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At least 37 records · Page 2

A 3D visualization system for molecular structures

The properties of molecules derive in part from their structures. Because of the importance of understanding molecular structures various methodologies, ranging from first principles to empirical technique, were developed for computing the structure of molecules. For large molecules such as polymer model compounds, the structural information is difficult to comprehend by examining tabulated data. Therefore, a molecular graphics display system, called MOLDS, was developed to help interpret the data. MOLDS is a menu-driven program developed to run on the LADC SNS computer systems. This program can read a data file generated by the modeling programs or data can be entered using the keyboard. MOLDS has the following capabilities: draws the 3-D representation of a molecule using stick, ball and ball, or space filled model from Cartesian coordinates, draws different perspective views of the molecule; rotates the molecule on the X, Y, Z axis or about some arbitrary line in space, zooms in on a small area of the molecule in order to obtain a better view of a specific region; and makes hard copy representation of molecules on a graphic printer. In addition, MOLDS can be easily updated and readily adapted to run on most computer systems.

Green, Terry J.↗

Applying Bayesian inference and deterministic anisotropy to retrieve the molecular structure ∣Ψ(R)∣2 distribution from gas-phase diffraction experiments

Abstract Currently, our general approach to retrieving molecular structures from ultrafast gas-phase diffraction heavily relies on complex ab initio electronic or vibrational excited state simulations to make conclusive interpretations. Without such simulations, inverting this measurement for the structural probability distribution is typically intractable. This creates a so-called inverse problem. Here we address this inverse problem by developing a broadly applicable method that approximates the molecular frame structure ∣Ψ( R , t )∣ 2 distribution independent of these complex simulations. We retrieve the vibronic ground state ∣Ψ( R )∣ 2 for both simulated stretched NO 2 and measured N 2 O. From measured N 2 O, we observe 40 mÅ coordinate-space resolution from 3.75 Å −1 reciprocal space range and poor signal-to-noise, a 50X improvement over traditional Fourier transform methods. In simulated NO 2 diffraction experiments, typical to high signal-to-noise levels predict 100–1000X resolution improvements, down to 0.1 mÅ. By directly measuring the width of ∣Ψ( R )∣ 2 , we open ultrafast gas-phase diffraction capabilities to measurements beyond current analysis approaches. This method has the potential to effectively turn gas-phase ultrafast diffraction into a discovery-oriented technique to probe systems that are prohibitively difficult to simulate.

74 ATOMIC AND MOLECULAR PHYSICS↗

Effect of Molecular Structure of Quinones and Carbon Electrode Surfaces on the Interfacial Electron Transfer Process

Quinones can undergo thermodynamically reversible proton-coupled electron transfer reactions and are being applied as electroactive compounds in aqueous organic batteries. However, the electrochemical reversibility of these compounds is affected not only by their molecular structure but also by the properties of a carbon-based electrode surface. This study combines experimental and theoretical approaches to understand this dependence. Specifically, we study the electron transfer kinetics of two synthesized quinone derivatives and two commercially available ones with a glassy carbon, a highly ordered pyrolytic graphite, and a high-edge-density graphite electrode (HEDGE). The electrochemical reversibility is notably improved on the HEDGE, which shows a higher density of defects and presents oxygenated functional groups at its surface. The electron transfer kinetics are controlled by adsorbed species onto the HEDGE. Molecular dynamics simulation and quantum mechanics calculations suggest defects with oxygen-containing functional groups, such as C-O and C$=$O, on HEDGE surfaces drive the interaction with the functional groups of the molecules, during physisorption from van der Waals forces. The presence of sulfonic acid side groups and a greater number of aromatic rings in the molecular structure may contribute to a higher stabilization of quinone derivatives on HEDGEs. We propose that high-performance carbon-based electrodes can be obtained without catalysts for organic batteries, by the engineering of carbon-based surfaces with edge-like defects and oxygenated functional groups.

25 ENERGY STORAGE↗

The Crystal and Molecular Structure of Acetatochlorobis(4-methylpyridine)oxovanadium (IV)

The crystal and molecular structure of the title compound, VOCl(O2CCH3)(4-CH3C5H4N)2, has been determined by single-crystal x-ray diffraction. The material crystallizes in the space group P 1(bar) (#2) with a = 7.822(2), b = 8.023(l), c = 14.841(2) Angstroms, alpha = 99.73(l), beta = 91.41(l), and gamma = 117.13(l). The coordination geometry around the vanadium is a highly distorted octahedron. The molecule is remarkable for being a monomeric oxovanadium (IV) carboxylate. A generalized synthetic strategy is proposed for the preparation of oxovanadium (IV) monomers.

