Browse Articles

Comparative plastome evaluation, phylogenomic analysis, and DNA signatures of medicinally important malvaceous genera and their adulterants

Scalable free energy computation of polymers in explicit solvent using TMMC and pre-generated conformation libraries

We present a novel application of the Transition Matrix Monte Carlo (TMMC) algorithm to compute the relative free energies of polymers in explicit solvents as a function of a selected order parameter. Our method leverages a pre-generated library of polymer conformations in vacuum, coupled with explicit solvent environments using the Growth Expanded Ensemble (GEE) framework. The integration of TMMC within GEE addresses sampling challenges by introducing bias in Monte Carlo simulations while enabling the computation of unbiased probability distributions and relative free energies. A key advantage of our approach is its flexibility—the polymer conformation library can be generated using any sampling technique, including Molecular Dynamics or Monte Carlo simulations, in implicit or explicit solvents and at different temperatures. The method is adaptable to any collective variable (CV) and can be extended to compute free energies as a function of multiple CVs. Furthermore, its parallelizable structure makes it highly scalable on multi-core central processing units and graphics processing unit architectures. To demonstrate its applicability, we apply it to a fully flexible polymer model consisting of Lennard-Jones particles connected via a harmonic potential, immersed in an explicit solvent of Lennard-Jones particles. The relative free energies are computed as a function of the radius of gyration. Results for three different solvents, obtained by varying the polymer–solvent interaction strength, reveal that the polymer preferentially adopts an extended conformation in good solvents and a collapsed conformation in poor solvents, consistent with theoretical expectations. Our method provides a computationally efficient and scalable framework for free energy calculations, with broad applications in polymer physics and macromolecular thermodynamics.

Correction: Comprehensive study of rapid capacity fade in prismatic Li-ion cells with flexible Packaging

Chemical interactions in active droplets

Active droplets serve as simple artificial model systems to elucidate the chemical and hydrodynamics-driven interactions between biological organisms. We investigate the pairwise interactions between such micellar solubilization based active droplets, capable of self-generating chemical and hydrodynamic fields. We experimentally demonstrate that the solute Péclet number (Pe), characterizing the relative strength of its convective to diffusive transport, plays a crucial role in determining how the chemical and hydrodynamic fields impact their interactions. At low Pe, strong chemo-repulsive interactions dominate, resulting in consistent scattering behavior regardless of the approach symmetry. In contrast, at high Pe, hydrodynamic interactions become dominant, enabling transient contact, synchronized motion, or reduced repulsion. Furthermore, by analyzing droplet–wake interactions across both high and low Pe regimes, we demonstrate that the scattering behavior is invariant to the relative approach orientation and is fundamentally governed by the droplet’s intrinsic chemical polarity, which in turn is set by its Pe number. Our results not only offer robust experimental validation of recent theoretical predictions on the scattering behavior of active droplets but also present a clear rationale for the observed angular deflection and its invariance to the approach angle of droplets. Our findings establish a systematic framework correlating the Pe-dependent intrinsic chemical polarity of droplets to the scattering outcomes in both droplet–droplet and droplet–wake interactions. These mechanistic insights advance our understanding of active droplet interactions and can serve as a basis for modeling and engineering collective behaviors in chemically active systems within the framework of multi-agent interactions, where simple local interaction rules result in emergent collective dynamics.

Effect of hardness matching of aero spline sub-materials on wear performance

A better multi-reference Davidson correction for internally contracted and uncontracted multi-reference configuration interaction calculations

We propose a new multi-reference Davidson correction and show that it gives a much better prediction of the role of quadruple excitations compared to existing corrections. However, due to the neglect of triple excitations, our most promising correction is a hybrid scheme whereby the average of the new correction and a conventional correction is used. This hybrid correction performs well in a wide variety of cases, including the avoided crossing of two roots of the same symmetry.

