Machine-Learning-Driven High-Throughput Screening of Transition-Metal Atom Intercalated g-C3N4/MX2 (M = Mo, W; X = S, Se, Te) Heterostructures for the Hydrogen Evolution Reaction

Rising global energy demand, accompanied by environmental concerns linked to conventional fossil fuels, necessitates a shift toward cleaner and sustainable alternatives. This study focuses on the machine-learning (ML)-driven high-throughput screening of transition-metal (TM) atom intercalated g-C3N4/MX2 (M = Mo, W; X = S, Se, Te) heterostructures to unravel the rich landscape of possibilities for enhancing the hydrogen evolution reaction (HER) activity. The stability of the heterostructures and the intercalation within the substrates are verified through adhesion and binding energies, showcasing the significant impact of chalcogenide selection on the interaction properties. Based on hydrogen adsorption Gibbs free energy (ΔGH) computed via density functional theory (DFT) calculations, several ML models were evaluated, particularly random forest regression (RFR) emerges as a robust tool in predicting HER activity with a low mean absolute error (MAE) of 0.118 eV, thereby paving the way for accelerated catalyst screening. The Shapley Additive exPlanation (SHAP) analysis elucidates pivotal descriptors that influence the HER activity, including hydrogen adsorption on the C site (HC), MX layer (HMX), S site (HS), and intercalation of TM atoms at the N site (IN). Overall, our integrated approach utilizing DFT and ML effectively identifies hydrogen adsorption on the N site (site-3) of g-C3N4 as a pivotal active site, showcasing exceptional HER activity in heterostructures intercalated with Sc and Ti, underscoring their potential for advancing catalytic performance.

Accelerating In Silico Discovery of Metal-Organic Frameworks for Ethane/Ethylene and Propane/Propylene Separation: A Synergistic Approach Integrating Molecular Simulation, Machine Learning, and Active Learning

Cryogenic distillation, a currently employed method for C2H4/C2H6 and C3H6/C3H8 mixture separation, is energy-intensive, prompting the research toward alternative technologies, including adsorbent-based separation. In this work, we combine machine learning (ML) technique with high-throughput screening to screen ∼23,000 hypothetical metal-organic frameworks (MOFs) for paraffin (C2H6 and C3H8) selective adsorbent separation. First, structure-based prescreening was employed to remove MOFs with undesired geometric properties. Further, a random forest model built upon the multicomponent grand canonical Monte Carlo (m-GCMC) simulation data of training set MOFs was found to be the most successful in learning the relationship between MOF features and olefin/paraffin mixture separation. Using this technique, the separation performance of the remaining (test set) MOFs was predicted, and the top-performing MOFs were identified. We also employed active learning (AL) to evaluate its effectiveness in improving the prediction of olefin/paraffin selectivity. AL was discovered to be ∼29 times more efficient than the best-supervised ML model, as it was able to identify the top materials in limited training data and at a fraction of computational cost and time as compared to ML techniques. Among the top selected materials, framework chemistry was found to be the most important parameter. Nickel and copper (as a metal node) in a tfzd and hms topological arrangement respectively, were discovered to be a prevalent attribute in high-performing MOFs, further demonstrating the prominent significance of framework chemistry. Additionally, the top MOFs discovered were studied in detail and further compared to the previously reported MOFs. These MOFs show the highest selectivity for C2H4/C2H6 and C3H6/C3H8 mixture separation, as reported until date. The hierarchical strategy devised in this study will facilitate the quick screening of MOFs across multiple databases toward industrially significant separation processes by leveraging molecular simulations and AL.

Does freezing induce self-assembly of polymers? A molecular dynamics study

This work investigates the freezing-induced self-assembly (FISA) of polyvinyl alcohol (PVA) and PVA-like polymers using molecular dynamics simulations. In particular, the effect of the degree of supercooling, degree of polymerization, polymer type, and initial local concentration on the FISA was studied. It was found that the preeminent factor responsible for FISA is not the diffusion of the polymers away from the nucleating ice front, but the increase in the polymer's local concentration upon freezing of the solvent (water). At a higher degree of supercooling, the polymers are engulfed by the growing ice front, impeding their diffusion into the supercooled solution and finally inhibiting their self-assembly. Conversely, at a relatively lower degree of supercooling, the rate of diffusion of the polymers into the supercooled solution is higher, which increases their local concentration and results in FISA. FISA was also observed to depend on the polymer-solvent interactions. Strongly favorable solute-solvent interactions hinder the self-assembly, whereas unfavorable solute-solvent interactions promote the self-assembly. The polymer and aggregate morphology were investigated using the radius of gyration, end-to-end distance, and asphericity analysis. This study brings molecular insights into the quintessential factors governing self-assembly via freezing of the solvent, which is a novel self-assembly technique especially suitable for biomedical applications.

