (v4).

This dataset represents results from an experimental study designed to compare how the chemical composition of organic matter changes across different burn conditions and feedstock materials. The dataset provides both solid and dissolved phase bulk concentration and organic matter characterization data from experimentally generated chars. Chars were created in a closed muffle furnace or on an open burn table from four different feedstock species representing vegetation commonly impacted by fire regimes across the Pacific Northwest, USA. This data can be used to compare how different burn conditions may influence resultant organic matter chemistry and help further our understanding of potential biogeochemical impacts on river corridors post-fire. This dataset is comprised of one data package readme, one data dictionary (dd), one file level metadata (flmd), fourteen burn table videos, burn table video metadata and three folders containing (A) data; (B) metadata and protocols; and (C) photos. The folder names and the file name of the data package readme include a version number which will be updated with future iterations of this data package. The data folder includes (1) solid carbon and solid nitrogen; (2) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) and total dissolved nitrogen (TN); (3) pH; (4) thermocouple time series temperature; (5) methods codes; (6) installation methods; (7) excitation emissions matrix (EEM) methods information; (8) a folder of excitation emissions matrix (EEM) fluorescence and absorbance spectra in dissolved organic matter and EEMs processing instructions; (9) solid state carbon-13 and solution state phosphorus nuclear magnetic resonance (13-C NMR and 31-P NMR) data and methods; (10) benzene polycarboxylic acid (BPCA) concentration and stable isotope data; (11) FTICR-MS methods; (12) Inductively coupled plasma (ICP) data for total calcium, magnesium, iron, aluminum, potassium, phosphorus, sodium, and sulfur along with sodium hydroxide-ethylenediaminetetraacetic acid (sodium hydroxide-EDTA) extractable calcium, magnesium, iron, aluminum, potassium, phosphorus, and sulfur; (13) a folder of phosphorus, carbon, and nitrogen X-ray absorption near edge structure (P-XANES, N-XANES, C-XANES) data for samples and standards; (14) P-XANES, N-XANES, C-XANES methods; (15) molybdate reactive phosphorus; and (16) folder of high resolution characterization of organic matter via 21 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). The FTICR folder contains .txt data files and a subfolder containing instruments for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. The metadata and protocols folder includes (1) international geo-sample number (IGSN) mapping file (2) burn and laboratory metadata; (3) burn protocol; (4) laboratory protocol; (5) vegetation collection metadata; and (6) vegetation collection protocol. The folder contains photos of the solid chars. All files are .csv, .txt, .pdf, .jpg, .jpeg, .R, .ref, or .mp4. The data package was originally published October 2022 (v1). It was updated April 2023 (v2; new data files), September 2023 (v3; new and corrected data files), and September 2024 (v4; new and added/updated files). Metadata files were also updated to reflect these changes. See the change history section in the readme for more details.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

ChIMES: A Machine-Learned Interatomic Model Targeting Improved Description of Condensed Phase Chemistry in Energetic Materials

