Browse Articles
Discover research articles across all indexed journals
Hydrogen bonding blues: Vibrational spectroscopy of the TIP3P water model
The computational spectroscopy of water has proven to be a powerful tool for probing the structure and dynamics of chemical systems and for providing atomistic insight into experimental vibrational spectroscopic results. However, such calculations have been limited for biochemical systems due to the lack of empirical vibrational frequency maps for the TIP3P water model, which is used in many popular biomolecular force fields. Here, we develop an empirical map for the TIP3P model and evaluate its efficacy for reproducing the experimental vibrational spectroscopy of water. We observe that the calculated infrared and Raman spectra are blueshifted and narrowed compared to the experimental spectra. Further analysis finds that the blueshift originates from a shifted distribution of frequencies, rather than other dynamical effects, suggesting that the TIP3P model forms a significantly different electrostatic environment than other three-point water models. This is explored further by examining the two-dimensional infrared spectra, which demonstrates that the blueshift is significant for the first two vibrational transitions. Similarly, spectral diffusion timescales, evaluated through both the center line slope and the frequency–frequency time correlation function demonstrate that TIP3P exhibits significantly faster spectral dynamics than other three-point models. Finally, sum-frequency generation spectroscopy calculations suggest that despite these challenges, the TIP3P empirical map can provide phenomenological, qualitative, insight into the behavior of water at the air–water and lipid–water interfaces. As these interfaces are models for hydrophobic and hydrophilic environments observed in biochemical systems, the presently developed empirical map will be useful for future studies of biochemical systems.
Database of soil properties incorporating organic content from roots and soil organisms for regional slope stabilisation
High-throughput computational screening of auxetic two-dimensional metal dichalcogenides and dihalides
Auxetic materials hold tremendous potential for many advanced applications, but candidates are quite scarce, especially at two dimensions. Here, we focus on two-dimensional (2D) metal dichalcogenides and dihalides with the chemical formula MX2 by screening structures sharing the P4̄m2 space group among 330 MX2 compounds from the computational 2D materials database. Via high-throughput first-principles computations, 25 stable MX2 (M = Mg, Ca, Mn, Co, Ni, Cu, Zn, Ge, Cd, Sn; X = F, Cl, Br, I, O, S, Se) systems with in-plane negative Poisson’s ratios (NPRs) are successfully identified. Within these structures, 2D NiCl2 has the largest NPR value of −0.34, with a magnitude significantly higher than those of black phosphorene (−0.027) and SnO2 (−0.1). The distinct auxetic effect in MX2 originates from both the unique local corner-sharing tetrahedral structural motif under the low-dimensional effect and the strong orbital interaction between the d orbitals of M and the p orbitals of halogen/chalcogen atoms. As a result, Poisson’s ratio can be effectively tuned by enhancing the d–p interaction through an external biaxial strain. We reveal that these auxetic materials exhibit rich electronic and magnetic properties, covering nonmagnetic, ferromagnetic, or anti-ferromagnetic metals, semiconductors, and insulators. The extraordinary auxetic behaviors in combination with rich physical properties could lead to multifunctional nanomechanical, optoelectronic, and spintronic applications.
Prediction of white matter hyperintensities evolution one-year post-stroke from a single-point brain MRI and stroke lesions information
AbstractPredicting the evolution of white matter hyperintensities (WMH), a common feature in brain magnetic resonance imaging (MRI) scans of older adults (i.e., whether WMH will grow, remain stable, or shrink with time) is important for personalised therapeutic interventions. However, this task is difficult mainly due to the myriad of vascular risk factors and comorbidities that influence it, and the low specificity and sensitivity of the image intensities and textures alone for predicting WMH evolution. Given the predominantly vascular nature of WMH, in this study, we evaluate the impact of incorporating stroke lesion information to a probabilistic deep learning model to predict the evolution of WMH 1-year after the baseline image acquisition, taken soon after a mild stroke event, using T2-FLAIR brain MRI. The Probabilistic U-Net was chosen for this study due to its capability of simulating and quantifying the uncertainties involved in the prediction of WMH evolution. We propose to use an additional loss called volume loss to train our model, and incorporate stroke lesions information, an influential factor in WMH evolution. Our experiments showed that jointly segmenting the disease evolution map (DEM) of WMH and stroke lesions, improved the accuracy of the DEM representing WMH evolution. The combination of introducing the volume loss and joint segmentation of DEM of WMH and stroke lesions outperformed other model configurations with mean volumetric absolute error of 0.0092 ml (down from 1.7739 ml) and 0.47% improvement on average Dice similarity coefficient in shrinking, growing and stable WMH.
