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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 OSTI2024

Fast, Nondestructive and Precise Biomass Measurements Are Possible Using Lidar-Based Convex Hull and Voxelization Algorithms

Light detection and ranging (lidar) scanning tools are available that can make rapid digital estimations of biomass. Voxelization and convex hull are two algorithms used to calculate the volume of the scanned plant canopy, which is correlated with biomass, often the primary trait of interest. Voxelization splits the scans into regular-sized cubes, or voxels, whereas the convex hull algorithm creates a polygon mesh around the outermost points of the point cloud and calculates the volume within that mesh. In this study, digital estimates of biomass were correlated against hand-harvested biomass for field-grown corn, broom corn, and energy sorghum. Voxelization (r = 0.92) and convex hull (r = 0.95) both correlated well with plant dry biomass. Lidar data were also collected in a large breeding trial with nearly 900 genotypes of energy sorghum. In contrast to the manual harvest studies, digital biomass estimations correlated poorly with yield collected from a forage harvester for both voxel count (r = 0.32) and convex hull volume (r = 0.39). However, further analysis showed that the coefficient of variation (CV, a measure of variability) for harvester-based estimates of biomass was greater than the CV of the voxel and convex-hull-based biomass estimates, indicating that poor correlation was due to harvester imprecision, not digital estimations. Overall, results indicate that the lidar-based digital biomass estimates presented here are comparable or more precise than current approaches.

Environmental Sciences & Ecology↗
DOE OSTI2025

Hydrogen Bond Benchmark: Focal‐Point Analysis and Assessment of DFT Functionals

We performed a hierarchical, convergent ab initio benchmark study and systematically analyzed the performance of density functional approximations for describing hydrogen bonds in small neutral, cationic, and anionic complexes, as well as in larger systems involving amide, urea, deltamide, and squaramide moieties. Focal point analyses (FPA), extrapolating to the ab initio limit, were carried out using correlated wave function methods up to CCSDT(Q) for the small complexes and CCSD(T) for the larger systems, together with correlation-consistent Gaussian basis sets up to the complete basis set limit. Optimized geometries and vibrational frequencies were obtained at the CCSD(T) level. The resulting FPA hydrogen-bond energies converge within a few tenths of a kcal mol −1 . These reference data were used to evaluate 60 density functionals (including 12 dispersion-corrected), spanning the local-density approximation (LDA), generalized gradient approximations (GGAs), meta-GGAs, hybrids, meta-hybrids, double-hybrids, and range-separated hybrids. Overall, the meta-hybrid M06-2X provides the best performance for both hydrogen bond energies and geometries, while the dispersion-corrected GGAs BLYP-D3(BJ) and BLYP-D4 also yield accurate hydrogen-bond data and can serve as cost-effective options for studying large and complex systems.

coupled cluster theory↗
DOE OSTI2020

PyCDFT: A Python package for constrained density functional theory

In this paper, we present PyCDFT, a Python package to compute diabatic states using constrained density functional theory (CDFT). PyCDFT provides an object-oriented, customizable implementation of CDFT, and allows for both single-point self-consistent-field calculations and geometry optimizations. PyCDFT is designed to interface with existing density functional theory (DFT) codes to perform CDFT calculations where constraint potentials are added to the Kohn–Sham Hamiltonian. Here, we demonstrate the use of PyCDFT by performing calculations with a massively parallel first-principles molecular dynamics code, Qbox, and we benchmark its accuracy by computing the electronic coupling between diabatic states for a set of organic molecules. We show that PyCDFT yields results in agreement with existing implementations and is a robust and flexible package for performing CDFT calculations. The program is available at https://dx.doi.org/10.5281/zenodo.3821097.

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

Exploring nonlinear Rashba effect and spin Hall conductivity in Janus MXenes W 2 ⁢CO ⁢𝑋 (𝑋=S, Se, Te)