In this report we detail completion of a Physics and Engineering Model Level Two Milestone targeting improved reactive interatomic potentials (IAPs) for energetic materials (EM) through machine learning. The specific goals of this milestone were to develop, validate, and document a new reactive molecular dynamics method for EM, based on machine learning by (1) generating databases of first-principles-derived forces, stresses, and energies for HN3 and 3,4-bis(3-nitrofurazan- 4-yl)furoxan (DNTF) (2) generate atomistic force fields from these databases via ML, and (3) benchmark model performance against first principles calculations. These goals were achieved by (1) further developing a machine learned reactive IAP and generation approach (i.e. the Chebyshev Interaction Model for Efficient Simulation or “ChIMES”), for which resulting IAPs can approach the predictive power of quantum-mechanical approaches at a fraction of the computational expense, and (2) applying the ChIMES framework to develop models for HN3 and DNTF. We find that for simple energetic materials like HN3, high accuracy ChIMES models can be obtained through application of a fitting approach that does not use active machine learning. We demonstrate the suitability of ChIMES models for simulations involving EM by using the HN3 model in multiscale shock technique simulations to predict the HN3 Chapman-Jouguet detonation state and investigate chemical evolution out to 1 ns following shock compression. This model is then used in larger direct shock (DS) simulations for a preliminary investigation of how bubbles (i.e. voids) influence material response under shock compression. We find that more complex EM (i.e. DNTF) necessitate a more sophisticated fitting approach, and develop a new active learning method and python tool to meet this challenge. We demonstrate that this fitting approach yields ChIMES models that out-perform commonly used standard reactive IAPs as well as semi-empirical quantum methods, and discuss the systematic improvability of these actively learned ChIMES models. We also describe challenges related to model development for EM such as DNTF, for which few experimental or previous simulation data are available (e.g. which could otherwise inform generation of training data). To overcome this issue, we establish a semi-empirical quantum ChIMES capability which can be used to efficiently map out relevant thermodynamic and configurational space, and generate ChIMES-IAP training data in a multiscale manner. We also show that these semi-empirical quantum ChIMES models can be used to generate predictions for the shock Hugoniot (the Hugoniot is the locus of thermodynamic states found in a shocked material) equation of state, investigate related thermochemistry, and explore carbon condensation following shock compression. This work represents a substantial advance in our atomistic modeling capability for EM that will provide much needed information on the chemistry of detonation for continued development of continuum models based on the Cheetah thermochemical code.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1994

The MITy micro-rover: Sensing, control, and operation

The sensory, control, and operation systems of the 'MITy' Mars micro-rover are discussed. It is shown that the customized sun tracker and laser rangefinder provide internal, autonomous dead reckoning and hazard detection in unstructured environments. The micro-rover consists of three articulated platforms with sensing, processing and payload subsystems connected by a dual spring suspension system. A reactive obstacle avoidance routine makes intelligent use of robot-centered laser information to maneuver through cluttered environments. The hazard sensors include a rangefinder, inclinometers, proximity sensors and collision sensors. A 486/66 laptop computer runs the graphical user interface and programming environment. A graphical window displays robot telemetry in real time and a small TV/VCR is used for real time supervisory control. Guidance, navigation, and control routines work in conjunction with the mapping and obstacle avoidance functions to provide heading and speed commands that maneuver the robot around obstacles and towards the target.

Malafeew, Eric↗
DOE OSTI2022

Selection-enriched genomic loci (SEGL) reveals genetic loci for environmental adaptation and photosynthetic productivity in Chlamydomonas reinhardtii

This work demonstrates an approach to produce and select hybrid algal strains exhibiting increased photosynthetic productivity under multiple environmental conditions. This simultaneously addresses two major impediments to improving algal bioenergy production: 1) generating new genetic variants with improved performance; and 2) disentangling complex interactions between genetic and physiological factors contributing to these improvements. We pooled progeny generated from mating two environmental isolates of the green alga Chlamydomonas reinhardtii and cultured the pools under multiple environmental conditions. Strains from the outcompeting populations showed substantial (in some cases over 3 fold) increases in productivity over the parental lines under certain environments related to biomass production, including laboratory conditions as well as hyperoxia, fluctuating light, high salinity and high temperature. The results indicate that C. reinhardtii has remarkable, untapped, directed evolution capacity that may be harnessed using breeding and competition approaches. The populations were deep sequenced at multiple time points to identify “Selection-Enriched Genomic Loci” (SEGL) that accumulated in the populations, and thus likely confer increased fitness under the respective environmental conditions. With improved resolution, SEGL mapping can identify allelic combinations used for targeted breeding approaches, generating elite algal lines with multiple desirable traits, as well as to further understand the genetic and mechanistic bases of photosynthetic productivity. Increasing the photosynthetic efficiency of algae during biomass production is perhaps the most critical hurdle for economically sustainable algal based biofuels. This presents unique challenges because modifications designed to increase photosynthesis often result in decreased fitness, due to production of toxic reactive oxygen species when photosynthesis is not adequately regulated. These problems are exacerbated under natural and outdoor production environments because of the complex nature of photosynthesis and the multifaceted interactions between genetic, environmental and physiological factors. Here, we demonstrate a high throughput biotechnological screening approach that simultaneously produces algal strains with highly increased autotrophic productivity and identifies genomic loci contributing to these improvements. Our results demonstrate that Chlamydomonas reinhardtii exhibits high directed evolutionary capacity readily accessed through breeding and selection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Trihydrogen Formation on Gold Nanoparticles in Strong Laser Fields