Accurate DFT simulation of complex functional materials: Synergistic enhancements achieved by SCAN meta-GGA
Complex functional materials are characterized by intricate and competing bond orders, making them an excellent platform for evaluating the newly developed strongly constrained and appropriately normed (SCAN) density functional. In this study, we explore the effectiveness of SCAN in simulating the electronic properties of displacive ferroelectrics (BaTiO3 and PbTiO3) and magnetoelectric multiferroics (BiFeO3 and YMnO3), which encompass a broad spectrum of bonding characteristics. Due to a significant reduction in self-interaction error, SCAN manifests its improvements over the Perdew–Burke–Ernzerhof (PBE) method in three aspects: SCAN predicts more accurate ionicity, produces more compact orbitals, and better captures d-orbital anisotropy. Particularly, these synergistic enhancements lead to notable phenomena in calculating the bandgap of YMnO3: while the PBE+U simulation may suggest a strong correlation appearance attributed to high Hubbard-like U values (∼5 eV), the value is dramatically lower (∼1 eV) in the SCAN+U method. Furthermore, we provide an intuitive analysis of SCAN’s operational principles by examining the complex electron densities involved. These insights are theoretically intriguing and have practical implications, potentially encouraging wider adoption of SCAN in the computational modeling of complex functional materials.
Numerical simulation and experimental validation of the oleogel formation from grape seed oil and beeswax
Loss of structural specificity in 3D genome organization upon viral infection is predicted by polymer physics
In the last years, it has been proved that some viruses are able to re-structure chromatin organization and alter the epigenomic landscape of the host genome. In addition, they are able to affect the physical mechanisms shaping chromatin 3D structure, with a consequent impact on gene activity. Here, we investigate with polymer physics genome re-organization of the host genome upon SARS-CoV-2 viral infection and how it can impact structural variability within the population of single-cell chromatin configurations. Using published Hi-C data and molecular dynamics simulations, we build ensembles of 3D configurations representing single-cell chromatin conformations in control and SARS-CoV-2 infected conditions. We focus on genomic length scales of TADs and consider, as a case study, models of real loci containing DDX58 and IL6 genes, belonging, respectively, to the antiviral interferon response and pro-inflammatory genes. Clustering analysis applied to the ensemble of polymer configurations reveals a generally increased variability and a more heterogeneous population of 3D structures in infected conditions. This points toward a scenario in which viral infection leads to a loss of chromatin structural specificity with, likely, a consequent impact on the correct regulation of host cell genes.
Sodium selenite enhanced the selenium content in black soldier fly
Molecular orientation of dielectric layers at indigo/dielectric interfaces impacts the ordering of indigo films in organic field-effect transistors
Organic multilayer systems, which are stacked layers of different organic materials, are used in various organic electronic devices such as organic light-emitting diodes (OLEDs) and organic field-effect transistors (OFETs). In particular, OFETs are promising as key components in flexible electronic devices. In this study, we investigated how the inclusion of an insulating tetratetracontane (TTC) interlayer in ambipolar indigo-based OFETs can be used to alter the crystallinity and electrical properties of the indigo charge transport layer. We find that the inclusion of a 20-nm-thick TTC film thermally annealed at a low temperature of 70 °C acts to significantly increase the ambipolar electrical transport of the indigo layer. X-ray diffraction, atomic force microscopy, and vibrational sum frequency generation measurements showed that annealing the TTC film significantly improved its ordering. The electronic sum-frequency generation spectra of TTC/indigo bilayers show that this improved ordering of TTC films promotes the growth of crystalline indigo films that exhibit charge mobilities in OFET that are nearly an order of magnitude larger than those measured for devices grown on unannealed TTC layers. Furthermore, using vibrational sum-frequency generation spectroscopy, we found that pre-annealing the TTC layer prior to indigo deposition can suppress the formation of defects within the TTC layer during indigo film growth, which also contributes to enhanced charge transport. Our results highlight the importance of controlling the molecular ordering within the interlayer contacts in OFET structures to achieve an enhanced performance.
