Deep-Learning Interatomic Potential Connects Molecular Structural Ordering to the Macroscale Properties of Polyacrylonitrile.

Polyacrylonitrile (PAN) is an important commercial polymer, bearing atactic stereochemistry resulting from nonselective radical polymerization. As such, an accurate, fundamental understanding of governing interactions among PAN molecular units is indispensable for advancing the design principles of final products at reduced processability costs. While ab initio molecular dynamics (AIMD) simulations can provide the necessary accuracy for treating key interactions in polar polymers, such as dipole-dipole interactions and hydrogen bonding, and analyzing their influence on the molecular orientation, their implementation is limited to small molecules only. Herein, we show that the neural network interatomic potentials (NNIPs) that are trained on the small-scale AIMD data (acquired for oligomers) can be efficiently employed to examine the structures and properties at large scales (polymers). NNIP provides critical insight into intra- and interchain hydrogen-bonding and dipolar correlations and accurately predicts the amorphous bulk PAN structure validated by modeling the experimental X-ray structure factor. Furthermore, the NNIP-predicted PAN properties, such as density and elastic modulus, are in good agreement with their experimental values. Overall, the trend in the elastic modulus is found to correlate strongly with the PAN structural orientations encoded in the Hermans orientation factor. This study enables the ability to predict the structure-property relations for PAN and analogues with sustainable ab initio accuracy across scales.

Adsorption, Orientation, and Speciation of Amino Acids at Air-Aqueous Interfaces for the Direct Air Capture of CO2.

Amino acids make up a promising family of molecules capable of direct air capture (DAC) of CO2 from the atmosphere. Under alkaline conditions, CO2 reacts with the anionic form of an amino acid to produce carbamates and deactivated zwitterionic amino acids. The presence of the various species of amino acids and reactive intermediates can have a significant effect on DAC chemistry, the role of which is poorly understood. In this study, all-atom molecular dynamics (MD) based computational simulations and vibrational sum frequency generation (vSFG) spectroscopy studies were conducted to understand the role of competitive interactions at the air-aqueous interface in the context of DAC. We find that the presence of potassium bicarbonate ions, in combination with the anionic and zwitterionic forms of amino acids, induces concentration and charge gradients at the interface, generating a layered molecular arrangement that changes under pre- and post-DAC conditions. In parallel, an enhancement in the surface activity of both anionic and zwitterionic forms of amino acids is observed, which is attributed to enhanced interfacial stability and favorable intermolecular interactions between the adsorbed amino acids in their anionic and zwitterionic forms. The collective influence of these competitive interactions, along with the resulting interfacial heterogeneity, may in turn affect subsequent capture reactions and associated rates. These effects underscore the need to consider dynamic changes in interfacial chemical makeup to enhance DAC efficiency and to develop successful negative emission and storage technologies.

Observation of a promethium complex in solution.

Lanthanide rare-earth metals are ubiquitous in modern technologies1-5, but we know little about chemistry of the 61st element, promethium (Pm)6, a lanthanide that is highly radioactive and inaccessible. Despite its importance7,8, Pm has been conspicuously absent from the experimental studies of lanthanides, impeding our full comprehension of the so-called lanthanide contraction phenomenon: a fundamental aspect of the periodic table that is quoted in general chemistry textbooks. Here we demonstrate a stable chelation of the 147Pm radionuclide (half-life of 2.62 years) in aqueous solution by the newly synthesized organic diglycolamide ligand. The resulting homoleptic PmIII complex is studied using synchrotron X-ray absorption spectroscopy and quantum chemical calculations to establish the coordination structure and a bond distance of promethium. These fundamental insights allow a complete structural investigation of a full set of isostructural lanthanide complexes, ultimately capturing the lanthanide contraction in solution solely on the basis of experimental observations. Our results show accelerated shortening of bonds at the beginning of the lanthanide series, which can be correlated to the separation trends shown by diglycolamides9-11. The characterization of the radioactive PmIII complex in an aqueous environment deepens our understanding of intra-lanthanide behaviour12-15 and the chemistry and separation of the f-block elements16.

