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At least 559 records · Page 31

A comparative analysis of different van der Waals treatments for molecular adsorption on the basal plane of 2H-MoS 2

The binding energy of hydrogen sulfide, ammonia, ethane, ethylene, butadiene, benzene, toluene, pyridine, pyrrole, and thiophene on the basal plane of the semi-conducting 2H-molybdenum sulfide (MoS 2 ) was calculated with the following flavors of Density Functional Theory (DFT): GGA-PW91, PBE-D3, vdW-DF, optPBE, optB86b, optB88, vdW-TS, and BEEF-vdW. The GGA-PW91 binding energies are negligible (<0.07 eV in magnitude) in all cases. The predictions with vdW-DF and PBE-D3 are the closest (error <0.05 eV) to the isosteric heats of adsorption calculated from reported temperature programmed desorption data for thiophene and butadiene. For all dispersion flavors examined here, the magnitude of the dispersion contribution to the binding energy increases linearly with the number of heavy atoms in the adsorbate, with each atom contributing 0.05 eV (BEEF-vdW) – 0.09 eV (optB88-vdW). Further, this implies that the calculated adsorption constants of molecules larger than acridine (i.e., comprising > 14 non-heavy atoms) can vary by more than four orders of magnitude at industrial conditions depending on the chosen method of dispersion correction. Further, dispersion effects fall off rapidly (>0.03 eV/ non-hydrogen atom/Å) as the adsorbate-surface distance increases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synchronous RNA conformational changes trigger ordered phase transitions in crystals

Time-resolved studies of biomacromolecular crystals have been limited to systems involving only minute conformational changes within the same lattice. Ligand-induced changes greater than several angstroms, however, are likely to result in solid-solid phase transitions, which require a detailed understanding of the mechanistic interplay between conformational and lattice transitions. Here we report the synchronous behavior of the adenine riboswitch aptamer RNA in crystal during ligand-triggered isothermal phase transitions. Direct visualization using polarized video microscopy and atomic force microscopy shows that the RNA molecules undergo cooperative rearrangements that maintain lattice order, whose cell parameters change distinctly as a function of time. The bulk lattice order throughout the transition is further supported by time-resolved diffraction data from crystals using an X-ray free electron laser. The synchronous molecular rearrangements in crystal provide the physical basis for studying large conformational changes using time-resolved crystallography and micro/nanocrystals.

59 BASIC BIOLOGICAL SCIENCES↗

Proposed crystal structure of carbadox, C 11 H 10 N 4 O 4

A model for the crystal structure of carbadox has been generated and refined using synchrotron X-ray powder diffraction data and optimized using density functional theory techniques. Carbadox crystallizes in space groupP2 1 (#4) witha= 13.8155(3),b= 21.4662(1),c= 16.3297(3) Å,β= 110.0931(7)°,V= 4548.10(3) Å 3 , andZ= 16. The crystal structure is characterized by approximately parallel stacking of the eight independent carbadox molecules parallel to thebc-plane. There are two different molecular configurations of the eight carbadox molecules; five are in the lower-energy configuration and three are in a ~10% higher-energy configuration. This arrangement likely achieves the lowest-energy crystalline packing via hydrogen bonding. Hydrogen bonds link the molecules both within and between the planes. Each of the amino groups forms a N–H⋯O hydrogen bond to an oxygen atom of the 1,4-dioxidoquinoxaline ring system of another molecule. The result is four pairs of hydrogen-bonded molecules, which form rings with graph setR2,2(14). Variation in specimen preparation can affect the preferred orientation of particles considerably. The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File™ (PDF®).