Rashba spin-orbit coupling (RSOC) facilitates spin manipulation without relying on an external magnetic field, opening up exciting possibilities for advanced spintronic devices. In this paper, we examine the effects of crystal momentum (𝑘) nonlinearity and anisotropy on the conventional Rashba effect, with a particular focus on their impact on the spin Hall conductivity (SHC) in a newly predicted family of 2D Janus materials, W 2 ⁢CO⁢𝑋 (𝑋 =S, Se, Te). Using first-principles density functional theory calculations, we confirm the dynamical and mechanical stability of the studied 2D materials. Strikingly, this materials family exhibits pronounced nonlinear Rashba spin splitting at the Γ point of Brillouin zone near the Fermi level, which cannot be adequately described by the linear-𝑘 Rashba model. Therefore, third-order momentum contributions (𝑘 3 ) must be incorporated into the Rashba Hamiltonian. Our analysis reveals that among the studied systems, W 2 ⁢COS exhibits the highest 𝑘 3 contribution of −45.9 eV Å 3 , despite having the lowest linear Rashba constant. Here, a detailed analysis of electronic structure reveals topologically nontrivial behavior in these 2D materials, yielding sizable SHC that is primarily governed by the nonlinear Rashba effect. Notably, these materials also exhibit large spin Hall angle (0.018–2.5 at E 𝐹 ), which is comparable to that of in bulk topological insulators like Bi 2 ⁢Se 3 and Bi 2 ⁢Te 3 , and surpassing those in narrow bandgap bulk semiconductors GeTe and SnTe, as well as heavy metals such as Pt. Sizable SHC, large spin Hall angles, and the ability to tune SHC via electric fields without altering the topological properties, rooted in the crystal field splitting, underscore the potential of these materials for spintronic applications.

Electronic structure↗
DOE OSTI2022

Path to Increasing p-B11 Reactivity via ps and ns Lasers

The Lawson criterion for proton-boron (p-11B) thermonuclear fusion is substantially higher than that for deuterium-tritium (DT) because the fusion cross section is lower and peaks at higher ion energies. The Maxwellian averaged p-11B reactivity peaks at several hundred keV, where bremsstrahlung radiation emission may dominate over fusion reactions if electrons and ions are in thermal equilibrium and the losses are unrestricted. Nonequilibrium burn has often been suggested to realize the benefits of this aneutronic reaction, but the predominance of elastic scattering over fusion reactivity makes this difficult to achieve. The development of ultrashort pulse lasers (USPL) has opened new possibilities for initiating nonequilibrium thermonuclear burns and significant numbers of p-11B alpha particles have been reported from several experiments. We present an analysis that shows that these significant alpha yields are the result of beam fusion reactions that do not scale to net energy gain. We further find that the yields can be explained by experimental parameters and recently updated cross sections such that a postulated avalanche mechanism is not required. We use this analysis to understand the underlying physics of USPL-driven nonequilibrium fusion reactions and whether they can be used to initiate fusion burns. We conclude by outlining a path to increasing the p-11B reactivity towards the goal of achieving ignition and describing the design principles that we will use to develop a computational point design.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Microalgae Hydrothermal Liquefaction and Biocrude Upgrading: 2022 State of Technology

A preliminary techno-economic analysis (TEA) was developed for the fiscal year (FY) 2022 state of technology (SOT) assessment to evaluate the benefits and risks of using demonstrated, high-productivity algae strains for fuels generation, including sustainable aviation fuel (SAF). In 2022, the marine algal strain, Picochlorum celeri, which demonstrated the highest outdoor biomass productivities reported to date in the DOE-funded open-pond raceway testbed at the Arizona Center for Algae Technology and Innovation (AzCATI), was tested for continuous hydrothermal liquefaction (HTL) processing at PNNL. HTL testing results demonstrated a biocrude yield of 0.33 g/g algae on an ash-free dry weight (AFDW) basis from P. celeri. The hydrotreatment testing of the HTL biocrude from P. celeri was also conducted to investigate the production of jet fuel from marine algal biomass. To the best of our knowledge, this is the first report of jet fuel production from autotrophically grown marine algal biomass. The current hydrotreating testing demonstrated approximately 22.7 wt% of the hydrotreated oil within the typical boiling-point range of jet fuel (150–250 °C). Initial testing of the jet fuel cut (JFC) showed that the physical properties under investigation were within typical ranges for petroleum-based jet fuels. The experimental work of this study closes the gap between outdoor algae cultivation and algae conversion to critical transportation fuels using the same algae strain for both cultivation and conversion testing. The continuous HTL and the upgrading testing described herein demonstrate the potential of producing sustainable aviation fuel (SAF) from algae cultivated in open-pond systems using the primary inputs of sunlight and carbon dioxide.

