Machine Learning for Polaritonic Chemistry: Accessing Chemical Kinetics.

Altering chemical reactivity and material structure in confined optical environments is on the rise, and yet, a conclusive understanding of the microscopic mechanisms remains elusive. This originates mostly from the fact that accurately predicting vibrational and reactive dynamics for soluted ensembles of realistic molecules is no small endeavor, and adding (collective) strong light-matter interaction does not simplify matters. Here, we establish a framework based on a combination of machine learning (ML) models, trained using density-functional theory calculations and molecular dynamics to accelerate such simulations. We then apply this approach to evaluate strong coupling, changes in reaction rate constant, and their influence on enthalpy and entropy for the deprotection reaction of 1-phenyl-2-trimethylsilylacetylene, which has been studied previously both experimentally and using ab initio simulations. While we find qualitative agreement with critical experimental observations, especially with regard to the changes in kinetics, we also find differences in comparison with previous theoretical predictions. The features for which the ML-accelerated and ab initio simulations agree show the experimentally estimated kinetic behavior. Conflicting features indicate that a contribution of dynamic electronic polarization to the reaction process is more relevant than currently believed. Our work demonstrates the practical use of ML for polaritonic chemistry, discusses limitations of common approximations, and paves the way for a more holistic description of polaritonic chemistry.

Temperature and pressure dependent rate constants of the reactions of OH• with cyclopentene from variational TST and SS-QRRK methods.

In this work, the pressure- and temperature-dependent reaction rate constants for the hydrogen abstraction and addition of hydroxyl radicals to the unsaturated cyclopentene were studied. Geometries and vibrational frequencies of reactants, products, and transition states were calculated using density functional theory, with single-point energy corrections determined at the domain-based local pair natural orbital-coupled-cluster single double triple/cc-pVTZ-F12 level. The high-pressure limit rate constants were calculated using the canonical variational transition state theory with the small-curvature tunneling approximation. The vibrational partition functions were corrected by the effects of torsional and ring-puckering anharmonicities of the transition states and cyclopentene, respectively. Variational effects are shown to be relevant for all the hydrogen abstraction reactions. The increasing of the rate constants by tunneling is significant at temperatures below 500 K. The pressure dependence on the rate constants of the addition of OH• to cyclopentene was calculated using the system-specific quantum Rice-Ramsperger-Kassel model. The high-pressure limit rate constants decrease with increasing temperature in the range 250-1000 K. The falloff behavior was studied at several temperatures with pressures varying between 10-3 and 103 bar. At temperatures below 500 K, the effect of the pressure on the addition rate constant is very modest. However, at temperatures around and above 1000 K, taking pressure into account is mandatory for an accurate rate constant calculation. Branching ratio analyses reveal that the addition reaction dominates at temperatures below 500 K, decreasing rapidly at higher temperatures. Arrhenius parameters are provided for all reactions and pressure dependent Arrhenius parameters are given for the addition of OH• to cyclopentene.

GPUMD: A package for constructing accurate machine-learned potentials and performing highly efficient atomistic simulations.

We present our latest advancements of machine-learned potentials (MLPs) based on the neuroevolution potential (NEP) framework introduced in Fan et al. [Phys. Rev. B 104, 104309 (2021)] and their implementation in the open-source package gpumd. We increase the accuracy of NEP models both by improving the radial functions in the atomic-environment descriptor using a linear combination of Chebyshev basis functions and by extending the angular descriptor with some four-body and five-body contributions as in the atomic cluster expansion approach. We also detail our efficient implementation of the NEP approach in graphics processing units as well as our workflow for the construction of NEP models and demonstrate their application in large-scale atomistic simulations. By comparing to state-of-the-art MLPs, we show that the NEP approach not only achieves above-average accuracy but also is far more computationally efficient. These results demonstrate that the gpumd package is a promising tool for solving challenging problems requiring highly accurate, large-scale atomistic simulations. To enable the construction of MLPs using a minimal training set, we propose an active-learning scheme based on the latent space of a pre-trained NEP model. Finally, we introduce three separate Python packages, viz., gpyumd, calorine, and pynep, that enable the integration of gpumd into Python workflows.

Theoretical analysis of screened many-body electrostatic interactions between charged polarizable particles.

