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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 217 records · Page 12

A chemical dynamics study on the gas-phase formation of triplet and singlet C 5 H 2 carbenes

Significance Carbenes represent key reactive intermediates in molecular mass growth processes leading to carbonaceous nanostructures in the interstellar medium and in combustion systems. However, due to their short lifetimes and tendency for dimerization, carbenes represent one of the foremost obscured classes of reactive intermediates, with the preparation of carbenes in the gas phase remaining largely elusive. By merging molecular beams with electronic structure and quasi-classical trajectory calculations and exploiting triplet pentadiynylidene (HCCCCCH) and singlet ethynylcyclopropenylidene (c-C 5 H 2 ) carbene as benchmarks, we present a versatile protocol to unravel the dynamics leading to exotic carbenes under single-collision conditions. These elementary mechanisms are of significance to our understanding of the fundamental processes leading to unsaturated organic transients in extreme, hydrocarbon-rich environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Controlling the Morphology of Dynamic Thia-Michael Networks to Target Pressure-Sensitive and Hot Melt Adhesives

A series of multistage (pressure-sensitive/hot melt) adhesives utilizing dynamic thia-Michael bonding motifs are reported. The benzalcyanoacetate Michael acceptors used in this work undergo bond exchange under ambient conditions without external catalysis, facilitating pressure-sensitive adhesion. A key feature of this system is the dynamic reaction-induced phase separation that lends reinforcement to the otherwise weakly bonded materials, enabling weak, repeatable pressure-sensitive adhesion under ambient conditions and strong adhesion when processed as a hot melt adhesive. Furthermore, by using different pairs of benzalcyanoacetate cross-linking units, the phase separation characteristics of the adhesives can be directly manipulated, allowing for a tailored adhesive response.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ultrafast photochemistry of gas-phase transition metal carbonyls

Organometallic photochemistry lies at the heart of photochemical energy conversions in applications such as photocatalysis, photovoltaic cells, and luminescent materials. Thus, understanding how metal and ligand interactions in organometallic complexes modify electronic excited-state properties and reactivity has been the subject of intense studies for decades. Transition metal carbonyls [M n (CO) m ] have long served as prototypical organometallic complexes for understanding metal–ligand bonding and photochemistry and have been studied extensively in solution, matrices, and the gas phase on time scales ranging from femtoseconds to microseconds and longer. This review chronicles the past two and a half decades of efforts in understanding the ultrafast (sub-nanosecond) dynamics of transition metal carbonyls in the gas phase, where complicating solvent influences are absent and multiple experimental probes and high-level electronic structure theory can come together to yield rich information on the intricate interplay of electronic and structural dynamics. This review first lays the groundwork by briefly describing the electronic structure of transition metal carbonyls and introducing the various ultrafast techniques that have been applied to study their unimolecular dynamics. We then provide a detailed historical account on the ultrafast photochemistry of iron pentacarbonyl, nickel tetracarbonyl, and transition metal hexacarbonyls and decacarbonyls, putting the more recent ultrafast studies in the context of prior investigations. In conclusion, we end this review with an outlook on open questions and future possibilities.

Core level spectroscopy↗

Probing potential energy landscapes via electron-beam-induced single atom dynamics

Structure, bonding, and chemical dynamics of reactions at surfaces and interfaces, and therefore most material properties are intrinsically tied to the energetic landscape in which each atom resides. Here, we demonstrate that a moving atom under electron beam excitation can be used to probe the energy landscape along (confined) step edges, providing information about atomic-scale potentials. In conclusion, the techniques for experimentally exploring atomic potentials holds promise for predictive atom-by-atom fabrication using electron beams.