09 BIOMASS FUELS↗
DOE OSTI2020

A Thermal and Nanomechanical Study of Molecular Crystals as Versatile Mocks for Pentaerythritol Tetranitrate

Pentaerythritol tetranitrate (PETN) is a commonly used high explosive (HE) in detonators. Often, surrogate or “mock” materials are used in place of HE for mechanical tests, proofing out equipment, or developing new diagnostics. However, there is no commonly accepted mock for PETN. A good mock should match at least one physical property of the target material, and ideally mimic multiple thermal and mechanical properties. Here, we investigate several molecular crystals to evaluate their efficacy in mocking PETN density, melting point, elastic modulus, hardness, plastic deformation, and fracture behavior. Materials were tested with a combination of calorimetry and nanoindentation. Two materials, 2,4,6-trifluorobenzoic acid (246 TFBA) and mesoerythritol, were downselected for detailed indentation study after the initial round of screening experiments, both were found to mimic PETN mechanical behavior quite well, 246 TFBA closer to PETN in most properties (hardness, modulus, and density) than erythritol, but erythritol having advantages in relative cost and matching the onset of yield. Depending on the desired implementation of the mock, one material may be preferred over the other, but both have potential as generic mocks for PETN. Nanoindentation is demonstrated as a versatile tool to provide rapid screening of these materials’ mechanical properties.

42 ENGINEERING↗
DOE OSTI2024

Enhancing Docking Accuracy with PECAN2, a 3D Atomic Neural Network Trained without Co-Complex Crystal Structures

Decades of drug development research have explored a vast chemical space for highly active compounds. The exponential growth of virtual libraries enables easy access to billions of synthesizable molecules. Computational modeling, particularly molecular docking, utilizes physics-based calculations to prioritize molecules for synthesis and testing. Nevertheless, the molecular docking process often yields docking poses with favorable scores that prove to be inaccurate with experimental testing. To address these issues, several approaches using machine learning (ML) have been proposed to filter incorrect poses based on the crystal structures. However, most of the methods are limited by the availability of structure data. Here, we propose a new pose classification approach, PECAN2 (Pose Classification with 3D Atomic Network 2), without the need for crystal structures, based on a 3D atomic neural network with Point Cloud Network (PCN). The new approach uses the correlation between docking scores and experimental data to assign labels, instead of relying on the crystal structures. We validate the proposed classifier on multiple datasets including human mu, delta, and kappa opioid receptors and SARS-CoV-2 Mpro. Our results demonstrate that leveraging the correlation between docking scores and experimental data alone enhances molecular docking performance by filtering out false positives and false negatives.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Irradiation-assisted Stress Corrosion Cracking of PWRirradiated Type 347 Stainless Steel (NSUF CINR 19-16567)

This document serves as the final report for NSUF Project 19-16567 (Reference 1) and its supporting contracts (References 2 and 3). It documents completion of testing of specimens fabricated as previously described in Reference 4. At a high level, the purpose of the testing is to generate data to support continued operation of light water reactors (LWR) and provide further understanding of irradiation-assisted stress corrosion crack (IASCC) initiation in baffle-former bolt materials. Baffle-former bolts that had been extracted from commercial pressurized water reactors (PWRs) were machined into miniature 4-point bend specimens and TEM samples at the Westinghouse Churchill Site hot cell facility. These samples were then shipped to the University of Michigan to undergo IASCC initiation testing in simulated PWR primary coolant containing either LiOH or KOH additions. Overall, 15 samples were tested, 8 in water with KOH additions and 7 in water with LiOH additions, until indications of cracking were observed. Crack initiation stress was similar in both water environments at 50-60% of the irradiated yield stress. Post-test examination of the cracking sites, including scanning electron microscopy and transmission electron microscopy, demonstrated that the crack initiation mechanism and crack initiation rates were similar between the two different water chemistries. A grain boundary oxidation and oxide fracture mechanism was observed to be responsible for crack initiation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Hydrothermal liquefaction of wastewater-grown algae to produce synthetic aviation fuel: A combined experimental study and techno-economic assessment

Large-scale algae farms may someday become a consistent source of biomass feedstock for biofuels. Near-term supplies of algal biomass are available at certain water resource recovery facilities as algae cultivation is used as a method for nutrient recovery from specific effluent streams. Algae grown as a service shifts the value to the service rather than its sole use as a feedstock, which could enable the provision of algal biomass at low to no cost to biofuel producers. Hydrothermal liquefaction (HTL) can readily upgrade wet feedstock slurries, such as algae, to produce a carbon-enriched biocrude. The HTL biocrude can be hydrotreated and distilled, producing a variety of distillate fuels, including synthetic aviation fuel (SAF). We present a pathway, showing the experimental production of SAF from wastewater-grown algae via HTL, along with a techno-economic assessment to identify opportunities for process improvements. Critical quality attributes of the SAF, such as density, viscosity, surface tension, and freeze point, were estimated within the expected fuel experience ranges when compared against petroleum jet fuel. The average minimum fuel selling price of fuels from wastewater-grown algae for breakeven economics was $\$9.04$ per gasoline gallon equivalent (GGE). The sale of co-products such as struvite fertilizers and cement additives can add revenue to reduce the net cost. Ultimately, the selling price is influenced by the scale of the HTL processing facility. Adjusting estimations in the process scale, algae yield, and capital cost estimation can lower the price to $\$6.51$/GGE or raise it to $13.07/GGE.

