Quantum nature of the hydrogen bond

Application of Recurrence Plot Analysis to Examine Dynamics of Biological Molecules on the Example of Aggregation of Seed Mucilage Components

The goal of the research is to describe the aggregation process inside the mucilage produced by plant seeds using molecular dynamics (MD) combined with time series algorithmic analysis based on the recurrence plots. The studied biological molecules model is seed mucilage composed of three main polysaccharides, i.e. pectins, hemicellulose, and cellulose. The modeling of biological molecules is based on the assumption that a classical-quantum passage underlies the aggregation process in the mucilage, resulting from non-covalent interactions, as they affect the macroscopic properties of the system. The applied recurrence plot approach is an important tool for time series analysis and data mining dedicated to analyzing time series data originating from complex, chaotic systems. In the current research, we demonstrated that advanced algorithmic analysis of seed mucilage data can reveal some features of the dynamics of the system, namely temperature-dependent regions with different dynamics of increments of a number of hydrogen bonds and regions of stable oscillation of increments of a number of hydrophobic-polar interactions. Henceforth, we pave the path for automatic data-mining methods for the analysis of biological molecules with the intermediate step of the application of recurrence plot analysis, as the generalization of recurrence plot applications to other (biological molecules) datasets is straightforward.

Modulation of Al Distribution in High-Silica ZSM-5 Zeolites for Enhancing Catalytic Performance

The spatial distribution of framework Al (AlF) has been one of the important factors that affect the catalytic properties of zeolites in diverse chemical reactions; however, the synthesis of high-silica zeolites with special AlF distribution remains a challenge. In this study, we successfully synthesized high-silica ZSM-5 zeolites with a unique AlF distribution by employing pentaerythritol (PET) as an additive in the presence of a few tetrapropylammonium hydroxide (TPAOH). The results demonstrated that the introduction of PET led to a higher proportion of Al atoms located at the sinusoidal and/or straight channels. It was observed that the addition of PET prevented the interaction between TPA+ and tetrahedral [AlO4]- during the crystallization process, resulting in enhanced availability of TPA species in the form of ion-paired TPA+. This effect leads to AlF atoms dominantly distributed away from the intersection and located in narrow channels, where acidic sites more effectively inhibit hydrogen transfer and coke formation. In the reaction of dimethyl ether (DME) to olefins, the catalyst with a unique Al distribution exhibited a significant prolonged catalytic lifetime, surpassing traditional TPA-ZSM-5 by more than 2-fold and maintaining DME conversion above 90% for a maximum of 148 h. The results of multiple pulse experiments also showed that these PET-assisted ZSM-5 zeolites significantly enhanced the selectivity of propene and butene. This approach provides an effective strategy to regulate AlF distribution in high-silica ZSM-5 catalysts with the assistance of neutral alcohol. It holds great potential for application in the synthesis of other high-silica zeolites, thereby enriching the diversity of zeolite catalysis.

Location of the Shared Proton in Proton-Bound Dimer Compound of Hydrogen Sulfate and Formate: Path Integral Molecular Dynamics Study

The structure of the proton-bound dimer compound of hydrogen sulfate and formate has been studied by considering nuclear quantum effects (NQEs) using the path integral molecular dynamics method. This study unveiled the location of the shared proton and answered the following question: "Is the shared proton localized on either an anion or located around the center of two anions?" We have elucidated that the shared proton is distributed in the region beyond the transition state due to the NQEs, even though the shared proton did not completely overcome the transition state for the proton shuttle.

Spectroscopic and Theoretical Identifications of Two Structural Motifs of (H2O)10 Cluster

Precise characterization of archetypal systems of aqueous hydrogen-bonding networks is essential for developing accurate potential functions and universal models of water. The structures of water clusters (H2O)n (n = 2-9) have been verified recently through size-specific infrared spectroscopy with a vacuum ultraviolet free electron laser (VUV-FEL) and quantum chemical studies. For (H2O)10, the pentagonal prism and butterfly motifs were proposed to be important building blocks and were observed in previous experiments. Here we report the size-specific infrared spectra of (H2O)10 via a joint experimental and theoretical study. Well-resolved spectra provide a unique signature for the coexistence of pentagonal prism and butterfly motifs. These (H2O)10 motifs develop from the dominant structures of (H2O)n (n = 8, 9) clusters. This work provides an intriguing prelude to the diverse structure of liquid water and opens avenues for size-dependent measurement of larger systems to understand the stepwise formation mechanism of hydrogen-bonding networks.

Nuclear Quantum Effects Accelerate Charge Recombination but Boost the Stability of Inorganic Perovskites in Mild Humidity

Experiments have demonstrated that mild humidity can enhance the stability of the CsPbBr3 perovskite, though the underlying mechanism remains unclear. Utilizing ab initio molecular dynamics, ring polymer molecular dynamics, and non-adiabatic molecular dynamics, our study reveals that nuclear quantum effects (NQEs) play a crucial role in stabilizing the lattice rigidity of the perovskite while simultaneously shortening the charge carrier lifetime. NQEs reduce the extent of geometric disorder and the number of atomic fluctuations, diminish the extent of hole localization, and thereby improve the electron-hole overlap and non-adiabatic coupling. Concurrently, these effects significantly suppress phonon modes and slow decoherence. As a result, these factors collectively accelerate charge recombination by a factor of 1.42 compared to that in scenarios excluding NQEs. The resulting sub-10 ns recombination time scales align remarkably well with experimental findings. This research offers novel insight into how moisture resistance impacts the stability and charge carrier lifetime in all-inorganic perovskites.

Nuclear Quantum Effects in Hydroxide Hydrate Along the H-Bond Bifurcation Pathway

Path integral (PI) simulations are used to explore nuclear quantum effects (NQEs) in hydroxide hydrate and its perdeuterated isotopomer along the H-bond bifurcation pathway. Toward this, a new potential energy surface using the symmetric gradient domain machine learning method with ab initio data at the CCSD(T)/aug-cc-pVTZ level is built. From PI umbrella sampling (US) simulations, free energy profiles along the bifurcation coordinate are explored as a function of temperature. At ambient temperature, the bifurcation barrier is increased upon inclusion of NQEs. At low temperatures in the deep tunneling regime, the barrier is strongly decreased and flattened. These trends are examined, and the role of the O-O distance is also investigated through two-dimensional US simulations.