Heterogeneous Structure, Mechanisms of Counterion Exchange, and the Spacer Salt Effect in Complex Molten Salt Mixtures Including LaCl3.

Complex molten chloride salt mixtures of uranium, magnesium, and sodium are top candidates for promising nuclear energy technologies to produce electricity based on molten salt reactors. From a local structural perspective, LaCl3 is similar to UCl3 and hence a good proxy to study these complex salt mixtures. As fission products, lanthanide salts and their mixtures are also very important in their own right. This article describes from an experimental and theory perspective how very different the structural roles of MgCl2 and NaCl are in mixtures with LaCl3. We find that, whereas MgCl2 becomes an integral part of multivalent ionic networks, NaCl separates them. In a recent article (J. Am. Chem. Soc. 2022, 144, 21751-21762) we have called the disruptive behavior of NaCl "the spacer salt effect". Because of the heterogeneous nature of these salt mixtures, there are multiple structural motifs in the melt, each with its particular free energetics. Our work identifies and quantifies these; it also elucidates the mechanisms through which Cl- ions exchange between Mg2+-rich and La3+-rich environments.

Tracing mechanistic pathways and reaction kinetics toward equilibrium in reactive molten salts.

In the dynamic environment of multi-component reactive molten salts, speciation unfolds as a complex process, involving multiple competing reaction pathways that are likely to face free energy barriers before reaching the reaction equilibria. Herein, we unravel intricate speciation in the AlCl3-KCl melt compositions with rate theory and ab initio molecular dynamics simulations. We find that the compositions with 100 and 50 mol% AlCl3 exclusively comprise neutral Al2Cl6 dimers and charged AlCl4- monomers, respectively. In intermediate AlCl3-KCl compositions, the chemical speciation proves to be a very complex process, requiring over 0.5 nanosecond to reach an equilibrium distribution of multiple species. It is a consequence of the competitive formation and dissociation of additional species, including charged Al dimers, trimers, and tetramers. Here, the species formation occurs through ion exchange events, which we explain by computing free energy landscapes and employing a Marcus-like rate theory. We show that both interspecies and intraspecies ion exchanges are probable and are dictated by the local structural reorganization reflected in the change of local coulombic fields. The species distributions are validated by comparing computed Raman spectra and neutron structure factors with the available experimental data. We find an excellent simulation-experiment agreement in both cases. Nevertheless, Raman spectroscopy turns out to be particularly advantageous for distinguishing between unique species distributions because of the distinct vibrational signatures of different species. The mechanistic insight into reaction dynamics gained in this study will be essential for the advancement of molten salts as reactive media in high-temperature energy applications.

Synergistic Assembly of Charged Oligomers and Amino Acids at the Air-Water Interface: An Avenue toward Surface-Directed CO2 Capture.

Interfaces are considered a major bottleneck in the capture of CO2 from air. Efforts to design surfaces to enhance CO2 capture probabilities are challenging due to the remarkably poor understanding of chemistry and self-assembly taking place at these interfaces. Here, we leverage surface-specific vibrational spectroscopy, Langmuir trough techniques, and simulations to mechanistically elucidate how cationic oligomers can drive surface localization of amino acids (AAs) that serve as CO2 capture agents speeding up the apparent rate of absorption. We demonstrate how tuning these interfaces provides a means to facilitate CO2 capture chemistry to occur at the interface, while lowering surface tension and improving transport/reaction probabilities. We show that in the presence of interfacial AA-rich aggregates, one can improve capture probabilities vs that of a bare interface, which holds promise in addressing climate change through the removal of CO2 via tailored interfaces and associated chemistries.

Urinary extracellular vesicle dynamics in Parkinson's disease patients with urinary dysfunction.

