Browse Articles

The nature of water interactions and the molecular signatures of hydrophobicity

Despite being of utmost relevance in central fields ranging from biophysics to self-assembly processes in materials science, we still lack a precise comprehensive definition of hydrophobicity to replace the usual, merely qualitative descriptions that rely on water repellency or a lack of affinity. Building on recent findings regarding the structure and interactions of bulk water, we use a recently introduced water structural indicator to reach the following quantitative molecular elucidation: “hydrophobicity is the inability of a system to pay for the lacking hydrogen bonds (HBs) it produces in its hydration layer at least the same cost that this kind of defect imposes on bulk water, a defect interaction threshold whose magnitude is significantly lower than the HB energy.” We will demonstrate that such a defect interaction threshold not only marks the transition to hydrophobicity that occurs at a contact angle of θ = 90° in surfaces with different polarity degrees (allowing for an absolute scale) but also accurately signals the onset of drying regimes in nanoconfined aqueous systems. This is relevant from a practical perspective, as the possibility of being (locally) wet or dry becomes crucial in many fields. Specifically, our approach allows for assessing local hydrophobicity with unprecedented resolution (suitable for regions of different sizes, even at the single-atom level), particularly for self-assembly processes in biology and materials science, which often entail patterned regions combining hydrophobic and hydrophilic sites, thus posing challenges (and opportunities) for rational design efforts.

Translational diffusion in supercooled water at and near the glass transition temperature—136 K

The properties of amorphous solid water at and near the calorimetric glass transition temperature, Tg, of 136 K have been debated for years. One hypothesis is that water turns into a “true” liquid at Tg (i.e., it becomes ergodic) and exhibits all the characteristics of an ergodic liquid, including translational diffusion. A competing hypothesis is that only rotational motion becomes active at Tg, while the “real” glass transition in water is at a considerably higher temperature. To address this dispute, we have investigated the diffusive mixing in nanoscale water films, with thicknesses up to ∼100 nm, using infrared (IR) spectroscopy. The experiments used films that were composed of at least 90% H2O with D2O making up the balance and were conducted under conditions where H/D exchange was essentially eliminated. Because the IR spectra of multilayer D2O films (e.g., thicknesses of ∼3–6 nm) embedded within thick H2O films are distinct from the spectrum of isolated D2O molecules within H2O, the diffusive mixing of (initially) isotopically layered water films could be followed as a function of annealing time and temperature. The results show that water films with total thicknesses ranging from ∼20 to 100 nm diffusively mixed prior to crystallization for temperatures between 120 and 144 K. The translational diffusion had an Arrhenius temperature dependence with an activation energy of 40.8 ± 3.5 kJ/mol, which indicates that water at and near Tg is a strong liquid. The measured diffusion coefficient at 136 K is 6.25 ± 1.4 × 10−21 m2/s.

Symmetry breaking as predicted by a phase space Hamiltonian with a spin Coriolis potential

We perform electronic structure calculations for a set of molecules with degenerate spin-dependent ground states (CH23, CH3•2, O23) going beyond the Born–Oppenheimer approximation and accounting for nuclear motion. According to a phase space approach that parameterizes electronic states (|Φ⟩) and electronic energies (E) by nuclear position and momentum [i.e., |Φ(R, P)⟩ and E(R, P)], we find that the presence of degenerate spin degrees of freedom leads to broken symmetry ground states. More precisely, rather than a single degenerate minimum at (R, P) = (Rmin, 0), the ground state energy has two minima at (R,P)=(Rmin′,±Pmin) (where Rmin′ is close to Rmin), dramatically contradicting the notion that the total energy of the system can be written in separable form as E=P22M+Vel. Although we find that the broken symmetry solutions have small barriers between them for the small molecules, we hypothesize that the barriers should be macroscopically large for metallic solids, thus offering up a new phase-space potential energy surface for simulating the Einstein–de Haas effect.

