Deformation dynamics of nanopores upon water imbibition.

Capillarity-driven transport in nanoporous solids is widespread in nature and crucial for modern liquid-infused engineering materials. During imbibition, curved menisci driven by high negative Laplace pressures exert an enormous contractile load on the porous matrix. Due to the challenge of simultaneously monitoring imbibition and deformation with high spatial resolution, the resulting coupling of solid elasticity to liquid capillarity has remained largely unexplored. Here, we study water imbibition in mesoporous silica using optical imaging, gravimetry, and high-resolution dilatometry. In contrast to an expected Laplace pressure-induced contraction, we find a square-root-of-time expansion and an additional abrupt length increase when the menisci reach the top surface. The final expansion is absent when we stop the imbibition front inside the porous medium in a dynamic imbibition-evaporation equilibrium, as is typical for transpiration-driven hydraulic transport in plants, especially in trees. These peculiar deformation behaviors are validated by single-nanopore molecular dynamics simulations and described by a continuum model that highlights the importance of expansive surface stresses at the pore walls (Bangham effect) and the buildup or release of contractile Laplace pressures as menisci collectively advance, arrest, or disappear. Our model suggests that these observations apply to any imbibition process in nanopores, regardless of the liquid/solid combination, and that the Laplace contribution upon imbibition is precisely half that of vapor sorption, due to the linear pressure drop associated with viscous flow. Thus, simple deformation measurements can be used to quantify surface stresses and Laplace pressures or transport in a wide variety of natural and artificial porous media.

Accounting for the Quantum Capacitance of Graphite in Constant Potential Molecular Dynamics Simulations.

Molecular dynamics (MD) simulations at a constant electric potential are an essential tool to study electrochemical processes, providing microscopic information on the structural, thermodynamic, and dynamical properties. Despite the numerous advances in the simulation of electrodes, they fail to accurately represent the electronic structure of materials such as graphite. In this work, a simple parameterization method that allows to tune the metallicity of the electrode based on a quantum chemistry calculation of the density of states (DOS) is introduced. As a first illustration, the interface between graphite electrodes and two different liquid electrolytes, an aqueous solution of NaCl and a pure ionic liquid, at different applied potentials are studied. It is shown that the simulations reproduce qualitatively the experimentally-measured capacitance; in particular, they yield a minimum of capacitance at the point of zero charge (PZC), which is due to the quantum capacitance (QC) contribution. An analysis of the structure of the adsorbed liquids allows to understand why the ionic liquid displays a lower capacitance despite its large ionic concentration. In addition to its relevance for the important class of carbonaceous electrodes, this method can be applied to any electrode materials (e.g. 2D materials, conducting polymers, etc), thus enabling molecular simulation studies of complex electrochemical devices in the future.

Water, Not Salt, Causes Most of the Seebeck Effect of Nonisothermal Aqueous Electrolytes.

A temperature difference between two electrolyte-immersed electrodes often yields a voltage Δψ between them. This electrolyte Seebeck effect is usually explained by cations and anions flowing differently in thermal gradients. However, using molecular simulations, we found almost the same Δψ for cells filled with pure water as with aqueous alkali halides. Water layering and orientation near polarizable electrodes cause a large temperature-dependent potential drop χ there. The difference in χ of hot and cold electrodes captures most of the thermovoltage, Δψ≈χ_{hot}-χ_{cold}.

Integrating Explainability into Graph Neural Network Models for the Prediction of X-ray Absorption Spectra.

The use of sophisticated machine learning (ML) models, such as graph neural networks (GNNs), to predict complex molecular properties or all kinds of spectra has grown rapidly. However, ensuring the interpretability of these models' predictions remains a challenge. For example, a rigorous understanding of the predicted X-ray absorption spectrum (XAS) generated by such ML models requires an in-depth investigation of the respective black-box ML model used. Here, this is done for different GNNs based on a comprehensive, custom-generated XAS data set for small organic molecules. We show that a thorough analysis of the different ML models with respect to the local and global environments considered in each ML model is essential for the selection of an appropriate ML model that allows a robust XAS prediction. Moreover, we employ feature attribution to determine the respective contributions of various atoms in the molecules to the peaks observed in the XAS spectrum. By comparing this peak assignment to the core and virtual orbitals from the quantum chemical calculations underlying our data set, we demonstrate that it is possible to relate the atomic contributions via these orbitals to the XAS spectrum.

Mapping the electronic transitions of protonation sites in peptides using soft X-ray action spectroscopy.