Materials Science↗

Quantum Simulation of Polarized Light-Induced Electron Transfer with a Trapped-Ion Qutrit System

Electron transfer within and between molecules is crucial in chemistry, biochemistry, and energy science. Here this study describes a quantum simulation method that explores the influence of light polarization on electron transfer between two molecules. By implementing precise and coherent control among the quantum states of trapped atomic ions, we can induce quantum dynamics that mimic the electron-transfer dynamics in molecules. We use three-level systems (qutrits), rather than traditional two-level systems (qubits), to enhance the simulation efficiency and realize high-fidelity simulations of electron-transfer dynamics. We treat the quantum interference between the electron coupling pathways from a donor with two degenerate excited states to an acceptor and analyze the transfer efficiency. We also examine the potential error sources that enter the quantum simulations. The trapped-ion systems have favorable scalings with system size compared to those of classical computers, promising access to richer electron-transfer simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Deep Potential model for liquid–vapor equilibrium and cavitation rates of water

Computational studies of liquid water and its phase transition into vapor have traditionally been performed using classical water models. Here, we utilize the Deep Potential methodology—a machine learning approach—to study this ubiquitous phase transition, starting from the phase diagram in the liquid–vapor coexistence regime. The machine learning model is trained on ab initio energies and forces based on the SCAN density functional, which has been previously shown to reproduce solid phases and other properties of water. Here, we compute the surface tension, saturation pressure, and enthalpy of vaporization for a range of temperatures spanning from 300 to 600 K and evaluate the Deep Potential model performance against experimental results and the semiempirical TIP4P/2005 classical model. Moreover, by employing the seeding technique, we evaluate the free energy barrier and nucleation rate at negative pressures for the isotherm of 296.4 K. Further, we find that the nucleation rates obtained from the Deep Potential model deviate from those computed for the TIP4P/2005 water model due to an underestimation in the surface tension from the Deep Potential model. From analysis of the seeding simulations, we also evaluate the Tolman length for the Deep Potential water model, which is (0.091 ± 0.008) nm at 296.4 K. Finally, we identify that water molecules display a preferential orientation in the liquid–vapor interface, in which H atoms tend to point toward the vapor phase to maximize the enthalpic gain of interfacial molecules. We find that this behavior is more pronounced for planar interfaces than for the curved interfaces in bubbles. This work represents the first application of Deep Potential models to the study of liquid–vapor coexistence and water cavitation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Atomic Layer Deposition with TiO2 for Enhanced Reactivity and Stability of Aromatic Hydrogenation Catalysts

Hydrogenation of aromatic molecules in fossil- and bio-derived fuels is essential for decreasing emissions of harmful combustion products and addressing growing concerns around urban air pollution. In this work, we used atomic layer deposition to significantly enhance the hydrogenation performance of a conventional supported Pd catalyst by applying an ultrathin coating of TiO2 in a scalable powder coating process. The TiO2-coated catalyst showed substantial gains in the conversion of multiple aromatic molecules, including a 5-fold improvement in turnover frequency versus the uncoated catalyst in the hydrogenation of naphthalene. This activity enhancement was maintained upon scaling the coating synthesis process from 3 to 100 g. Based on the results from Xray photoelectron spectroscopy, X-ray absorption spectroscopy, and computational modeling, the activity enhancement was attributed to ensemble effects resulting from partial TiO2 coverage of the Pd surface rather than fundamental changes to the Pd electronic structure. Additional durability testing confirmed that the TiO2 coating improved the thermal and hydrothermal stability of the catalyst as well as tolerance toward sulfur impurities in the reactant stream. Using an economic model of an industrial deep hydrogenation process, we found that an increase in catalyst activity or lifetime of 2× would justify even a relatively high estimate for the cost of TiO2 atomic layer deposition coatings at scale

atomic layer↗

Effects of isoalcohol blending with gasoline on autoignition behavior in a rapid compression machine: Isopropanol and isobutanol

