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At least 91 records · Page 5

A new perspective on lone pair dynamics in halide perovskites

Halide perovskites form the foundation of an emerging class of materials for broad application in renewable and sustainable applications, including photocatalysis and solar energy harvesting. These materials exhibit beneficial photophysical properties, including bandgaps suitable for solar energy harvesting and efficient charge screening that underlies efficient charge carrier separation and resistance to defects. For organic–inorganic hybrid perovskites, these benefits are thought to arise, in part, from dipolar molecular cations that can reorient in response to charged particles and defects. In this work, we provide a similar perspective for inorganic metal halide perovskites, which do not contain molecular species with permanent dipoles. We discuss how lone pair electrons lead to dipolar ions that exhibit dynamics in analogy with traditional molecular plastic crystals and hybrid perovskites. We argue that further understanding these electronic plastic crystal motions with first principles simulations and synchrotron scattering can help create a basic understanding of photophysical properties of metal halide perovskites and inform the design of advanced functional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A modular and extensible CHARMM-compatible model for all-atom simulation of polypeptoids

Peptoids (N-substituted glycines) are a class of sequence-defined synthetic peptidomimetic polymers with applications including drug delivery, catalysis, and biomimicry. Classical molecular simulations have been used to predict and understand the conformational dynamics of single chains and their self-assembly into morphologies including sheets, tubes, spheres, and fibrils. The CGenFF-NTOID model based on the CHARMM General Force Field has demonstrated success in accurate all-atom molecular modeling of peptoid structure and thermodynamics. Extension of this force field to new peptoid side chains has historically required reparameterization of side chain bonded interactions against ab initio data. This fitting protocol improves the accuracy of the force field but is also burdensome and precludes modular extensibility of the model to arbitrary peptoid sequences. In this work, we develop and demonstrate a Modular Side Chain CGenFF-NTOID (MoSiC-CGenFF-NTOID) as an extension of CGenFF-NTOID employing a modular decomposition of the peptoid backbone and side chain parameterizations, wherein arbitrary side chains within the large family of substituted methyl groups (i.e., –CH 3 , –CH 2 R, –CHRR', and –CRR'R") are directly ported from CGenFF. We validate this approach against ab initio calculations and experimental data to develop a MoSiC-CGenFF-NTOID model for all 20 natural amino acid side chains along with 13 commonly used synthetic side chains and present an extensible paradigm to efficiently determine whether a novel side chain can be directly incorporated into the model or whether refitting of the CGenFF parameters is warranted. We make the model freely available to the community along with a tool to perform automated initial structure generation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Toward Edge-Defined Holey Boron Nitride Nanosheets

"Holey" two-dimensional (2D) nanosheets with well-defined holy morphology and edge chemistry are highly desirable for applications such as energy storage, catalysis, sensing, transistors, and molecular transport/separation. For example, holey grapheme is currently under extensive investigation for energy storage applications because of the improvement in ion transport due to through the thickness pathways provided by the holes. Without the holes, the 2D materials have significant limitations for such applications in which efficient ion transport is important. As part of an effort to apply this approach to other 2D nanomaterials, a method to etch geometrically defined pits or holes on the basal plane surface of hexagonal boron nitride (h-BN) nanosheets has been developed. The etching, conducted via heating in ambient air using metal nanoparticles as catalysts, was facile, controllable, and scalable. Starting h-BN layered crystals were etched and subsequently exfoliated into boron nitride nanosheets (BNNSs). The as-etched and exfoliated h-BN nanosheets possessed defined pit and hole shapes that were comprised of regulated nanostructures at the edges. The current finding are the first step toward the bulk preparation of holey BNNSs with defined holes and edges.