Near-edge X-ray absorption mass spectrometry (NEXAMS) around the nitrogen and oxygen K-edges was employed on gas-phase peptides to probe the electronic transitions related to their protonation sites, namely at basic side chains, the N-terminus and the amide oxygen. The experimental results are supported by replica exchange molecular dynamics and density-functional theory and restricted open-shell configuration with single calculations to attribute the transitions responsible for the experimentally observed resonances. We studied five tailor-made glycine-based pentapeptides, where we identified the signature of the protonation site of N-terminal proline, histidine, lysine and arginine, at 406 eV, corresponding to N 1s → σ*(NHx+) (x = 2 or 3) transitions, depending on the peptides. We compared the spectra of pentaglycine and triglycine to evaluate the sensitivity of NEXAMS to protomers. Separate resonances have been identified to distinguish two protomers in triglycine, the protonation site at the N-terminus at 406 eV and the protonation site at the amide oxygen characterized by a transition at 403.1 eV.

Discovery of MK-8768, a Potent and Selective mGluR2 Negative Allosteric Modulator.

Glutamate plays a key role in cognition and mood, and it has been shown that inhibiting ionotropic glutamate receptors disrupts cognition, while enhancing ionotropic receptor activity is pro-cognitive. One approach to elevating glutamatergic tone has been to antagonize presynaptic metabotropic glutamate receptor 2 (mGluR2). A desire for selectivity over the largely homologous mGluR3 motivated a strategy to achieve selectivity through the identification of mGluR2 negative allosteric modulators (NAMs). Extensive screening and optimization efforts led to the identification of a novel series of 4-arylquinoline-2-carboxamides. This series was optimized for mGluR2 NAM potency, clean off-target activity, and desirable physical properties, which resulted in the identification of improved C4 and C7 substituents. The initial lead compound from this series was Ames-positive in a single strain with metabolic activation, indicating that a reactive metabolite was likely responsible for the genetic toxicity. Metabolic profiling and Ames assessment across multiple analogs identified key structure-activity relationships associated with Ames positivity. Further optimization led to the Ames-negative mGluR2 negative allosteric modulator MK-8768.

Discovery of [11C]MK-8056: A Selective PET Imaging Agent for the Study of mGluR2 Negative Allosteric Modulators.

Modification of potent, selective metabotropic glutamate receptor 2 negative allosteric modulator (mGluR2 NAM) led to a series of analogues with excellent binding affinity, lipophilicity, and suitable physicochemical properties for a PET tracer with convenient chemical handles for incorporation of a 11C or 18F radiolabel. [11C]MK-8056 was synthesized and evaluated in vivo and demonstrated appropriate affinity, selectivity, and physicochemical properties to be used as a positron emission tomography tracer for mGluR2.

Oxidation-State Dynamics and Emerging Patterns in Magnetite.

Magnetite is an important mineral with many interesting applications related to its magnetic, electrical, and thermal properties. Typically studied by electronic structure calculations, these methods are unable to capture the complex ion dynamics at relevant temperatures, time, and length scales. We present a hybrid Monte Carlo/molecular dynamics (MC/MD) method based on iron oxidation-state swapping for accurate atomistic modeling of bulk magnetite, magnetite surfaces, and nanoparticles that captures the complex ionic dynamics. By comparing the oxidation-state patterns with those obtained from density functional theory, we confirmed the accuracy of our approach. Lattice distortions leading to the stabilization of excess charges and a critical surface thickness at which the oxidation states transition from ordered to disordered were observed. This simple yet efficient approach paves the way for elucidating aspects of oxidation-state ordering of inverse spinel structures in general and battery materials in particular.

Orientation order of a nonpolar molecular fluid compressed into a nanosmall space.

The ordering structures of non-polar carbon tetrachloride liquid compressed to nano-scales between parallel substrates is studied in this work. The theoretical considerations show that the potential well formed by the confined parallel substrates induces orientational ordering of non-polar molecules. Through molecular dynamic (MD) simulations, the relations between various ordered structures of a non-polar liquid (carbon tetrachloride) and the confined gap size are demonstrated. The density distribution shows that the confinement does affect the ordering modes and induces an orientational ordering of molecules at the solid-liquid interface under extreme confinement conditions. This molecular orientation suggested from the theoretical model and MD simulation is directly supported by the experimental studies for the first time. The X-ray reflectivity data reveal a strong layering effect with splitting of the density profile in C and Cl-rich sublayers. The investigation shows that the liquid structure factor in confinement has a characteristic length similar to the short-range ordering in bulk, but the confined structure is strongly influenced by the surface potential and the interface properties. This introduces preferred molecular orientation and ordering which are not favorable in the bulk phase. As the orientational ordering is closely related to crystallization, our results provide a new perspective to control the crystallization in nano-confined space by compression.