Alcohols, and particularly isoalcohols, are potentially advantageous blendstocks towards achieving efficient, low-carbon intensity internal combustion engines. Their use in advanced configurations, such as boosted spark-ignition or spark-assisted compression ignition, requires a comprehensive understanding of their blending effects on the low- and intermediate-temperature autoignition behavior of petroleum-derived gasoline. This work reports an experimental and modeling study of such autoignition characteristics quantified in a twin-piston rapid compression machine. Isopropanol and isobutanol are blended into a research-grade gasoline (FACE-F) at oxygenate blend levels of 0 to 30% vol/vol, with tests conducted at pressures of 20 and 40 bar, temperatures from 700 to 1000 K, and dilute stoichiometric fuel loadings. Changes to overall reactivity, including first-stage and main ignition times, and preliminary exothermicity are established, with comparisons made to previous measurements with ethanol-blended FACE-F gasoline. Furthermore, it is found that at low-temperature/NTC conditions (700–860 K) the isoalcohols suppress first-stage reactivity and associated heat release while main ignition times are extended. At NTC/intermediate-temperature (860–1000 K) conditions changes to fuel reactivity are less significant with isopropanol slightly suppressing reactivity and isobutanol promoting ignition. Detailed chemical kinetic modeling is used to interpret the experimental measurements. Overall trends of suppression or promotion in the blending behavior are reasonably captured by the model. Sensitivity and rate of production analyses indicate that at lower temperatures H-atom abstraction reactions from the surrogate fuel molecules (e.g., cyclopentane, isooctane) and the isoalcohols via OH are important leading to TC 3 H 6 OH and IC 4 H 8 OH–C radicals, for isopropanol and isobutanol respectively, which act as scavengers in the system. At higher temperatures, similar chemistries are dominant, but there is an increasing importance of abstraction by HO 2 . The kinetic modeling also indicates that the promoting effect of isobutanol at higher temperatures is due to the increased abstractions at the γ-sites, while at lower temperatures abstraction at the α-site leads to greater reactivity suppression.

36 MATERIALS SCIENCE↗

Building Atomic and Plasmonic Devices via Electron Beams: from Desired Structures to Desired Properties

The evolution of the aberration correction in Scanning Transmission Electron Microscopy (STEM) has enabled multiple advances including high-resolution structural imaging, pm-level position detection of atomic columns, and ~3-5 mV resolution electron energy loss spectroscopy of the chemical and physical functionalities. These developments have further enabled the precise manipulation of the atomic structure of materials, including removal and formation of atomic planes in 3D materials, controlled atomic motion, and even direct atomic assembly of homo- and heteroatomic artificial molecules. Here, we will discuss several recent advances in STEM-EELS automated experiments as applied to quantum and nanoplasmonic systems.

42 ENGINEERING↗

Molecular Dynamics Simulation of the Structures, Dynamics, and Aggregation of Dissolved Organic Matter

Dissolved organic matter (DOM) plays a significant role in the transport and transformation of pollutants in the aquatic environment. However, the experimental characterization of DOM has been limited mainly to bulk properties, and the molecular-level interactions among various components of DOM remain to be fully characterized. In this study, we use molecular dynamics (MD) simulations to probe the structural properties of model DOM systems at atomic detail. The 200 ns simulations, validated by available experimental data, reveal processes and mechanisms by which chemical species (cations, peptides, lipids, lignin, carbohydrates, and some low-molecular-weight aliphatic and aromatic compounds) aggregate to form complex DOM. The DOM aggregates are dynamic, consisting of a hydrophobic core and amphiphilic exterior. The lipid tails and other hydrophobic fragments form the core, with hydrophilic and amphiphilic groups exposed to water, making DOM accessible to both polar and nonpolar species. Thus, the lipid component acts as a nucleator, whereas cations (especially Ca 2+ ) connect the molecular fragments on the surface by coordinating with the O-containing functional groups of DOM. The structural details revealed here provide new insights including surface accessible atoms, overall assemblage, and interactions among the molecules of DOM for understanding the kinetics and mechanisms through which DOM interacts with metal and other contaminants.

54 ENVIRONMENTAL SCIENCES↗

High Accuracy Transition Metal Effective Cores for the Many-Body Diffusion Monte Carlo Method

