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At least 163 records · Page 9

Driving chemical reactions with polariton condensates

Abstract When molecular transitions strongly couple to photon modes, they form hybrid light-matter modes called polaritons. Collective vibrational strong coupling is a promising avenue for control of chemistry, but this can be deterred by the large number of quasi-degenerate dark modes. The macroscopic occupation of a single polariton mode by excitations, as observed in Bose-Einstein condensation, offers promise for overcoming this issue. Here we theoretically investigate the effect of vibrational polariton condensation on the kinetics of electron transfer processes. Compared with excitation with infrared laser sources, the vibrational polariton condensate changes the reaction yield significantly at room temperature due to additional channels with reduced activation barriers resulting from the large accumulation of energy in the lower polariton, and the many modes available for energy redistribution during the reaction. Our results offer tantalizing opportunities to use condensates for driving chemical reactions, kinetically bypassing usual constraints of fast intramolecular vibrational redistribution in condensed phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantum dynamical effects of vibrational strong coupling in chemical reactivity

Abstract Recent experiments suggest that ground state chemical reactivity can be modified when placing molecular systems inside infrared cavities where molecular vibrations are strongly coupled to electromagnetic radiation. This phenomenon lacks a firm theoretical explanation. Here, we employ an exact quantum dynamics approach to investigate a model of cavity-modified chemical reactions in the condensed phase. The model contains the coupling of the reaction coordinate to a generic solvent, cavity coupling to either the reaction coordinate or a non-reactive mode, and the coupling of the cavity to lossy modes. Thus, many of the most important features needed for realistic modeling of the cavity modification of chemical reactions are included. We find that when a molecule is coupled to an optical cavity it is essential to treat the problem quantum mechanically to obtain a quantitative account of alterations to reactivity. We find sizable and sharp changes in the rate constant that are associated with quantum mechanical state splittings and resonances. The features that emerge from our simulations are closer to those observed in experiments than are previous calculations, even for realistically small values of coupling and cavity loss. This work highlights the importance of a fully quantum treatment of vibrational polariton chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Diffusion Monte Carlo evaluation of disiloxane linearisation barrier

The disiloxane molecule is a prime example of silicate compounds containing the Si-O-Si bridge. The molecule is of significant interest within the field of quantum chemistry, owing to the difficulty in theoretically predicting its properties. Herein, the linearisation barrier of disiloxane is investigated using a fixed-node diffusion Monte Carlo (FNDMC) approach, which is one of the most reliable ab initio methods in accounting for the electronic correlation. Calculations utilizing the density functional theory (DFT) and the coupled cluster method with single and double substitutions, including noniterative triples (CCSD(T)) are carried out alongside FNDMC for comparison. It is concluded that FNDMC successfully predicts the disiloxane linearisation barrier and does not depend on the completeness of the basis-set as much as DFT or CCSD(T), thus establishing its suitability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Site-Selective Atomic Layer Deposition at Thermally Generated Surface Oxygen Vacancies on Rutile TiO 2

Unique atomic arrangements (i.e., defects) on material surfaces may exhibit distinctive reactivity that affords opportunities for selective surface chemistry exclusively at those sites. While theoretically appealing, site-selective atomic layer deposition (ALD) processes remain largely unrealized experimentally. Here we provide evidence for site-selective ALD that exclusively targets oxygen vacancies thermally generated at the surface of TiO 2 single crystals. High-resolution in situ ellipsometry reveals the nucleation behavior of dimethylaluminum isopropoxide (DMAI) and water at process conditions precisely tuned for selective hydroxylation of surface defects. An island growth model for nucleation and atomic force microscopy (AFM) imaging are consistent with a site-selective growth mechanism that depends on the surface oxygen vacancy density. This approach to direct ALD reactions at defective surface sites may provide future opportunities for targeted remediation of electronically imperfect interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Progress on continuum modeling of lithium–sulfur batteries