An amine decorated MOF for direct capture of CO2 from ambient air

A Zn(II)-based metal-organic framework (MOF) was synthesized by the self-assembly of the dicarboxylate ligand terephthalic acid (TPA), 2-aminoterephthalic acid (NH2-TPA) and N-donor auxiliary ligand 1,4-bis(4-pyridinylmethyl)piperazine (bpmp) using Zn(NO3)2·6H2O under hydrothermal conditions. {[Zn(TPA)0.5(NH2TPA)0.5(bpmp)]·DMF·7H2O}n (framework 1) has an sra topology with a BET surface area of 756 m2 g-1. The microporous nature of the framework is apparent from the significant CO2 adsorption capacities observed at various temperatures: 57 cc g-1 at 283 K, 46 cc g-1 at 293 K, 37 cc g-1 at 303 K, and 30 cc g-1 at 313 K. The considerable CO2 adsorption may be caused by the existence of free carboxylate and amine substituents that interact with the gas molecules and micropores. At room temperature, the activated MOF readily converts CO2 into cyclic carbonates when a suspension of the MOF is bubbled with ambient air and different epoxides under solvent-free conditions. The amine groups located within the pores of the MOF interact with CO2 molecules, enhancing their sorption and conversion to cyclic carbonates. However, due to interpenetration within framework 1, only smaller size epoxides can be accommodated and converted to cyclic carbonates in good yields. Additionally, the effectiveness of the catalyst is further confirmed by the positive outcomes obtained from the hot filtration control test. Grand canonical Monte Carlo (GCMC) molecular simulations were utilized to gain a better understanding of molecular interactions. GCMC results are in line with the experiments. The substantial adsorption of CO2 can be ascribed to the strong intermolecular interactions that occur between the amine groups within the framework and the CO2 molecules.

Does supercooled water retain its universal nucleation behavior under shear at high pressure?

Understanding the nucleation of homogeneous flow systems at high pressures is vital in protein crystallization and cryopreservation, where high pressure prevents the freezing of biological samples. This study examines the behavior of ice nucleation under shear at various pressures and explores the universal nucleation behavior of the sheared systems applied to supercooled water at higher pressures. In this study, the nucleation rates for the TIP4P/Ice model via a seeding method based on extended classical nucleation theory (CNT) are computed at pressures of 1, 100, 500, 700, and 1000 bar and a constant temperature of 240 K. Using extended CNT with explicitly embodying the shear rate, we analyzed the dependence of pressure on the transport and thermodynamic properties. In line with previous studies, we observed that Δμliq-ice and viscosity decrease while diffusivity increases with an increase in pressure. Furthermore, we showed that the dependence of the nucleation rate on shear at higher pressure is non-monotonic, with the maximum at optimal shear rates between 107 and 108 s-1. Our results demonstrate a non-monotonic pressure dependence of the optimal shear rates, which could originate from a violation of the Stokes-Einstein relation.

Understanding the role of polymers on the nucleating behavior of water in dilute supercooled solutions

Understanding the nucleation behavior of water in dilute polymeric solutions is quintessential for the development of suitable artificial ice recrystallization inhibition (IRI) agents. Although poly(vinyl alcohol) (PVA) is found to be one of the most potent biomimetic IRI agents, the molecular understanding of the nucleation behavior of water in the presence of PVA is still lacking. Here, we use molecular dynamics to elucidate the role of concentration, degree of supercooling, degree of polymerization, and amphiphilicity of PVA and PVA-like polymers on the homogeneous nucleation of water in dilute polymeric solutions using the seeding method. Using classical nucleation theory (CNT), our simulations indicate an increase in the chemical potential difference between ice and melt that favors ice nucleation. However, it also predicts a significant increase in the ice-melt interfacial energy that impedes nucleation. The relative increase in the interfacial energy dominates the increase in the chemical potential difference, which results in a decrease in the nucleation rate of water with an increase in the solute concentration. This study contradicts the previous simulation study that suggested the promotion of homogeneous ice nucleation by PVA and supports the experimental observations of the heterogeneous origins of ice nucleation. Our results also suggest the non-classical origins of ice nucleation in polymeric solutions and the limitation of the CNT in predicting heterogeneous ice nucleation in polymeric solutions.

Machine Learning-Driven Discovery of Key Descriptors for CO2 Activation over Two-Dimensional Transition Metal Carbides and Nitrides

Fusing high-throughput quantum mechanical screening techniques with modern artificial intelligence strategies is among the most fundamental ─yet revolutionary─ science activities, capable of opening new horizons in catalyst discovery. Here, we apply this strategy to the process of finding appropriate key descriptors for CO₂ activation over two-dimensional transition metal (TM) carbides/nitrides (MXenes). Various machine learning (ML) models are developed to screen over 114 pure and defective MXenes, where the random forest regressor (RFR) ML scheme exhibits the best predictive performance for the CO₂ adsorption energy, with a mean absolute error ± standard deviation of 0.16 ± 0.01 and 0.42 ± 0.06 eV for training and test data sets, respectively. Feature importance analysis revealed d-band center (ε_d), surface metal electronegativity (χ_M), and valence electron number of metal atoms (M_V) as key descriptors for CO₂ activation. These findings furnish a fundamental basis for designing novel MXene-based catalysts through the prediction of potential indicators for CO₂ activation and their posterior usage.