Practical applications of the real-space diffusion Monte Carlo (DMC) method require the removal of core electrons, where currently localization approximations of semilocal potentials are generally used in the projector. Accurate calculations of complex solids and large molecules demand minimizing the impact of approximated atomic cores. Prior works have shown that the errors from such approximations can be sizable in both finite and periodic systems. In this work, we show that a class of differential pseudopotentials, known as pseudo-Hamiltonians, can be constructed for the 3d transition metal atoms, entirely removing the need for any localization scheme in the DMC projector. As a proof of principle, we demonstrate the approach for the case of Co. In order to minimize errors in the pseudo-Hamiltonian at the many-body level, we generalize the recently proposed correlation-consistent pseudopotential generation scheme to successively close semilocal representations of the differential potentials. Our generation scheme successfully produces potentials tailored specifically for real space projector quantum Monte Carlo methods with low error at the many-body level, i.e., with many-body scattering properties very close to relativistic all-electron results. In particular, we show that the agreement with respect to atomic and molecular quantities reach chemical accuracy in many cases-on par with the most accurate semilocal pseudopotentials available. Further, our pseudo-Hamiltonian generation scheme utilizes standard quantum chemistry codes designed only to work with semilocal pseudopotentials, enabling straightforward generation of pseudo-Hamiltonians for additional elements in future works.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improved Treatment of 1–4 Interactions in Force Fields for Molecular Dynamics Simulations

Traditional force fields commonly use a combination of bonded torsional terms and empirically scaled nonbonded interactions to capture 1-4 energies and forces of atoms separated by three bonds in a molecule. While this approach can yield accurate torsional energy barriers, it often leads to inaccurate forces and erroneous geometries and creates an interdependence between dihedral terms and nonbonded interactions, complicating parametrization and reducing transferability. Here, in this paper, we demonstrate that 1-4 interactions can be accurately modeled using only bonded coupling terms, eliminating the need for arbitrarily scaled nonbonded interactions altogether. Furthermore, by leveraging the automated parametrization capabilities of the Q-Force toolkit, we efficiently determine the necessary coupling terms without the need for manual adjustment. Our approach is first validated on a range of small molecule systems, encompassing both flexible and rigid structures, and shows a significant improvement in force field accuracy, obtaining subkcal/mol mean absolute error for every molecule tested. We further extend the bonded-only model for 1-4 interactions to Amber ff14sb, CHARMM36, and OPLS-AA force fields to reproduce ab initio gas and implicit solvent ϕ,ψ surfaces of alanine dipeptide.

Abdullah, Aalim S. [University of California, Berk↗

Three-Dimensional Patterning of Nanoparticles by Molecular Stamping

Directing the formation of nanoscale architectures from nanoparticles is one of the key challenges in designing nanomaterials with prescribed functions. Atomic systems, given their ability to form molecules and crystals via directional chemical bonds, provide an inspiration for establishing approaches where nanoparticles with designed anisotropic binding modalities can be assembled into nanoscale architectures. However, fabricating such nanoparticles has been challenging due to their small dimensions and limited ways for site-specific control of their surface. To this end, we present a Molecular Stamping (MOST) approach to pattern DNA-coated nanoparticles with molecules at the predefined positions on a nanoparticle surface. This patterning is realized by use of a rigid and coordinative DNA frame as a molecular stamping apparatus (MOST App). The MOST App transfers multiple types of molecular “inks”, DNA sequences, onto nanoparticle surface and fixes these molecular inks into place to form a designed pattern. After a nanoparticle release from MOST App, it possesses single-molecule patches that can provide anisotropic bonds with distinctive affinities. We further use these stamped nanoparticles to assemble prescribed clusters, whose structure is determined by the locations of patches. Using electron microscopy and tomographic methods, we investigate the efficiency of cluster formation and the resulting spatial arrangements of nanoparticles. The presented approach provides a single-molecule and spatiallydetermined control over nanoparticle functionalization for creating nanoparticles with designed placement of different molecules and for realizing a rational fabrication of nanomaterial architectures.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Metal-Coordinated Phthalocyanines as Platform Molecules for Understanding Isolated Metal Sites in the Electrochemical Reduction of CO 2

Single-atom catalysts (SACs) of non-precious transition metals (TMs) often show unique electrochemical performance, including the electrochemical carbon dioxide reduction reaction (CO 2 RR). However, the inhomogeneity in their structures makes it difficult to directly compare SACs of different TM for their CO 2 RR activity, selectivity, and reaction mechanisms. Here, the comparison of isolated TMs (Fe, Co, Ni, Cu, and Zn) is systematically investigated using a series of crystalline molecular catalysts, namely TM-coordinated phthalocyanines (TMPcs), to directly compare the intrinsic role of the TMs with identical local coordination environments on the CO 2 RR performance. The combined experimental measurements, in situ characterization, and density functional theory calculations of TM-Pc catalysts reveal a TM dependent CO 2 RR activity and selectivity, with the free energy difference of ΔG(*HOCO) - ΔG(*CO) being identified as a descriptor for predicting the CO 2 RR performance.