This paper builds on two previous studies [Lindgren et al., J. Comput. Phys. 371, 712 (2018) and Quan et al., "A domain decomposition method for the Poisson-Boltzmann solvation models," SIAM J. Sci. Comput. (to be published); e-print arXiv:1807.05384] to devise a new method to solve the problem of calculating electrostatic interactions in a system composed by many dielectric particles, embedded in a homogeneous dielectric medium, which in turn can also be permeated by charge carriers. The system is defined by the charge, size, position, and dielectric constant of each particle, as well as the dielectric constant and the Debye length of the medium. The effects of taking into account the dielectric nature of the particles are explored in selected scenarios where the presence of electrolytes in the medium can significantly influence the total undergoing interactions. The description of the mutual interactions between all particles in the system as being truly of many-body nature reveals how such effects can effectively influence the magnitudes and even directions of the resulting forces, especially those acting on particles that have a null net charge. Particular attention is given to a situation that can be related to colloidal particles in an electrolyte solution, where it is shown that polarization effects alone can substantially raise or lower-depending on the dielectric contrast between the particles and the medium-the energy barrier that divides particle coagulation and flocculation regions, when an interplay between electrostatic and additional van der Waals forces is considered. Overall, the results suggest that for an accurate description of the type of system in question, it is essential to consider particle polarization if the separation between the interacting particles are comparable to or smaller than the Debye length of the medium.

Dynamic simulations of many-body electrostatic self-assembly.

Two experimental studies relating to electrostatic self-assembly have been the subject of dynamic computer simulations, where the consequences of changing the charge and the dielectric constant of the materials concerned have been explored. One series of calculations relates to experiments on the assembly of polymer particles that have been subjected to tribocharging and the simulations successfully reproduce many of the observed patterns of behaviour. A second study explores events observed following collisions between single particles and small clusters composed of charged particles derived from a metal oxide composite. As before, observations recorded during the course of the experiments are reproduced by the calculations. One study in particular reveals how particle polarizability can influence the assembly process.This article is part of the theme issue 'Modern theoretical chemistry'.

Coulomb fission in multiply charged molecular clusters: Experiment and theory.

A series of three multiply charged molecular clusters, (C6H6)nz+ (benzene), (CH3CN)nz+ (acetonitrile), and (C4H8O)nz+ (tetrahydrofuran), where the charge z is either 3 or 4, have been studied for the purpose of identifying the patterns of behaviour close to the charge instability limit. Experiments show that on a time scale of ∼10-4 s, ions close to the limit undergo Coulomb fission where the observed pathways exhibit considerable asymmetry in the sizes of the charged fragments and are all associated with kinetic (ejection) energies of between 1.4 and 2.2 eV. Accurate kinetic energies have been determined through a computer simulation of peak profiles recorded in the experiments and the results modelled using a theory formulated to describe how charged particles of dielectric materials interact with one another [E. Bichoutskaia et al., J. Chem. Phys. 133, 024105 (2010)]. The calculated electrostatic interaction energy between separating fragments gives an accurate account for the measured kinetic energies and also supports the conclusion that +4 ions fragment into +3 and +1 products as opposed to the alternative of two +2 fragments. This close match between the theory and experiment reinforces the assumption that a significant fraction of excess charge resides on the surfaces of the fragment ions. It is proposed that the high degree of asymmetry seen in the fragmentation patterns of the multiply charged clusters is due, in part, to limits imposed by the time window during which observations are made.

Progress in the theory of electrostatic interactions between charged particles.

In this perspective we examine recent theoretical developments in methods for calculating the electrostatic properties of charged particles of dielectric materials. Particular attention is paid to the phenomenon of like-charge attraction and we investigate the specific conditions under which particles carrying the same sign of charge can experience an attractive interaction. Given favourable circumstances, it is shown that even weakly polarisable materials, such as oil droplets and polymer particles, can experience like-charge attraction. Emphasis is also placed on the numerical accuracy of the multipole approach adopted in many electrostatic solutions and on the importance of establishing strict convergence criteria when addressing problems involving particulate materials with high dielectric constants.

Synthesis and biological evaluation of novel 6-hydroxy-benzo[d][1,3]oxathiol-2-one Schiff bases as potential anticancer agents.

With the aim of discovering new anticancer agents, we have designed and synthesized novel 6-hydroxy-benzo[d][1,3]oxathiol-2-one Schiff bases. The synthesis started with the selective nitration at 5-position of 6-hydroxybenzo[d][1,3]oxathiol-2-one (1) leading to the nitro derivative 2. The nitro group of 2 was reduced to give the amino intermediate 3. Schiff bases 4a-r were obtained from coupling reactions between 3 and various benzaldehydes and heteroaromatic aldehydes. All the new compounds were fully identified and characterized by NMR (1H and 13C) and specifically for 4q by X-ray crystallography. The in vitro cytotoxicity of the compounds was evaluated against cancer cell lines (ACP-03, SKMEL-19 and HCT-116) by using MTT assay. Schiff bases 4b and 4o exhibited promising cytotoxicity against ACP-03 and SKMEL-19, respectively, with IC50 values lower than 5 µM. This class of compounds can be considered as a good starting point for the development of new lead molecules in the fight against cancer.