Rapid quantitative analysis of double-stranded plasmid DNA with capillary gel electrophoresis for applications in quality control and radiation research
AbstractThe quantification of different structures, isoforms and types of damage in plasmid DNA is of importance for applications in radiation research, DNA based bio-dosimetry, and pharmaceutical applications such as vaccine development. The standard method for quantitative analysis of plasmid DNA damage such as single-strand breaks (SSB), double-strand breaks (DSB) or various types of base-damage is Agarose gel electrophoresis (AGE). Despite being well established, AGE has various drawbacks in terms of time consuming handling and analysis procedures. A more modern, faster, cheaper and more reliable method is capillary gel electrophoresis (CGE). However, to establish this method in biotechnology, radiation-research and related fields, certain criteria in terms of accuracy, repeatability and linearity have to be tested and protocols have to be established. This study performs the relevant tests with a common model plasmid (pUC19, double-stranded DNA with 2686 basepairs) to establish a CGE based methodology for quantitative analysis with readily available commercial CGE systems. The advantages and limitations of the methods are evaluated and discussed, and the range of applicability is presented. As a further example, the kinetics of enzyme digestion of plasmid DNA by capillary gel electrophoresis was studied. The results of the study show for a model system consisting out of pUC19, the suitability of CGE for the quantification of different types of DNA damage and the related isoforms, such as supercoiled, open-circular and linear plasmid DNA.
Mean lifetime of diffusing particle in cylindrical cavity with absorbing spots of arbitrary radii on its bases
This paper deals with the trapping of a particle diffusing in a cylindrical cavity by two circular absorbing spots of arbitrary radii located in the centers of the cavity bases. The focus is on the mean particle lifetime, which is its mean first-passage time to one of the spots. When the spots are small and their radii are well below the cavity radius, this time can be analyzed using the narrow escape (NE) theory, which describes it as a function of the spot radii and the only parameter of the cavity, its volume, independent of the cavity shape and the particle initial position. We derive an approximate analytical solution for the mean particle lifetime that goes beyond the scope of the NE theory. In particular, our solution shows how this mean lifetime depends on the cavity shape, i.e., its length and radius, the particle initial position in the cavity, and the spot radii, which can be arbitrary. It reduces to the NE solution, as the spot radii tend to zero. To check the accuracy of our approximate result, we determine the mean lifetimes from three-dimensional Brownian dynamics simulations. The comparison shows excellent agreement between the theoretical predictions and simulation results when the initial distance from the particle to both cavity bases exceeds the cavity radius.
A cutting-edge neural network approach for predicting the thermoelectric efficiency of defective gamma-graphyne nanoribbons
Bee-yond the plateau: Training QNNs with swarm algorithms
In the quest to harness the power of quantum computing, training quantum neural networks (QNNs) presents a formidable challenge. This study introduces an innovative approach, integrating the Bees Optimization Algorithm (BOA) to overcome one of the most significant hurdles—barren plateaus. Our experiments across varying qubit counts and circuit depths demonstrate the BOA’s superior performance compared to the Adam algorithm. Notably, BOA achieves faster convergence, higher accuracy, and greater computational efficiency. This study confirms BOA’s potential to enhance the applicability of QNNs in complex quantum computations.
A novel approach to assess acid diversion efficiency in horizontal wells
AbstractUsing an acid to stimulate a heterogeneous carbonate reservoir during matrix acidizing may lead to over-treating the high permeability zones, leaving low permeability zones untreated. This is particularly exacerbated in long horizontal sections, necessitating the use of acid diverters for effective acid distribution across the formation. In previous studies, conventional core flooding systems were utilized where single inlet and outlet lines were used or, at best, two outlet lines for dual-core flooding. This paper proposes a new method for simulating matrix acidizing in horizontal wells by introducing five injection points and two outlet lines. The injection points are perpendicular to the core samples to simulate multiple perforations in a horizontal well while the outlet lines are parallel. Four experiments were conducted in this study using Indiana limestone cores that were 1.5 inches in diameter. For the first three tests, the length of the core was 12 inches, and the cores’ average permeabilities were 16 mD. For the fourth one, two 6-inch length cores with different average permeability (10 and 50 mD) were employed. Hydrochloric acid was used in the first experiment, while hydrochloric acid with viscoelastic surfactant (VES) was used in subsequent experiments. To the best of our knowledge, this is the first study to introduce a multi-point injection system with enhanced coverage and distribution, resulting in a more precise representation of acidizing a horizontal well.