Lin, Yi↗

Quantum Hardware-Enabled Molecular Dynamics via Transfer Learning

The ability to perform ab initio molecular dynamics simulations using potential energy surfaces provided by quantum computers would open the door to virtually exact dynamics for a variety of chemical and biochemical systems, with impacts on catalysis and biophysics. Nonetheless, performing molecular dynamics on surfaces produced by quantum hardware has been hampered by the noisy energies typically produced by quantum computers and challenges associated with computing gradients and scaling to large systems interest. A recent set of advances in machine learning, known as transfer learning, provides a new path forward for molecular dynamics simulations on quantum hardware. Transfer learning offers a workaround, where one first trains models on larger, less accurate classical datasets and then refines them on smaller, more accurate quantum datasets. We explore this approach by training machine learning models to predict a molecule's potential energy based on its geometric structure using Behler-Parrinello neural networks. When successfully trained, the model enables energy gradient predictions necessary for dynamic simulations. To reduce the quantum resources needed, the model is initially trained with data derived from classical density functional theory and subsequently refined with a smaller dataset obtained from a variational quantum eigensolver optimization of the unitary coupled cluster ansatz. We show that this approach significantly reduces the size of the needed quantum training dataset while capturing the high accuracies needed within quantum chemistry simulations. The success of this two-step training method opens more opportunities to apply machine learning models on quantum data, a significant stride towards efficient quantum-classical hybrid computational models.

quantum computing↗

Compact Peptoid Molecular Brushes for Nanoparticle Stabilization

Controlling the interfaces and interactions of colloidal nanoparticles (NPs) via tethered molecular moieties is crucial for NP applications in engineered nanomaterials, optics, catalysis, and nanomedicine. Despite a broad range of molecular types explored, there is a need for a flexible approach to rationally vary the chemistry and structure of these interfacial molecules for controlling NP stability in diverse environments, while maintaining a small size of the NP molecular shell. Here, we demonstrate that low-molecular-weight, bifunctional comb-shaped, and sequence-defined peptoids can effectively stabilize gold NPs (AuNPs). The generality of this robust functionalization strategy was also demonstrated by coating of silver, platinum, and iron oxide NPs with designed peptoids. Each peptoid (PE) is designed with varied arrangements of a multivalent AuNP-binding domain and a solvation domain consisting of oligo-ethylene glycol (EG) branches. Among designs, a peptoid (PE5) with a diblock structure is demonstrated to provide a superior nanocolloidal stability in diverse aqueous solutions while forming a compact shell (similar to 1.5 nm) on the AuNP surface. We demonstrate by experiments and molecular dynamics simulations that PE5-coated AuNPs (PE5/AuNPs) are stable in select organic solvents owing to the strong PE5 (amine)-Au binding and solubility of the oligo-EG motifs. At the vapor-aqueous interface, we show that PE5/AuNPs remain stable and can self-assemble into ordered 2D lattices. The NP films exhibit strong near-field plasmonic coupling when transferred to solid substrates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effect of Solvent on the Local Structure, Dynamics, and Vibrational Density of States in Sn-BEA Zeolite

Lewis acid zeolites are attractive catalysts for epoxidation and biomass valorization, as they are highly active and selective in the liquid phase and can operate at or near ambient conditions. While a rich experimental literature exists on liquid-phase Lewis acid zeolite catalysis, our understanding of the molecular organization and solvent dynamics in the vicinity of Lewis acid sites with differing metal site speciation remains limited. In this work, we investigate the molecular coordination and diffusion of two common solvents (methanol and water) around the closed and open Sn-BEA zeolite active sites using molecular dynamics simulations with a machine-learned interatomic potential trained on ab initio molecular dynamics trajectories. Molecular dynamics simulations reveal that introducing active sites significantly enhances local order in the first and second solvation shells compared to the pure silica case. For methanol, both closed and open active sites are singly coordinated, while more than two water molecules coordinate the open site. In contrast to methanol, we observed that water molecules dissociate, leading to the formation of additional Sn-OH and silanol groups away from the active site. The diffusion coefficients of water and methanol are functions of the solvent population in the pore. Here, our work provides insights into how active site speciation in Lewis acid zeolites affects solvent coordination, diffusion, and vibrational signature. This information is foundational for catalyst design and optimization of liquid-phase catalytic processes in zeolites. It also demonstrates the suitability of machine-learned interatomic potentials for modeling reactive systems, enabling sufficiently long trajectories for appropriate statistical averaging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling study on the cleavage step of the self-splicing reaction in group I introns