Towards a robust approach to infer causality from molecular dynamics simulations

The ability to distinguish between correlation and causation of variables in molecular systems remains an interesting and open area of investigation. In this work, we probe causality in a molecular system using two independent computational methods that infer the causal direction through the language of information transfer. Specifically, we demonstrate that a molecular dynamics simulation involving a single tryptophan in liquid water displays asymmetric information transfer between specific collective variables, such as solute and solvent coordinates. Analyzing a discrete Markov-state and Langevin dynamics on a 2D free energy surface, we show that the same kind of asymmetries can emerge even in extremely simple systems undergoing equilibrium and time-reversible dynamics. We use these model systems to rationalize the unidirectional information transfer in the molecular system in terms of asymmetries in the underlying free energy landscape and/or relaxation dynamics of the relevant coordinates. Finally, we propose a computational experiment that allows one to decide if an asymmetric information transfer between two variables corresponds to a genuine causal link.

Water tree damage self-healing properties of plasma modified tri-layer shell-nucleated microcapsules/cross-linked polyethylene composites

This paper proposes a self-repairing material for cross-linked polyethylene (XLPE) based on a microcapsule system to solve the problem of insulation degradation caused by water tree aging. The microcapsules are extrinsic self-healing systems, which not only have good stability and high repair rates but also have little impact on the performance of the matrix. Plasma-modified tri-layer shell-nucleated microcapsules/XLPE composites were prepared by room temperature air radio frequency plasma discharge, and their insulation properties were tested to analyze the effect of microcapsule doping content on material properties. The accelerated water tree aging experiment was carried out by water needle electrode method, and the repair capability of microcapsules to water tree damage area before and after plasma modification was analyzed. The results show that compared with pure XLPE samples, when the content of microcapsules is 1.0 wt. %, the AC breakdown field strength and DC conductivity of the composites change little, and the dielectric properties of composites are improved. When the water tree breaks the microcapsule wall, due to the capillary effect, repair solution and catalyst flow into the water tree branch damage channel and react with water to repair the water tree damage. The average water tree length of plasma-modified microcapsules/XLPE specimens after water tree aging was reduced by 24.86% compared to non-plasma-modified microcapsules/XLPE specimens. The outermost layer of plasma modified microcapsules is nano-SiO2 modified by plasma hydroxylation, which can graft more silane coupling agents, so that the distribution of microcapsules in XLPE matrix is more uniform, the agglomeration of microcapsules is reduced, and the water tree repair ability of composite materials is improved.

Viscosity of polymer melts using non-affine theory based on vibrational modes

Viscosity, a fundamental transport and rheological property of liquids, quantifies the resistance to relative motion between molecular layers and plays a critical role in understanding material behavior. Conventional methods, such as the Green–Kubo (GK) approach, rely on time integration of correlation functions, which becomes computationally intensive near the glass transition due to slow correlation decay. A recently proposed method based on non-affine lattice dynamics (NALD) and instantaneous normal mode analysis offers a promising alternative for estimating the viscosity. In this study, we apply the NALD approach to compute the viscosity of the Kremer–Grest polymer system over a range of temperatures and compare these results with those from the GK method and non-equilibrium molecular dynamics simulations. Our findings reveal that all vibration modes, including the instantaneous normal modes, contribute to the viscosity. This work presents an efficient framework for calculating viscosity across diverse systems, including near the glass transition, where the GK method is no longer applicable. In addition, it opens the avenue to understanding the role of different vibrational modes linked with structure, facilitating the design of materials with tunable rheological properties.

Wavepacket and reduced-density approaches for high-dimensional quantum dynamics: Application to the nonlinear spectroscopy of asymmetrical light-harvesting building blocks