Parkinson's disease (PD) presents with severe motor manifestations and a plethora of non-motor symptoms. Urinary dysfunctions are one of the most common non-motor symptoms of PD patients responsible for reduced quality of life. Urinary extracellular vesicles (EVs) are mostly considered to originate from the cells in the urogenital tract. In this study, we have performed urinary EV analysis in 29 PD cases with varied severity of urinary dysfunction and correlated it with the EV dynamics in 29 age-matched controls. In the studied cases, apart from urinary dysfunction, symptoms of depression, anxiety, cognitive dysfunction, sleep, and wakefulness were observed in >75% of the cases. No significant difference in urinary EV size, concentration and urinary EV protein concentration was observed between PD cases with urinary dysfunction and controls. However, a significant positive association was observed between urinary EV concentration and motor scores (p = 0.042), while no association was observed between urinary EV concentration and urinary dysfunction scores. Chronic stress induced by motor symptoms could be one of the reasons for excessive EV production in PD patients with urinary dysfunctions. Large-scale studies on the association of urinary EV dynamics with motor and non-motor symptoms may provide additional information on urinary dysfunction in PD.

Tuning aminopolycarboxylate chelators for efficient complexation of trivalent actinides.

The complexation of trivalent lanthanides and minor actinides (Am3+, Cm3+, and Cf3+) by the acyclic aminopolycarboxylate chelators 6,6'-((ethane-1,2-diylbis-((carboxymethyl)azanediyl))bis-(methylene))dipicolinic acid (H4octapa) and 6,6'-((((4-(1-(2-(2-(2-hydroxyethoxy)ethoxy)ethyl)-1H-1,2,3-triazol-4-yl)pyridine-2,6-diyl)bis-(methylene))bis-((carboxymethyl)azanediyl))bis-(methylene)) dipicolinic acid (H4pypa-peg) were studied using potentiometry, spectroscopy, competitive complexation liquid-liquid extraction, and ab initio molecular dynamics simulations. Two studied reagents are strong multidentate chelators, well-suited for applications seeking radiometal coordination for in-vivo delivery and f-element isolation. The previously reported H4octapa forms a compact coordination packet, while H4pypa-peg is less sterically constrained due to the presence of central pyridine ring. The solubility of H4octapa is limited in a non-complexing high ionic strength perchlorate media. However, the introduction of a polyethylene glycol group in H4pypa-peg increased the solubility without influencing its ability to complex the lanthanides and minor actinides in solution.

Magnetic resonance imaging investigations in patients with metallic dental prosthesis: "The associated dilemma for medical fraternity and the dentist's role".

Background: Interdisciplinary referrals for dental examination in hospital setups are common before radiotherapy, kidney transplants, or magnetic resonance imaging (MRI). The patients who walk in could be random patients with metallic or porcelain-fused-to-metal prostheses done elsewhere but might require an opinion before the MRI. This leaves quite a responsibility on the consulting dentist to green signal the procedure. There is a lack of evidence in the literature, to confirm the absence of any untoward consequence during such MRI, which might leave the dentist in dilemma. Dental materials' magnetic behavior raises concern regarding whether they are 100% nonferromagnetic; furthermore, the examining dentist might be unaware of the metal used (Co-Cr, Ni-Cr, or trace elements). Clinicians may also come across full-mouth rehabilitated patients with multiple crown-bridge prostheses or metallic superstructure for implant prostheses. Research in the area leaves many unanswered questions because most studies have evaluated artifacts during MRI and are in vitro. Titanium is considered to be safe due to its paramagnetic behavior, whereas the literature does not rule out the probability of dislodgment of other porcelain fused to metal (PFM) prostheses. Due to less reported literature there exists dilemma to ascertain MRI in these patients. An online Google Search, PubMed, and gray literature portray the ambiguity associated with metal and PFM crowns and their magnetic behavior during MRI. Most studies were associated with the artifacts caused during MRI and methods of reducing them under in vitro situations. The concern for dislodgment has also been expressed in a few reports. Technique: Certain steps of a pre-MRI checkup and an innovative technique have been discussed to assure patient safety during the MRI. Conclusion: The technique explained is inexpensive and a quick aid that can be executed before the investigation. Clinical and Research Implications: There is a need to study and understand the magnetic behavior of Co-Cr and Ni-Cr crowns in the presence of various MRI strengths.

