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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Nuclear spin conservation enables state-to-state control of ultracold molecular reactions

Quantum-state control of reactive systems has enabled microscopic probes of underlying interaction potentials and the alteration of reaction rates using quantum statistics. However, extending such control to the quantum states of reaction outcomes remains challenging. Here in this work, we realize this goal by utilizing the conservation of nuclear spins throughout the reaction. Using resonance-enhanced multiphoton ionization spectroscopy to investigate the products formed in bimolecular reactions between ultracold KRb molecules we find that the system retains a near-perfect memory of the reactants’ nuclear spins, manifested as a strong parity preference for the rotational states of the products. We leverage this effect to alter the occupation of these product states by changing the coherent superposition of initial nuclear spin states with an external magnetic field. In this way, we are able to control both the inputs and outputs of a reaction with quantum-state resolution. The techniques demonstrated here open up the possibilities to study quantum entanglement between reaction products, and ultracold reaction dynamics at the state-to-state level.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

Modeling the impact of structure and coverage on the reactivity of realistic heterogeneous catalysts

Adsorbates often cover the surfaces of catalysts densely as they carry out reactions, dynamically altering their structure and reactivity. Understanding adsorbate-induced phenomena and harnessing them in our broader quest for improved catalysts is a substantial challenge that is only beginning to be addressed. Here, in this work, we chart a path toward a deeper understanding of such phenomena by focusing on emerging in silico modeling methodologies, which will increasingly incorporate machine learning techniques. We first examine how adsorption on catalyst surfaces can lead to local and even global structural changes spanning entire nanoparticles, and how this affects their reactivity. We then evaluate current efforts and the remaining challenges in developing robust and predictive simulations for modeling such behavior. Last, we provide our perspectives in four critical areas—integration of artificial intelligence, building robust catalysis informatics infrastructure, synergism with experimental characterization, and adaptive modeling frameworks—that we believe can help surmount the remaining challenges in rationally designing catalysts in light of these complex phenomena.

catalytic mechanisms↗
DOE OSTI2021

Potential-induced wetting and dewetting in pH-responsive block copolymer membranes for mass transport control

Wetting and dewetting behavior in channel-confined hydrophobic volumes is used in biological membranes to effect selective ion/molecular transport. Artificial biomimetic hydrophobic nanopores have been devised utilizing wetting and dewetting, however, tunable mass transport control utilizing multiple transport modes is required for applications such as controllable release/transport, water separation/purification and energy conversion. Here, we investigate the potential-induced wetting and dewetting behavior in a pH-responsive membrane composed of a polystyrene-b-poly(4-vinylpyridine) (PS-b-P4VP) block copolymer (BCP) when fabricated as a hierarchically-organized sandwich structure on a nanopore electrode array (NEA), i.e. BCP@NEA. At pH < pK a (P4VP) (pK a ~ 4.8), the BCP acts as an anion-exchange membrane due to the hydrophilic, protonated P4VP cylindrical nanodomains, but at pH > pK a (P4VP), the P4VP domains exhibit charge-neutral, hydrophobic and collapsed structures, blocking mass transport via the hydrophobic membrane. However, when originally prepared in a dewetted condition, mass transport in the BCP membrane may be switched on if sufficiently negative potentials are applied to the BCP@NEA architecture. When the hydrophobic BCP membrane is introduced on top of 2-electrode-embedded nanopore arrays, electrolyte solution in the nanopores is introduced, then isolated, by exploiting the potential-induced wetting and dewetting transitions in the BCP membrane. The potential-induced wetting/dewetting transition and the effect on cyclic voltammetry in the BCP@NEA structures is characterized as a function of the potential, pH and ionic strength. Additionally chronoamperometry and redox cycling experiments are used to further characterize the potential response. The multi-modal mass transport system proposed in this work will be useful for ultrasensitive sensing and single-molecule studies, which require long-time monitoring to explore reaction dynamics as well as molecular heterogeneity in nanoconfined volumes.