Excitation-energy transfer (EET) and relaxation in an optically excited building block of poly(phenylene ethynylene) (PPE) dendrimers are simulated using wavepackets with the multilayer multiconfiguration time-dependent Hartree (ML-MCTDH) method and reduced-density matrices with the hierarchical equations of motion (HEOM) approach. The dynamics of the ultrafast electronic funneling between the first two excited electronic states in the asymmetrically meta-substituted PPE oligomer with two rings on one branch and three rings on the other side, with a shared ring in between, is treated with 93-dimensional ab initio vibronic-coupling Hamiltonian (VCH) models, either linear or with bilinear and quadratic terms. The linear VCH model is also used to calibrate an open quantum system that falls in a computationally demanding non-perturbative non-Markovian regime. The linear-response absorption and emission spectra are simulated with both the ML-MCTDH and HEOM methods. The latter is further used to explore the nonlinear regime toward two-dimensional spectroscopy. We illustrate how a minimal VCH model with the two main active bright states and the impulsive-pulse limit in third-order response theory may provide at lower cost polarization-sensitive time-resolved signals that monitor the early EET dynamics. We also confirm the essential role played by the high-frequency acetylenic and quinoidal vibrational modes.

Assisting calculation of vibrational circular dichroism spectra by molecular tailoring approach

Theoretical investigation of the vibrational circular dichroism (VCD) spectrum requires computationally demanding construction of Hessian matrix elements along with atomic polar- and atomic axial-tensors. The fragmentation-based method, molecular tailoring approach (MTA) [Sahu et al., Acc. Chem. Res. 47, 2739 (2014)], is used for the first time to calculate the VCD spectra of large molecular systems. The accurate computation of these quantities is achieved by reduction of errors arising due to the approximate nature of MTA through the grafting correction from a smaller basis set. The performance of the methodology in reproducing the VCD spectral features is tested out on a variety of molecules, viz. sugars, polypeptides, and proteins using different density functionals with large basis sets. Regardless of the spectral regions, the vibrational peak positions and VCD intensities derived from the current methodology agree well with the full calculation results for these systems. Furthermore, a comparison of gas- and solvent-phase VCD spectra of Oxo-helicene shows excellent agreement with the experimental spectrum in the CDCl3 solvent. This study opens the possibility of an accurate yet inexpensive calculation of VCD spectra of large molecular systems within the MTA-framework.

Unraveling electronic structure and aromaticity differences in cyclo[12]carbon (C12), B4C4N4, and B6N6 isoelectronic ring molecules

Cyclo[12]carbon (C12) is the smallest recently synthesized carbon ring molecule that conforms to Hückel anti-aromaticity. Unraveling the electronic structure and aromaticity differences between C12 and its isoelectronic analogs (B4C4N4, B6N6) is essential for elucidating the impact of C-atom bridging and the physicochemical properties of novel ring systems. Herein, robust first-principle computational methods (including static density functional theory calculations and ab initio molecular dynamics simulations) are employed to investigate the electronic populations, bonding features, and kinetic behavior of different electron types. The molecular aromaticity is also examined by using various analytical indicators, such as anisotropy of induced current density, ZZ component of isochemical shielding surfaces, electron localization function-π, and Fermi holes. It is revealed that C12 and B4C4N4 exhibit pronounced anti-aromatic properties, while B6N6 is non-aromatic. The distinct in-plane and out-of-plane π-orbital features and differences in electronic delocalization capacity are fundamental to their anti-aromatic and non-aromatic nature, contrasting with classical aromatic molecules such as C18. This work provides valuable references for understanding the electronic structures of novel carbon ring molecules and their isoelectronic analogs that lack aromaticity, which can aid in comprehending the physicochemical properties of classic main-group elements and advance the design and synthesis of new ring molecules.

Role of molecular structure in defining the dynamical landscape of deep eutectic solvents