Chemical Feedback in the Self-Assembly and Function of Air-Liquid Interfaces: Insight into the Bottlenecks of CO2 Direct Air Capture.

As fossil fuels remain a major source of energy throughout the world, developing efficient negative emission technologies, such as direct air capture (DAC), which remove carbon dioxide (CO2) from the air, becomes critical for mitigating climate change. Although all DAC processes involve CO2 transport from air into a sorbent/solvent, through an air-solid or air-liquid interface, the fundamental roles the interfaces play in DAC remain poorly understood. Herein, we study the interfacial behavior of amino acid (AA) solvents used in DAC through a combination of vibrational sum frequency generation spectroscopy and molecular dynamics simulations. This study revealed that the absorption of atmospheric CO2 has antagonistic effects on subsequent capture events that are driven by changes in bulk pH and specific ion effects that feedback on surface organization and interactions. Among the three AAs (leucine, valine, and phenylalanine) studied, we identify and separate behaviors from CO2 loading, chemical changes, variations in pH, and specific ion effects that tune structural and chemical degrees of freedom at the air-aqueous interface. The fundamental mechanistic findings described here are anticipated to enable new approaches to DAC based on exploiting interfaces as a tool to address climate change.

Nucleation Rate Theory for Coordination Number: Elucidating Water-Mediated Formation of a Zigzag Na2SO4 Morphology.

Predicting and controlling nanostructure formation during nucleation can pave the way to synthesizing novel energy materials via crystallization. However, such control over nucleation and crystallization remains challenging due to an inadequate understanding of critical factors that govern evolving atomistic structures and dynamics. Herein, we utilize coordination number as a reaction coordinate and rate theory to investigate how sodium sulfate, commonly known as a phase-change energy material, nucleates in a supersaturated aqueous solution. In conjunction with ab initio and force field-based molecular dynamics simulation, the rate theoretical analysis reveals that sodium sulfate from an initially dissolved metastable state transits to a heterogeneous mixture of prenucleated clusters and finally to a large cylindrical zigzag morphology. Measurements of Raman spectra and their ab initio modeling confirm that this nucleated morphology contains a few waters for every sulfate. Rate processes such as solvent exchange and desolvation exhibit high sensitivity to the evolving prenucleation/nucleation structures, providing a means to distinguish between critical nucleation precursors. Desolvation and forming the first-shell interionic coordination structure via monomer-by-monomer addition around sulfates are found to explain the formation of large nuclei. Thus, a detailed understanding of the step-by-step structure formation across scales has been achieved. This can be leveraged to predict nucleation-related structures and dynamics and potentially control the synthesis of novel phase-change materials for energy applications.

Complete Description of the LaCl3-NaCl Melt Structure and the Concept of a Spacer Salt That Causes Structural Heterogeneity.

Lanthanides are important fission products in molten salt reactors, and understanding their structure and that of their mixtures is relevant to many scientific and technological problems including the recovery and separation of rare earth elements using molten salt electrolysis. The literature on molten salts and specifically on LaCl3 and LaCl3-NaCl mixtures is often fragmented, with different experiments and simulations coinciding in their explanation for certain structural results but contradicting or questioning for others. Given the very practical importance that actinide and lanthanide salts have for energy applications, it is imperative to arrive at a clear unified picture of their local and intermediate-range structure in the neat molten state and when mixed with other salts. This article aims to unequivocally answer a set of specific questions: is it correct to think of long-lived octahedral coordination structures for La3+? What is the nature as a function of temperature of networks and intermediate-range order particularly upon dilution of the trivalent ion salt? Is the so-called scattering first sharp diffraction peak (FSDP) for neat LaCl3 truly indicative of intermediate-range order? If so, why is there a new lower-q peak when mixed with NaCl? Are X-ray scattering and Raman spectroscopy results fully consistent and easily described by simulation results? We will show that answers to these questions require that we abandon the idea of a most prominent coordination state for M3+ ions and instead think of multiple competing coordination states in exchange due to significant thermal energy in the molten state.