The significance of multipole interactions for the stability of regular structures composed from charged particles.

Identifying the forces responsible for stabilising binary particle lattices is key to the controlled fabrication of many new materials. Experiments have shown that the presence of charge can be integral to the formation of ordered arrays; however, a complete analysis of the forces responsible has not included many of the significant lattice types that may form during fabrication. A theory of many-body electrostatic interactions has been applied to six lattice stoichiometries, AB, AB2, AB3, AB4, AB5 and AB6, to show that induced multipole interactions can make a very significant (>80 %) contribution to the total lattice energy of arrays of charged particles. Particle radii ratios which favour global minima in electrostatic energy are found to be the same or a close match to those observed by experiment. Although certain lattice types exhibit local energy minima, the calculations show that many-body rather than two-body interactions are ultimately responsible for the structures observed by experiment. For a lattice isostructural with CFe4, a particle size ratio not previously observed is found to be particularly stable due to many-body effects.

Tensorial Properties via the Neuroevolution Potential Framework: Fast Simulation of Infrared and Raman Spectra.

Infrared and Raman spectroscopy are widely used for the characterization of gases, liquids, and solids, as the spectra contain a wealth of information concerning, in particular, the dynamics of these systems. Atomic scale simulations can be used to predict such spectra but are often severely limited due to high computational cost or the need for strong approximations that limit the application range and reliability. Here, we introduce a machine learning (ML) accelerated approach that addresses these shortcomings and provides a significant performance boost in terms of data and computational efficiency compared with earlier ML schemes. To this end, we generalize the neuroevolution potential approach to enable the prediction of rank one and two tensors to obtain the tensorial neuroevolution potential (TNEP) scheme. We apply the resulting framework to construct models for the dipole moment, polarizability, and susceptibility of molecules, liquids, and solids and show that our approach compares favorably with several ML models from the literature with respect to accuracy and computational efficiency. Finally, we demonstrate the application of the TNEP approach to the prediction of infrared and Raman spectra of liquid water, a molecule (PTAF-), and a prototypical perovskite with strong anharmonicity (BaZrO3). The TNEP approach is implemented in the free and open source software package gpumd, which makes this methodology readily available to the scientific community.

Postpartum Length of Stay and Hospital Readmission Before and During the Coronavirus Disease 2019 (COVID-19) Pandemic.

OBJECTIVE: To compare postpartum hospitalization length of stay (LOS) and hospital readmission among obstetric patients before (March 2017-February 2020; prepandemic) and during the coronavirus disease 2019 (COVID-19) pandemic (March 2020-February 2021). METHODS: We conducted a retrospective cohort study, using Epic Systems' Cosmos research platform, of obstetric patients who delivered between March 1, 2017, and February 28, 2021, at 20-44 weeks of gestation and were discharged within 7 days of delivery. The primary outcome was short postpartum hospitalization LOS (less than two midnights for vaginal births and less than three midnights for cesarean births) and secondary outcome was hospital readmission within 6 weeks of postpartum hospitalization discharge. Analyses compared outcomes before and during the pandemic using standardized differences and Bayesian logistic mixed-effects models, among all births and stratified by mode of delivery. RESULTS: Of the 994,268 obstetric patients in the study cohort, 742,113 (74.6%) delivered prepandemic and 252,155 (25.4%) delivered during the COVID-19 pandemic. During the COVID-19 pandemic, the percentage of short postpartum hospitalizations increased among all births (28.7-44.5%), vaginal births (25.4-39.5%), and cesarean births (35.3-55.1%), which was consistent with the adjusted analysis (all births: adjusted odds ratio [aOR] 2.35, 99% credible interval 2.32-2.39; vaginal births: aOR 2.14, 99% credible interval 2.11-2.18; cesarean births aOR 2.90, 99% credible interval 2.83-2.98). Although short postpartum hospitalizations were more common during the COVID-19 pandemic, there was no change in readmission in the unadjusted (1.4% vs 1.6%, standardized difference=0.009) or adjusted (aOR 1.02, 99% credible interval 0.97-1.08) analyses for all births or when stratified by mode of delivery. CONCLUSION: Short postpartum hospitalization LOS was significantly more common during the COVID-19 pandemic for obstetric patients with no change in hospital readmissions within 6 weeks of postpartum hospitalization discharge. The COVID-19 pandemic created a natural experiment, suggesting shorter postpartum hospitalization may be reasonable for patients who are self-identified or health care professional-identified as appropriate for discharge.