Reconstructing the infrared spectrum of a peptide from representative conformers of the full canonical ensemble.

Leucine enkephalin (LeuEnk), a biologically active endogenous opioid pentapeptide, has been under intense investigation because it is small enough to allow efficient use of sophisticated computational methods and large enough to provide insights into low-lying minima of its conformational space. Here, we reproduce and interpret experimental infrared (IR) spectra of this model peptide in gas phase using a combination of replica-exchange molecular dynamics simulations, machine learning, and ab initio calculations. In particular, we evaluate the possibility of averaging representative structural contributions to obtain an accurate computed spectrum that accounts for the corresponding canonical ensemble of the real experimental situation. Representative conformers are identified by partitioning the conformational phase space into subensembles of similar conformers. The IR contribution of each representative conformer is calculated from ab initio and weighted according to the population of each cluster. Convergence of the averaged IR signal is rationalized by merging contributions in a hierarchical clustering and the comparison to IR multiple photon dissociation experiments. The improvements achieved by decomposing clusters containing similar conformations into even smaller subensembles is strong evidence that a thorough assessment of the conformational landscape and the associated hydrogen bonding is a prerequisite for deciphering important fingerprints in experimental spectroscopic data.

ELECTRODE: An electrochemistry package for atomistic simulations.

Constant potential methods (CPMs) enable computationally efficient simulations of the solid-liquid interface at conducting electrodes in molecular dynamics. They have been successfully used, for example, to realistically model the behavior of ionic liquids or water-in-salt electrolytes in supercapacitors and batteries. CPMs model conductive electrodes by updating charges of individual electrode atoms according to the applied electric potential and the (time-dependent) local electrolyte structure. Here, we present a feature-rich CPM implementation, called ELECTRODE, for the Large-scale Atomic/Molecular Massively Parallel Simulator, which includes a constrained charge method and a thermo-potentiostat. The ELECTRODE package also contains a finite-field approach, multiple corrections for nonperiodic boundary conditions of the particle-particle particle-mesh solver, and a Thomas-Fermi model for using nonideal metals as electrodes. We demonstrate the capabilities of this implementation for a parallel-plate electrical double-layer capacitor, for which we have investigated the charging times with the different implemented methods and found an interesting relationship between water and ionic dipole relaxations. To prove the validity of the one-dimensional correction for the long-range electrostatics, we estimated the vacuum capacitance of two coaxial carbon nanotubes and compared it to structureless cylinders, for which an analytical expression exists. In summary, the ELECTRODE package enables efficient electrochemical simulations using state-of-the-art methods, allowing one to simulate even heterogeneous electrodes. Moreover, it allows unveiling more rigorously how electrode curvature affects the capacitance with the one-dimensional correction.

Atomistic Insight into the Hydration States of Layered Double Hydroxides.

Effective protective coatings are an essential component of lightweight engineering materials in a large variety of applications as they ensure structural integrity of the base material throughout its whole service life. Layered double hydroxides (LDHs) loaded with corrosion inhibitors depict a promising approach to realize an active corrosion protection for aluminum and magnesium. In this work, we employed a combination of density functional theory and molecular dynamics simulations to gain a deeper understanding of the influence of intercalated water content on the structure, the stability, and the anion-exchange capacity of four different LDH systems containing either nitrate, carbonate, or oxalate as potential corrosion inhibiting agents or chloride as a corrosion initiator. To quantify the structural change, we studied the atom density distribution, radial distribution function, and orientation of the intercalated anions. Additionally, we determined the stability of the LDH systems by calculating their respective hydration energies, hydrogen-bonded network connected to the intercalated water molecules, as well as the self-diffusion coefficients of the intercalated anions to provide an estimate for the probability of their release after intercalation. The obtained computational results suggest that the hydration state of LDHs has a significant effect on their key properties like interlayer spacing and self-diffusion coefficients of the intercalated anions. Furthermore, we conclude from our simulation results that a high self-diffusion coefficient which is linked to the mobility of the intercalated anions is vital for its release via an anion-exchange mechanism and to subsequently mitigate corrosion reactions. Furthermore, the presented theoretical study provides a robust force field for the computer-assisted design of further LDH-based active anticorrosion coatings.