A three-dimensional model of the Tetrahymena thermophila group I intron is used to further explore the catalytic mechanism of the transphosphorylation reaction of the cleavage step. Based on the coordinates of the catalytic core model proposed by Michel and Westhof (Michel, F., Westhof, E. J. Mol. Biol. 216, 585-610 (1990)), we first converted their ligation step model into a model of the cleavage step by the substitution of several bases and the removal of helix P9. Next, an attempt to place a trigonal bipyramidal transition state model in the active site revealed that this modified model for the cleavage step could not accommodate the transition state due to insufficient space. A lowering of P1 helix relative to surrounding helices provided the additional space required. Simultaneously, it provided a better starting geometry to model the molecular contacts proposed by Pyle et al. (Pyle, A. M., Murphy, F. L., Cech, T. R. Nature 358, 123-128. (1992)), based on mutational studies involving the J8/7 segment. Two hydrated Mg2+ complexes were placed in the active site of the ribozyme model, using the crystal structure of the functionally similar Klenow fragment (Beese, L.S., Steitz, T.A. EMBO J. 10, 25-33 (1991)) as a guide. The presence of two metal ions in the active site of the intron differs from previous models, which incorporate one metal ion in the catalytic site to fulfill the postulated roles of Mg2+ in catalysis. The reaction profile is simulated based on a trigonal bipyramidal transition state, and the role of the hydrated Mg2+ complexes in catalysis is further explored using molecular orbital calculations.

NASA Discipline Exobiology↗

Reaction Chemistry at Discrete Organometallic Fragments on Black Phosphorus

Abstract Black phosphorus (bP) is a two‐dimensional van der Waals material unique in its potential to serve as a support for single‐site catalysts due to its similarity to molecular phosphines, ligands quintessential in homogeneous catalysis. However, there is a scarcity of synthetic methods to install single metal centers on the bP lattice. Here, we demonstrate the functionalization of bP nanosheets with molecular Re and Mo complexes. A suite of characterization techniques, including infrared, X‐ray photoelectron and X‐ray absorption spectroscopy as well as scanning transmission electron microscopy corroborate that the functionalized nanosheets contain a high density of discrete metal centers directly bound to the bP surface. Moreover, the supported metal centers are chemically accessible and can undergo ligand exchange transformations without detaching from the surface. The steric and electronic properties of bP as a ligand are estimated with respect to molecular phosphines. Sterically, bP resembles tri(tolyl)phosphine when monodentate to a metal center, and bis(diphenylphosphino)propane when bidentate, whereas electronically bP is a σ‐donor as strong as a trialkyl phosphine. This work is foundational in elucidating the nature of black phosphorus as a ligand and underscores the viability of using bP as a basis for single‐site catalysts.

Mitra, Kendahl L. Walz↗

Reaction Chemistry at Discrete Organometallic Fragments on Black Phosphorus

Abstract Black phosphorus (bP) is a two‐dimensional van der Waals material unique in its potential to serve as a support for single‐site catalysts due to its similarity to molecular phosphines, ligands quintessential in homogeneous catalysis. However, there is a scarcity of synthetic methods to install single metal centers on the bP lattice. Here, we demonstrate the functionalization of bP nanosheets with molecular Re and Mo complexes. A suite of characterization techniques, including infrared, X‐ray photoelectron and X‐ray absorption spectroscopy as well as scanning transmission electron microscopy corroborate that the functionalized nanosheets contain a high density of discrete metal centers directly bound to the bP surface. Moreover, the supported metal centers are chemically accessible and can undergo ligand exchange transformations without detaching from the surface. The steric and electronic properties of bP as a ligand are estimated with respect to molecular phosphines. Sterically, bP resembles tri(tolyl)phosphine when monodentate to a metal center, and bis(diphenylphosphino)propane when bidentate, whereas electronically bP is a σ‐donor as strong as a trialkyl phosphine. This work is foundational in elucidating the nature of black phosphorus as a ligand and underscores the viability of using bP as a basis for single‐site catalysts.