The tri-hydrogen cation (H+ 3 ) plays a central role in proton-transfer chemistry, astrochemical pathways, and hydrogen plasma environments, acting as a key indicator of ultrafast proton rearrangement. Although H+ 3 formation is studied extensively in the gas phase, its surface-mediated generation and its sensitiv- ity to nanoparticle morphology remain largely unexplored. Gold nanoparticles (AuNPs), which can localize surface charge and sustain strong electric fields, offer an ideal platform to probe such nonequilibrium reaction pathways. Us- ing reaction nanoscopy, we spatially map H+ 3 production on AuNPs exposed to intense femtosecond laser fields. By comparing spherical and faceted nanopar- ticles, we demonstrate how morphology modulates charge density and governs reaction efficiency. We find that sharp features on faceted particles concen- trate charge more effectively, promoting molecular fragmentation and enabling proton rearrangement and migration that enhance H+ 3 yields. This work opens new directions for exploiting strong-field interactions at metal interfaces to drive nanoscale reactivity and photocatalysis.

Dagar, Ritika [SLAC National Accelerator Laborator↗
DOE OSTI2024

Chlorophyllase from Arabidopsis thaliana Reveals an Emerging Model for Controlling Chlorophyll Hydrolysis

Chlorophyll (Chl) is one of Nature’s most complex pigments to biosynthesize and derivatize. This pigment is vital for survival and also paradoxically toxic if overproduced or released from a protective protein scaffold. Therefore, along with the mass production of Chl, organisms also invest in mechanisms to control its degradation and recycling. One important enzyme that is involved in these latter processes is chlorophyllase. This enzyme is employed by numerous photosynthetic organisms to hydrolyze the phytol tail of Chl. Although traditionally thought to catalyze the first step of Chl degradation, recent work suggests that chlorophyllase is instead employed during times of abiotic stress or conditions that produce reactive oxygen species. However, the molecular details regarding how chlorophyllases are regulated to function under such conditions remain enigmatic. Here, we investigate the Arabidopsis thaliana chlorophyllase isoform AtCLH2 using site-directed mutagenesis, mass spectrometry, dynamic light scattering, size-exclusion multiangle light scattering, and both steady-state enzyme kinetic and thermal stability measurements. Through these experiments, we show that AtCLH2 exists as a monomer in solution and contains two disulfide bonds. One disulfide bond putatively maps to the active site, whereas the other links two N-terminal Cys residues together. These disulfide bonds are cleaved by chemical or chemical and protein-based reductants, respectively, and are integral to maintaining the activity, stability, and substrate scope of the enzyme. This work suggests that Cys residue oxidation in chlorophyllases is an emerging regulatory strategy for controlling the hydrolysis of Chl pigments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Boltzmann machine modeling of layered MoS 2 synthesis on a quantum annealer

Two-dimensional layered materials are usually synthesized by chemical vapor deposition (CVD). Here we use the Restricted Boltzmann Machine (RBM) and its enhancement called Limited Boltzmann Machine (LBM) on a quantum computer to model the chemical vapor deposition (CVD) growth data for a MoS 2 monolayer. The CVD data for Boltzmann machines are generated by reactive molecular dynamics (RMD) simulations. The Boltzmann machines give insight into the semiconducting (2H) and metallic (1T) phases and defects generated during the CVD growth of MoS 2 . We compare the performances of the two types of Boltzmann machine models, i.e. RBM versus augmented topologies with limited intra-layer coupling between the hidden units (LBM). We show that limited topologies have a performance advantage over restricted topologies. We examine connectivity within our topological variants, explore hardware qubit mapping schemes, and discuss what performance differences may imply about locality within the data without prior knowledge.

36 MATERIALS SCIENCE↗