Biofuels↗
DOE OSTI2023

Accelerating crystal structure determination with iterative AlphaFold prediction

Experimental structure determination can be accelerated with artificial intelligence (AI)-based structure-prediction methods such as AlphaFold . Here, an automatic procedure requiring only sequence information and crystallographic data is presented that uses AlphaFold predictions to produce an electron-density map and a structural model. Iterating through cycles of structure prediction is a key element of this procedure: a predicted model rebuilt in one cycle is used as a template for prediction in the next cycle. This procedure was applied to X-ray data for 215 structures released by the Protein Data Bank in a recent six-month period. In 87% of cases our procedure yielded a model with at least 50% of C α atoms matching those in the deposited models within 2 Å. Predictions from the iterative template-guided prediction procedure were more accurate than those obtained without templates. It is concluded that AlphaFold predictions obtained based on sequence information alone are usually accurate enough to solve the crystallographic phase problem with molecular replacement, and a general strategy for macromolecular structure determination that includes AI-based prediction both as a starting point and as a method of model optimization is suggested.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Threshold Collision-Induced Dissociation of Hydrated Thorium(IV) Trihydroxide Cation: Experimental and Theoretical Investigation of the Binding Energies for Th(OH) 3 + (H 2 O) n Complexes ( n = 1–4)

Threshold collision-induced dissociation of Th(OH) 3 + (H 2 O) n Complexes ( n = 1–4) with xenon was performed using a guided ion beam tandem mass spectrometer. The primary dissociation pathway for all complexes is a loss of a single water molecule followed by the sequential loss of additional water molecules at higher collision energies. Here, the data were analyzed using a statistical model after accounting for lifetime effects and reactant internal and kinetic energy distributions to obtain 0 K bond dissociation energies (BDEs). These were also converted using rigid rotor/harmonic oscillator approximations to yield thermodynamic values at room temperature. The 0 K BDEs of H 2 O ligands to Th(OH) 3 + (IV) are experimentally determined for the first time as 106 ± 6, 89 ± 6, 76 ± 4, and 51 ± 4 kJ/mol for the first, second, third, and fourth water ligand added. These values agree reasonably well with values calculated at the B3LYP, B3PW91, and PBE0 levels of theory with aug-cc-pVQZ basis sets, whereas B3LYP-GD3BJ, MP2, and CCSD(T) single point energies with (without) counterpoise corrections systematically overestimate the bond energies by about 15 (20), 19 (25), and (18) kJ/mol, respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Design, Synthesis, and Characterization of Polymer Precursors to Li x PON and Li x SiPON Glasses: Materials That Enable All-Solid-State Batteries (ASBs)

LiPON-like glasses that form lithium dendrite impenetrable interfaces between lithium battery components are enabling materials that may replace liquid electrolytes permitting production of all-solid-state batteries (ASBs). Unfortunately, to date, such materials are introduced only via gas-phase deposition. Furthermore, we demonstrate the design and synthesis of easily scaled, lowtemperature, low-cost, solution-processable inorganic polymers containing LiPON/LiSiPON elements. OPCl 3 and hexachlorophosphazene [Cl 2 P=N] 3 provide starting points for elaboration using MNH 2 (M = Li/Na) or (Me 3 Si)NH followed by reaction with controlled amounts of LiNH 2 to produce oligomers/polymers with molecular weights (MWs) ≈1–2 kDa characterized by multinuclear NMR, gel permeation chromatography (GPC), thermogravimetric analysis (TGA), Fourier-transform infrared (FTIR), X-ray powder diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and matrix-assisted laser desorption/ ionization (MALDI)-time-of-flight (ToF) offering stabilities to 150–200 °C and ceramic yields (800 °C) of 50–60%. 7 Li NMR suggests that precursor-bound Li + dissociates easily, beneficial for electrochemical applications. XPS shows higher N/P ratios (1–3) than via gas-phase methods (<1) correlating N/P ratios, 7 Li shifts, and Li + conductivities. Li 2 SiPHN offers the highest ambient conductivity of 3 × 10 –1 mS cm –1 at 400 °C/2 h/N 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2024