36 MATERIALS SCIENCE↗

Long-time integration of parametric evolution equations with physics-informed DeepONets

Ordinary and partial differential equations (ODEs/PDEs) play a paramount role in analyzing and simulating complex dynamic processes across all corners of science and engineering. In recent years machine learning tools are aspiring to introduce new effective ways of simulating such equations, however existing approaches are not able to reliably return stable and accurate predictions across long temporal horizons. We aim to address this challenge by introducing an effective framework for learning evolution operators that map random initial conditions to associated ODE/PDE solutions within a short time interval. Such operators can be parametrized by deep neural networks that are trained in an entirely self-supervised manner without requiring one to generate any paired input-output observations. Global long-time predictions across a range of initial conditions can be then obtained by iteratively evaluating the trained model using each prediction as the initial condition for the next evaluation step. Here, this introduces a new approach to temporal domain decomposition that is shown to be effective in performing accurate long-time simulations for a wide range of parametric ODE and PDE systems, from wave propagation, to reaction-diffusion dynamics and stiff chemical kinetics, introducing a new way of rapidly emulating non-equilibrium processes in science and engineering.

97 MATHEMATICS AND COMPUTING↗

Many roads to the seam: How conformational flexibility drives nonadiabatic relaxation in a prototypical tetrapyrrolic chromophore

Large and structurally flexible chromophores pose challenges for in silico modeling of photodeactivation due to the many vibrational modes that can funnel the system toward energy degeneracy. In this work, we examine how the multiple degrees of freedom in biliverdin, a prototypical tetrapyrrolic chromophore, cooperate to drive access to the S 1 /S 0 intersection seam in vacuo. We begin by mapping the ground-state potential energy surface to identify representative biliverdin conformers relevant to photoexcitation. We then use a CASSCF-based framework to map the excited-state landscape and characterize the intersection seam, identifying distinct conical-intersection types. Finally, we employ ab initio multiple spawning to resolve the dynamical pathways by which the system accesses these regions. DFT potential-energy and free-energy mappings indicate that, although several conformers are relevant, the “locked-helix” ZsZsZs conformer predominates in the ground state. The intersection seam comprises numerous geometrically distinct regions characterized by varying degrees and combinations of dihedral torsion, pyramidalization, and bond-length alternation. Yet only select regions lie within energetic reach, and moderate barriers separate them from the S 1 minimum. Nonadiabatic dynamics combined with multivariate analyses show that, despite extensive mode coupling during deactivation that guides the system toward multiple regions of the seam, a single dihedral torsion, together with bond-length alternation, predominantly drives energy degeneracy. This work offers new insight into biliverdin’s intrinsic photochemical response and underscores a general feature of flexible chromophores: many modes may participate during photorelaxation, but only a limited subset ultimately dictates seam accessibility.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Genetic Algorithm Approaches to Prebiobiotic Chemistry Modeling

We model an artificial chemistry comprised of interacting polymers by specifying two initial conditions: a distribution of polymers and a fixed set of reversible catalytic reactions. A genetic algorithm is used to find a set of reactions that exhibit a desired dynamical behavior. Such a technique is useful because it allows an investigator to determine whether a specific pattern of dynamics can be produced, and if it can, the reaction network found can be then analyzed. We present our results in the context of studying simplified chemical dynamics in theorized protocells - hypothesized precursors of the first living organisms. Our results show that given a small sample of plausible protocell reaction dynamics, catalytic reaction sets can be found. We present cases where this is not possible and also analyze the evolved reaction sets.

Lohn, Jason↗

Hidden features in the OH-stretching spectra of amino acid decorated air–water interfaces

Chemical reactivity at the air–water interface is governed by the interfacial solvation of reactive species. For instance, during aqueous amino acid-based CO 2 absorption, water reorganizes around the reactive sites and couples dynamically with reaction pathways, facilitating the reaction. In this context, surface-sensitive vibrational sum-frequency generation (vSFG) spectroscopy can probe the OH stretch vibrations of interfacial water and determine the solvation structures around reactants and products, thereby furthering our understanding of the role of interfacial solvation. However, vSFG spectra of the air–water interface in the presence of charged species can be remarkably complex; key species-bound local water structures with distinct orientations may be hidden beneath prominent vSFG peaks arising from water–water hydrogen bonds and remain difficult to resolve. Here, we measure and compute vSFG spectra of the water OH stretch at air–water interfaces decorated with amino acids in their zwitterionic and anionic forms, as well as equimolar mixtures of these forms with bicarbonate. The latter represents post-CO 2 -absorption conditions. We find that computing depth- and frequency-dependent spectral densities—decomposed into contributions from water molecules hydrogen-bonded exclusively to other water molecules, exclusively to amines, exclusively to carboxylates, or shared between these polar/charged groups—is indispensable for accurate interpretation of the vSFG spectra. Key findings include orientational flip-flop in water sub-layers, strong carboxylate-water H-bonding, and water orientational ordering extending into the bulk aqueous phase induced by anionic amino acids. Here, this study provides a computational spectroscopic platform for improved understanding of interfacial solvation relevant to interfacial reactivity.