The energy landscape of the ribosome

The ribosome is a prototypical assembly that can be used to establish general principles and techniques for the study of biological molecular machines. Motivated by the fact that the dynamics of every biomolecule is governed by an underlying energy landscape, there has been great interest to understand and quantify ribosome energetics. In the present review, we will focus on theoretical and computational strategies for probing the interactions that shape the energy landscape of the ribosome, with an emphasis on more recent studies of the elongation cycle. These efforts include the application of quantum mechanical methods for describing chemical kinetics, as well as classical descriptions to characterize slower (microsecond to millisecond) large-scale (10-100 Å) rearrangements, where motion is described in terms of diffusion across an energy landscape. Together, these studies provide broad insights into the factors that control a diverse range of dynamical processes in this assembly.

Nuclear quantum effects in gas-phase 2-fluoroethanol

Torsional motions along the FCCO and HOCC dihedrals lead to the five unique conformations of 2-fluoroethanol, of which the conformer that is gauche along both dihedrals has the lowest energy. In this work, we explore how nuclear quantum effects (NQEs) manifest in the structural parameters of the lowest energy conformer, in the intramolecular free energy landscape along the FCCO and HOCC dihedrals, and also in the infrared spectrum of the title molecule, through the use of path integral simulations. We have first developed a full dimensional potential energy surface using the reaction surface Hamiltonian framework. On this potential, we have carried out path integral molecular dynamics simulations at several temperatures starting from the minimum energy well to explore structural influences of NQEs including geometrical markers of the interaction between the OH and F groups. From the computed free energy landscapes, significant reduction of the torsional barrier is found at low temperature near the cis region of the dihedrals, which can be understood through the trends in the radii of gyration of the atomic ring polymers. We find that the inclusion of NQEs in the computation of infrared spectrum is important to obtain good agreement with the experimental band positions.

Prediction and Control in DNA Nanotechnology

DNA nanotechnology is a rapidly developing field that uses DNA as a building material for nanoscale structures. Key to the field's development has been the ability to accurately describe the behavior of DNA nanostructures using simulations and other modeling techniques. In this Review, we present various aspects of prediction and control in DNA nanotechnology, including the various scales of molecular simulation, statistical mechanics, kinetic modeling, continuum mechanics, and other prediction methods. We also address the current uses of artificial intelligence and machine learning in DNA nanotechnology. We discuss how experiments and modeling are synergistically combined to provide control over device behavior, allowing scientists to design molecular structures and dynamic devices with confidence that they will function as intended. Finally, we identify processes and scenarios where DNA nanotechnology lacks sufficient prediction ability and suggest possible solutions to these weak areas.

Origin of dielectric polarization suppression in confined water from first principles

It has long been known that the dielectric constant of confined water should be different from that in bulk. Recent experiments have shown that it is vanishingly small, however the origin of the phenomenon remains unclear. Here we used ab initio molecular dynamics simulations (AIMD) and AIMD-trained machine-learning potentials to understand water's structure and electronic properties underpinning this effect. For the graphene and hexagonal boron-nitride substrates considered, we find that it originates in the spontaneous anti-parallel alignment of the water dipoles in the first two water layers near the solid interface. The interfacial layers exhibit net ferroelectric ordering, resulting in an overall anti-ferroelectric arrangement of confined water. Together with constrained hydrogen-bonding orientations, this leads to much reduced out-of-plane polarization. Furthermore, we directly contrast AIMD and simple classical force-field simulations, revealing important differences. This work offers insight into a property of water that is critical in modulating surface forces, the electric-double-layer formation and molecular solvation, and shows a way to compute it.

Evolution of Consciousness

The natural evolution of consciousness in different animal species mandates that conscious experiences are causally potent in order to confer any advantage in the struggle for survival. Any endeavor to construct a physical theory of consciousness based on emergence within the framework of classical physics, however, leads to causally impotent conscious experiences in direct contradiction to evolutionary theory since epiphenomenal consciousness cannot evolve through natural selection. Here, we review recent theoretical advances in describing sentience and free will as fundamental aspects of reality granted by quantum physical laws. Modern quantum information theory considers quantum states as a physical resource that endows quantum systems with the capacity to perform physical tasks that are classically impossible. Reductive identification of conscious experiences with the quantum information comprised in quantum brain states allows for causally potent consciousness that is capable of performing genuine choices for future courses of physical action. The consequent evolution of brain cortical networks contributes to increased computational power, memory capacity, and cognitive intelligence of the living organisms.

Force-field-enhanced neural network interactions: from local equivariant embedding to atom-in-molecule properties and long-range effects

We introduce FENNIX (Force-Field-Enhanced Neural Network InteraXions), a hybrid approach between machine-learning and force-fields. We leverage state-of-the-art equivariant neural networks to predict local energy contributions and multiple atom-in-molecule properties that are then used as geometry-dependent parameters for physically-motivated energy terms which account for long-range electrostatics and dispersion. Using high-accuracy ab initio data (small organic molecules/dimers), we trained a first version of the model. Exhibiting accurate gas-phase energy predictions, FENNIX is transferable to the condensed phase. It is able to produce stable Molecular Dynamics simulations, including nuclear quantum effects, for water predicting accurate liquid properties. The extrapolating power of the hybrid physically-driven machine learning FENNIX approach is exemplified by computing: (i) the solvated alanine dipeptide free energy landscape; (ii) the reactive dissociation of small molecules.

Structure and anomalous underscreening in ethylammonium nitrate solutions confined between two mica surfaces

The observation of long-range interactions across ionic liquids and highly concentrated electrolytes, extending far beyond the Debye-Hückel prediction and beyond the range predicted in liquid state theory, has been called 'anomalous underscreening'. A number of theoretical and experimental works have explored this phenomenon over recent years, although its origin is not yet fully understood. Most of the experimental studies of anomalous underscreening until now involved aprotic ionic liquids, and so it is of interest to explore interactions in protic ionic liquids where the distribution of charge in the fluid is different in nature. Here we present direct measurements of the interaction force as a function of separation distance, measured using a surface force balance, across solutions of a protic ionic liquid ethylammonium nitrate (EAN) and its mixtures with water over a range of volume fractions from 10 vol% to 100 vol% EAN. The results reveal intricate details about near-surface ordering and dynamics at the EAN-mica interface as well as anomalous underscreening consistent with that observed in the past with aprotic ionic liquids.