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

Quantum machine learning for chemistry and physics

Machine learning (ML) has emerged as a formidable force for identifying hidden but pertinent patterns within a given data set with the objective of subsequent generation of automated predictive behavior. In recent years, it is safe to conclude that ML and its close cousin, deep learning (DL), have ushered in unprecedented developments in all areas of physical sciences, especially chemistry. Not only classical variants of ML, even those trainable on near-term quantum hardwares have been developed with promising outcomes. Such algorithms have revolutionized materials design and performance of photovoltaics, electronic structure calculations of ground and excited states of correlated matter, computation of force-fields and potential energy surfaces informing chemical reaction dynamics, reactivity inspired rational strategies of drug designing and even classification of phases of matter with accurate identification of emergent criticality. In this review we shall explicate a subset of such topics and delineate the contributions made by both classical and quantum computing enhanced machine learning algorithms over the past few years. We shall not only present a brief overview of the well-known techniques but also highlight their learning strategies using statistical physical insight. The objective of the review is not only to foster exposition of the aforesaid techniques but also to empower and promote cross-pollination among future research in all areas of chemistry which can benefit from ML and in turn can potentially accelerate the growth of such algorithms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Solvent-dependent complex reaction pathways of bromoform revealed by time-resolved X-ray solution scattering and X-ray transient absorption spectroscopy

The photochemical reaction pathways of CHBr3 in solution were unveiled using two complementary X-ray techniques, time-resolved X-ray solution scattering (TRXSS) and X-ray transient absorption spectroscopy, in a wide temporal range from 100 ps to tens of microseconds. By performing comparative measurements in protic (methanol) and aprotic (methylcyclohexane) solvents, we found that the reaction pathways depend significantly on the solvent properties. In methanol, the major photoproducts are CH3OCHBr2 and HBr generated by rapid solvolysis of iso-CHBr2-Br, an isomer of CHBr3. In contrast, in methylcyclohexane, iso-CHBr2-Br returns to CHBr3 without solvolysis. In both solvents, the formation of CHBr2 and Br is a competing reaction channel. From the structural analysis of TRXSS data, we determined the structures of key intermediate species, CH3OCHBr2 and iso-CHBr2-Br in methanol and methylcyclohexane, respectively, which are consistent with the structures from density functional theory calculations.

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

Deep learning-enabled probing of irradiation-induced defects in time-series micrographs

Modeling time-series data with convolutional neural networks (CNNs) requires building a model to learn in batches as opposed to training sequentially. Coupling CNNs with in situ or operando techniques opens the possibility of accurately segmenting dynamic reactions and mass transport phenomena to understand how materials behave under the conditions in which they are used. In this article, in situ ion irradiation transmission electron microscopy (TEM) images are used as inputs into the CNN to assess the defect generation rate, defect cluster density, and saturation of defects. We then use the output segmentation maps to correlate with conventional TEM micrographs to assess the model’s ability to detail nanoscale interactions. Next, we discuss the implications of preprocessing and hyperparameters on model variability, accuracy when expanded to other datasets, and the role of regularization when controlling model variance. Ultimately, we eliminate human bias when extrapolating physical metrics, speed up analysis time, decouple reactions that happen at 100 ms intervals, and deploy models that are both accurate and transferable to similar experiments.

Burns, Kory (ORCID:0000000158019909)↗
DOE OSTI2025

Direct structural retrieval from gas-phase ultrafast diffraction data using a genetic algorithm

Ultrafast scattering techniques such as ultrafast electron diffraction and ultrafast x-ray diffraction have been utilized to elucidate the structural dynamics, reaction intermediates, and final products in molecular reactions following photoexcitation. The time-dependent structures are typically not directly retrieved from the experimental data, but they rely on comparison with calculations. The genetic algorithm (GA), a global optimization strategy, can be used to retrieve the molecular structures directly from diffraction patterns without any theoretical input. However, the robustness of the GA with respect to real experimental conditions such as a limited momentum transfer range, noise, and artifacts has not been studied in detail. In this work, we characterize the performance of the GA with simulated data that mimic realistic experimental conditions. We have developed and implemented a variant of the GA specific to diffraction measurements which performs better in the presence of imperfect data compared to the standard implementation of the GA. We demonstrate this method with both synthetic data and experimental ultrafast electron diffraction data on the UV-induced photodissociation of trifluoroiodomethane (C⁢F 3⁡ I) molecules.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