SVD-CLAHE boosting and balanced loss function for Covid-19 detection from an imbalanced Chest X-Ray dataset.

Covid-19 disease has had a disastrous effect on the health of the global population, for the last two years. Automatic early detection of Covid-19 disease from Chest X-Ray (CXR) images is a very crucial step for human survival against Covid-19. In this paper, we propose a novel data-augmentation technique, called SVD-CLAHE Boosting and a novel loss function Balanced Weighted Categorical Cross Entropy (BWCCE), in order to detect Covid 19 disease efficiently from a highly class-imbalanced Chest X-Ray image dataset. Our proposed SVD-CLAHE Boosting method is comprised of both oversampling and under-sampling methods. First, a novel Singular Value Decomposition (SVD) based contrast enhancement and Contrast Limited Adaptive Histogram Equalization (CLAHE) methods are employed for oversampling the data in minor classes. Simultaneously, a Random Under Sampling (RUS) method is incorporated in major classes, so that the number of images per class will be more balanced. Thereafter, Balanced Weighted Categorical Cross Entropy (BWCCE) loss function is proposed in order to further reduce small class imbalance after SVD-CLAHE Boosting. Experimental results reveal that ResNet-50 model on the augmented dataset (by SVD-CLAHE Boosting), along with BWCCE loss function, achieved 95% F1 score, 94% accuracy, 95% recall, 96% precision and 96% AUC, which is far better than the results by other conventional Convolutional Neural Network (CNN) models like InceptionV3, DenseNet-121, Xception etc. as well as other existing models like Covid-Lite and Covid-Net. Hence, our proposed framework outperforms other existing methods for Covid-19 detection. Furthermore, the same experiment is conducted on VGG-19 model in order to check the validity of our proposed framework. Both ResNet-50 and VGG-19 model are pre-trained on the ImageNet dataset. We publicly shared our proposed augmented dataset on Kaggle website (https://www.kaggle.com/tr1gg3rtrash/balanced-augmented-covid-cxr-dataset), so that any research community can widely utilize this dataset. Our code is available on GitHub website online (https://github.com/MrinalTyagi/SVD-CLAHE-and-BWCCE).

Transferable Deep Learning Potential Reveals Intermediate-Range Ordering Effects in LiF-NaF-ZrF4 Molten Salt.

LiF-NaF-ZrF4 multicomponent molten salts are promising candidate coolants for advanced clean energy systems owing to their desirable thermophysical and transport properties. However, the complex structures enabling these properties, and their dependence on composition, is scarcely quantified due to limitations in simulating and interpreting experimental spectra of highly disordered, intermediate-ranged structures. Specifically, size-limited ab initio simulations and accuracy-limited classical models used in the past are unable to capture a wide range of fluctuating motifs found in the extended heterogeneous structures of liquid salt. This greatly inhibits our ability to design tailored compositions and materials. Here, accurate, efficient, and transferable machine learning potentials are used to predict structures far beyond the first coordination shell in LiF-NaF-ZrF4. Neural networks trained at only eutectic compositions with 29% and 37% ZrF4 are shown to accurately simulate a wide range of compositions (11-40% ZrF4) with dramatically different coordination chemistries, while showing a remarkable agreement with theoretical and experimental Raman spectra. The theoretical Raman calculations further uncovered the previously unseen shift and flattening of bending band at ∼250 cm-1 which validated the simulated extended-range structures as observed in compositions with higher than 29% ZrF4 content. In such cases, machine learning-based simulations capable of accessing larger time and length scales (beyond 17 Å) were critical for accurately predicting both structure and ionic diffusivities.

A Holistic Approach for Elucidating Local Structure, Dynamics, and Speciation in Molten Salts with High Structural Disorder.