While lithium–sulfur batteries are a promising next-generation chemistry devices due to their high theoretical energy density, commercialization has been slow due to low coulombic efficiency and poor cycle life. This review explores the ways in which continuum modeling contributes to the understanding of lithium–sulfur (LiS) battery mechanisms and cell-level performance through the lens of micro- and macroscale phenomena. We examine different approaches to modeling important physical phenomena such as reaction mechanisms, cathode microstructure, shuttling, nucleation and precipitation, and transport limitations. This paper also emphasizes the significance and challenge of connecting typical modeling parameters and assumptions to systems-level metrics of a standard state-of-art high performing lithium–sulfur cell. Particularly important, the considerations for high energy density cells and the areas where continuum models can facilitate better collaboration are discussed. Here, we also summarize a few selected works to highlight experimentally-driven modeling, use of electroanalytical techniques, and parameter identification approaches to enable model-based design and advanced battery management systems.

25 ENERGY STORAGE↗

Energy-Screened Many-Body Expansion for Protein–Ligand Interactions: Examining Convergence for Metalloenzymes Through Seven–Body Interactions

Fragment-based quantum chemistry is a powerful strategy for calculating protein−ligand interaction energies using quantum chemistry methods. Rigorous convergence often requires hundreds of atoms in the protein binding-site model, especially if that model is constructed using distance-based criteria to select amino acid residues, while three- and four-body calculations exhibit instability related to combinatorial proliferation in the number of subsystem calculations. Here, we report an energy-based screening protocol for the many-body expansion applied to protein−ligand interactions, implemented in the open-source FRAGME∩T code. Using a combination of aggressive screening based on semiempirical quantum chemistry, with an improved graph-theoretical algorithm to eliminate unimportant subsystems, we are able to perform n-body calculations up to n = 7 using density functional theory in triple-ζ basis sets. Distance cutoffs further reduce the cost without compromising accuracy. Rapid and stable convergence of the many-body expansion is obtained by n = 4, for a pair of metalloenzymes in which a divalent ion coordinates directly to the ligand. As compared to previous results that relied solely on distance cutoffs, oscillations in the n-body corrections are reduced or eliminated, although residual errors remain in one case. This work demonstrates that benchmark-quality protein−ligand interaction energies can be systematically converged using a method with excellent parallel efficiency and scalability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding intercalation chemistry for sustainable aqueous zinc–manganese dioxide batteries

Rechargeable aqueous Zn-MnO 2 technology combines one of the oldest battery chemistries with favourable sustainability characteristics, including safety, cost and environmental compatibility. However, the ambiguous charge storage mechanism presents a challenge to fulfil the great potential of this energy technology. In this work, we leverage on advanced electron microscopy, electrochemical analysis and theoretical calculations to look into the intercalation chemistry within the cathode material, or α-MnO 2 more specifically. We show that Zn 2+ insertion into the cathode is unlikely in the aqueous system; rather, the charge storage process is dominated by proton intercalation to form α-H x MnO 2 . We further reveal anisotropic lattice change as a result of entering protons proceeding from the surface into the bulk of α-MnO 2 , which accounts for the structural failure and capacity decay of the electrode upon cycling. Our work not only advances the fundamental understanding of rechargeable zinc batteries but also suggests the possibility to optimize proton intercalation kinetics for better-performing cell designs. A rechargeable aqueous Zn-MnO 2 battery features a combination of favourable sustainability characteristics from safety to cost. The authors deploy advanced characterizations and theoretical calculations to provide fresh insight into the charge storage mechanism, which not only closes an ongoing debate but suggests ways forward.