Detection of asbestos-based cement rooftops in conflict-affected settings using EnMAP hyperspectral data: a research article

Active wetting transitions induced by rotational noise at solid interfaces

We investigate the wetting transitions displayed by the collection of active Brownian particles confined within rigid, impenetrable, flat walls. In our computational study using Brownian dynamics simulations, the wall–particle interactions are implemented with a short-range repulsive potential. Our analyses reveal that an enhanced rotational diffusion at the walls can be used as a control parameter for wetting transitions in the dense aggregates of active particles at the wall. Increasing the wall rotational diffusion destabilizes a uniform, complete wetting state, and the aggregate shows morphological transitions. We observe a sequence of morphological transitions with an increase in wall rotational diffusion: symmetric complete wetting, asymmetric complete wetting, partial wetting with droplet formation, and drying. We compute the contact angle in the PW state as a function of activity and rotational noise. Our analysis indicates that these transitions are linked to enhanced kinetic energy fluctuations of particles and bubble formations in the dense state. We further characterize the nature of these transitions by systematically analyzing an order parameter. Our work shows that modifying local reorientation rates alone is sufficient to induce wetting transitions in active systems.

A nationwide survey on current practices in anesthesia management for lung transplantation in China

Reaction dynamics for the NH3+ + H2 → NH4+ + H reaction on a full-dimensional accurate potential energy surface

The NH3+ + H2 reaction is one of the crucial steps for understanding the chemical network of nitrogen in the interstellar medium. The dynamics and kinetics of this reaction are studied using the quasi-classical trajectory method and microcanonical optimized multidimensional tunneling corrected-canonical variational transition state theory on a newly developed potential energy surface (PES). The PES is fitted by the fundamental invariant-neural network approach, giving a total root mean square error of 0.066 kcal mol−1. Dynamics calculations show that exciting the low-frequency umbrella mode of NH3+ promotes the reactivity remarkably more than exciting the high-frequency stretching modes over the collision energy studied. This special dynamical behavior can be rationalized by the enlarged attractive interaction between reactants, which increases the chance of H2 being captured by NH3+, along with the enhancement of direct rebound mechanisms at low collision energies and stripping mechanisms at high collision energies. In addition, the calculated rate coefficients of the reaction agree reasonably well with the available experimental results.

Thermally stable Sm3+ doped SrCeO3 single-phase white phosphor with Y3+ sensitization for fabricating wLEDs

Distal residues contribute to enzymatic catalysis in human phosphoglucose isomerase through modulation of dynamics and electrostatics

Distal residues in enzymes, although spatially remote from the active site, play critical roles in modulating catalytic efficiency through structural dynamics and electrostatics. In this study, we investigate the contribution of distal residues to the catalytic activity of human phosphoglucose isomerase (hPGI) using molecular dynamics simulations and electrostatic calculations. Six key residues located in the second and third layers around the active site were studied previously through systematic mutagenesis. Variants, including those in the second shell K362A, Q388A, E495Q, and D511N and those in the third shell H100L and H396L, were previously reported to show significant reductions in catalytic turnover and efficiency. Analysis of structural dynamics demonstrates increased flexibility in helices critical for maintaining active site geometry, including helix-17 and helix-18, leading to destabilization of catalytic residues E358, R273, and H389′. In addition, the important interaction between H389′ and E217, essential for the ring-opening step, was disrupted across all variants. Electrostatic perturbations, including altered protonation equilibria and pKa values of catalytic residues, further impede key steps of the catalytic mechanism, such as ligand binding, ring opening, and isomerization. These findings reveal the complex interplay between distal residues, structural dynamics, and electrostatics in regulating hPGI’s catalytic mechanism, providing insights into enzyme function and guiding future enzyme engineering and drug design efforts.

Strong seismic reflections indicating possible eruptible magma beneath the Tatun Volcano Group in Taiwan

Algorithmic approaches to automate OPA tuning for frequency domain spectroscopy

Frequency domain nonlinear spectroscopies are a useful probe of linear and non-linear transitions in a variety of biological, chemical, and materials systems. They require scanning of optical parametric amplifiers (OPAs). Each OPA contains multiple motors that move to prerecorded positions to optimize output at each desired color. OPA optimization and color accuracy are crucial for frequency domain experiments, where OPA color is scanned. Such performance is highly sensitive to environmental fluctuations, so motor positions must be regularly optimized and tuned. Despite the widespread availability of motorized OPAs, this frequent maintenance can make frequency domain spectroscopy a cumbersome and time-consuming process. We have found that fully automated approaches to tuning are invaluable when scanning OPAs. Here, we report four algorithms that accurately and robustly tune a variety of ultrafast laser systems—picosecond and femtosecond, homebuilt and commercial OPAs. Using case studies from previously published work, we illustrate how these four algorithms can be combined to tune all motors of an ultrafast laser system. These algorithms are available through open-source software and can be applied to existing instruments, significantly lowering the threshold for executing frequency domain spectroscopy.