To examine ion solvation, exchange, and speciation for minority components in molten salts (MS) typically found as corrosion products, we propose a multimodal approach combining extended X-ray absorption fine structure (EXAFS) spectroscopy, optical spectroscopy, ab initio molecular dynamics (AIMD) simulations, and rate theory of ion exchange. Going beyond conventional EXAFS analysis, our method can accurately quantify populations of different coordination states of ions with highly disordered coordination environments via linear combination fitting of the EXAFS spectra of these coordination states computed from AIMD to the experimental EXAFS spectrum. In a case study of dilute Ni(II) dissolved in the ZnCl2+KCl melts, our method reveals heterogeneous distributions of coordination states of Ni(II) that are sensitive to variations in temperature and melt composition. These results are fully explained by the difference in the chloride exchange dynamics at varied temperatures and melt compositions. This insight will enable a better understanding and control of ion solubility and transport in MS.

X-ray scattering reveals ion clustering of dilute chromium species in molten chloride medium.

Enhancing the solar energy storage and power delivery afforded by emerging molten salt-based technologies requires a fundamental understanding of the complex interplay between structure and dynamics of the ions in the high-temperature media. Here we report results from a comprehensive study integrating synchrotron X-ray scattering experiments, ab initio molecular dynamics simulations and rate theory concepts to investigate the behavior of dilute Cr3+ metal ions in a molten KCl-MgCl2 salt. Our analysis of experimental results assisted by a hybrid transition state-Marcus theory model reveals unexpected clustering of chromium species leading to the formation of persistent octahedral Cr-Cr dimers in the high-temperature low Cr3+ concentration melt. Furthermore, our integrated approach shows that dynamical processes in the molten salt system are primarily governed by the charge density of the constituent ions, with Cr3+ exhibiting the slowest short-time dynamics. These findings challenge several assumptions regarding specific ionic interactions and transport in molten salts, where aggregation of dilute species is not statistically expected, particularly at high temperature.

Unraveling Local Structure of Molten Salts via X-ray Scattering, Raman Spectroscopy, and Ab Initio Molecular Dynamics.

In this work, we resolve a long-standing issue concerning the local structure of molten MgCl2 by employing a multimodal approach, including X-ray scattering and Raman spectroscopy, along with the theoretical modeling of the experimental spectra based on ab initio molecular dynamics (AIMD) simulations utilizing several density functional theory (DFT) methods. We demonstrate the reliability of AIMD simulations in achieving excellent agreement between the experimental and simulated spectra for MgCl2 and 50 mol % MgCl2 + 50 mol % KCl, and ZnCl2, thus allowing structural insights not directly available from experiment alone. A thorough computational analysis using five DFT methods provides a convergent view that octahedrally coordinated magnesium in pure MgCl2 upon melting preferentially coordinates with five chloride anions to form distorted square pyramidal polyhedra that are connected via corners and to a lesser degree via edges. This is contrasted with the results for ZnCl2, which does not change its tetrahedral coordination on melting. Although the five-coordinate MgCl53- complex was not considered in the early literature, together with an increasing tendency to form a tetrahedrally coordinated complex with decreasing the MgCl2 content in the mixture with alkali metal chloride systems, current work reconciles the results of most previous seemingly contradictory experimental studies.

Spatial prediction of COVID-19 epidemic using ARIMA techniques in India.

The latest Coronavirus (COVID-19) has become an infectious disease that causes millions of people to infect. Effective short-term prediction models are designed to estimate the number of possible events. The data obtained from 30th January to 26 April, 2020 and from 27th April 2020 to 11th May 2020 as modelling and forecasting samples, respectively. Spatial distribution of disease risk analysis is carried out using weighted overlay analysis in GIS platform. The epidemiologic pattern in the prevalence and incidence of COVID-2019 is forecasted with the Autoregressive Integrated Moving Average (ARIMA). We assessed cumulative confirmation cases COVID-19 in Indian states with a high daily incidence in the task of time-series forecasting. Such efficiency metrics such as an index of increasing results, mean absolute error (MAE), and a root mean square error (RMSE) are the out-of-samples for the prediction precision of model. Results shows west and south of Indian district are highly vulnerable for COVID-2019. The accuracy of ARIMA models in forecasting future epidemic of COVID-2019 proved the effectiveness in epidemiological surveillance. For more in-depth studies, our analysis may serve as a guide for understanding risk attitudes and social media interactions across countries.