25 ENERGY STORAGE↗

Metalloborophenes: Structural Diversity and Emerging Properties of Metal–Boron Two‐Dimensional Frameworks

Metalloborophenes, an emerging subclass of 2D materials, have attracted growing attention owing to their exceptional structural diversity and highly tunable electronic and magnetic properties. Constructed from vacancy‐rich borophene frameworks stabilized by electron donation from incorporated metal atoms, metalloborophenes merge the chemical versatility of boron with the functional richness of metal dopants. The first experimental realization of Cu–borophene nanoribbons in 2024 marked a pivotal advance, confirming long‐standing theoretical predictions and revitalizing interest in this new frontier of boron‐based 2D chemistry. Despite this progress, most studies to date remain conceptual and theoretical, constrained by challenges in scalable synthesis, dopant precision, and substrate control. Computational investigations have revealed a broad landscape of stable metalloborophene structures, exhibiting metallic, semiconducting, and magnetic behavior across diverse dopant families, including alkali, alkaline‐earth, transition, and lanthanide elements. These tunable characteristics open promising avenues for applications in spintronics, catalysis, and hydrogen storage. This review provides a comprehensive overview of metalloborophenes, emphasizing the interplay between structure, stability, and functionality, and outlining future directions toward bridging predictive modeling with experimental realization of this rapidly evolving class of 2D materials.

2D materials↗

The effects of thermospheric winds and chemistry in the diurnal variations of thermospheric species

The reported investigation considers on the basis of a theoretical model, the diurnal variations of the thermospheric composition (H, He, O, O2, and Ar) in terms of thermal expansion with diffusive equilibrium and transport effects associated with thermospheric winds, chemistry, and exospheric flow. The theoretical results are compared with satellite composition data which indicate that the fundamental diurnal tide can be reasonably well understood. It is found that winds are only important for molecular oxygen below 180 km, while thermal expansion due to the larger mass is relatively more important for O2 than for O. Distinct from O, photodissociation and in particular photoionization of O2 are very significant for molecular oxygen.

Mayr, H. G.↗

Inhibition of Extracellular Enzyme Activity by Reactive Oxygen Species upon Oxygenation of Reduced Iron-Bearing Minerals

The dual roles of minerals in inhibiting and prolonging extracellular enzyme activity in soils and sediments are governed by enzyme adsorption to mineral surface. Oxigenation of mineral-bound Fe(II) generates reactive oxygen species (ROS), yet it is unknown whether and how this process alters the activity and functional lifespan of extracellular enzymes. Here, the effect of mineral-bound Fe(II) oxidation on the hydrolytic activity of a cellulose-degrading enzyme ß-glucosidase (BG) was studied using two pre-reduced Fe-bearing clay minerals (nontronite and montmorillonite) and one pre-reduced iron oxide (magnetite) at pH 5 and 7. Under anoxic condition, BG adsorption to mineral surface decreased its activity but prolonged its lifespan. Under oxic condition, ROS was produced, with the amount of •OH, the most abundant ROS, being positively correlated with the extent of structural Fe(II) oxidation in reduced minerals. •OH decreased BG activity and shortened its lifespan via conformational change and structural decomposition of BG. These results suggest that under oxic condition the ROS-induced inhibitory role of Fe(II)-bearing minerals outweighed their adsorption-induced protective role in controlling enzyme activity. These results disclose a previously unknown mechanism of extracellular enzyme inactivation, which have pivotal implications for predicting the active enzyme pool in redox-oscillating environments.

58 GEOSCIENCES↗

PemNet: A Transfer Learning-Based Modeling Approach of High-Temperature Polymer Electrolyte Membrane Electrochemical Systems

Widespread adoption of high-temperature electrochemical systems such as polymer electrolyte membrane fuel cells (HT-PEMFCs) requires models and computational tools for accurate optimization and guiding new materials for enhancing fuel cell performance and durability. Furthermore, while robust and better suited for extrapolation, knowledge-based modeling has limitations as it is time-consuming and requires information about the system that is not always available (e.g., material properties and interfacial behavior between different materials). Data-driven modeling, on the other hand, is easier to implement but often necessitates large datasets that could be difficult to obtain. In this contribution, knowledge-based modeling and data-driven modeling are combined by implementing a few-shot learning (FSL) approach. A knowledge-based model originally developed for a HT-PEMFCs was used to generate simulated data (887,735 points) and used to pretrain a neural network source model tuned via a genetic algorithm-based AutoML. Then, experimental datasets from HT-PEMFCs with different materials and operating conditions (~50 points each) were used to train six target models via FSL. Models for the unseen data reached high accuracies in all cases (rRMSE < 10%).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Hybrid Machine Learning for Scanning Near-Field Optical Spectroscopy