25 ENERGY STORAGE↗

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)↗

A quantum eigenvalue solver based on tensor networks

Electronic ground states are of central importance in chemical simulations, but have remained beyond the reach of efficient classical algorithms except in cases of weak electron correlation or one-dimensional spatial geometry. We introduce a hybrid quantum-classical eigenvalue solver that constructs a wavefunction ansatz from a linear combination of matrix product states in rotated orbital bases, enabling the characterization of strongly correlated ground states with arbitrary spatial geometry. The energy is converged via a gradient-free generalized sweep algorithm based on quantum subspace diagonalization, with a potentially exponential speedup in the off-diagonal matrix element contractions upon translation into compact quantum circuits of linear depth in the number of qubits. Chemical accuracy is attained in numerical experiments for both a stretched water molecule and an octahedral arrangement of hydrogen atoms, achieving substantially better correlation energies compared to a unitary coupled-cluster benchmark, with orders of magnitude reductions in quantum resource estimates and a surprisingly high tolerance to shot noise. This proof-of-concept study suggests a promising new avenue for scaling up simulations of strongly correlated chemical systems on near-term quantum hardware.

chemistry↗

How does your gyroid grow? A mesoatomic perspective on supramolecular, soft matter network crystals

We propose and describe a framework to understand the structure of supramolecular network crystals formed in soft matter in terms of mesoatomic building blocks, collective groupings of amphiphilic molecules that play a role analogous to atomic or molecular subunits of hard matter crystals. While the concept of mesoatoms is intuitive and widely invoked in crystalline arrangements of spherelike or cylinderlike (micellelike) domains, analogous notions of natural and physically meaningful building blocks of triply periodic network (TPN) crystals, like the double-gyroid or double-diamond structures are obscured by the complex, bicontinuous domain shapes and intercatenated topologies of the double networks. Focusing on the specific example of diblock copolymer melts, we propose generic rules for decomposing TPN crystals into a unique set of mesoatomic building blocks. Based on physically motivated principles, the combination of symmetries and topologies of these structures point to mesoatomic elements associated with the nodal connections, leading to mesoatomic volumes that are nonconvex and bound by smoothly curved faces, unlike the more familiar Voronoi polyhedral shapes associated with spherelike and cylinderlike mesoatoms. We analyze the shapes of these mesoatoms, their internal structure, and importantly, their local packing with neighbor mesoatomic units. Importantly, we hypothesize that mesoatoms are kinetically favored intermediate structures whose local shapes and packing template network crystal assembly on long time scales. We propose and study a minimal energetic model of mesoatom assembly for three different cubic double-network crystals, based on local shape packing, which predicts a detailed picture for kinetics of intercatenation and surface growth. Based on these analyses, we discuss several possible extensions and elaborations of the mesoatomic description of supramolecular soft matter network crystals, most notably the implications of mesoatomic malleability, a feature that distinguishes soft matter from hard matter crystals. We describe experimental observations of malleable mesoatomic units in the precursor sponge phase as well as in ordered cubic networks and suggest possibilities for observing mesoatoms in primordial, precrystalline states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Materials Data on AlBr3 by Materials Project

AlBr3 crystallizes in the monoclinic P2_1/c space group. The structure is zero-dimensional and consists of two al2br6 molecules. Al3+ is bonded to four Br1- atoms to form edge-sharing AlBr4 tetrahedra. There are a spread of Al–Br bond distances ranging from 2.26–2.46 Å. There are three inequivalent Br1- sites. In the first Br1- site, Br1- is bonded in a single-bond geometry to one Al3+ atom. In the second Br1- site, Br1- is bonded in a single-bond geometry to one Al3+ atom. In the third Br1- site, Br1- is bonded in an L-shaped geometry to two equivalent Al3+ atoms.

36 MATERIALS SCIENCE↗