Molecular Insights on Morphology, Composition, and Stability of Mixed Micelles Formed by Ionic Surfactant and Nonionic Block Copolymer in Water Using Coarse-Grained Molecular Dynamics Simulations

The nanoscale association domains are the ultimate determinants of the macroscopic properties of complex fluids involving amphiphilic polymers and surfactants, and hence, it is foremost important to understand the role of polymer/surfactant concentration on these domains. We have used coarse-grained molecular dynamics simulations to investigate the effect of polymer/surfactant concentration on the morphology of poly(ethylene oxide)-poly(propylene oxide)-poly(ethylene oxide) (PEO-PPO-PEO, i.e., pluronics or poloxamers) block copolymer, and ionic surfactants sodium dodecyl sulfate (SDS), mixed micelles in aqueous solution. The proclivity of the surfactant to form the mixed micelles is also probed using umbrella sampling simulations. In this study, we observed that the core of the pluronic + SDS formed mixed micelles consists of PPO, the alkyl tail of SDS, and some water molecules, whereas the PEO, water, and sulfate headgroups of SDS form a shell, consistent with experimental observations. The micelles are spherical at high-pluronic/low-SDS compositions, ellipsoidal at high-SDS/low-pluronic compositions, and wormlike-cylindrical at high-pluronic/high-SDS compositions. The transitions in micelle morphology are governed by the solvent accessible surface area of mixed aggregates, electrostatic repulsion between SDS-headgroups, and dehydration of PEO and PPO segments. The free energy barrier for SDS escape is much higher in mixed micelles than in pure SDS micelles, indicating a stronger tendency for SDS to form pluronic-SDS mixed micelles.

Integrated docking and enhanced sampling-based selection of repurposing drugs for SARS-CoV-2 by targeting host dependent factors

Since the onset of global pandemic, the most focused research currently in progress is the development of potential drug candidates and clinical trials of existing FDA approved drugs for other relevant diseases, in order to repurpose them for the COVID-19. At the same time, several high throughput screenings of drugs have been reported to inhibit the viral components during the early course of infection but with little proven efficacies. Here, we investigate the drug repurposing strategies to counteract the coronavirus infection which involves several potential targetable host proteins involved in viral replication and disease progression. We report the high throughput analysis of literature-derived repurposing drug candidates that can be used to target the genetic regulators known to interact with viral proteins based on experimental and interactome studies. In this work we have performed integrated molecular docking followed by molecular dynamics (MD) simulations and free energy calculations through an expedite in silico process where the number of screened candidates reduces sequentially at every step based on physicochemical interactions. We elucidate that in addition to the pre-clinical and FDA approved drugs that targets specific regulatory proteins, a range of chemical compounds (Nafamostat, Chloramphenicol, Ponatinib) binds to the other gene transcription and translation regulatory proteins with higher affinity and may harbour potential for therapeutic uses. There is a rapid growing interest in the development of combination therapy for COVID-19 to target multiple enzymes/pathways. Our in silico approach would be useful in generating leads for experimental screening for rapid drug repurposing against SARS-CoV-2 interacting host proteins.Communicated by Ramaswamy H. Sarma.

Efficient CO2 Capture and Activation on Novel Two-Dimensional Transition Metal Borides

The large-scale production of CO₂ in the atmosphere has triggered global warming, the greenhouse effect, and ocean acidification. The CO₂ conversion to valuable chemical products or its capture and storage are of fundamental importance to mitigate the greenhouse effect on the environment. Therefore, exploring new two-dimensional (2D) materials is indispensable due to their potential intriguing properties. Here, we report a new family of 2D transition metal borides (M₂B₂, M = Sc, Ti, V, Cr, Mn, and Fe; known as MBenes) and demonstrate their static and dynamic stability. These MBenes show a metallic nature and exhibit excellent electrical conductivity. The CO₂ adsorption energy on MBenes ranges from -1.04 to -3.95 eV and exhibits the decreasing order as Sc₂B₂ > Ti₂B₂ > V₂B₂ > Cr₂B₂ > Mn₂B₂ > Fe₂B₂. The spin-polarization calculation shows a reduction in the adsorption energy for magnetic systems. Bader charge transfer indicates the formation of CO₂^δ- moiety on the MBene surface, so-called activated CO₂, which is essential for its reaction with other surface chemicals. Differential charge density plots reveal a significant charge accumulation around the CO₂ molecule. Our theoretical results predict the usage of new MBenes as a cost-effective catalyst for CO₂ capture and activation.

Insights into the Phase Diagram of Pluronic L64 Using Coarse-Grained Molecular Dynamics Simulations

We investigate the concentration-dependent phase diagram of pluronic L64 in aqueous media at 300 and 320 K using coarse-grained (CG) molecular dynamics (MD) simulations. The CG model is derived by adapting the Martini model for nonbonded interactions along with the Boltzmann inversion (BI) of bonded interactions from all-atom (AA) simulations. Our derived CG model successfully captures the experimentally observed micellar-, hexagonal-, lamellar-, and polymer-rich solution phase. The end-to-end distance reveals the conformational change from an open-chain structure in the micellar phase to a folded-chain structure in the lamellar phase, increasing the orientational order. An increase in temperature leads to expulsion of water molecules from the L64 moiety, suggesting an increase in L64 hydrophobicity. Thermodynamic analysis using the two-phase thermodynamics (2PT) method suggests the entropy of the system decreases with increasing L64 concentration and the decrease in free energy (F) with temperature is mainly driven by the entropic factor (-TS). Further, the increase in aggregation number at lower concentrations and self-assembly at very high concentrations is energetically driven, whereas the change from the micellar phase to the lamellar phase with increasing L64 concentration is entropically driven. Our model provides molecular insights into L64 phases which can be further explored to design functionality-based suprastructures for drug delivery and tissue engineering applications.