The molecular dynamics of deep eutectic solvents (DESs) are highly complex, characterized by pronounced spatial and temporal heterogeneity. Understanding these dynamics is crucial for tailoring transport properties such as diffusion, viscosity, and ionic conductivity. Molecular diffusion in DESs stems from transient caging and translation jumps, necessitating an understanding of how molecular structure regulates these processes. This study explores the influence of alkyl chain length on the dynamical behavior of alkylamide–lithium perchlorate based DESs using quasielastic neutron scattering (QENS) and molecular dynamics simulations. QENS results show that, despite its shorter chain length and lighter mass, acetamide exhibited the lowest mobility among the alkylamides, including propanamide (PRM) and butyramide (BUT). Detailed analysis of distinct degrees of freedom including the long-range jump diffusion of the alkylamide center of mass and localized diffusion, a clear trend emerges. The jump dynamics typically slowed with increasing chain length, essentially due to their differences in molecular size, mass, and also enhanced complexation in longer alkyl chain molecules. However, localized dynamics, dictated by the interplay between molecular flexibility and caging effects, exhibit an unusual trend, with PRM emerging as the fastest due to its optimal balance of molecular flexibility and reduced caging effects. In contrast, although BUT exhibited greater flexibility due its longer chain, its localized dynamics were slower, owing to stronger caging effects. Our findings highlight the complex interplay between alkyl chain length and the dynamical properties of DESs, demonstrating the relevance of molecular structure in governing the dynamics and transport properties of these systems.

A simulation study on Raman cross sections of OH and OD stretches in isotopically pure and diluted liquid water

The Raman scattering activity spectra of isotopically pure and diluted liquid water are theoretically calculated to examine the mole-fraction dependence of the OH- and OD-stretch cross sections. This mole-fraction dependence was once claimed to be anomalous and attributed to nuclear quantum correlations of protons and deuterons when it was discovered experimentally. The present study demonstrates that the experimental data of the mole-fraction dependence of the cross sections, as well as the Raman scattering activity spectra in the stretch region, are well reproduced by the theoretical calculations according to the quantum/classical mixed approach in which the nuclear quantum correlations are not taken into account. This suggests that the anomalous dependence does not serve as evidence of the nuclear quantum correlations. The present study provides a more plausible interpretation that the OH- and OD-stretch cross sections depend on the mole fraction because of the inter- and intra-molecular vibrational couplings.

Motors based on photo-magnetic materials

Absorption of light by a substance does not change its magnetic properties. However, if redox reactions occur on the surface of a material when irradiated with light and a current loop is formed, it turns into a magnet. This study reports a method for producing a new type of material—photo-magnets, which are capable of changing their magnetic properties when exposed to light. The simplest photo-magnet is a bimetallic plate made of two dissimilar metals, one part of which is coated with a semiconductor material—zinc oxide—and it is immersed in a solution of hydrogen peroxide. When exposed to light, holes and electrons are formed in the semiconductor, which take part in redox reactions during the decomposition of hydrogen peroxide. Since a current loop is formed in this case, the photo-magnet becomes a source of a magnetic field. In addition, any loop with current in a non-uniform magnetic field is affected by a force whose nature is determined by the action of the Lorentz force on moving charges. Therefore, on the basis of photo-magnets, it is possible to create motors that will move in a non-uniform magnetic field when irradiated with light.

Erratum: “Machine learning surrogate models for particle insertions and element substitutions” [J. Chem. Phys. 161, 194110 (2024)]

Ultrafast microwave construction of stabilized RuCo alloys for overall water splitting

Ruthenium-based catalysts are considered efficient and cost-effective potential alkaline electrolysis water catalysts that exhibit both hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) activities. Therefore, it is crucial to develop straightforward and low-energy synthesis methods for ruthenium-based alloy catalysts. In this study, we present a microwave synthesis approach for rapidly fabricating RuCo alloy supported on copper foam. Microwave heating, with its unique heating method, enables the efficient and rapid synthesis of alloy particles in a very short period of time. The synthesized RuCo/Cu2O/CF demonstrates excellent bifunctional HER and OER activities in alkaline media. Compared to commercial precious metal catalysts, RuCo/Cu2O/CF exhibits lower overpotentials and improved electrocatalytic kinetics, with an overpotential of 43 mV (10 mA cm−2) for HER and a Tafel slope of 37.6 mV dec−1, and an overpotential of 253 mV (10 mA cm−2) for OER, also with a Tafel slope of 189.1 mV dec−1. Moreover, the synthesized RuCo/Cu2O/CF shows remarkable stability. Theoretical calculations indicate that after alloying with Ru, both the water dissociation energy barrier and hydrogen adsorption energy on the Co surface are optimized. In a symmetric dual-electrode system, the RuCo/Cu2O/CF electrolyzer requires only 1.56 V to achieve a current density of 10 mA cm−2, outperforming commercial precious metal catalysts while exhibiting excellent long-term stability. These findings reveal a simple, low-energy preparation method for alloy catalysts, providing new insights into the development of water-splitting catalysts.