FACEDIG automated tool for placing landmarks on facial portraits for geometric morphometrics users

Accelerating the exploration of material space for hydride double perovskite superconductors under ambient pressure through machine learning

In the field of hydride superconductors, a great challenge is to achieve superconducting states under ambient pressure conditions rather than the extreme high-pressure environments that have been required in experiments. Achieving this goal is crucial for advancing the practical applications of high-temperature superconducting materials. We discover a family of compounds (hydride double perovskite superconductors with space group Fm3̄m and chemical formula A2MM′H6) to achieves this goal. A machine-learning-accelerated approach is utilized to search for hydride double perovskite superconductors under ambient pressure within an extensive dataset comprising over 106 535 hypothetical compounds. 15 stable hydride double perovskite superconductors are discovered under ambient pressure, with the highest superconducting transition temperature (Tc) reaching 18.7 K. The structural stability, electronic properties, and superconducting behavior of these materials have been comprehensively analyzed. Phonon dispersion analysis has highlighted the critical role of lattice vibrations in electron–phonon coupling (EPC), where the contribution of H atom vibrations is essential for facilitating electron pairing and the onset of superconductivity. This demonstrates that the machine-learning-accelerated approach is a highly effective method and can be easily extended to other compounds.

AG-MS3D-CNN multiscale attention guided 3D convolutional neural network for robust brain tumor segmentation across MRI protocols

Site-selective reactivity modulation with intact reaction dynamics in H2 dissociation on single-atom alloy Au1/Ag(111) surface: Six dimensional quantum insights

The dissociative dynamics of molecular H2 on the Au1/Ag(111) single-atom alloy (SAA) surface was systematically investigated through full-dimensional quantum dynamical calculations. A neural network-derived potential energy surface with a 4.2 meV root-mean-square error was employed to ensure high-fidelity simulations. Density functional theory calculations identified a reduced static dissociation barrier of 1.08 eV for the SAA system, compared to the 1.22 and 1.25 eV values for pristine Ag(111) and Au(111) surfaces, respectively. Despite this energetic advantage, the six-dimensional quantum dynamical analysis revealed that the dissociation probabilities for H2 in the vibrational ground (v = 0) state exceeded those on Ag(111) only at kinetic energies below 1.33 eV. This reactivity suppression at elevated energies was attributed to the site-specific modulation induced by the Au dopant, which selectively enhanced reactivities at the top-Au, hcp, and fcc sites while inhibiting those at bridge and top-Ag sites. Furthermore, the vibrational excitation, rotational alignment, and rotational excitation effects were found to closely resemble those observed for H2 dissociation on pristine Ag(111), demonstrating that the fundamental dynamical characteristics of the reaction remain qualitatively preserved despite SAA modification. These findings provide critical insights into the interplay between local electronic structure modification and global reaction dynamics in SAA systems.

Development of BaSrTiO3 nanomaterial based dispersive solid phase microextraction method for cadmium determination in thyme samples using flame atomic absorption spectrometry

Shock wave energy absorption via structural phase transition and bond breakage in metal–organic frameworks

Metal–organic frameworks (MOFs) are nanoporous materials with a tunable structure and high porosity, making them attractive for mechanical energy absorption applications. This study explores shock-induced structural transitions and energy absorption in ZIF-8 and SALEM-2 using ReaxFF molecular dynamics simulations and density functional theory. Results reveal a phase transition at pressures below 1 GPa, characterized by pore collapse, amorphization, and alterations in electronic and bonding structures. Thermodynamic analyses attribute the transition to enthalpy-driven mechanisms and increased entropy. SALEM-2 exhibits superior shock attenuation, attributed to greater volume reduction and extensive bond breakage, underscoring the role of linker chemistry. The ability of MOFs to absorb shock arises from dramatic volume reductions facilitated by bond bending and the sacrificial breaking of metal-linker coordination bonds, with moderate increases in internal energy compared to dense solids. This work provides molecular-level insights into MOF-based shock attenuation and guides the design of optimized MOFs for enhanced mechanical energy absorption.