The pressure induced phase diagram of double-layer ice under confinement: a first-principles study

Here, we present double-layer ice confined within various carbon nanotubes (CNTs) using state-of-the-art pressure induced (-5 GPa to 5 GPa) dispersion corrected density functional theory (DFT) calculations. We find that the double-layer ice exhibits remarkably rich and diverse phase behaviors as a function of pressure with varying CNT diameters. The lattice cohesive energies for various pure double layer ice phases follow the order of hexagonal > pentagonal > square tube > hexagonal-close-packed (HCP) > square > buckled-rhombic (b-RH). The confinement width was found to play a crucial role in the square and square tube phases in the intermediate pressure range of about 0-1 GPa. Unlike the phase transition in pure bilayer ice structures, the relative enthalpies demonstrate that the pentagonal phase, rather than the hexagonal structure, is the most stable ice polymorph at ambient pressure as well as in a deep negative pressure region, whereas the b-RH phase dominates under high pressure. The relatively short O⋯O distance of b-RH demonstrates the presence of a strong hydrogen bonding network, which is responsible for stabilizing the system.

Mechanistic insights for electrochemical reduction of CO2 into hydrocarbon fuels over O-terminated MXenes

Two-dimensional (2D) transition metal carbides/nitrides (MXenes) has attracted intensive attention in electrochemical reduction of CO2 into renewable fuels and chemical feedstock. Although encouraging progress has been made so far, but...

Building Unit Extractor for Metal-Organic Frameworks

Metal-organic frameworks (MOFs) have relevance in extensive applications such as gas adsorption, separation, and energy storage. The tunability demonstrated by MOFs has encouraged research on MOF database generation via distinct methodologies. One of the crucial stages of these procedures is pre-processing, which often includes extraction of the building units (BUs). The process of BU extraction is intricate, and it is further amplified with the presence of solvent molecules/ions in the structure. This work presents MOF BU developer (mBUD), a platform to deconstruct the BUs, such as metal nodes, organic linkers, and functional groups of the MOF structure. The deconstruction algorithm has been assessed on the MOF structures of the CoRE MOF 2019 database. A total of 2,580 BUs have been extracted and provided as a database. This platform has been utilized to create a ready-to-use database of unique BUs deconstructed from the CoRE MOF database. We have also provided the web version of mBUD that can be easily used to extract BUs. These BUs can be employed to develop hypothetical MOF structures. It is envisaged that the BU database built with the deconstruction platform will aid the design of novel application-specific MOFs.

Phase Behavior of Pure PSPC and PEGylated Multicomponent Lipid and Their Interaction with Paclitaxel: An All-Atom MD Study

Exploring structural behavior of pure 1-palmitoyl-2-stearoyl-sn-glycero-3-phosphocholine (PSPC) and multicomponent PSPC and 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N[amino(poly(ethylene glycol))-2000] (DSPE-PEG₂₀₀₀) membranes and their interaction with pharmaceutically important drugs carry huge importance in drug delivery. Using all-atom molecular dynamics (MD) simulations, we investigated the phase behavior of pure and PEGylated membranes at the temperature range of 280-360 K. We observe a gel-to-liquid crystalline phase transition for pure PSPC between 320 and 330 K, and in the case of multicomponent membranes, at 320 K, a coexistence of order-disorder phases is observed, which gradually transform to a complete liquid crystalline to gel phase between 320 and 310 K. We further studied the interaction of Paclitaxel with pure PSPC and PEGylated bilayers and elucidated the interaction behavior of Paclitaxel at the bilayer interfaces. Understanding of structural and interaction behaviors of the PEGylated bilayers with Paclitaxel will help to explore Paclitaxel-based drug applications in the future.

High-Throughput Screening of Atomic Defects in MXenes for CO2 Capture, Activation, and Dissociation

The capture, activation, and dissociation of carbon dioxide (CO₂) is of fundamental interest to overcome the ramifications of the greenhouse effect. In this regard, high-throughput screening of two-dimensional MXenes has been examined using well-resolved first-principles simulations through DFT-D3 dispersion correction. We systematically investigated different types of structural defects to understand their influence on the performance of M₂X-type MXenes. Defect calculations demonstrate that the formation of M₂C(V_MC) and M₂N(V_MN) vacancies require higher energy, while M₂C(V_C) and M₂N(V_N) vacancies are favorable to form during the synthesis of M₂X-type MXenes. The M₂X-type MXenes from group III to VII series show remarkable behavior for active capturing of CO₂, especially group IV (Ti₂X and Zr₂X) MXenes exhibit unprecedentedly high adsorption energies and charge transfer (>2e) from M₂X to CO₂. The potential CO₂ capture, activation, and dissociation abilities of MXenes are emanated from Dewar interactions involving hybridization between π orbitals of CO₂ and metal d-orbitals. Our high-throughput screening demonstrates chemisorption of CO₂ on pure and defective MXenes, followed by dissociation into CO and O species.