Endohedral vs exohedral boron in C60: Bonding nature and impact on hot-electron relaxation dynamics
Endohedral and exohedral fullerenes have both been employed as electron acceptors in polymer solar cells (PSCs). However, their differences in hot-electron relaxation dynamics remain unclear. Previous studies have shown that the location of a single atom, whether inside or outside the fullerene cage, results in significant differences in charge distribution. In this work, the hot-electron relaxations of endohedral B@C60+ and exohedral C60B+ are investigated using nonadiabatic molecular dynamics simulations. Our results reveal that the location of the boron atom—inside or outside the fullerene—significantly impacts the bonding interactions between boron and C60. Compared to C60B+, the weaker interactions in B@C60+ reduce the orbital overlap between LUMO+3 and LUMO+2 and increase the energy gap between them. This, in turn, slows hot-electron relaxation by weak nonadiabatic coupling, making B@C60+ more suitable for PSC applications. This study provides valuable insights into how atomic positioning affects the electronic properties in fullerene-based materials, contributing to the design of more efficient electron acceptors for photovoltaic devices.
Randomized controlled trial on effect of different routes of dexmedetomidine on Haemodynamics in patients undergoing saphenectomy under epidural anaesthesia
Tunable phase behaviors of diblock copolyelectrolytes under alternating electric fields: A coarse-grained molecular dynamics study
Diblock copolyelectrolytes have significant potential in applications such as solid-state single-ion conductors, but precisely controlling their nanostructures for efficient ion transport remains a challenge. In this study, we explore the phase behavior and microphase transitions of AX BY-type diblock copolyelectrolytes under alternating electric fields using coarse-grained molecular dynamics simulations. We systematically investigate the effects of various electric field features, including unipolar and bipolar square-waves, as well as offset and non-offset sine-waves, focusing on how field strength and period influence the self-assembling morphology of the copolyelectrolytes. Under unipolar square-waves, both the lamellar and cylindrical phase regions expand, while the disordered phase regions shrink as the field strength increases. In contrast, bipolar square-waves maintain lamellar structures more robustly, with reversed stretching behavior observed in the polymer chains. As the electric field period exceeds a critical value, both waveforms converge with the results seen under constant electric fields. In addition, sine-waves induce smoother phase transitions, expanding the ordered phase regions, particularly the cylindrical phase, due to continuous field variation. We further examine the detailed structural and dynamic properties, such as mean-square displacement, polymer conformation, and chain orientation during these transitions. This work provides fundamental insights into the structural regulation of diblock copolyelectrolytes under oscillating electric fields, guiding the design of advanced polymeric electrolytes with tailored nanostructures.
The associations between dietary advanced glycation-end products intake and self-reported infertility in U.S. women: data from the NHANES 2013–2018
Direct Givens rotation method based on error back-propagation algorithm for self-consistent field solution
The self-consistent field (SCF) procedure is the standard technique for solving the Hartree–Fock and Kohn–Sham density functional theory calculations, while convergence is not theoretically guaranteed. Direct minimization methods, such as the augmented Lagrangian method (ALM) and second-order SCF (SOSCF), obtain the SCF solution by minimizing the Lagrangian with the gradient. In SOSCF, molecular orbitals are optimized by truncating the Taylor expansion of a unitary matrix represented in exponential form to ensure the orthonormality condition. This study proposes an alternative algorithm for direct-energy minimization to obtain an SCF solution using ALM Lagrangian by adopting sequential Givens rotations between occupied and virtual orbitals. The Givens rotation corresponds to unitary transformations that guarantee orthogonality and avoid variational collapse. Complex gradients for sequential Givens rotation were obtained by the error back-propagation method, which is based on the chain rule. Illustrative applications clarified the features of the present DGR methods by comparing with other SCF algorithms such as direct inversion in iterative subspace, SOSCF, and ALM.