Nanocrystal BaTiO3: Pressure-induced transformation from mixed ionic–electronic to pure electronic cyclic conduction

The electrical transport characteristics of nano-barium titanate (BaTiO3) were systematically investigated under high pressures up to 35.64 GPa using AC impedance spectroscopy measurements and first-principles calculations. Impedance spectroscopy measurements provide insights into the conduction mechanism involving pressure-induced transformation from mixed ionic–electronic to pure electronic cyclic conduction. Through first-principles calculations, we have elucidated the underlying physical mechanisms responsible for the emergence of transformation from mixed ionic–electronic to pure electronic cyclic conduction. This phenomenon arises from variations in C-axis compressibility and phase transition from tetragonal to cubic phase, resulting in abrupt changes in electron density around oxygen atoms. These discontinuous changes are accompanied by alterations in initial resistance (R), relaxation frequency (F), and dielectric constant. By applying pressure, it becomes possible to effectively control the lattice spacing, thereby manipulating the charge density of OII ions and facilitating a seamless transition between mixed ionic–electronic and pure electronic conduction pathways. Pressure modulation also regulates the migration behavior of O2− ions, leading to an enhancement in the conductivity of nano-BaTiO3 materials. This study contributes to advancing our understanding of the transformation from mixed ionic–electronic to pure electronic cyclic conduction occurring within solid electrolytes.

Toward salinity-gradient modulated ionic transport in a nanoslit: A framework accelerating electrical energy generation

Motivated by the need for environmentally friendly energy-generating devices toward sustainable development and a secure energy future for the planet, the current work investigates high energy-density-producing devices utilizing the nanofluidic reverse electrodialysis approach, considering salinity gradients and pH influences in the ionic transport. Non-uniformly charged nanochannels have been considered to achieve the desired goal. This choice is expected to facilitate the regulation of the ionic field. The negative–positive–negative (NPN) and positive–negative–positive (PNP) surface-charged nanochannels are considered to be the non-uniform charged configurations. By altering the pH of the right-side reservoir (pHright) in comparison to the corresponding uniformly charged designs having positively charged walls and negatively charged walls, it was possible to compare the corresponding ionic and fluidic characteristics. By altering the pHright value, it becomes evident that the nanoslit’s unevenly charged surface can substantially affect the potential field and its gradient locally. The competition between cationic and anionic currents enables a highly cationic selective PNP nanoslit for the extremely acidic right reservoir. In contrast, the NPN nanoslit allows for greater anionic selectivity in the highly basic right reservoir. In addition, the PNP case achieves maximum electrical conductance, enabling a larger maximum generated power in the lower pHright range. Whereas, for the highly basic solution, electrical conductance as well as generated power were found to be higher for the NPN configuration. Remarkably, power density in the PNP and NPN configurations exceeds the commercial threshold limit in highly acidic and basic pHright values, respectively. We showed that the non-uniformly charged designs have higher average flow velocity or mass flow rate for almost every pHright (except close to pHright 4 and 10) under the salinity gradient. As such, information from this work can contribute to the development of more efficient nanofluidic devices that control flow and generate greater power density and flow rates.