Chemistry↗

Developing Scaling Relationships for Molecular Electrocatalysis through Studies of Fe-Porphyrin-Catalyzed O 2 Reduction

The oxygen reduction reaction (ORR) is a multiproton/multielectron transformation in which dioxygen (O 2 ) is reduced to water or hydrogen peroxide and serves as the cathode reaction in most fuel cells. The ORR (O 2 + 4e – + 4H + → 2H 2 O) involves up to nine substrates and thus requires navigating a complicated reaction landscape, typically with several high-energy intermediates. Many catalysts can perform this reaction, though few operate with fast rates and at low overpotentials (close to the thermodynamic potential). Attempts to optimize these parameters, both in homogeneous and heterogeneous electrocatalytic systems, have focused on modifying catalyst design and understanding kinetic/thermodynamic relationships between catalytic intermediates. One such method for analyzing and predicting catalyst reactivity and efficiency has been the development of “molecular scaling relationships”. In this work, we share our experience deriving and utilizing molecular scaling relationships for soluble, iron-porphyrin-catalyzed O 2 reduction in organic solvents. These relationships correlate turnover frequencies (TOF max ) and effective overpotentials (η eff ), properties uniquely defined for homogeneous catalysts. Following a general introduction of scaling relationships for both homogeneous and heterogeneous electrocatalysis, we describe the components of such scaling relationships: (i) the overall thermochemistry of the reaction and (ii) the rate and rate law of the catalyzed reaction. We then show how connecting these thermodynamic and kinetic parameters reveals multiple molecular scaling relationships for iron-porphyrin-catalyzed O 2 reduction. For example, the log(TOF max ) responds steeply to changes in ηeff that result from different catalyst reduction potentials (18.5 decades in TOF max /V in η eff ) but much less dramatically to changes in η eff that arise from varying the pKa of the acid buffer (5.1 decades in TOF max /V in η eff ). Thus, a single scaling relationship is not always sufficient for describing molecular electrocatalysis. This is particularly evident when the catalyst identity and reaction conditions are coupled. Using these multiple scaling relationships, we demonstrate that the metrics of turnover frequency and effective overpotential can be predictably tuned to achieve faster rates at lowered overpotentials. This Account uses a collection of related stories describing our research on soluble iron-porphyrin-catalyzed ORR to show how molecular scaling relationships can be derived and used for any electrocatalytic reaction. Such scaling relationships are powerful tools that connect the thermochemistry, mechanism, and rate law for a catalytic system. We hope that this collection shows the utility and simplicity of the molecular scaling approach for understanding catalysis, for enabling direct comparisons between catalyst systems, and for optimizing catalytic processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Neural Network Sampling of the Free Energy Landscape for Nitrogen Dissociation on Ruthenium

In heterogeneous catalysis, free energy profiles of reactions govern the mechanisms, rates, and equilibria. Energetics are conventionally computed using the harmonic approximation (HA), which requires determination of critical states a priori. Here, we use neural networks to efficiently sample and directly calculate the free energy surface (FES) of a prototypical heterogeneous catalysis reaction—the dissociation of molecular nitrogen on ruthenium—at density-functional-theory-level accuracy. We find that the vibrational entropy of surface atoms, often neglected in HA for transition metal catalysts, contributes significantly to the reaction barrier. The minimum free energy path for dissociation reveals an “on-top” adsorbed molecular state prior to the transition state. While a previously reported flat-lying molecular metastable state can be identified in the potential energy surface, it is absent in the FES at relevant reaction temperatures. Finally, these findings demonstrate the importance of identifying critical points self-consistently on the FES for reactions that involve considerable entropic effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Barrierless nucleation in glassy precursors drives zeolite formation