Evaluation of Converter Performance Considering Static and Dynamic Device Part-to-Part Variability

This paper presents a methodology to incorporate and analyze the impact of semiconductor device part-to-part variation on power converter performance. By integrating extensive static and dynamic device characterization data with an automated compact model generation process that reflects manufacturing variability, device models with inherent variability features are utilized in converter simulations for a comprehensive assessment of performance impacts. The traditional converter performance evaluation process typically yields fixed efficiency values, often dismissing the inherent part-to-part variability caused by the manufacturing process of semiconductor devices. To address this limitation, a large population of devices was characterized to capture variations in static parameters-such as transfer, output, and capacitance characteristics-as well as dynamic behaviors, including switching losses. This data-driven approach enables the development of individual compact models, which were then integrated into converter simulations to evaluate efficiency ranges rather than single point estimated values. The converter simulation results show that part-to-part component variation can lead to significant efficiency deviations, exceeding several percentage points in high-power conversion applications. By offering a more accurate representation of converter behavior under real-world manufacturing conditions, this methodology enables designers to anticipate performance variability, improving the robustness of power converter designs.

device characterization↗
DOE OSTI2022

Monolithic Multigrid for a Reduced-Quadrature Discretization of Poroelasticity

Advanced finite-element discretizations and preconditioners for models of poroelasticity have attracted significant attention in recent years. The equations of poroelasticity offer significant challenges in both areas, due to the potentially strong coupling between unknowns in the system, saddle-point structure, and the need to account for wide ranges of parameter values, including limiting behavior such as incompressible elasticity. This paper was motivated by an attempt to develop monolithic multigrid preconditioners for the discretization developed in [C. Rodrigo et al., Comput. Methods App. Mech. Engrg, 341 (2018), pp. 467--484]; we show here why this is a difficult task and, as a result, we modify the discretization in [Rodrigo et al.] through the use of a reduced-quadrature approximation, yielding a more “solver-friendly” discretization. Local Fourier analysis is used to optimize parameters in the resulting monolithic multigrid method, allowing a fair comparison between the performance and costs of methods based on Vanka and Braess--Sarazin relaxation. Further, numerical results are presented to validate the local Fourier analysis predictions and demonstrate efficiency of the algorithms. Finally, a comparison to existing block-factorization preconditioners is also given.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Development of Scalable Coastal and Offshore Macroalgal Farming

The US DOE/ARPA-E MARINER program funded a four-year project to determine an optimal way to grow kelps in large, nearshore and offshore arrays for the eventual purpose of biofuel production with the goal of keeping the cost below $\$$80 USD per dry metric ton of kelp. This project specifically looked at how Saccharina latissima can be grown in the Gulf of Alaska to reach that goal. There were three major aspects of the research: 1) optimizing nursery production and seeding lines for outplanting, 2) designing an economical, modular outplanting structure and 3) developing methods to efficiently harvest the product. Farm designs were based on catenary structures and the use of spreader bars with variable spacing of grow lines and line types. The spacing of the grow lines makes a difference in the yield. Grow line spacing of ≥1.5m showed about a 50% increase in kg/m. There was no statistical difference in the growth of Saccharina latissima whether in the middle or the outside of the array, but the line type and perhaps line thickness can make a difference in yield. Sagging caused by the weight of the mature fronds resulted in lower growth at depth. Various harvesting approaches for mature kelps were tested by collaborating farmers. One promising innovation is the use of large bags for holding the freshly harvested fronds. Although the weight of the fronds on the growlines causes the lines to sink, the bags packed with the harvested fronds float, allowing for easy loading to the transfer vessel. Another advance in harvesting is a specially built harvest vessel, the Harvest Buddy, allowing a more mechanized and faster way to harvest. A significant aspect of this project was the TTO/T2M. Several different outreach activities were performed by the Alaska Fisheries Development Foundation and GreenWave. A techno-economic assessment (TEA) using our data has pointed to solutions to reach the $\$$80 goal. A second phase of this project involved the co-culture of two different species of kelps. Interest in farming kelps has grown beyond using kelp for food, feed or biofuels. There is considerable interest in generating biomass from seaweed for use in bioplastics and other products that would substitute for petroleum-derived products. For these uses to be viable, large amounts of biomass are needed. Very large kelp farms can be expensive to build and maintain, leading to the need to optimize the biomass per unit area. Although close spacing of growlines can lead to poor growth, a viable approach may be to grow two species of kelps together: one that hangs down and one that is buoyant, growing up. This system would increase the spacing in three dimensions. In Alaska, Saccharina latissima is commonly grown hanging down from longlines. One of the buoyant Alaskan kelps is Nereocystis luetkeana. Because there are commercial uses for wild-harvested Nereocystis in Alaska, we undertook a preliminary trial in Kodiak, Alaska that grew both Saccharina and Nereocystis in the same longline array. Closely spaced lines were seeded the first week of February 2023 and set at 3m below the surface. The arrays were harvested in late June 2023. Despite having 45% fewer grow-lines, the total yield of the Nereocystis on the combined arrays was statistically similar to the Nereocystis only arrays. Total yields were greatest on the combined arrays, followed by the Nereocystis only and Saccharina only arrays. These results may have significance for large scale macroalgal production.