New framework for extracting GPDs from exclusive photon electroproduction

Recently, a new framework for studying generic 2 → 3 hard exclusive reactions, referred to as single-diffractive hard exclusive processes, has been introduced to provide a cleaner separation of the underlying physical mechanisms. In this work, we expand this formalism to the case of exclusive real-photon electroproduction off a nucleon, 𝑒⁡(ℓ) +𝑁⁡(𝑝) →𝑒⁡(ℓ′) +𝑁⁡(𝑝′) + 𝛾⁡(𝑞′), which represents the classical channel for accessing generalized parton distributions (GPDs) in nucleons and nuclei. This extension enables a more systematic and physically transparent formulation of the reaction dynamics, paving the way for improved extractions of GPDs from experimental data as compared to existing approaches.

Qiu, Jian-Wei [Thomas Jefferson National Accelerat↗
DOE OSTI2022

The time-resolved atomic, molecular and optical science instrument at the Linac Coherent Light Source

The newly constructed time-resolved atomic, molecular and optical science instrument (TMO) is configured to take full advantage of both linear accelerators at SLAC National Accelerator Laboratory, the copper accelerator operating at a repetition rate of 120 Hz providing high per-pulse energy as well as the superconducting accelerator operating at a repetition rate of about 1 MHz providing high average intensity. Both accelerators power a soft X-ray free-electron laser with the new variable-gap undulator section. With this flexible light source, TMO supports many experimental techniques not previously available at LCLS and will have two X-ray beam focus spots in line. Thereby, TMO supports atomic, molecular and optical, strong-field and nonlinear science and will also host a designated new dynamic reaction microscope with a sub-micrometer X-ray focus spot. The flexible instrument design is optimized for studying ultrafast electronic and molecular phenomena and can take full advantage of the sub-femtosecond soft X-ray pulse generation program.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

In situ atomic-resolution imaging of water vapor–driven multistep oxidation dynamics in strontium cobaltite

Understanding how water vapor interacts with transition metal oxides (TMOs) is critical for tailoring material properties to improve performance and enable new technologies. Despite extensive research efforts, atomic-scale mechanisms underpinning dynamic reactions and reaction-induced phase transitions remain elusive. Here, we use in situ environmental transmission electron microscopy to investigate how water vapor oxidizes vacancy-ordered SrCoO 2.5 at moderately elevated temperatures, demonstrating that water molecules can initiate oxidation more effectively than oxygen under comparable conditions. We discover a distinct “staging” behavior during the oxidation process: A fully ordered intermediate phase, SrCoO 2.75 , forms before transitioning into a near-perovskite SrCoO 3−δ . In addition, antiphase boundaries, originating at step terraces of SrTiO 3 , alleviate strain by creating reversible nanoscale “gaps” during lattice contraction under oxidation, providing a pathway for preserving structural integrity throughout redox cycling. This work provides atomic-level guidance for engineering TMOs by leveraging water vapor to control their redox behavior and tailor functional properties.

Science & Technology - Other Topics↗
DOE OSTI2022

Imaging elliptically polarized infrared near-fields on nanoparticles by strong-field dissociation of functional surface groups

Abstract We investigate the strong-field ion emission from the surface of isolated silica nanoparticles aerosolized from an alcoholic solution, and demonstrate the applicability of the recently reported near-field imaging at 720 nm [Rupp et al., Nat. Comm., 10(1):4655, 2019] to longer wavelength (2 $$\mu $$ μ m) and polarizations with arbitrary ellipticity. Based on the experimental observations, we discuss the validity of a previously introduced semi-classical model, which is based on near-field driven charge generation by a Monte-Carlo approach and classical propagation. We furthermore clarify the role of the solvent in the surface composition of the nanoparticles in the interaction region. We find that upon injection of the nanoparticles into the vacuum, the alcoholic solvent evaporates on millisecond time scales, and that the generated ions originate predominantly from covalent bonds with the silica surface rather than from physisorbed solvent molecules. These findings have important implications for the development of future theoretical models of the strong-field ion emission from silica nanoparticles, and the application of near-field imaging and reaction dynamics of functional groups on isolated nanoparticles. Graphical abstract