Universal Nucleation Behavior of Sheared Systems

Using molecular simulations and a modified classical nucleation theory, we study the nucleation, under flow, of a variety of liquids: different water models, Lennard-Jones, and hard sphere colloids. Our approach enables us to analyze a wide range of shear rates inaccessible to brute-force simulations. Our results reveal that the variation of the nucleation rate with shear is universal. A simplified version of the theory successfully captures the nonmonotonic temperature dependence of the nucleation behavior, which is shown to originate from the violation of the Stokes-Einstein relation.

Effects of interfaces on structure and dynamics of water droplets on a graphene surface: A molecular dynamics study

The structure and dynamics of water droplets on a bilayer graphene surface are investigated using molecular dynamics simulations. The effects of solid/water and air/water interfaces on the local structure of water droplets are analyzed in terms of the hydrogen bond distribution and tetrahedral order parameter. It is found that the local structure in the core region of a water droplet is similar to that in liquid water. On the other hand, the local structure of water molecules at the solid/water and air/water interfaces, referred to as the interface and surface regions, respectively, consists mainly of three-coordinated molecules that are greatly distorted from a tetrahedral structure. This study reveals that the dynamics in different regions of the water droplets affects the intermolecular vibrational density of states: It is found that in the surface and interface regions, the intensity of vibrational density of states at ∼50 cm^-1 is enhanced, whereas those at ∼200 and ∼500 cm^-1 are weakened and redshifted. These changes are attributed to the increase in the number of molecules having fewer hydrogen bonds in the interface and surface regions. Both single-molecule and collective orientation relaxations are also examined. Single-molecule orientation relaxation is found to be marginally slower than that in liquid water. On the other hand, the collective orientation relaxation of water droplets is found to be significantly faster than that of liquid water because of the destructive correlation of dipole moments in the droplets. The negative correlation between distinct dipole moments also yields a blueshifted libration peak in the absorption spectrum. It is also found that the water-graphene interaction affects the structure and dynamics of the water droplets, such as the local water structure, collective orientation relaxation, and the correlation between dipole moments. This study reveals that the water/solid and water/air interfaces strongly affect the structure and intermolecular dynamics of water droplets and suggests that the intermolecular dynamics, such as energy relaxation dynamics, in other systems with interfaces are different from those in liquid water.

The NeST (Neoadjuvant systemic therapy in breast cancer) study: National Practice Questionnaire of United Kingdom multi-disciplinary decision making

BACKGROUND

Neoadjuvant systemic therapy (NST) is increasingly used in the treatment of breast cancer, yet it is clear that there is significant geographical variation in its use in the UK. This study aimed to examine stated practice across UK breast units, in terms of indications for use, radiological monitoring, pathological reporting of treatment response, and post-treatment surgical management.

METHODS

Multidisciplinary teams (MDTs) from all UK breast units were invited to participate in the NeST study. A detailed questionnaire assessing current stated practice was distributed to all participating units in December 2017 and data collated securely usingREDCap. Descriptive statistics were calculated for each questionnaire item.

RESULTS

Thirty-nine MDTs from a diverse range of hospitals responded. All MDTs routinely offered neoadjuvant chemotherapy (NACT) to a median of 10% (range 5-60%) of patients. Neoadjuvant endocrine therapy (NET) was offered to a median of 4% (range 0-25%) of patients by 66% of MDTs. The principal indication given for use of neoadjuvant therapy was for surgical downstaging. There was no consensus on methods of radiological monitoring of response, and a wide variety of pathological reporting systems were used to assess tumour response. Twenty-five percent of centres reported resecting the original tumour footprint, irrespective of clinical/radiological response. Radiologically negative axillae at diagnosis routinely had post-NACT or post-NET sentinel lymph node biopsy (SLNB) in 73.0 and 84% of centres respectively, whereas 16% performed SLNB pre-NACT. Positive axillae at diagnosis would receive axillary node clearance at 60% of centres, regardless of response to NACT.

DISCUSSION

There is wide variation in the stated use of neoadjuvant systemic therapy across the UK, with general low usage of NET. Surgical downstaging remains the most common indication of the use of NAC, although not all centres leverage the benefits of NAC for de-escalating surgery to the breast and/or axilla. There is a need for agreed multidisciplinary guidance for optimising selection and management of patients for NST. These findings will be corroborated in phase II of the NeST study which is a national collaborative prospective audit of NST utilisation and clinical outcomes.