Selective reactivity of glycosyl cation stereoisomers: the role of intramolecular hydrogen bonding

The impact of the stereochemistry of the glycosyl cation species upon its dynamic properties is examined together with their vibrational spectra in order to gain insight into the effects of configurational isomerism on conformer dynamics and proton mobility. Ab initio molecular dynamics (AIMD) simulations and infrared multiple photon dissociation (IRMPD) spectroscopy explore the conformational and reactive dynamics of two pairs of glycosyl cation isomers: (1) protonated α- and β- anomers of methyl-D-galactopyranoside and (2) the oxocarbenium ions of the D-aldohexose C2 epimers galactose and talose. Analysis of these simulations together with experimental spectroscopy, interpreted by anharmonic calculations, points to the key role played by the intramolecular hydrogen bonds which are present in a unique pattern and extent in each isomer. We find that the reactivity of galactoside stereoisomers toward acid-catalyzed nucleophilic substitution, as gauged by the ability to form free oxocarbenium ions, differs markedly in a way that agrees with experimental measurements in the condensed phase. Other properties such as conformer stability and vibrational transitions were also found to reflect the characteristic hydrogen bonding interactions present in each isomer. In both systems, the stereochemistry is shown to determine the strength of intramolecular hydrogen bonding as well as between which substituents proton transfer is possible. We expect that the critical impact of non-covalent interactions on stereoisomer selectivity may be a widely found phenomenon whose effects should be further investigated.

Locking water molecules via ternary O-H⋯O intramolecular hydrogen bonds in perhydroxylated closo-dodecaborate

A multitude of applications related to perhydroxylated closo-dodecaborate B12(OH)122- in the condensed phase are inseparable from the fundamental mechanisms underlying the high water orientation selectivity based on the base B12(OH)122-. Herein, we directly compare the structural evolution of water clusters, ranging from monomer to hexamer, oriented by functional groups in the bases B12H122-, B12H11OH2- and B12(OH)122- using multiple theoretical methods. A significant revelation is made regarding B12(OH)122-: each additional water molecule is locked into the intramolecular hydrogen bond B-O-H ternary ring in an embedded form. This new pattern of water cluster growth suggests that B-(H-O)⋯H-O interactions prevail over the competition from water-hydrogen bonds (O⋯H-O), distinguishing it from the behavior observed in B12H122- and B12H11OH2- bases, in which competition arises from a mixed competing model involving dihydrogen bonds (B-H⋯H-O), conventional hydrogen bonds (B-(H-O)⋯H-O) and water hydrogen bonds (O⋯H-O). Through aqueous solvation and ab initio molecular dynamics analysis, we further demonstrate the largest water clusters in the first hydrated shell with exceptional thermodynamic stability around B12(OH)122-. These findings provide a solid scientific foundation for the design of boron cluster chemistry incorporating hydroxyl-group-modified borate salts with potential implications for various applications.

When Quantum Fluctuations Meet Structural Instabilities: The Isotope- and Pressure-Induced Phase Transition in the Quantum Paraelectric NaOH

Anhydrous sodium hydroxide, a common and structurally simple compound, shows spectacular isotope effects: NaOD undergoes a first-order transition, which is absent in NaOH. By combining ab initio electronic structure calculations with Feynman path integrals, we show that NaOH is an unusual example of a quantum paraelectric: zero-point quantum fluctuations stretch the weak hydrogen bonds (HBs) into a region where they are unstable and break. By strengthening the HBs via isotope substitution or applied pressure, the system can be driven to a broken-symmetry antiferroelectric phase. In passing, we provide a simple quantitative criterion for HB breaking in layered crystals and show that nuclear quantum effects are crucial in paraelectric to ferroelectric transitions in hydrogen-bonded hydroxides.

Chemical features and machine learning assisted predictions of protein-ligand short hydrogen bonds

There are continuous efforts to elucidate the structure and biological functions of short hydrogen bonds (SHBs), whose donor and acceptor heteroatoms reside more than 0.3 Å closer than the sum of their van der Waals radii. In this work, we evaluate 1070 atomic-resolution protein structures and characterize the common chemical features of SHBs formed between the side chains of amino acids and small molecule ligands. We then develop a machine learning assisted prediction of protein-ligand SHBs (MAPSHB-Ligand) model and reveal that the types of amino acids and ligand functional groups as well as the sequence of neighboring residues are essential factors that determine the class of protein-ligand hydrogen bonds. The MAPSHB-Ligand model and its implementation on our web server enable the effective identification of protein-ligand SHBs in proteins, which will facilitate the design of biomolecules and ligands that exploit these close contacts for enhanced functions.

Characterization of the Hydrogen-Bond Network in High-Pressure Water by Deep Potential Molecular Dynamics

The hydrogen-bond (H-bond) network of high-pressure water is investigated by neural-network-based molecular dynamics (MD) simulations with first-principles accuracy. The static structure factors (SSFs) of water at three densities, i.e., 1, 1.115, and 1.24 g/cm3, are directly evaluated from 512 water MD trajectories, which are in quantitative agreement with the experiments. We propose a new method to decompose the computed SSF and identify the changes in the SSF with respect to the changes in H-bond structures. We find that a larger water density results in a higher probability for one or two non-H-bonded water molecules to be inserted into the inner shell, explaining the changes in the tetrahedrality of water under pressure. We predict that the structure of the accepting end of water molecules is more easily influenced by the pressure than by the donating end. Our work sheds new light on explaining the SSF and H-bond properties in related fields.

Developing machine-learned potentials to simultaneously capture the dynamics of excess protons and hydroxide ions in classical and path integral simulations

The transport of excess protons and hydroxide ions in water underlies numerous important chemical and biological processes. Accurately simulating the associated transport mechanisms ideally requires utilizing ab initio molecular dynamics simulations to model the bond breaking and formation involved in proton transfer and path-integral simulations to model the nuclear quantum effects relevant to light hydrogen atoms. These requirements result in a prohibitive computational cost, especially at the time and length scales needed to converge proton transport properties. Here, we present machine-learned potentials (MLPs) that can model both excess protons and hydroxide ions at the generalized gradient approximation and hybrid density functional theory levels of accuracy and use them to perform multiple nanoseconds of both classical and path-integral proton defect simulations at a fraction of the cost of the corresponding ab initio simulations. We show that the MLPs are able to reproduce ab initio trends and converge properties such as the diffusion coefficients of both excess protons and hydroxide ions. We use our multi-nanosecond simulations, which allow us to monitor large numbers of proton transfer events, to analyze the role of hypercoordination in the transport mechanism of the hydroxide ion and provide further evidence for the asymmetry in diffusion between excess protons and hydroxide ions.