Air-water interface↗

Characterizing the Geometry and Quantifying the Impact of Nanoscopic Electrocatalyst/Semiconductor Interfaces under Solar Water Splitting Conditions

The materials that are receiving the most attention in photoelectrochemical water splitting are metallic nanoparticle electrocatalysts (np-EC) attached to the surface of a semiconductor (SC) light absorber. In these multicomponent systems, the interface between the semiconductor and electrocatalysts critically affects performance. However, the np-EC/SC interface remains poorly understood as it is complex on atomic scales, dynamic under reaction conditions, and inaccessible to direct experimental probes. This contribution sheds light on how the electrocatalyst/semiconductor interface evolves under reaction conditions by investigating the behavior of nickel electrocatalysts (as nanoparticles and films) deposited on silicon semiconductors. Rigorous electrochemical experiments, interfacial atomistic characterization, and computational modeling are combined to demonstrate critical links between the atomistic features of the interface and the overall performance. It is shown that electrolyte-induced atomistic changes to the interface lead to (1) modulation of the charge carrier fluxes and a dramatic decrease in the electron/hole recombination rates and (2) a change in the barrier height of the interface. Additionally, the critical roles of nonidealities and electrocatalyst coverage due to interfacial geometry are explored. Each of these factors must be considered to optimize the design of metal/semiconductor interfaces which are broadly applicable to photoelectrocatalysis and photovoltaic research.

36 MATERIALS SCIENCE↗

Demonstration of Complete Recycling Processes of Reversible Epoxies Using Solar Energy Conversion

Reversible epoxies using the Diels–Alder chemistry enables recycling processes through depolymerizing the polymer at higher temperature and then repolymerizing upon cooling. Compared to conventional bulk heating, photothermal heating can save time and resource and, consequently, reduce costs to reach an elevated temperature for recycling processes of the reversible epoxies. In previous studies, self‐healing of cracks and reattachments of two broken pieces have been presented using a laser; however, recycling of a sample as a whole is not feasible by using such a point light source. Herein, complete recycling processes are demonstrated utilizing an area light source, i.e., sunlight. Reversible epoxies are incorporated with carbon black and refractory plasmonic titanium nitride nanoparticles (NPs). Under concentrated (10 times) sunlight, they can generate sufficient heat (≈140 °C) to completely liquefy, reprocess, and reshape the samples multiple times. Recycling processes are validated by evaluation of mechanical properties for each cycle. Using an integrated experimental and theoretical approach, photothermal performance is investigated in terms of the dispersion and loading of photothermal NPs in the matrix, as well as the sample thickness. In this study, an insight is provided into the design of polymer/photothermal nanomaterial composites which can be sustainably recycled using abundant solar energy.

14 SOLAR ENERGY↗

Ni5Ga3 Catalysts for CO2 Reduction to Methanol: Exploring the Role of Ga Surface Oxidation/reductions on Catalytic Activity

Ad-Ni5Ga3/SiO2 catalyst, which is highly active and stable for thermal CO2 hydrogenation to methanol, was investigated to understand its surface dynamics during reaction conditions. The catalyst was prepared, tested and characterized using a multitude of techniques, including ex-situ XRD, TEM, H2-TPR, CO chemisorption and in-situ ETEM and APXPS. The formation of Ga2O3 upon air exposure was observed and the consequences on catalytic activity were investigated. Results revealed that upon air exposure Ga migrates from the subsurface region to the surface of the nanoparticles forming a Ga-oxide shell surrounding a metallic core. The oxide shell can be reduced completely at high temperatures and the temperature of the reduction activation treatment plays a crucial role on the catalytic activity. This air exposure-reduction procedure results in a redistribution of the Ga species in the surface/subsurface region, promoted by a higher Ga affinity for oxygen. XRD analysis of the post-reaction samples provide evidence for the partial transformation of a Ni5Ga3 intermetallic phase into a Ni-rich Ni3Ga phase. APXPS data indicate that the Ni-rich phase forms in the subsurface region. A Ga-rich phase exists on the surface, where the Ni/Ga ratio reaches 2/3 upon activation in hydrogen. At low reduction temperatures an amorphous Ga2O3 shell remains, indicating a promotion effect on methanol synthesis activity.