The underlying physics behind an experimental observation often lacks a simple analytical description. This is especially the case for scanning probe microscopy techniques, where the interaction between the probe and the sample is nontrivial. Realistic modeling to include the details of the probe is always exponentially more difficult than its "spherical cow" counterparts. On the other hand, a well-trained artificial neural network based on real data can grasp the hidden correlation between the signal and sample properties. In this work, we show that, via a combination of model calculation and experimental data acquisition, a physics-infused hybrid neural network can predict the tip-sample interaction in the widely used scattering-type scanning near-field optical microscope. This hybrid network provides a long-sought solution for accurate extraction of material properties from tip-specific raw data. The methodology can be extended to other scanning probe microscopy techniques as well as other data-oriented physical problems in general.

36 MATERIALS SCIENCE↗

'Thunder' - Shock waves in pre-biological organic synthesis.

Theoretical study of the gasdynamics and chemistry of lightning-produced shock waves in a postulated primordial reducing atmosphere. It is shown that the conditions are similar to those encountered in a previously performed shock-tube experiment which resulted in 36% of the ammonia in the original mixture being converted into amino acids. The calculations give the (very large) energy rate of about 0.4 cal/sq cm/yr available for amino acid production, supporting previous hypotheses that 'thunder' could have been responsible for efficient large-scale production of organic molecules serving as precursors of life.

Bar-Nun, A.↗

Rate constant for the reaction NH2 + NO from 216 to 480 K

The absolute rate constant was measured by the technique of flash photolysis-laser induced fluorescence (FP-LIF). NH2 radicals were produced by the flash photolysis of ammonia and the fluorescent NH2 photons were measured by multiscaling techniques. At each temperature, the results were independent of variations in total pressure, and flash intensity. The results are compared with previous determinations using the techniques of mass spectrometry, absorption spectroscopy, laser absorption spectroscopy, and laser induced fluorescence. The implications of the results are discussed with regard to combustion, post combustion, and atmospheric chemistry. The results are also discussed theoretically.

Stief, L. J.↗

Theoretical research program to predict the properties of molecules and clusters containing transition metal atoms

The primary focus of this research has been the theoretical study of transition metal (TM) chemistry. A major goal of this work is to provide reliable information about the interaction of H atoms with iron metal. This information is needed to understand the effect of H atoms on the processes of embrittlement and crack propagation in iron. The method in the iron hydrogen studies is the cluster method in which the bulk metal is modelled by a finite number of iron atoms. There are several difficulties in the application of this approach to the hydrogen iron system. First the nature of TM-TM and TM-H bonding for even diatomic molecules was not well understood when these studies were started. Secondly relatively large iron clusters are needed to provide reasonable results.

Walch, S.↗

Review of solar fuel-producing quantum conversion processes

The status and potential of fuel-producing solar photochemical processes are discussed. Research focused on splitting water to produce dihydrogen and is at a relatively early stage of development. Current emphasis is primarily directed toward understanding the basic chemistry underlying such quantum conversion processes. Theoretical analyses by various investigators predict a limiting thermodynamic efficiency of 31% for devices with a single photosystem operating with unfocused sunlight at 300 K. When non-idealities are included, it appears unlikely that actual devices will have efficiencies greater than 12 to 15%. Observed efficiencies are well below theoretical limits. Cyclic homogeneous photochemical processes for splitting water have efficiencies considerably less than 1%. Efficiency can be significantly increased by addition of a sacrificial reagent; however, such systems are no longer cyclic and it is doubtful that they would be economical on a commercial scale. The observed efficiencies for photoelectrochemical processes are also low but such systems appear more promising than homogeneous photochemical systems. Operating and systems options, including operation at elevated temperature and hybrid and coupled quantum-thermal conversion processes, are also considered.

Peterson, D. B.↗