09 BIOMASS FUELS↗
DOE OSTI2022

On the use of vibronic coherence to identify reaction coordinates for ultrafast excited-state dynamics of transition metal-based chromophores

In this study, the question of whether one can use information from quantum coherence as a means of identifying vibrational degrees of freedom that are active along an excited-state reaction coordinate is discussed. Specifically, we are exploring the notion of whether quantum oscillations observed in single-wavelength kinetics data exhibiting coherence dephasing times that are intermediate between that expected for either pure electronic or pure vibrational dephasing are vibronic in nature and therefore may be coupled to electronic state-to-state evolution. In the case of a previously published Fe(ιι) polypyridyl complex, coherences observed subsequent to 1 A 1 → 1 MLCT excitation were linked to large-amplitude motion of a portion of the ligand framework; dephasing times on the order of 200–300 fs suggested that these degrees of freedom could be associated with ultrafast (~100 fs) conversion from the initially formed MLCT excited state to lower-energy, metal-centered ligand-field excited state(s) of the compound. Incorporation of an electronically benign but sterically restrictive Cu(ι) ion into the superstructure designed to interfere with this motion yielded a compound exhibiting a ~25-fold increase in the compound’s MLCT lifetime, a result that was interpreted as confirmation of the initial hypothesis. However, new data acquired on a different chemical system – Cr(acac') 3 (where acac' represents various derivatives of acetylacetonate) – yielded results that call into question this same hypothesis. Coherences observed subsequent to 4 A 2 → 4 T 2 ligand-field excitation on a series of molecules implicated similar vibrational degrees of freedom across the series, but exhibited dephasing times ranging from 340 fs to 2.5 ps without any clear correlation to the dynamics of excited-state evolution in the system. Taken together, the results obtained on both of these chemical platforms suggest that while identification of coherences can indeed point to degrees of freedom that should be considered as candidate modes for defining reaction trajectories, our understanding of the factors that determine the interplay across coherences, dephasing times, and electronic and geometric structure is insufficient at the present time to view this parameter as a robust metric for differentiating active versus spectator modes for ultrafast dynamics.

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

Unsupervised learning approaches to characterizing heterogeneous samples using X-ray single-particle imaging

One of the outstanding analytical problems in X-ray single-particle imaging (SPI) is the classification of structural heterogeneity, which is especially difficult given the low signal-to-noise ratios of individual patterns and the fact that even identical objects can yield patterns that vary greatly when orientation is taken into consideration. Proposed here are two methods which explicitly account for this orientation-induced variation and can robustly determine the structural landscape of a sample ensemble. The first, termed common-line principal component analysis (PCA), provides a rough classification which is essentially parameter free and can be run automatically on any SPI dataset. The second method, utilizing variation auto-encoders (VAEs), can generate 3D structures of the objects at any point in the structural landscape. Both these methods are implemented in combination with the noise-tolerant expand–maximize–compress (EMC) algorithm and its utility is demonstrated by applying it to an experimental dataset from gold nanoparticles with only a few thousand photons per pattern. Both discrete structural classes and continuous deformations are recovered. These developments diverge from previous approaches of extracting reproducible subsets of patterns from a dataset and open up the possibility of moving beyond the study of homogeneous sample sets to addressing open questions on topics such as nanocrystal growth and dynamics, as well as phase transitions which have not been externally triggered.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