Quantum Dynamical Investigation of Dihydrogen-Hydride Exchange in a Transition-Metal Polyhydride Complex

The ongoing shift toward clean, sustainable energy is a primary driving force behind hydrogen fuel research. Safe and effective storage of hydrogen is a major challenge (particularly for mobile applications) and requires a detailed understanding of the atomic level interactions of hydrogen with its host materials. The light mass of hydrogen, however, implies that quantum effects are important, so a quantum dynamical treatment is required to properly account for these effects in computational simulations. As one such example, we describe herein the hydrogen exchange dynamics between a hydride and a dihydrogen ligand in the [FeH(H2)(PH3)4]+ model complex. A global three-dimensional (3D) potential energy surface (PES) was constructed by fitting to and interpolating from a discrete set of grid points computed using density functional theory; exact quantum dynamical calculations were then carried out on the 3D PES using discrete variable representation basis sets. Energy levels and their quantum tunneling splittings were computed up to 3000 cm-1 above the ground state. Within that energy range, all three fundamentals have been identified using wave function plots, as well as the first three overtones of the exchange (reaction coordinate) motion and several of its combination bands. From the tunneling splittings, the Boltzmann-averaged tunneling rates were computed. The Arrhenius plot of the total exchange rate shows a clear transition around 150 K, below which the activation energy is essentially zero and above which it is less than half of the electronic structure barrier. This indicates that exchange rates are governed by quantum tunneling throughout the relevant temperature range with the low-temperature regime dominated by a single quantum (ground) state. This work is the first-ever fully quantum dynamical study to investigate the hydrogen exchange dynamics between hydride and dihydrogen ligands coordinated to a transition-metal complex.

Polyether phases of formic acid revealed under high pressure

Evolutionary structure searches reveal that at 20 GPa, formic acid (FA) transforms to an orthorhombic ether-chain polymer phase, ruling out hydrogen bond symmetrization, followed by a novel crowned cyclic-ether tetragonal phase above 60 GPa. Emergence of characteristic polyether and new OH stretching modes in infrared experiments validate the findings. Resemblance of polymer chain with a cosmopolymer polyoxymethylene, shows an engrossing multifaceted evolution of FA.

Constrained Nuclear-Electronic Orbital Density Functional Theory with a Dielectric Continuum Solvent Model

Solvent effects are crucial for simulating chemical and biological processes in solutions. The continuum solvation model is widely used for incorporating solvent effects with different levels of theoretical descriptions of solutes. For solutes and solutions containing hydrogen atoms, nuclear quantum effects can also be nonnegligible for reliable simulations. In this work, we couple our recently developed constrained nuclear-electronic orbital density functional theory with a dielectric continuum solvation model to cover nuclear quantum effects and solvent effects simultaneously. This approach is applied to the formate ion, where an anomalous solvatochromic shift in C-H stretch frequency was reported in experiments. By using this new approach to account for nuclear quantum effects and solvent effects, we show that the vibrational frequency of the C-H stretch and the solvatochromic shift are accurately described.

Nuclear-Electronic Orbital QM/MM Approach: Geometry Optimizations and Molecular Dynamics

Hybrid quantum mechanical/molecular mechanical (QM/MM) methods allow simulations of chemical reactions in atomistic solvent and heterogeneous environments such as proteins. Herein, the nuclear-electronic orbital (NEO) QM/MM approach is introduced to enable the quantization of specified nuclei, typically protons, in the QM region using a method such as NEO-density functional theory (NEO-DFT). This approach includes proton delocalization, polarization, anharmonicity, and zero-point energy in geometry optimizations and dynamics. Expressions for the energies and analytical gradients associated with the NEO-QM/MM method, as well as the previously developed polarizable continuum model (NEO-PCM), are provided. Geometry optimizations of small organic molecules hydrogen bonded to water in either dielectric continuum solvent or explicit atomistic solvent illustrate that aqueous solvation can strengthen hydrogen-bonding interactions for the systems studied, as indicated by shorter intermolecular distances at the hydrogen-bond interface. We then performed a real-time direct dynamics simulation of a phenol molecule in explicit water using the NEO-QM/MM method. These developments and initial examples provide the foundation for future studies of nuclear-electronic quantum dynamics in complex chemical and biological environments.

Accurate calculation of tunneling splittings in water clusters using path-integral based methods

Tunneling splittings observed in molecular rovibrational spectra are significant evidence for tunneling motion of hydrogen nuclei in water clusters. Accurate calculations of the splitting sizes from first principles require a combination of high-quality inter-atomic interactions and rigorous methods to treat the nuclei with quantum mechanics. Many theoretical efforts have been made in recent decades. This Perspective focuses on two path-integral based tunneling splitting methods whose computational cost scales well with the system size, namely, the ring-polymer instanton method and the path-integral molecular dynamics (PIMD) method. From a simple derivation, we show that the former is a semiclassical approximation to the latter, despite that the two methods are derived very differently. Currently, the PIMD method is considered to be an ideal route to rigorously compute the ground-state tunneling splitting, while the instanton method sacrifices some accuracy for a significantly smaller computational cost. An application scenario of such a quantitatively rigorous calculation is to test and calibrate the potential energy surfaces of molecular systems by spectroscopic accuracy. Recent progress in water clusters is reviewed, and the current challenges are discussed.

Realistic phase diagram of water from "first principles" data-driven quantum simulations

Since the experimental characterization of the low-pressure region of water's phase diagram in the early 1900s, scientists have been on a quest to understand the thermodynamic stability of ice polymorphs on the molecular level. In this study, we demonstrate that combining the MB-pol data-driven many-body potential for water, which was rigorously derived from "first principles" and exhibits chemical accuracy, with advanced enhanced-sampling algorithms, which correctly describe the quantum nature of molecular motion and thermodynamic equilibria, enables computer simulations of water's phase diagram with an unprecedented level of realism. Besides providing fundamental insights into how enthalpic, entropic, and nuclear quantum effects shape the free-energy landscape of water, we demonstrate that recent progress in "first principles" data-driven simulations, which rigorously encode many-body molecular interactions, has opened the door to realistic computational studies of complex molecular systems, bridging the gap between experiments and simulations.