Zeolites are crystalline, microporous silicates widely used in catalysis and separations, yet the molecular mechanisms of their formation remain unresolved. Experiments indicate that hydrothermal synthesis of silica zeolites from clear solution proceeds through amorphous nanoaggregates that gradually develop zeolite order in an apparently continuous amorphous to crystal transformation. Here, we combine molecular simulations with advanced algorithms that identify zeolite order and computer vision to elucidate the pathway from clear solution to zeolite nanocrystal. We show that at conditions of hydrothermal synthesis of silica zeolites, the transformation of precursor aggregate into zeolite is not limited by nucleation barriers but by the slow dynamics of reorganization in the glassy precursor matrix. The negligible nucleation barriers result in spinodal-like crystallization that leads to a gradual formation of a mosaic of small crystallites that explain the seemingly continuous character of zeolite crystallization and the catalytic activity of X-ray amorphous, protozeolites and embryonic zeolites. We find that zeolite-like porosity and short-range order emerge early within glassy precursors, well before crystallinity is detected in transmission electron microscopy (TEM) images or X-ray diffraction. The nanoaggregate’s temperature-size phase diagram reveals a convergence of the zeolite–amorphous equilibrium and maximum crystallization rate at ~3 nm diameter nanoparticle diameters and ~200 °C. This convergence signals the termination of the first-order amorphous-to-zeolite transition. Our results provide a unifying framework for understanding nucleation of silica zeolites from solution and suggest that barrierless nucleation may govern the formation of other nanoparticle systems, including minerals and oxides synthesized far below their bulk melting points.

36 MATERIALS SCIENCE↗

Availability and reactivity of N 2 ( v ) for NH 3 synthesis by plasma catalysis

Production of vibrationally excited N 2 (N 2 (v)) in atmospheric pressure nonthermal plasma and loss of N 2 (v) by gas-phase reactions and reactions on catalytic surfaces are analyzed to examine the role of N 2 (v) in NH 3 formation by plasma catalysis. Vibrational state-to-state kinetic models complemented with molecular beam mass spectrometry (MBMS) measurements demonstrate that N 2 (v> 0) is produced with densities 100× greater than the density of N radicals by a radiofrequency atmospheric pressure plasma jet. The experimentally measured loss of N 2 (v) corresponds with a state-to-state kinetic model that describes loss of N 2 (v) by surface-mediated vibrational relaxation without consideration of reactions that convert N 2 (v) to NH 3 over the catalyst surface. Rate constants for vibrational relaxation of N 2 (v) on catalyst surfaces exceed upper bounds on proposed rate constants for NH 3 formation reactions from N 2 (v) over Fe when v < 9, Ni when v < 18, and Ag when v < 39, which indicates that only higher vibrational levels can possibly contribute to catalytic NH 3 formation faster than they undergo vibrational relaxation on the surface. Densities of N 2 (v> 8), vibrational levels that can possibly react over Fe to form NH 3 faster than they undergo vibrational relaxation, are less than or similar to N densities at the inlet of the catalyst bed and measured NH 3 formation for the investigated conditions in this work, while densities of N 2 (v> 17) and N 2 (v> 38) are orders of magnitude below the N density at the inlet of the catalyst bed and the measured NH 3 formation. The loss of N 2 (v) by vibrational relaxation on the surface limits the ability of N 2 (v) to contribute to catalytic NH 3 formation and explains why N 2 (v) does not produce NH 3 in quantities that are comparable to NH 3 formation from N even though N 2 (v > 0) is more abundantly produced by the plasma.