Homogeneous nucleation of sheared liquids: advances and insights from simulations and theory

One of the most ubiquitous and technologically important phenomena in nature is the nucleation of homogeneous flowing systems. The microscopic effects of shear on a nucleating system are still imperfectly understood, although in recent years a consistent picture has emerged. The opposing effects of shear can be split into two major contributions for simple atomic and molecular liquids: increase of the energetic cost of nucleation, and enhancement of the kinetics. In this perspective, we describe the latest computational and theoretical techniques which have been developed over the past two decades. We collate and unify the overarching influences of shear, temperature, and supersaturation on the process of homogeneous nucleation. Experimental techniques and capabilities are discussed, against the backdrop of results from simulations and theory. Although we primarily focus on simple systems, we also touch upon the sheared nucleation of more complex systems, including glasses and polymer melts. We speculate on the promising directions and possible advances that could come to fruition in the future.

Rationally Designed Semiconducting 2D Surface-Confined Metal-Organic Network

Two-dimensional (2D) surface-confined metal-organic networks (SMONs) are metal-doped self-assembled monolayers of molecules on solid surfaces. We report the formation of uniform large-area solution-processed semiconducting SMONs of Pd and Zn with mellitic acid (MA) on a highly oriented pyrolytic graphite (HOPG) surface under ambient conditions. The microscopic structure is determined using scanning tunneling microscopy (STM), atomic force microscopy (AFM), and X-ray photoelectron spectroscopy (XPS). Using tunneling spectroscopy, we observed a reduction in the band gap of ≈900 and ≈300 meV for MA-Pd and MA-Zn SMONs, respectively, compared to the pure MA assembly. Concomitant density functional theory (DFT) calculations reveal that the coordination geometry and microscopic arrangement give rise to the observed reduction in the band gap. The dispersion of the frontier bands and their delocalization due to strong electronic coupling (between MA and metal) suggest that the MA-Pd SMON could potentially be a 2D electronic material.

Fe3O4-Functionalized Boron Nitride Nanosheets as Novel Adsorbents for Removal of Arsenic(III) from Contaminated Water

We report the application of Fe3O4-functionalized boron nitride nanosheets (BNNS-Fe3O4 nanocomposite) for the remediation of As(III) ions from contaminated water. The specific surface area of the nanocomposite has been found as 179.5 m2 g-1. Due to its superparamagnetic nature at room temperature, the nanocomposite can be easily isolated from the solution under an external magnetic field. For As(III) ions, the maximum adsorption capacity of the nanocomposite is obtained as 30.3 mg g-1, which is approximately 4 times more than that of the bare BNNSs (8.5 mg g-1). The results from density functional theory calculations are also in close agreement with experimental findings and show that As(OH)3 binds more (∼4 times) efficiently to the BNNS-Fe3O4 nanocomposite than the bare BNNSs, implying a 4 times higher adsorption capacity of the nanocomposite. Especially, it is found that the synthesized nanocomposite could lessen the concentration of As(III) ions from 134 to 2.67 ppb in a solution at 25 °C. On increasing the temperature to 35 °C, the level of As(III) ions could be reduced from 556 to 10.29 ppb, which is close to the limit prescribed by the World Health Organization. The adsorbent was easily separable and showed regeneration properties. These outcomes depict the prospect of using BNNS-Fe3O4 nanocomposites as commercial adsorbents for the removal of As(III) ions from contaminated water.

Revealing the Limits of Intermolecular Interactions: Molecular Rings of Ferrocene Derivatives on Graphite Surface

We report the formation of discrete molecular rings/spirals of small molecules (1,3-dithia derivatives of ferrocene) on a highly oriented pyrolytic graphite (HOPG) surface. On the basis of microscopy and theoretical calculations, molecular level arrangement within the molecular rings is understood. The molecular rings show a limiting inner diameter, and we interpret it to be related to the critical intermolecular interaction limit. This limiting value of the inner diameter is surprisingly correlated with that observed for molecular rings/disks of a few reported molecules. The correlation reveals that molecular rings formed typically by weak van der Waals interactions should always show a limiting inner diameter and should be independent of molecular structure, size, and chemical nature.

A simple molecular design for tunable two-dimensional imine covalent organic frameworks for optoelectronic applications

We systematically study the electronic structure, carrier mobility and work function of imine based 2D-COFs. The bandgaps of these semiconducting materials can be tailored by doping with nitrogen for tunable electronic/optoelectronic properties.

A general topological network criterion for exploring the structure of icy nanoribbons and monolayers

We develop intuitive metrics for quantifying complex nucleating systems under confinement.

Electronic Structure of a Semiconducting Imine-Covalent Organic Framework

Imine COF (covalent organic framework) based on the Schiff base reaction between p-phenylenediamine (PDA) and benzene-1,3,5-tricarboxaldehyde (TCA) was prepared on the HOPG-air (air=humid N₂ ) interface and characterized using different probe microscopies. The role of the molar ratio of TCA and PDA has been explored, and smooth domains of imine COF up to a few μm are formed for a high TCA ratio (>2) compared to PDA. It is also observed that the microscopic roughness of imine COF is strongly influenced by the presence of water (in the reaction chamber) during the Schiff base reaction. The electronic property of imine COF obtained by tunneling spectroscopy and dispersion corrected density functional theory (DFT) calculation are comparable and show semiconducting nature with a band gap of ≈1.8 eV. Further, we show that the frontier orbitals are delocalized entirely over the framework of imine COF. The calculated cohesive energy shows that the stability of imine COF is comparable to that of graphene.