Routine Molecular Dynamics Simulations Including Nuclear Quantum Effects: From Force Fields to Machine Learning Potentials

We report the implementation of a multi-CPU and multi-GPU massively parallel platform dedicated to the explicit inclusion of nuclear quantum effects (NQEs) in the Tinker-HP molecular dynamics (MD) package. The platform, denoted Quantum-HP, exploits two simulation strategies: the Ring-Polymer Molecular Dynamics (RPMD) that provides exact structural properties at the cost of a MD simulation in an extended space of multiple replicas and the adaptive Quantum Thermal Bath (adQTB) that imposes the quantum distribution of energy on a classical system via a generalized Langevin thermostat and provides computationally affordable and accurate (though approximate) NQEs. We discuss some implementation details, efficient numerical schemes, and parallelization strategies and quickly review the GPU acceleration of our code. Our implementation allows an efficient inclusion of NQEs in MD simulations for very large systems, as demonstrated by scaling tests on water boxes with more than 200,000 atoms (simulated using the AMOEBA polarizable force field). We test the compatibility of the approach with Tinker-HP's recently introduced Deep-HP machine learning potentials module by computing water properties using the DeePMD potential with adQTB thermostatting. Finally, we show that the platform is also compatible with the alchemical free energy estimation capabilities of Tinker-HP and fast enough to perform simulations. Therefore, we study how NQEs affect the hydration free energy of small molecules solvated with the recently developed Q-AMOEBA water force field. Overall, the Quantum-HP platform allows users to perform routine quantum MD simulations of large condensed-phase systems and will help to shed new light on the quantum nature of important interactions in biological matter.

Collective Proton Transfers in Cyclic Water-Ammonia Tetramers: A Path Integral Machine-Learning Study

We present results from machine-learning-based path integral molecular dynamics simulations that describe isomerization paths articulated via collective proton transfers along mixed, cyclic tetramers combining water and ammonia at cryogenic conditions. The net result of such isomerizations is a reverse of the chirality of the global hydrogen-bonding architecture along the different cyclic moieties. In monocomponent tetramers, the classical free energy profiles associated with these isomerizations present the usual symmetric double-well characteristics whereas the reactive paths exhibit full concertedness among the different intermolecular transfer processes. Contrastingly, in mixed water/ammonia tetramers, the incorporation of a second component introduces imbalances in the strengths of the different hydrogen bonds leading to a partial loss of concertedness, most notably at the vicinity of the transition state. As such, the highest and lowest degrees of progression are registered along OH···N and O···HN coordinations, respectively. These characteristics lead to polarized transition state scenarios akin to solvent-separated ion-pair configurations. The explicit incorporation of nuclear quantum effects promotes drastic depletions in the activation free energies and modifications in the overall shape of the profiles which include central plateau-like stages, indicating the prevalence of deep tunneling regimes. On the other hand, the quantum treatment of the nuclei partially restores the degree of concertedness among the evolutions of the individual transfers.

Nuclear quantum effects on zeolite proton hopping kinetics explored with machine learning potentials and path integral molecular dynamics

Proton hopping is a key reactive process within zeolite catalysis. However, the accurate determination of its kinetics poses major challenges both for theoreticians and experimentalists. Nuclear quantum effects (NQEs) are known to influence the structure and dynamics of protons, but their rigorous inclusion through the path integral molecular dynamics (PIMD) formalism was so far beyond reach for zeolite catalyzed processes due to the excessive computational cost of evaluating all forces and energies at the Density Functional Theory (DFT) level. Herein, we overcome this limitation by training first a reactive machine learning potential (MLP) that can reproduce with high fidelity the DFT potential energy surface of proton hopping around the first Al coordination sphere in the H-CHA zeolite. The MLP offers an immense computational speedup, enabling us to derive accurate reaction kinetics beyond standard transition state theory for the proton hopping reaction. Overall, more than 0.6 μs of simulation time was needed, which is far beyond reach of any standard DFT approach. NQEs are found to significantly impact the proton hopping kinetics up to ~473 K. Moreover, PIMD simulations with deuterium can be performed without any additional training to compute kinetic isotope effects over a broad range of temperatures.

Competing Nuclear Quantum Effects and Hydrogen-Bond Jumps in Hydrated Kaolinite

Recent work has shown that the dynamics of hydrogen bonds in pure clays are affected by nuclear quantum fluctuations, with different effects for the hydrogen bonds holding different layers of the clay together and for those within the same layer. At the clay-water interface there is an even wider range of types of hydrogen bond, suggesting that the quantum effects may be yet more varied. We apply classical and thermostated ring polymer molecular dynamics simulations to show that nuclear quantum effects accelerate hydrogen-bond dynamics to varying degrees. By interpreting the results in terms of the extended jump model of hydrogen-bond switching, we can understand the origins of these effects in terms of changes in the quantum kinetic energy of hydrogen atoms during an exchange. We also show that the extended jump mechanism is applicable not only to the hydrogen bonds involving water, but also those internal to the clay.

Solvation structures of calcium and magnesium ions in water with the presence of hydroxide: a study by deep potential molecular dynamics

The solvation structures of calcium (Ca²⁺) and magnesium (Mg²⁺) ions with the presence of hydroxide (OH^-) ion in water are essential for understanding their roles in biological and chemical processes but have not been fully explored. Ab initio molecular dynamics (AIMD) is an important tool to address this issue, but two challenges exist. First, an accurate description of OH^- from AIMD needs an appropriate exchange-correlation functional. Second, a long trajectory is needed to reach an equilibrium state for the Ca²⁺-OH^- and Mg²⁺-OH^- ion pairs in aqueous solutions. Herein, we adopt a deep potential molecular dynamics (DPMD) method to simulate 1 ns trajectories for the Ca²⁺-OH^- and Mg²⁺-OH^- ion pairs in water; the DPMD method provides efficient machine-learning-based models that have the accuracy of the SCAN exchange-correlation functional within the framework of density functional theory. The solvation structures of the cations and the OH^- in terms of three different species have been systematically investigated. On the one hand, we find that OH^- have more significant effects on the solvation structure of Ca²⁺ than that of Mg²⁺. We observe that the OH^- substantially affects the orientation angles of water molecules surrounding the cation. Through the time correlation functions, we conclude that the water molecules in the first solvation shell of Ca²⁺ change their preferred orientation faster than those of Mg²⁺. On the other hand, with the presence of the cation in the first solvation shell of OH^-, we find that the hydrogen bonds of OH^- are severely altered, and the adjacent water molecules of OH^- are squeezed. The two cations have substantially different effects on the solvation structure of OH^-. Our work provides new insight into the solvation structures of Ca²⁺ and Mg²⁺ in water with the presence of OH^-.