Elucidating Curvature-Capacitance Relationships in Carbon-Based Supercapacitors.

Nanoscale surface curvatures, either convex or concave, strongly influence the charging behavior of supercapacitors. Rationalizing individual influences of electrode atoms to the capacitance is possible by interpreting distinct elements of the charge-charge covariance matrix derived from individual charge variations of the electrode atoms. An ionic liquid solvated in acetonitrile and confined between two electrodes, each consisting of three undulated graphene layers, serves as a demonstrator to illustrate pronounced and nontrivial features of the capacitance with respect to the electrode curvature. In addition, the applied voltage determines whether a convex or concave surface contributes to increased capacitance. While at lower voltages capacitance variations are in general correlated with ion number density variations in the double layer formed in the concave region of the electrode, for certain electrode designs a surprisingly strong contribution of the convex part to the differential capacitance is found both at higher and lower voltages.

Impact of confinement and polarizability on dynamics of ionic liquids.

Polarizability is a key factor when it comes to an accurate description of different ionic systems. The general importance of including polarizability into molecular dynamics simulations was shown in various recent studies for a wide range of materials, ranging from proteins to water to complex ionic liquids and for solid-liquid interfaces. While most previous studies focused on bulk properties or static structure factors, this study investigates in more detail the importance of polarizable surfaces on the dynamics of a confined ionic liquid in graphitic slit pores, as evident in modern electrochemical capacitors or in catalytic processes. A recently developed polarizable force field using Drude oscillators is modified in order to describe a particular room temperature ionic liquid accurately and in agreement with recently published experimental results. Using the modified parameters, various confinements are investigated and differences between non-polarizable and polarizable surfaces are discussed. Upon introduction of surface polarizability, changes in the dipole orientation and in the density distribution of the anions and cations at the interface are observed and are also accompanied with a dramatic increase in the molecular diffusivity in the contact layer. Our results thus clearly underline the importance of considering not only the polarizability of the ionic liquid but also that of the surface.

Adsorption of oleic acid on magnetite facets.

The microscopic understanding of the atomic structure and interaction at carboxylic acid/oxide interfaces is an important step towards tailoring the mechanical properties of nanocomposite materials assembled from metal oxide nanoparticles functionalized by organic molecules. We have studied the adsorption of oleic acid (C17H33COOH) on the most prominent magnetite (001) and (111) crystal facets at room temperature using low energy electron diffraction, surface X-ray diffraction and infrared vibrational spectroscopy complemented with molecular dynamics simulations used to infer specific hydrogen bonding motifs between oleic acid and oleate. Our experimental and theoretical results give evidence that oleic acid adsorbs dissociatively on both facets at lower coverages. At higher coverages, the more pronounced molecular adsorption causes hydrogen bond formation between the carboxylic groups, leading to a more upright orientation of the molecules on the (111) facet in conjunction with the formation of a denser layer, as compared to the (001) facet. This is evidenced by the C=O double bond infrared line shape, in depth molecular dynamics bond angle orientation and hydrogen bond analysis, as well as X-ray reflectivity layer electron density profile determination. Such a higher density can explain the higher mechanical strength of nanocomposite materials based on magnetite nanoparticles with larger (111) facets.

Discovery and Preclinical Characterization of BIIB091, a Reversible, Selective BTK Inhibitor for the Treatment of Multiple Sclerosis.

Multiple Sclerosis is a chronic autoimmune neurodegenerative disorder of the central nervous system (CNS) that is characterized by inflammation, demyelination, and axonal injury leading to permeant disability. In the early stage of MS, inflammation is the primary driver of the disease progression. There remains an unmet need to develop high efficacy therapies with superior safety profiles to prevent the inflammation processes leading to disability. Herein, we describe the discovery of BIIB091, a structurally distinct orthosteric ATP competitive, reversible inhibitor that binds the BTK protein in a DFG-in confirmation designed to sequester Tyr-551, an important phosphorylation site on BTK, into an inactive conformation with excellent affinity. Preclinical studies demonstrated BIB091 to be a high potency molecule with good drug-like properties and a safety/tolerability profile suitable for clinical development as a highly selective, reversible BTKi for treating autoimmune diseases such as MS.

How water wets and self-hydrophilizes nanopatterns of physisorbed hydrocarbons.