Magnetite-Coated Boron Nitride Nanosheets for the Removal of Arsenic(V) from Water

It is widely known that the existence of arsenic (As) in water negatively affects humans and the environment. We report the synthesis, characterization, and application of boron nitride nanosheets (BNNSs) and Fe₃O₄-functionalized BNNS (BNNS-Fe₃O₄) nanocomposite for removal of As(V) ions from aqueous systems. The morphology, surface properties, and compositions of synthesized nanomaterials were examined using scanning electron microscopy, transmission electron microscopy, X-ray powder diffraction, surface area analysis, zero-point charge, and magnetic moment determination. The BNNS-Fe₃O₄ nanocomposites have a specific surface area of 119 m² g^-1 and a high saturation magnetization of 49.19 emu g^-1. Due to this strong magnetic property at room temperature, BNNS-Fe₃O₄ can be easily separated in solution by applying an external magnetic field. From the activation energies, it was found that the adsorption of As(V) ions on BNNSs and BNNS-Fe₃O₄ was due to physical and chemical adsorption, respectively. The maximum adsorption capacity of BNNS-Fe₃O₄ nanocomposite for As(V) ions has been found to be 26.3 mg g^-1, which is 5 times higher than that of unmodified BNNSs (5.3 mg g^-1). This closely matches density functional theory simulations, where it is found that binding energies between BNNS-Fe₃O₄ nanocomposite and As(OH)₅ are 5 times higher than those between BNNSs and As(OH)₅, implying 5 times higher adsorption capacity of BNNS-Fe₃O₄ nanocomposite than unmodified BNNSs. More importantly, it was observed that the synthesized BNNS-Fe₃O₄ nanocomposite could reduce As(V) ion concentration from 856 ppb in a solution to below 10 ppb (>98.83% removal), which is the permissible limit according to World Health Organization recommendations. Finally, the synthesized adsorbent showed both separation and regeneration properties. These findings demonstrate the potential of BNNS-Fe₃O₄ nanocomposite for commercial application in separation of As(V) ions from potable and waste water streams.

Density Functional Theory Study of Aspirin Adsorption on BCN Sheets and their Hydrogen Evolution Reaction Activity: a Comparative Study with Graphene and Hexagonal Boron Nitride

We explored the aspirin adsorption and their hydrogen evolution reaction (HER) activity in waste water of borocarbonitride sheets. Our results indicate that BCN sheets considered here show HER activity and exhibit superior performance regarding adsorption of aspirin in waste water in comparison with graphene and hexagonal boron nitride (h-BN). The drug molecule (aspirin) possesses a strong affinity to BCN, with the order of binding energy on following the order BCN∼h-BN>graphene. Upon drug adsorption, the band gap of h-BN is found to be reduced by up to 33 %, whereas the bandgaps of graphene and BCN remain unaltered that makes BCN a potential candidate for HER in waste water.

Optimization of USSP duration for enhanced corrosion resistance of AA7075

This investigation was carried out following our earlier work on the effect of ultrasonic shot peening (USSP) on corrosion resistance of the 7075 aluminium alloy in 3.5 wt% NaCl solution to optimize the duration of USSP. The samples not treated with USSP and different samples treated with USSP were subjected to potentiodynamic polarization and electrochemical impedance spectroscopy. Among the specimens USSP treated from 5 to 30 s, the one USSP treated for 15 s (USSP 15) was found to exhibit highest corrosion potential (E_corr) and lowest corrosion current density (i_corr). Corrosion products were characterized by Scanning Electron Microscopy (SEM) and X-ray Photoelectron Spectroscopy (XPS). Scanning Kelvin Probe Force Microscopy (SKPFM) was used to measure the surface free potential. The enhanced corrosion resistance of the USSP 15 sample was found to be due to combined effect of surface nanostructure of the matrix, homogeneity and refinement of second phase precipitates. There was enhancement in formation of adherent passive layer in the USSP15 specimen.

Impact of specialist management on survival from radiation-associated angiosarcoma of the breast

BACKGROUND

Radiation-associated angiosarcoma of the breast (RAAS) is a rare complication of adjuvant radiotherapy associated with poor survival. The British Sarcoma Group guidelines recommend that all angiosarcomas are referred to a sarcoma multidisciplinary team, although there is no recommendation that patients are managed within a sarcoma service. The aims of this study were to compare survival, complete excision rates and local recurrence rates of patients managed within a sarcoma service and those managed within local hospitals.

METHODS

All patients with RAAS referred to a regional sarcoma service between 1998 and 2015 were identified from prospective databases. Patient records, and radiology, pathology and operation notes were reviewed retrospectively.

RESULTS

Thirty-six patients were operated on with curative intent; 26 were managed by the sarcoma service (of whom 21 underwent radical excision of the irradiated field followed by chest wall reconstruction) and ten were managed locally. Median age was 69·5 (range 43-85) years. Disease-specific survival was significantly longer in patients managed by the sarcoma service than in those managed locally: median 91·1 (range 69·2-113·0) versus 48·8 (18·6-79·1) months respectively (P = 0·012). Overall survival rates were similar (P = 0·112). There was no difference in complete excision rate (18 of 26 in sarcoma service versus 5 of 10 in local services; P = 0·456), although the local recurrence rate was significantly lower among patients managed by the sarcoma service (9 of 26 versus 8 of 10; P = 0·015).