Birth Hospital Length of Stay and Rehospitalization During COVID-19.

OBJECTIVES: To determine if birth hospitalization length of stay (LOS) and infant rehospitalization changed during the coronavirus disease 2019 (COVID-19) era among healthy, term infants. METHODS: Retrospective cohort study using Epic's Cosmos data from 35 health systems of term infants discharged ≤5 days of birth. Short birth hospitalization LOS (vaginal birth <2 midnights; cesarean birth <3 midnights) and, secondarily, infant rehospitalization ≤7 days after birth hospitalization discharge were compared between the COVID-19 (March 1 to August 31, 2020) and prepandemic eras (March 1 to August 31, 2017, 2018, 2019). Mixed-effects models were used to estimate adjusted odds ratios (aORs) comparing the eras. RESULTS: Among 202 385 infants (57 110 from the COVID-19 era), short birth hospitalization LOS increased from 28.5% to 43.0% for all births (vaginal: 25.6% to 39.3%, cesarean: 40.1% to 61.0%) during the pandemic and persisted after multivariable adjustment (all: aOR 2.30, 95% confidence interval [CI] 2.25-2.36; vaginal: aOR 2.12, 95% CI 2.06-2.18; cesarean: aOR 3.01, 95% CI 2.87-3.15). Despite shorter LOS, infant rehospitalizations decreased slightly during the pandemic (1.2% to 1.1%); results were similar in adjusted analysis (all: aOR 0.83, 95% CI 0.76-0.92; vaginal: aOR 0.82, 95% CI 0.74-0.91; cesarean: aOR 0.87, 95% CI 0.69-1.10). There was no change in the proportion of rehospitalization diagnoses between eras. CONCLUSIONS: Short infant LOS was 51% more common in the COVID-19 era, yet infant rehospitalization within a week did not increase. This natural experiment suggests shorter birth hospitalization LOS among family- and clinician-selected, healthy term infants may be safe with respect to infant rehospitalization, although examination of additional outcomes is needed.

Scattering of obliquely incident shear waves from a cylindrical cavity.

Prior work has proposed the use of ultrasonic angle-beam shear wave techniques to detect cracks of varying angular location around fastener sites by generating and detecting creeping waves. To better understand the nature of the scattering problem and quantify the role of creeping waves in fastener site inspections, a 3D analytical model was developed for the propagation and scattering of an obliquely incident plane shear wave from a cylindrical cavity with arbitrary shear wave polarization. The generation and decay of the spiral creeping waves was found to be dependent on both the angle of incidence and polarization of the plane shear wave. A difference between the angle of displacement in 3D and the direction of propagation for the spiral creeping wave was observed and attributed to differences in the curvature of the cavity surface for the tangential and vertical (z) directions. Using the model, practical insight was presented on measuring the displacement response in the far-field from the hole. Both analytical and experimental results highlighted the value of the diffracted and leaky spiral creeping wave signals for nondestructive evaluation of a crack located on the cavity. Last, array and signal processing methods are discussed to improve the resolution of the weaker creeping wave signals in the presence of noise.

Coronavirus Disease 2019 (COVID-19) Pandemic and Pregnancy Outcomes in a U.S. Population.

OBJECTIVE: To examine whether the coronavirus disease 2019 (COVID-19) pandemic altered risk of adverse pregnancy-related outcomes and whether there were differences by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection status among pregnant women. METHODS: In this retrospective cohort study using Epic's Cosmos research platform, women who delivered during the pandemic (March-December 2020) were compared with those who delivered prepandemic (matched months 2017-2019). Within the pandemic epoch, those who tested positive for SARS-CoV-2 infection were compared with those with negative test results or no SARS-CoV-2 diagnosis. Comparisons were performed using standardized differences, with a value greater than 0.1 indicating meaningful differences between groups. RESULTS: Among 838,489 women (225,225 who delivered during the pandemic), baseline characteristics were similar between epochs. There were no significant differences in adverse pregnancy outcomes between epochs (standardized difference<0.10). In the pandemic epoch, 108,067 (48.0%) women had SARS-CoV-2 testing available; of those, 7,432 (6.9%) had positive test results. Compared with women classified as negative for SARS-CoV-2 infection, those who tested positive for SARS-CoV-2 infection were less likely to be non-Hispanic White or Asian or to reside in the Midwest and more likely to be Hispanic, have public insurance, be obese, and reside in the South or in high social vulnerability ZIP codes. There were no significant differences in the frequency of preterm birth (8.5% vs 7.6%, standardized difference=0.032), stillbirth (0.4% vs 0.4%, standardized difference=-0.002), small for gestational age (6.4% vs 6.5%, standardized difference=-0.002), large for gestational age (7.7% vs 7.7%, standardized difference=-0.001), hypertensive disorders of pregnancy (16.3% vs 15.8%, standardized difference=0.014), placental abruption (0.5% vs 0.4%, standardized difference=0.007), cesarean birth (31.2% vs 29.4%, standardized difference=0.039), or postpartum hemorrhage (3.4% vs 3.1%, standardized difference=0.019) between those who tested positive for SARS-CoV-2 infection and those classified as testing negative. CONCLUSION: In a geographically diverse U.S. cohort, the frequency of adverse pregnancy-related outcomes did not differ between those delivering before compared with during the pandemic, nor between those classified as positive compared with negative for SARS-CoV-2 infection during pregnancy.