A Tug of War between the Self- and Cross-associating Hydrogen Bonds in Neutral Ammonia-Water Clusters: Energetic Insights by Molecular Tailoring Approach

In the present work, the energies of various types of individual HBs observed in neutral (NH₃ )_m (H₂ O)_n , (m+n=2 to 7) clusters were estimated using the molecular tailoring approach (MTA)-based method. The calculated individual HB energies suggest that the O-H…N HBs are the strongest (1.21 to 12.49 kcal mol^-1 ). The next ones are the O-H…O (3.97 to 9.30 kcal mol^-1 ) HBs. The strengths of N-H…N (1.09 to 5.29 kcal mol^-1 ) and N-H…O (2.85 to 5.56 kcal mol^-1 ) HBs are the weakest. The HB energies in dimers also follow this rank ordering. However, the HB energies in dimers are much smaller than those obtained by the MTA-based method due to the loss in cooperativity contribution in the dimers. Thus, the calculated cooperativity contributions, for different types of HBs, fall in the range 0.64 to 5.73 kcal mol^-1 . We wish to emphasize based on the energetic rank ordering obtained by the MTA-based method that the O-H of water is a better HB donor than the N-H of ammonia. The reasons for the observed energetic rank ordering are two folds: (i) intrinsically stronger O-H…N HBs than the O-H…O ones as revealed by dimer energies and (ii) the higher cooperativity contribution in the former than the later ones. Indeed, the MTA-based method is useful in providing the missing energetic rank ordering of various type of HBs in neutral (NH₃ )_m (H₂ O)_n clusters, in the literature.

Improving Condensed-Phase Water Dynamics with Explicit Nuclear Quantum Effects: The Polarizable Q-AMOEBA Force Field

We introduce a new parametrization of the AMOEBA polarizable force field for water denoted Q-AMOEBA, for use in simulations that explicitly account for nuclear quantum effects (NQEs). This study is made possible thanks to the recently introduced adaptive Quantum Thermal Bath (adQTB) simulation technique which computational cost is comparable to classical molecular dynamics. The flexible Q-AMOEBA model conserves the initial AMOEBA functional form, with an intermolecular potential including an atomic multipole description of electrostatic interactions (up to quadrupole), a polarization contribution based on the Thole interaction model and a buffered 14-7 potential to model van der Waals interactions. It has been obtained by using a ForceBalance fitting strategy including high-level quantum chemistry reference energies and selected condensed-phase properties targets. The final Q-AMOEBA model is shown to accurately reproduce both gas-phase and condensed-phase properties, notably improving the original AMOEBA water model. This development allows the fine study of NQEs on water liquid phase properties such as the average H-O-H angle compared to its gas-phase equilibrium value, isotope effects, and so on. Q-AMOEBA also provides improved infrared spectroscopy prediction capabilities compared to AMOEBA03. Overall, we show that the impact of NQEs depends on the underlying model functional form and on the associated strength of hydrogen bonds. Since adQTB simulations can be performed at near classical computational cost using the Tinker-HP package, Q-AMOEBA can be extended to organic molecules, proteins, and nucleic acids opening the possibility for the large-scale study of the importance of NQEs in biophysics.

Three-Dimensional Confinement of Water: H2O Exhibits Long-Range (>50 nm) Structure while D2O Does Not

Water is the liquid of life thanks to its three-dimensional adaptive hydrogen (H)-bond network. Confinement of this network may lead to dramatic structural changes influencing chemical and physical transformations. Although confinement effects occur on a <1 nm length scale, the upper length scale limit is unknown. Here, we investigate 3D-confinement over lengths scales ranging from 58-140 nm. By confining water in zwitterionic liposomes of different sizes and measuring the change in H-bond network conformation using second harmonic scattering (SHS), we determined long-range confinement effects in light and heavy water. D₂O displays no detectable 3D-confinement effects <58 nm (<3 × 10⁶ D₂O molecules). H₂O is distinctly different. The vesicle enclosed inner H-bond network has a different conformation compared to the outside network and the SHS response scales with the volume of the confining space. H₂O displays confinement effects over distances >100 nm (>2 × 10⁷ H₂O molecules).

Non-Covalent Interaction on the Self-Healing of Mechanical Properties in Supramolecular Polymers

Supramolecular polymers are widely utilized and applied in self-assembly or self-healing materials, which can be repaired when damaged. Normally, the healing process is classified into two types, including extrinsic and intrinsic self-healable materials. Therefore, the aim of this work is to review the intrinsic self-healing strategy based on supramolecular interaction or non-covalent interaction and molecular recognition to obtain the improvement of mechanical properties. In this review, we introduce the main background of non-covalent interaction, which consists of the metal–ligand coordination, hydrogen bonding, π–π interaction, electrostatic interaction, dipole–dipole interaction, and host–guest interactions, respectively. From the perspective of mechanical properties, these interactions act as transient crosslinking points to both prevent and repair the broken polymer chains. For material utilization in terms of self-healing products, this knowledge can be applied and developed to increase the lifetime of the products, causing rapid healing and reducing accidents and maintenance costs. Therefore, the self-healing materials using supramolecular polymers or non-covalent interaction provides a novel strategy to enhance the mechanical properties of materials causing the extended cycling lifetime of products before replacement with a new one.

Structural and Dynamic Properties of Solvated Hydroxide and Hydronium Ions in Water from Ab Initio Modeling

Predicting the asymmetric structure and dynamics of solvated hydroxide and hydronium in water has been a challenging task from ab initio molecular dynamics (AIMD). The difficulty mainly comes from a lack of accurate and efficient exchange-correlation functional in elucidating the amphiphilic nature and the ubiquitous proton transfer behaviors of the two ions. By adopting the strongly-constrained and appropriately normed (SCAN) meta-GGA functional in AIMD simulations, we systematically examine the amphiphilic properties, the solvation structures, the electronic structures, and the dynamic properties of the two water ions. In particular, we compare these results to those predicted by the PBE0-TS functional, which is an accurate yet computationally more expensive exchange-correlation functional. We demonstrate that the general-purpose SCAN functional provides a reliable choice in describing the two water ions. Specifically, in the SCAN picture of water ions, the appearance of the fourth and fifth hydrogen bonds near hydroxide stabilizes the pot-like shape solvation structure and suppresses the structural diffusion, while the hydronium stably donates three hydrogen bonds to its neighbors. We apply a detailed analysis of the proton transfer mechanism of the two ions and find the two ions exhibit substantially different proton transfer patterns. Our AIMD simulations indicate hydroxide diffuses slower than hydronium in water, which is consistent with the experiments.

Ultrafast charge transfer coupled to quantum proton motion at molecule/metal oxide interface

Understanding how the nuclear quantum effects (NQEs) in the hydrogen bond (H-bond) network influence the photoexcited charge transfer at semiconductor/molecule interface is a challenging problem. By combining two kinds of emerging molecular dynamics methods at the ab initio level, the path integral-based molecular dynamics and time-dependent nonadiabatic molecular dynamics, and choosing CH₃OH/TiO₂ as a prototypical system to study, we find that the quantum proton motion in the H-bond network is strongly coupled with the ultrafast photoexcited charge dynamics at the interface. The hole trapping ability of the adsorbed methanol molecule is notably enhanced by the NQEs, and thus, it behaves as a hole scavenger on titanium dioxide. The critical role of the H-bond network is confirmed by in situ scanning tunneling microscope measurements with ultraviolet light illumination. It is concluded the quantum proton motion in the H-bond network plays a critical role in influencing the energy conversion efficiency based on photoexcitation.