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

First Experimental Test of the Ratio Method

The ratio is a new reaction observable suggested to extract accurately structure information on halo nuclei. It corresponds to the ratio of differential cross sections for scattering and breakup, which is predicted to remove the uncertainty related to the reaction dynamics. We present here the first experimental test of the method for the 11 Be + 12 C collision at E Lab = 20A MeV performed at Texas A&M University. Differential cross sections for scattering and inclusive one-neutron breakup have been measured with the new detector array BlueSTEAl. The ratio of cross sections is very smooth and independent of the projectile-target interaction, which demonstrates the validity of the ratio method. We extend our analysis to existing 11 Be + 208 Pb data, confirming that the method works well on any target.

11Be↗
DOE OSTI2026

Time-, space-, and molecule-resolved multiple plasma reactive species in complex settings using an innovative approach of cavity ringdown spectroscopy (Project Final Report)

The primary research goal of this 2-year project is to demonstrate the feasibility of an innovative approach to measure reactive plasma species in the most challenging settings: right on the surface of water and under water. We propose to use the Brewster angle-cavity ringdown spextroscopy (BA-CRDS). Research objectives include: 1) Measurements of OH and NO in the plasma gas-phase zone (Z1) using different types of LTP sources including continuous and pulsed plasma jets, sheets, torches, etc. 2) Measurements of OH and NO in the multiphase reaction zones, right on the surface of water (Z2) and under water (Z3). 3) RS formation and loss mechanisms and reaction dynamics in the three zones. 4) Generalization of the proposed system to be configurable with other selected innovative techniques for other LTP parameters; invitation of selected PIs to form a strong collaborative team to pursue the follow-up effort (Category-2).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Transient Catalytic Reaction Analysis Through Signal Defragmentation

The Temporal Analysis of Products (TAP) pulse response technique provides valuable insights into catalytic function and reaction kinetics. However, complex fragmentation patterns in the TAP mass spectrometry signals can complicate precise quantification, particularly when analyzing transient gas flux data typical of TAP experiments. This work demonstrates a standard defragmentation method that deconvolves transient TAP signals while maintaining the temporal resolution of the experiment. First, the integrals of calibration gas fluxes are used to determine the fingerprint fragmentation pattern and construct a fragmentation matrix. This matrix is then used to defragment experimental flux data at each recorded time point via a non-negative least squares regression. The effectiveness of this method is demonstrated using virtual data and control experiments with a TAP reactor system. The defragmentation is then applied to the more complex propane dehydrogenation reaction on a chromia/alumina catalyst, which can contain up to ten significant gas species in the reactor outlet. Initial propane pulsing reveals an induction period during which propane is fully oxidized to CO2, followed by partial reduction to CO. Afterwards, there is a transition in chemistries towards coking and propylene production. Our example illustrates a practical method for the accurate determination of the time-dependent reactant/product concentrations and rates for a thorough analysis of the propane dehydrogenation kinetics. This approach can be broadly applied to any transient mass spectrometry experiment for a better understanding of catalyst-reaction dynamics.

36 - MATERIALS SCIENCE↗
NASA NTRS1973

Valence-bond study of the /H2, D2/ exchange reaction mechanism.

The exchange reaction of H2 with D2 to form 2 HD is important in that it is fundamentally the simplest four-body exchange reaction and should therefore represent a model system on which various theories of reactions dynamics might be tested. A number of theoretical and experimental investigations carried out on this system are reviewed. It is concluded that a Y yields T yields Y mechanism for the (H2, D2) exchange is not a low energy pathway that would make theory compatible with the shock-tube experiments of Bauer and Ossa (1966) and of Burcat and Lifshits (1967).

Freihaut, B.↗
NASA NTRS1978

Overview of laser applications to chemistry

The discussion is in three parts. First, laser spectroscopy is discussed with consideration given to single-photon and multiphoton processes. Second, attention is given to the use of lasers in studying molecular interactions and reaction dynamics. Finally, the paper discusses the relationship between chemistry and laser development.

George, T. F.↗