state-to-state kinetic modeling↗

Science Opportunities and Capabilities Enabled by LCLS-II and LCLS-II HE

X-Ray Science with LCLS-II and LCLS-II HE: Chemical dynamics: Reaction dynamics, charge transfer, molecular photocatalysts, natural & artificial photosynthesis; Catalysis: Homogeneous and heterogeneous catalysis, interfacial & geo/environmental chemistry; Materials Physics: Heterogeneity, spontaneous fluctuations, nonequilibrium dynamics, extreme environments; Quantum Materials: Emergent phenomena & collective excitations; Biological Function & Structural Dynamics: Dynamics in physiological environments.

43 PARTICLE ACCELERATORS↗

Electronic and Vibrational Coherence in Heterogeneous Electron Transfer (Final Report)

Interfacial electron transfer reactions constitute key physical phenomena central to a variety of energy related transport and conversion processes such as catalysis, photocatalysis, photovoltaics, energy storage, molecular electronics, etc. Heterogeneous material systems like organic/inorganic interfaces are of particular interest because they provide great potential to tailor properties according to application specific requirements. While electron transfer dynamics has been studied intensively in heterogeneous systems many questions remain unanswered. The significance of electronic-vibrational coupling and coherence is one aspect that has yet to be fully explored. The objective of this project is to develop and implement new ultrafast spectroscopic techniques based on pump four-wave mixing spectroscopy (pump-FWM) for studying the dynamics of vibrational coupling and coherence in heterogeneous electron transfer (HET) at molecule/semiconductor interfaces. The implementation of the spectroscopic setup allows to explore different four-wave mixing techniques and thus to identify a suitable approach to study the significance of vibrational as well as electronic coherence in HET.

14 SOLAR ENERGY↗

Structural Insights into the Dynamics of Water in SOD1 Catalysis and Drug Interactions

Superoxide dismutase 1 (SOD1) is a crucial enzyme that protects cells from oxidative damage by converting superoxide radicals into H 2 O 2 and O 2 . This detoxification process, essential for cellular homeostasis, relies on a precisely orchestrated catalytic mechanism involving the copper cation, while the zinc cation contributes to the structural integrity of the enzyme. This study presents the 2.3 Å crystal structure of human SOD1 (PDB ID: 9IYK), revealing an assembly of six homodimers and twelve distinct active sites. The water molecules form a complex hydrogen-bonding network that drives proton transfer and sustains active site dynamics. Our structure also uncovers subtle conformational changes that highlight the intrinsic flexibility of SOD1, which is essential for its function. Additionally, we observe how these dynamic structural features may be linked to pathological mutations associated with amyotrophic lateral sclerosis (ALS). By advancing our understanding of hSOD1’s mechanistic intricacies and the influence of water coordination, this study offers valuable insights for developing therapeutic strategies targeting ALS. Our structure’s unique conformations and active site interactions illuminate new facets of hSOD1 function, underscoring the critical role of structural dynamics in enzyme catalysis. Moreover, we conducted a molecular docking analysis using SOD1 for potential radical scavengers and Abelson non-receptor tyrosine kinase (c-Abl, Abl1) inhibitors targeting misfolded SOD1 aggregation along with oxidative stress and apoptosis, respectively. The results showed that CHEMBL1075867, a free radical scavenger derivative, showed the most promising docking results and interactions at the binding site of hSOD1, highlighting its promising role for further studies against SOD1-mediated ALS.

60 APPLIED LIFE SCIENCES↗

In vitro selection of catalytic RNAs

In vitro selection techniques are poised to allow a rapid expansion of the study of catalysis by RNA enzymes (ribozymes). This truly molecular version of genetics has already been applied to the study of the structures of known ribozymes and to the tailoring of their catalytic activity to meet specific requirements of substrate specificity or reaction conditions. During the past year, in vitro selection has been successfully used to isolate novel RNA catalysts from random sequence pools.

NASA Discipline Exobiology↗