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At least 19 records

Generative modeling enables molecular structure retrieval from Coulomb explosion imaging

Capturing the structural changes that molecules undergo during chemical reactions in real space and time is a long-standing dream and an essential prerequisite for understanding and ultimately controlling femtochemistry. A key approach to tackle this challenging task is Coulomb explosion imaging, which benefited decisively from recently emerging high-repetition-rate X-ray free-electron laser sources. With this technique, information on the molecular structure is inferred from the momentum distributions of the ions produced by the rapid Coulomb explosion of molecules. Retrieving molecular structures from these distributions poses a highly non-linear inverse problem that remains unsolved for molecules consisting of more than a few atoms. Here, we address this challenge using a diffusion-based Transformer neural network. We show that the network reconstructs unknown molecular geometries from ion-momentum distributions with a mean absolute error below one Bohr radius, which is half the length of a typical chemical bond.

Artificial Intelligence (cs.AI)

Nanoscopic Titanium Dioxide Overlayers Improve the Durability of Porphyrin Molecular Electrocatalysts while Maintaining Molecular Structure and Redox Activity

Molecular catalysts, such as metalated porphyrins, are attractive cocatalysts for photocatalytic water splitting owing to their potential to simultaneously catalyze target reactions at their metal center, extend charge-separated-state lifetimes, and accumulate the requisite charge for product formation. However, porphyrin catalysts, like most molecular catalysts, are often limited by poor stability associated with demetalation, inactivation by undesired bonding (e.g., O2 coordination/redox/dimerization), and detachment from electrode supports or semiconducting photoabsorbers. In this study, nanoscopic titanium dioxide (TiO2) overlayers, deposited by atomic layer deposition (ALD), are demonstrated to encapsulate cobalt(III) meso-tetra(4-carboxyphenyl) porphyrin chloride (CoTCPP) molecular catalysts and thereby improve their adhesion to electrode surfaces over a wide range of electrode potentials spanning from -1.0 V vs RHE to +1.8 V vs RHE. Through analysis of Raman and ultraviolet-visible spectroscopy, it was confirmed that the metalloporphyrin structure was maintained when the surface-bound CoTCPP was encapsulated by 10 - 250 ALD cycles (~2 - 18 nm thick) of TiO2. Additional characterization of CoTCPP catalysts before and after electrochemical measurements reveals that up to 97% of the encapsulated CoTCPP remains tethered to the electrode surface after chronoamperometry tests under hydrogen evolution reaction (HER) conditions, compared to <36% for unencapsulated CoTCPP. This study also shows that encapsulated CoTCPP molecules remain partially redox active for overlayers up to 8 nm, which can also attenuate undesired redox mediator back reactions like ferricyanide reduction.

08 HYDROGEN

Tuning the Molecular Structure and Reaction Mechanism of Olefin Metathesis by Model Bilayered Supported MoO x /AlO x /SiO 2 Catalysts

The molecular structure and activity of supported MoO x olefin metathesis catalysts are heavily impacted by the choice of catalyst support. In this study, surface modification of the SiO 2 support with AlO x and selective anchoring of the MoO x on the surface AlO x sites were used to tune the structure, activation, and reactivity of the resulting surface MoO x sites. Extensive in situ molecular characterization, chemical probe studies, and density functional theory (DFT) calculations reveal that the enhanced activity of the supported MoO x /AlO x /SiO 2 catalyst over the MoO x / SiO 2 catalyst is associated with more favorable activation and kinetics of surface MoO x anchored at AlO x sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Correlation of physical properties with molecular structure for some dicyclic hydrocarbons having high thermal-energy release per unit volume

As part of a program to study the correlation between molecular structure and physical properties of high-density hydrocarbons, the net heats of combustion, melting points, boiling points, densities, and kinematic viscosities of some hydrocarbons in the 2-n-alkylbiphenyl, 1,1-diphenylalkane, diphenylalkane, 1,1-dicyclohexylalkane, and dicyclohexylalkane series are presented.

Wise, P H

Molecular structures of residual solvent in polyacrylonitrile based electrolytes: Implications for conductivity and stability

Lithium-ion batteries increasingly play significant roles in modern technologies; however, increased energy density also raises concerns about electrolyte safety. Traditional electrolytes that use volatile organic solvents face risks of thermal runaways and fires from electrode shorting. In response, polymer-based solid electrolytes have been developed for replacement. Polyacrylonitrile (PAN) is a promising fire-resistant component for electrolyte fabrication, but its limited solubility necessitates using low-volatility solvents, which are notoriously difficult to remove in subsequent drying processes. Here, we use femtosecond two-dimensional infrared spectroscopy to provide an in-depth understanding of how residual solvent from processing affects the molecular structures and dynamics within a polymer electrolyte. To this end, linear and nonlinear infrared spectroscopies are employed to interrogate the molecular interactions in PAN-based electrolytes containing various contents of N,N-dimethylformamide (DMF). We show that the amount of DMF within the PAN electrolyte affects the Li+ structure. Further, the coordination can proceed through the carbonyl group and/or the amide nitrogen to form antiparallel structures with the nitrile groups of PAN through dipole–dipole interactions. The free motion of DMF is drastically inhibited upon interaction with Li+ and PAN, which decreases the ionic conductivity and potentially affects the stability (resistance toward removal and chemical decomposition). These findings have implications for the design and processing of solid polymer electrolytes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Exploiting correlations in multi-coincidence Coulomb explosion patterns for differentiating molecular structures using machine learning

Coulomb explosion imaging (CEI) is a powerful technique for capturing the real-time motion of individual atoms during ultrafast photochemical reactions. CEI generates high-dimensional data with naturally embedded correlations that allow mapping the coordinated motion of nuclei in molecules. This enables reliable separation of competing reaction pathways and makes this approach uniquely suited for characterizing weak reaction channels. However, rich information contained in experimental CEI patterns remains largely underexploited due to challenges in visualizing correlations between multiple observables in multi-dimensional parameter space. Here we present a new approach to CEI of intermediate-sized polyatomic molecules, detecting up to eight ionic fragments in coincidence and leveraging machine-learning-based analysis to identify patterns and correlations in the resulting high-dimensional momentum-space data, enabling robust molecular structure identification and differentiation. Our approach provides high-dimensional background-free data encoding exceptionally rich structural information and establishes an automated, scalable framework for extracting insightful information from the data. As a demonstration, we apply this method to image and distinguish dichloroethylene isomers, showcasing its potential for broader applications in molecular imaging. Our results pave the way for channel-specific analysis of ultrafast structural dynamics in chemically relevant systems, particularly for disentangling mixed reaction pathways and detecting contributions from weak channels and minority species.

Chemical Physics (physics.chem-ph)