Ni-Ga, intermetallic, methanol synthesis, in-situ ↗

On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks

Physics-informed neural networks (PINNs) are demonstrating remarkable promise in integrating physical models with gappy and noisy observational data, but they still struggle in cases where the target functions to be approximated exhibit high-frequency or multi-scale features. Here in this work we investigate this limitation through the lens of Neural Tangent Kernel (NTK) theory and elucidate how PINNs are biased towards learning functions along the dominant eigen-directions of their limiting NTK. Using this observation, we construct novel architectures that employ spatio-temporal and multi-scale random Fourier features, and justify how such coordinate embedding layers can lead to robust and accurate PINN models. Numerical examples are presented for several challenging cases where conventional PINN models fail, including wave propagation and reaction–diffusion dynamics, illustrating how the proposed methods can be used to effectively tackle both forward and inverse problems involving partial differential equations with multi-scale behavior.

42 ENGINEERING↗

Infrared spectroscopy data- and physics-driven machine learning for characterizing surface microstructure of complex materials

There is a need to characterize complex materials and their dynamics under reaction conditions to accelerate materials design. Adsorbate vibrational excitations are selective to adsorbate/surface interactions and infrared (IR) spectra associated with activating adsorbate vibrational modes are accurate, capture details of most modes, and can be obtained operando. Current interpretation depends on heuristic peak assignments for simple spectra, precluding the possibility of obtaining detailed structural information. Here, we combine data-based approaches with chemistry-dependent problem formulation to develop physics-driven surrogate models that generate synthetic IR spectra from first-principles calculations. Using synthetic IR spectra of carbon monoxide on platinum, we implement multinomial regression via neural network ensembles to learn probability distributions functions (pdfs) that describe adsorption sites and quantify uncertainty. We use these pdfs to infer detailed surface microstructure from experimental spectra and extend this methodology to other systems as a first step towards characterizing complex interfaces and closing the materials gap.

Science & Technology - Other Topics↗

Tolyporphins A–R, unusual tetrapyrrole macrocycles in a cyanobacterium from Micronesia, assessed quantitatively from the culture HT-58-2

The ‘pigments of life’ family has been enlarged by the discovery of the tetrapyrrole macrocycles dubbed tolyporphins, which are present in a cyanobacterial culture (HT-58-2). Of the 18 known tolyporphins, fourteen (A–J and L–O) are dioxobacteriochlorins, three (K, Q and R) are oxochlorins, and one (P) is a porphyrin. The members with a given chromophore absorb similarly but not identically with each other, presenting the problem of absorption spectral aliasing. Tolyporphins G and H are isomers, as are tolyporphins L–O, given the nature of the peripheral ( C -glycoside, –OH, or –OAc) substituents, presenting the (isobaric) problem of mass spectrometric analysis. The distribution of tolyporphin members is known to change over time and under different growth conditions, however, the complexity of the tolyporphins mixture presents challenges toward characterization of the underlying factors that alter such distributions. Liquid chromatography-mass spectrometry with dynamic multiple reaction monitoring (LC-MS-dMRM) was employed to characterize the distribution of tolyporphins under distinct growth media, using two semisynthetic standards, tolyporphin A O,O -dibutyrate and tolyporphin D O,O,O,O -tetrabutyrate. Growth in media containing both ammonium and nitrate salts versus nitrate alone affords increased production of tolyporphins. The absorption spectra of tolyporphins A–R have been reevaluated with regards to molar absorption coefficients, are compared with those of selected tetrapyrrole macrocycles to better understand the effects of chromophores and substituents, and are made available here in print and digital forms for comparison with isolated tolyporphins and mixtures thereof. Together, the work provides the foundation for quantitative assessment of these unusual natural products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