HYPOTHESIS: Weakly bound, physisorbed hydrocarbons could in principle provide a similar water-repellency as obtained by chemisorption of strongly bound hydrophobic molecules at surfaces. EXPERIMENTS: Here we present experiments and computer simulations on the wetting behaviour of water on molecularly thin, self-assembled alkane carpets of dotriacontane (n-C32H66 or C32) physisorbed on the hydrophilic native oxide layer of silicon surfaces during dip-coating from a binary alkane solution. By changing the dip-coating velocity we control the initial C32 surface coverage and achieve distinct film morphologies, encompassing homogeneous coatings with self-organised nanopatterns that range from dendritic nano-islands to stripes. FINDINGS: These patterns exhibit a good water wettability even though the carpets are initially prepared with a high coverage of hydrophobic alkane molecules. Using in-liquid atomic force microscopy, along with molecular dynamics simulations, we trace this to a rearrangement of the alkane layers upon contact with water. This restructuring is correlated to the morphology of the C32 coatings, i.e. their fractal dimension. Water molecules displace to a large extent the first adsorbed alkane monolayer and thereby reduce the hydrophobic C32 surface coverage. Thus, our experiments evidence that water molecules can very effectively hydrophilize initially hydrophobic surfaces that consist of weakly bound hydrocarbon carpets.

Constant potential simulations on a mesh.

Molecular dynamics simulations in a constant potential ensemble are an increasingly important tool to investigate charging mechanisms in next-generation energy storage devices. We present a highly efficient approach to compute electrostatic interactions in simulations employing a constant potential method (CPM) by introducing a particle-particle particle-mesh solver specifically designed for treating long-range interactions in a CPM. Moreover, we present evidence that a dipole correction term-commonly used in simulations with a slab-like geometry-must be used with caution if it is also to be used within a CPM. It is demonstrated that artifacts arising from the usage of the dipole correction term can be circumvented by enforcing a charge neutrality condition in the evaluation of the electrode charges at a given external potential.

Osmotic Transport at the Aqueous Graphene and hBN Interfaces: Scaling Laws from a Unified, First-Principles Description.

Osmotic transport in nanoconfined aqueous electrolytes provides alternative venues for water desalination and "blue energy" harvesting. The osmotic response of nanofluidic systems is controlled by the interfacial structure of water and electrolyte solutions in the so-called electrical double layer (EDL), but a molecular-level picture of the EDL is to a large extent still lacking. Particularly, the role of the electronic structure has not been considered in the description of electrolyte/surface interactions. Here, we report enhanced sampling simulations based on ab initio molecular dynamics, aiming at unravelling the free energy of prototypical ions adsorbed at the aqueous graphene and hBN interfaces, and its consequences on nanofluidic osmotic transport. Specifically, we predicted the zeta potential, the diffusio-osmotic mobility, and the diffusio-osmotic conductivity for a wide range of salt concentrations from the ab initio water and ion spatial distributions through an analytical framework based on Stokes equation and a modified Poisson-Boltzmann equation. We observed concentration-dependent scaling laws, together with dramatic differences in osmotic transport between the two interfaces, including diffusio-osmotic flow and current reversal on hBN but not on graphene. We could rationalize the results for the three osmotic responses with a simple model based on characteristic length scales for ion and water adsorption at the surface, which are quite different on graphene and on hBN. Our work provides fundamental insights into the structure and osmotic transport of aqueous electrolytes on 2D materials and explores alternative pathways for efficient water desalination and osmotic energy conversion.

Multi-frequency passive and active microrheology with optical tweezers.

Optical tweezers have attracted significant attention for microrheological applications, due to the possibility of investigating viscoelastic properties in vivo which are strongly related to the health status and development of biological specimens. In order to use optical tweezers as a microrheological tool, an exact force calibration in the complex system under investigation is required. One of the most promising techniques for optical tweezers calibration in a viscoelastic medium is the so-called active-passive calibration, which allows determining both the trap stiffness and microrheological properties of the medium with the least a-priori knowledge in comparison to the other methods. In this manuscript, we develop an optimization of the active-passive calibration technique performed with a sample stage driving, whose implementation is more straightforward with respect to standard laser driving where two different laser beams are required. We performed microrheological measurements over a broad frequency range in a few seconds implementing an accurate multi-frequency driving of the sample stage. The optical tweezers-based microrheometer was first validated by measuring water, and then exemplarily applied to more viscous medium and subsequently to a viscoelastic solution of methylcellulose in water. The described method paves the way to microrheological precision metrology in biological samples with high temporal- and spatial-resolution allowing for investigation of even short time-scale phenomena.