Submolecular Insights into Interfacial Water by Hydrogen-Sensitive Scanning Probe Microscopy

ConspectusWater-solid interfaces have attracted extensive attention because of their crucial roles in a wide range of chemical and physical processes, such as ice nucleation and growth, dissolution, corrosion, heterogeneous catalysis, and electrochemistry. To understand these processes, enormous efforts have been made to obtain a molecular-level understanding of the structure and dynamics of water on various solid surfaces. By the use of scanning probe microscopy (SPM), many remarkable structures of H-bonding networks have been directly visualized, significantly advancing our understanding of the delicate competition between water-water and water-solid interactions. Moreover, the detailed dynamics of water molecules, such as diffusion, clustering, dissociation, and intermolecular and intramolecular proton transfer, have been investigated in a well-controlled manner by tip manipulation. However, resolving the submolecular structure of surface water has remained a great challenge for a long time because of the small size and light mass of protons. Discerning the position of hydrogen in water is not only crucial for the accurate determination of the structure of H-bonding networks but also indispensable in probing the proton transfer dynamics and the quantum nature of protons.In this Account, we focus on the recent advances in the H-sensitive SPM technique and its applications in probing the structures, dynamics, and nuclear quantum effects (NQEs) of surface water and ion hydrates at the submolecular level. First, we introduce the development of high-resolution scanning tunneling microscopy/spectroscopy (STM/S) and qPlus-based atomic force microscopy (qPlus-AFM), which allow access to the degrees of freedom of protons in both real and energy space. qPlus-AFM even allows imaging of interfacial water in a weakly perturbative manner by measuring the high-order electrostatic force between the CO-terminated tip and the polar water molecule, which enables the subtle difference of OH directionality to be discerned. Next we showcase the applications of H-sensitive STM/AFM in addressing several key issues related to water-solid interfaces. The surface wetting behavior and the H-bonding structure of low-dimensional ice on various hydrophilic and hydrophobic solid surfaces are characterized at the atomic scale. Then we discuss the quantitative assessment of NQEs of surface water, including proton tunneling and quantum delocalization. Moreover, the weakly perturbative and H-sensitive SPM technique can be also extended to investigations of water-ion interactions on solid surfaces, revealing the effect of hydration structure on the interfacial ion transport. Finally, we provide an outlook on the further directions and challenges for SPM studies of water-solid interfaces.

Energetic Ordering of Hydrogen Bond Strengths in Methanol-Water Clusters: Insights via Molecular Tailoring Approach

In this work, we examine the strength of various types of individual hydrogen bond (HB) in mixed methanol-water M_n W_m , (n+m=2 to 7) clusters, with an aim to understand the relative order of their strength, using our recently proposed molecular tailoring-based approach (MTA). Among all the types of HB, it is observed that the O_M -H…O_W HBs are the strongest (6.9 to 12.4 kcal mol^-1 ). The next ones are O_M -H…O_M HBs (6.5 to 11.6 kcal mol^-1 ). The O_W -H…O_W (0.2 to 10.9 kcal mol^-1 ) and O_W -H…O_M HBs (0.3 to 10.3 kcal mol^-1 ) are the weakest ones. This energetic ordering of HBs is seen to be different from the respective HB energies in the dimer i. e., O_M -H…O_M (5.0 to 6.0 kcal mol^-1 )>O_W -H…O_M (1.5 to 6.0 kcal mol^-1 )>O_M -H…O_W (3.8 to 5.6 kcal mol^-1 )>O_W -H…O_W (1.2 to 5.0 kcal mol^-1 ). The plausible reason for the difference in the HB energy ordering may be attributed to the increase or decrease in HB strengths due to the formation of cooperative or anti-cooperative HB networks. For instance, the cooperativity contribution towards the different types of HB follows: O_M -H…O_W (2.4 to 8.6 kcal mol^-1 )>O_M -H…O_M (1.3 to 6.3 kcal mol^-1 )>O_W -H…O_W (-1.0 to 6.5 kcal mol^-1 )>O_W -H…O_M (-1.2 to 5.3 kcal mol^-1 ). This ordering of cooperativity contribution is similar to the HB energy ordering obtained by the MTA-based method. It is emphasized here that, the interplay between the cooperative and anti-cooperative contributions are indispensable for the correct energetic ordering of these HBs.

A 300-fold conductivity increase in microbial cytochrome nanowires due to temperature-induced restructuring of hydrogen bonding networks

Although proteins are considered as nonconductors that transfer electrons only up to 1 to 2 nanometers via tunneling, Geobacter sulfurreducens transports respiratory electrons over micrometers, to insoluble acceptors or syntrophic partner cells, via nanowires composed of polymerized cytochrome OmcS. However, the mechanism enabling this long-range conduction is unclear. Here, we demonstrate that individual nanowires exhibit theoretically predicted hopping conductance, at rate (>10¹⁰ s^-1) comparable to synthetic molecular wires, with negligible carrier loss over micrometers. Unexpectedly, nanowires show a 300-fold increase in their intrinsic conductance upon cooling, which vanishes upon deuteration. Computations show that cooling causes a massive rearrangement of hydrogen bonding networks in nanowires. Cooling makes hemes more planar, as revealed by Raman spectroscopy and simulations, and lowers their reduction potential. We find that the protein surrounding the hemes acts as a temperature-sensitive switch that controls charge transport by sensing environmental perturbations. Rational engineering of heme environments could enable systematic tuning of extracellular respiration.

Simulation of Nuclear Quantum Effects in Condensed Matter Systems via Quantum Baths

This paper reviews methods that aim at simulating nuclear quantum effects (NQEs) using generalized thermal baths. Generalized (or quantum) baths simulate statistical quantum features, and in particular zero-point energy effects, through non-Markovian stochastic dynamics. They make use of generalized Langevin Equations (GLEs), in which the quantum Bose–Einstein energy distribution is enforced by tuning the random and friction forces, while the system degrees of freedom remain classical. Although these baths have been formally justified only for harmonic oscillators, they perform well for several systems, while keeping the cost of the simulations comparable to the classical ones. We review the formal properties and main characteristics of classical and quantum GLEs, in relation with the fluctuation–dissipation theorems. Then, we describe the quantum thermostat and quantum thermal bath, the two generalized baths currently most used, providing several examples of applications for condensed matter systems, including the calculation of vibrational spectra. The most important drawback of these methods, zero-point energy leakage, is discussed in detail with the help of model systems, and a recently proposed scheme to monitor and mitigate or eliminate it—the adaptive quantum thermal bath—is summarised. This approach considerably extends the domain of application of generalized baths, leading, for instance, to the successful simulation of liquid water, where a subtle interplay of NQEs is at play. The paper concludes by overviewing further development opportunities and open challenges of generalized baths.