Photoemission spectroscopy of organic molecules using plane wave/pseudopotential density functional theory and machine learning: A comprehensive and predictive computational protocol for isolated molecules, molecular aggregates, and organic thin films

Photoemission measurements in the gas phase at low pressure have enabled the exploration of the intricate relationship between electronic and structural properties at the single-molecule level. Experimental data collected from isolated molecules, free from interactions with other species, have provided an ideal testing ground for developing ab initio simulations capable of interpreting and predicting photoemission spectra. In particular, accurate computational methods for determining atom- and site-specific core ionization binding energies (BEs) facilitate experimental data interpretation, enabling the assignment of contributions from non-equivalent atoms of the same species, even when spectral features remain unresolved due to molecular structure. In this context, we have developed, extensively tested, and made widely available a computational protocol based on plane wave/pseudopotential density functional theory (PW-DFT) within a ΔSCF framework to predict x-ray photoemission spectra (XPS) of isolated molecules. Moreover, we have preliminarily tested and demonstrated the applicability of the same method to large molecular aggregates and thin molecular films deposited on inorganic substrates. The protocol has been assessed using a representative set of semilocal and hybrid density functionals with increasing fractions of Hartree–Fock exact exchange (EXX), including PBE, B3LYP (20% EXX), HSE (range-separated with 25% EXX at short range), and BH&HLYP (50% EXX). As a benchmark, we have also employed the equation-of-motion coupled-cluster method with single and double excitations. Our protocol has been validated across a diverse range of molecular classes—including aromatic, heteroaromatic, and aliphatic compounds; drugs; and biomolecules—demonstrating high accuracy and robustness, even when using semilocal DFT. In addition, valence photoemission measurements complement core photoemission by providing insights into delocalized and π-conjugated molecular orbitals. These measurements are particularly useful for studying chemical modifications in large molecules mediated by non-covalent interactions. Using the same set of density functionals, we have evaluated their capability to predict valence-shell ionization spectra, employing Kohn–Sham eigenvalues as estimators. Finally, our PW-DFT dataset of C1s, N1s, and O1s BEs has been used to train machine learning (ML) models for predicting XPS spectra of isolated organic molecules based on their structure. To ensure reproducibility and encourage the adoption of our protocol, we have made available a public repository containing pseudopotentials, input files for ab initio calculations, and datasets used for ML model training.

High-resolution analysis of red deer (Cervus elaphus) management units in a Central European region of high human population density reveals severe effects on genetic diversity and differentiation

The threat of isolation to red deer (Cervus elaphus) has been described in numerous European studies. The consequences range from reduced genetic diversity and increased inbreeding to inbreeding depression. It has been shown that the underlying factors cannot be generalised, but vary greatly in their effects depending on local conditions. The aim of this study was to analyse in detail the genetics of red deer in a large German federal state with a population density of 532 inhabitants per km2 and 23.8% settlement and traffic area, in order to generate data for future management of the region. 1199 individual samples of red deer were collected in all 20 Administrative Management Units (AMUs) and compared with existing results from the neighbouring state of Hesse (19 AMUs). All 2490 individuals from both states were clustered using Bayesian methods and connectivity between neighbouring AMUs was quantified. Overall, 30% of the AMUs were found to be highly isolated, mostly with effective population sizes (Ne) < 100. In contrast, 47.5% of the AMUs still had clear connectivity, allowing them to be merged into 4 larger red deer regions. For the small isolated areas, low genetic diversity was found in units with high homozygosity and low Ne. With high sampling density and identical methodology, detailed information on AMUs can be obtained and the degree of vulnerability of individual AMUs as part of the overall population can specifically be validated. Such data can help improve future wildlife management.

Correction: Integrative bioinformatics analysis reveals STAT1, ORC2, and GTF2B as critical biomarkers in lupus nephritis with Monkeypox virus infection

Decomposition-reconstruction-optimization framework for hog price forecasting: Integrating STL, PCA, and BWO-optimized BiLSTM

This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. Finally, the Beluga Whale Optimization (BWO)-tuned STL-PCA-BWO-BiLSTM hybrid model delivered optimal performance on test sets (RMSE = 0.22, MAE = 0.16, MAPE = 0.99%, R2=0.98), exhibiting 40.7% higher accuracy than unoptimized BiLSTM (MAE = 0.27). The research demonstrates that the synergy of temporal decomposition, feature dimensionality reduction, and intelligent optimization reduces hog price prediction errors by over 80%, with STL-PCA feature engineering contributing 67.4% of the improvement. This work establishes an innovative “decomposition-reconstruction-optimization” framework for agricultural economic time series forecasting.