Schupp, John D.↗

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)↗

Polyurethanes Based on Unmodified and Refined Technical Lignins: Correlation between Molecular Structure and Material Properties

The structural complexity and robust intermolecular interactions have challenged the incorporation of technical lignin into value-added polymeric materials for decades. To study the correlation between lignin molecular structure and material properties of lignin-based polyurethanes, we applied co-solvent enhanced lignocellulosic fractionation pretreatment followed by sequential precipitation to produce three distinct lignin preparations with narrowly distributed (molecular weight dispersity <2) and comparatively low molecular weight (<1500 g/mol) from poplar biomass. Structural characterization indicated that these lignin preparations differed in average molecular chain length and stiffness as well as hydroxyl group distribution. Secondary hydroxyl group providers such as aliphatic diols and polyethers were incorporated as building blocks into the lignin-based polyurethanes to provide additional hydrogen capacity to improve the dispersion of lignin in the polyurethane network. The selected aliphatic diols and polyethers interacted with lignin molecules at different levels of strength depending on their molecular structure, and their impacts were ultimately reflected in the mechanical and thermal properties of the resulting lignin-based polyurethanes. The copolymerization of technical lignin with tailored structure and secondary hydroxyl providers could provide new strategies in formulating lignin-based/containing polyurethanes for various functional applications.

36 MATERIALS SCIENCE↗

Isotope effects in molecular structures and electronic properties of liquid water via deep potential molecular dynamics based on the SCAN functional

Here, Feynman path-integral deep potential molecular dynamics (PI-DPMD) calculations have been employed to study both light (H 2 O) and heavy water (D 2 O) within the isothermalisobaric ensemble. In particular, the deep neural network is trained based on ab initio data obtained from the strongly constrained and appropriately normed (SCAN) exchange-correlation functional. Because of the lighter mass of hydrogen than deuteron, the properties of light water are more influenced by nuclear quantum effect than those of heavy water. Clear isotope effects are observed and analyzed in terms of hydrogen-bond structure and electronic properties of water that are closely associated with experimental observables. The molecular structures of both liquid H 2 O and D 2 O agree well with the data extracted from scattering experiments. The delicate isotope effects on radial distribution functions and angular distribution functions are well reproduced as well. Our approach demonstrates that deep neural network combined with SCAN functional based ab initio molecular dynamics provides an accurate theoretical tool for modeling water and its isotope effects.

36 MATERIALS SCIENCE↗

Molecular Vision - Multimodal, multitask retrieval of molecular structure from measured signatures for reference-free compound identification

We are currently at risk of generating false conclusions based on limited methods to identify small molecules in biological systems and in chemical forensics. By definition, the chemical structures of novel small molecules have not been determined, let alone measured or synthesized. Currently, unambiguous structure determination of small molecules is constrained by the time and effort needed to isolate compounds and perform de novo structure elucidation using laboratory-based methods, significantly extending the time to inform mitigation strategies. To address this gap, we have developed a deep learning approach to directly map molecular structure to experimental signatures. We aim to unify measurement technologies employed in untargeted small molecule identification studies—such as infrared (IR) spectrometry, tandem mass spectrometry (MS/MS), ion mobility spectrometry-derived collision cross section (CCS)—through use of a multimodal, multitask deep learning architecture. Where existing methods require direct generation of information-rich spectra and/or properties, an inherently difficult task, we will simplify molecular signature-based identification by posing the problem as a recognition or retrieval task. The model is thus presented with relevant endpoints – structure and one or more molecular signatures – and need only determine whether they are semantically related. Thus, our approach offers the following advantages over existing techniques: (i) circumvents difficulties associated with direct generation of molecular signatures from structure and structure from signatures; (ii) incorporates multiple molecular signatures simultaneously, as available, to support identification; and (iii) enables rapid computation of structural embeddings toward broad coverage of known chemical space. Taken together, the approach removes the need to explicitly obtain or compute reference spectra, representing a powerful method for compound identification that requires only experimentally observed signatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

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↗

A methodology to generate crystal-based molecular structures for atomistic simulations

Abstract We propose a systematic method to construct crystal-based molecular structures often needed as input for computational chemistry studies. These structures include crystal ‘slabs’ with periodic boundary conditions (PBCs) and non-periodic solids such as Wulff structures. We also introduce a method to build crystal slabs with orthogonal PBC vectors. These methods are integrated into our code, Los Alamos Crystal Cut ( LCC ), which is open source and thus fully available to the community. Examples showing the use of these methods are given throughout the manuscript.

42 ENGINEERING↗

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↗