Importance of Nuclear Quantum Effects for Molecular Cocrystals with Short Hydrogen Bonds

Many efforts have been recently devoted to the design and investigation of multicomponent pharmaceutical solids, such as salts and cocrystals. The experimental distinction between these solid forms is often challenging. Here, we show that the transformation of a salt into a cocrystal with a short hydrogen bond does not occur as a sharp phase transition but rather a smooth shift of the positional probability of the hydrogen atoms. A combination of solid-state NMR spectroscopy, X-ray diffraction, and diffuse reflectance measurements with density functional theory calculations that include nuclear quantum effects (NQEs) provides evidence of temperature-induced hydrogen atom shift in cocrystals with short hydrogen bonds. We demonstrate that for the predictions of the salt/cocrystal solid forms with short H-bonds, the computations have to include NQEs (particularly hydrogen nuclei delocalization) and temperature effects.

Observing Mesoscopic Nucleic Acid Capacitance Effect and Mismatch Impact via Graphene Transistors

This work reports a molecular-scale capacitance effect of the double helical nucleic acid duplex structure for the first time. By quantitatively conducting large sample measurements of the electrostatic field effect using a type of high-accuracy graphene transistor biosensor, an unusual charge-transport behavior is observed in which the end-immobilized nucleic acid duplexes can store a part of ionization electrons like molecular capacitors, other than electric conductors. To elucidate this discovery, a cascaded capacitive network model is proposed as a novel equivalent circuit of nucleic acid duplexes, expanding the point-charge approximation model, by which the partial charge-transport observation is reasonably attributed to an electron-redistribution behavior within the capacitive network. Furthermore, it is experimentally confirmed that base-pair mismatches hinder the charge transport in double helical duplexes, and lead to directly identifiable alterations in electrostatic field effects. The bioelectronic principle of mismatch impact is also self-consistently explained by the newly proposed capacitive network model. The mesoscopic nucleic acid capacitance effect may enable a new kind of label-free nucleic acid analysis tool based on electronic transistor devices. The in situ and real-time nucleic acid detections for virus biomarkers, somatic mutations, and genome editing off-target may thus be predictable.

Effective prediction of short hydrogen bonds in proteins via machine learning method

Short hydrogen bonds (SHBs), whose donor and acceptor heteroatoms lie within 2.7 Å, exhibit prominent quantum mechanical characters and are connected to a wide range of essential biomolecular processes. However, exact determination of the geometry and functional roles of SHBs requires a protein to be at atomic resolution. In this work, we analyze 1260 high-resolution peptide and protein structures from the Protein Data Bank and develop a boosting based machine learning model to predict the formation of SHBs between amino acids. This model, which we name as machine learning assisted prediction of short hydrogen bonds (MAPSHB), takes into account 21 structural, chemical and sequence features and their interaction effects and effectively categorizes each hydrogen bond in a protein to a short or normal hydrogen bond. The MAPSHB model reveals that the type of the donor amino acid plays a major role in determining the class of a hydrogen bond and that the side chain Tyr-Asp pair demonstrates a significant probability of forming a SHB. Combining electronic structure calculations and energy decomposition analysis, we elucidate how the interplay of competing intermolecular interactions stabilizes the Tyr-Asp SHBs more than other commonly observed combinations of amino acid side chains. The MAPSHB model, which is freely available on our web server, allows one to accurately and efficiently predict the presence of SHBs given a protein structure with moderate or low resolution and will facilitate the experimental and computational refinement of protein structures.

Unraveling hydridic-to-protonic dihydrogen bond predominance in monohydrated dodecaborate clusters

Hydridic-to-protonic dihydrogen bonds (DHBs) are involved in comprehensive structural and energetic evolution, and significantly affect reactivity and selectivity in solution and solid states. Grand challenges exist in understanding DHBs’ bonding nature and strength, and how to harness DHBs. Herein we launched a combined photoelectron spectroscopy and multiscale theoretical investigation using monohydrated closo-dodecaborate clusters B₁₂X₁₂²⁻·H₂O (X = H, F, I) to address such challenges. For the first time, a consistent and unambiguous picture is unraveled demonstrating that B–H⋯H–O DHBs are superior to the conventional B–X⋯H–O HBs, being 1.15 and 4.61 kcal mol⁻¹ stronger than those with X = F and I, respectively. Energy decomposition analyses reveal that induction and dispersion terms make pronounced contributions resulting in a stronger B–H⋯H–O DHB. These findings call out more attention to the prominent roles of DHBs in water environments and pave the way for efficient and eco-friendly catalytic dihydrogen production based on optimized hydridic-to-protonic interactions.

A joint gas-phase ion spectroscopic and multiscale theoretical study reveals unequivocally the predominance of the hydridic-to-protonic dihydrogen bond over the prototypical strong hydrogen bond in monohydrated dodecaborate clusters.

Assessment of hydrogen bond strengths and cooperativity in self- and cross-associating cyclic (HF)m(H2O)n (m + n = 2 to 8) clusters

In this work, we investigated the strengths of various self- and cross-associating hydrogen bonds (HBs) in mixed hydrogen fluoride–water cyclic (HF)m(H2O)n (m + n = 2 to 8) clusters, employing a molecular tailoring approach (MTA)-based method.

Unprecedented observation and characterization of sulfur-centred bifurcated hydrogen bonds

Owing to the small electronegativity of the sulfur atom, it is commonly supposed that at most one weak H-bond can be formed between a sulfur atom and an H-bond donor. In this paper, an unprecedented 2 : 1 binding species generated from two molecules of phenol and a molecule of thioether was observed and characterized by various nuclear magnetic resonance (NMR) techniques, Fourier transform-infrared (FT-IR) techniques and density functional theory (DFT) calculations, revealing the formation of sulfur-centred O-H⋯S⋯H-O bifurcated H-bonds. This work may provide a simple and efficient method for the quantitative analysis of weak H-bonds between small organic molecules.