CONCLUSION

Specialist management of RAAS leads to fewer local recurrences and improved disease-specific survival. Early referral and management within specialist units is recommended.

A coarse-grain molecular dynamics study of oil-water interfaces in the presence of silica nanoparticles and nonionic surfactants

In this work, we have studied the effect of hydrophilic silica nanoparticles (NPs), in the presence of nonionic surfactants (Triethylene glycol monododecyl ether and Tween 20), on the oil-water (n-octane-water, n-dodecane-water and n-hexadecane-water) interfacial tensions (IFTs) at 300 K, using coarse-grained molecular dynamics simulations based on the MARTINI force field. Simulation results indicate that silica NPs solely do not affect the IFT. However, the silica NPs may or may not increase the IFT of oil-water containing nonionic surfactant, depending on the tendency of the surfactant to adsorb on the surface of NPs. The adsorption occurs due to the formation of hydrogen bonds, and adsorption increases with a decrease in pH, as seen in experimental studies. In this work, we found that the oil-water IFT increases with an increasing amount of adsorption of the surfactant on NPs. At a fixed amount of adsorption of the surfactant on NPs, the IFT behavior is indifferent to the change in concentration of NPs. However, the IFT decreases with an increase in surfactant concentration. We present a detailed analysis of the density profile and intrinsic width of the interface. The IFT behavior is found to correlate extremely well with the intrinsic width of the interface. The current study provides an explanation for the increase in IFT observed in a recent experiment [N. R. Biswal et al., J. Phys. Chem. B 120, 7265-7274 (2016)] for various types of NPs and nonionic surfactant systems.

Effect of Maternal Socio-demographic Factors and Child Feeding Practice on Wasting Among Under Five Years Children in Slum Area of Rupandehi District in Nepal

INTRODUCTION

Childhood wasting although well studied elsewhere, it has not been well understood about in slum area of Nepal. This study aimed to assess effect of socio-demographic factors and child feeding practice in the determination of wasting among the children under five years of age in slum area of Nepal.

METHODS

A community based cross-sectional study was performed among 150 children under five years of age from the slum area of Nepal between 1st January and 28th February 2013 using simple random sampling techniques. Multivariate analyses were performed to determine factors associated with wasting controlling the potential confounders.

RESULTS

In a total of 150 under five years children, the prevalence of wasting was 56 (37.33%). The current study demonstrated that children of mothers from dalit Adjusted Odds Ratio (OR) 11.5; 95% CI: 03.1 - 41.3), aadibasi/janajati (AOR 4.6; 95% CI: 1.2 - 17.0), illiterate mothers (AOR 3.6; 95% CI: 1.1 - 13.6), laborer mothers (AOR 2.1; 95% CI: 1.1-9.4), child age group 25-36 months (AOR 2.8; 95% CI: 1.5-5.3), multiple child birth order (AOR 10.0; 95% CI: 2.5-25.0), children who were not fed colostrums (AOR 15.0; 95% CI: 1.25-10.0) were more likely to develop wasting compared to their counterparts.

CONCLUSIONS

As incremental childhood wasting is associated with maternal socio-demographic factors and child feeding practice, health promotion strategies should focus maternal socio-demographic factors, age of children and early initiation of breast feeding for the improved child nutrition in slum area of Nepal.

Janus Gold Nanoparticles from Nanodroplets of Alkyl Thiols: A Molecular Dynamics Study

Janus particles provide an asymmetry in structure, which can impart diverse functionalities leading to immense importance in various applications, ranging from targeted delivery to interfacial phenomena, including catalysis, electronics, and optics. In this work, we present results of a molecular dynamics study of the growth mechanism of coating on gold nanoparticles (AuNPs) from droplets of n-alkyl thiols with different chain lengths (C5 and C11) and terminal groups (CH₃ and COOH). The effect of chain lengths and functional groups on the formation of a monolayer of alkyl thiols on AuNPs is investigated. A two-step mechanism, initiated by the binding of the droplet to the nanoparticle surface with a time constant on the order of ∼1 ns, followed by the diffusion-driven growth with a larger time constant (on the order of 100 ns), is shown to capture the growth dynamics of the monolayer. It is observed that the time required for complete wetting increases with an increase in the chain length. Moreover, the monolayer formation is slowed down in the presence of carboxyl groups because of strong hydrogen bonding. The kinetics of the n-alkyl thiols coating on the nanoparticles is found to be independent of the droplet size but carboxyl-terminated thiols spread more with increasing droplet size. Furthermore, different time constants for different chains and functional groups yield Janus coating when two droplets of alkyl thiols with different terminal groups are allowed to form monolayers on the nanoparticle. The Janus balance (β) for different combinations of alkyl thiols and nanoparticle sizes varies in the range of 0.42-0.71.