Electrostatic Self-Assembly: Understanding the Significance of the Solvent.

The electrostatic deposition of particles has become a very effective route to the assembly of many nanoscale materials. However, fundamental limitations to the process are presented by the choice of solvent, which can either suppress or promote self-assembly depending on specific combinations of nanoparticle/surface/solvent properties. A new development in the theory of electrostatic interactions between polarizable objects provides insight into the effect a solvent can have on electrostatic self-assembly. Critical to assembly is the requirement for a minimum charge on a surface of an object, below which a solvent can suppress electrostatic attraction. Examples drawn from the literature are used to illustrate how switches in behavior are mediated by the solvent; these in turn provide a fundamental understanding of electrostatic particle-surface interactions applicable to many areas of materials science and nanotechnology.

Electrokinetic ion transport through unsaturated soil: 2. Application to a heterogeneous field site.

Results of a field demonstration of electrokinetic transport of acetate through an unsaturated heterogeneous soil are compared to numerical modeling predictions. The numerical model was based on the groundwater flow and transport codes MODFLOW and MT3D modified to account for electrically induced ion transport. The 6-month field demonstration was conducted in an unsaturated layered soil profile where the soil moisture content ranged from 4% to 28% (m3 m(-3)). Specially designed ceramic-cased electrodes maintained a steady-state moisture content and electric potential field between the electrodes during the field demonstration. Acetate, a byproduct of acetic acid neutralization of the cathode electrolysis reaction, was transported from the cathode to the anode by electromigration. Field demonstration results indicated preferential transport of acetate through soil layers exhibiting higher moisture content/electrical conductivity. These field transport results agree with theoretical predictions that electromigration velocity is proportional to a power function of the effective moisture content. A numerical model using a homogeneous moisture content/electrical conductivity domain did not adequately predict the acetate field results. Numerical model predictions using a three-layer electrical conductivity/moisture content profile agreed qualitatively with the observed acetate distribution. These results suggest that field heterogeneities must be incorporated into electrokinetic models to predict ion transport at the field-scale.

Electrokinetic ion transport through unsaturated soil: 1. Theory, model development, and testing.

An electromigration transport model for non-reactive ion transport in unsaturated soil was developed and tested against laboratory experiments. This model assumed the electric potential field was constant with respect to time, an assumption valid for highly buffered soil, or when the electrode electrolysis reactions are neutralized. The model also assumed constant moisture contents and temperature with respect to time, and that electroosmotic and hydraulic transport of water through the soil was negligible. A functional relationship between ionic mobility and the electrolyte concentration was estimated using the chemical activity coefficient. Tortuosity was calculated from a mathematical relationship fitted to the electrical conductivity of the bulk pore water and soil moisture data. The functional relationship between ionic mobility, pore-water concentration, and tortuosity as a function of moisture content allowed the model to predict ion transport in heterogeneous unsaturated soils. The model was tested against laboratory measurements assessing anionic electromigration as a function of moisture content. In the test cell, a strip of soil was spiked with red dye No 40 and monitored for a 24-h period while a 10-mA current was maintained between the electrodes. Electromigration velocities predicted by the electromigration transport model were in agreement with laboratory experimental results. Both laboratory-measured and model-predicted dye migration results indicated a maximum transport velocity at moisture contents less than saturation due to competing effects between current density and tortuosity as moisture content decreases.

Synthesis and anticancer activity of (E)-2-benzothiazole hydrazones.

Benzothiazole hydrazones have been synthesized and evaluated for their in vitro antiproliferative activity against three human cancer cell lines: HL-60 (leukemia), MDAMB-435 (breast) and HCT-8 (colon). The good cytotoxicity for the three cancer cell lines and theoretical profile of compounds 3o and 3p pointed them as promising lead molecules for anticancer drug design.