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On the spectral shape of the structural relaxation in supercooled liquids
Structural relaxation in supercooled liquids is non-exponential. In susceptibility representation, χ″(ν), the spectral shape of the structural relaxation is observed as an asymmetrically broadened peak with a ν1 low- and ν−β high-frequency behavior. In this perspective article, we discuss common notions, recent results, and open questions regarding the spectral shape of the structural relaxation. In particular, we focus on the observation that a high-frequency behavior of ν−1/2 appears to be a generic feature in a broad range of supercooled liquids. Moreover, we review extensive evidence that contributions from orientational cross-correlations can lead to deviations from the generic spectral shape in certain substances, in particular in dielectric loss spectra. In addition, intramolecular dynamics can contribute significantly to the spectral shape in substances containing more complex and flexible molecules. Finally, we discuss the open questions regarding potential physical origins of the generic ν−1/2 behavior and the evolution of the spectral shape toward higher temperatures.
Electric vehicle braking energy recovery control method integrating fuzzy control and improved firefly algorithm
Braking energy recovery is crucial for improving the energy efficiency and extending the range of electric vehicles. If a large amount of braking energy is wasted, it will lead to problems such as reduced range and increased battery burden for electric vehicles. Therefore, an electric vehicle braking energy recovery control model that integrates fuzzy control algorithm with genetic firefly algorithm is proposed. Experimental analysis showed that the decrease in the state of charge of the model was 12.44%, and the braking energy recovery rate reached 52.1% in practical applications. Based on the above data, the proposed method can effectively control the amount of energy recovery. In addition, when the system chip value was 10%, the total amount of recovered energy at the battery end was the highest. Conversely, the total amount of recovered energy at the battery end was relatively small. In summary, the designed electric vehicle braking energy recovery control model can effectively control the amount of braking energy recovery of electric vehicles, ensuring the maximum recovery while also considering the durability and driving stability of the vehicle battery. The method can effectively extend mileage range in the electric vehicle industry, promoting the development and technological innovation of the new energy industry.
Triplet pair dynamics of singlet fission in orthorhombic polycrystalline powder of rubrene as revealed by magnetoluminescence
Singlet fission, which may increase the energy conversion efficiency of solar cells, proceeds via multiple spin levels of a triplet pair. To clarify the spin-related elementary processes of the triplet pair, we measured the magnetoluminescence effect of the fluorescence of rubrene, in the form of orthorhombic polycrystalline powder, in the range of ±300 mT at room temperature. Model simulations using the density matrix method were performed to elucidate how the features of the magnetoluminescence effect depend on the triplet pair dynamics. Simulations of the observed field dependence of the magnetoluminescence effect revealed an anisotropy of 1:100 for the two-dimensional hopping of triplet excitons forming a triplet pair in the ab plane, for which the exchange interaction depends on the separation distance between the two triplet excitons. The effective lifetime of the spin-correlated triplet pair responsible for the magnetoluminescence effect is estimated to be 2.2 ns.
DMCM: Dwo-branch multilevel feature fusion with cross-attention mechanism for infrared and visible image fusion
In response to the limitations of current infrared and visible light image fusion algorithms—namely insufficient feature extraction, loss of detailed texture information, underutilization of differential and shared information, and the high number of model parameters—this paper proposes a novel multi-scale infrared and visible image fusion method with two-branch feature interaction. The proposed method introduces a lightweight multi-scale group convolution, based on GS convolution, which enhances multi-scale information interaction while reducing network parameters by incorporating group convolution and stacking multiple small convolutional kernels. Furthermore, the multi-level attention module is improved by integrating edge-enhanced branches and depthwise separable convolutions to preserve detailed texture information. Additionally, a lightweight cross-attention fusion module is introduced, optimizing the use of differential and shared features while minimizing computational complexity. Lastly, the efficiency of local attention is enhanced by adding a multi-dimensional fusion branch, which bolsters the interaction of information across multiple dimensions and facilitates comprehensive spatial information extraction from multimodal images. The proposed algorithm, along with seven others, was tested extensively on public datasets such as TNO and Roadscene. The experimental results demonstrate that the proposed method outperforms other algorithms in both subjective and objective evaluation results. Additionally, it demonstrates good performance in terms of operational efficiency. Moreover, target detection performance experiments conducted on the M3FD dataset confirm the superior performance of the proposed algorithm.
Dimerization of model polymer chains under nonequilibrium conditions
Dimerization and subsequent aggregation of polymers and biopolymers often occur under nonequilibrium conditions. When the initial state of the polymer is not collapsed, or the final folded native state, the dynamics of dimerization can follow a course sensitive to both the initial conditions and the conformational dynamics. Here, we study the dimerization process by using computer simulations and analytical theory, where the two monomeric polymer chains are in the elongated state and are initially placed at a separation distance, d0. Subsequent dynamics lead to the concurrent processes of collapse, dimerization, and/or escape. We employ Langevin dynamics simulations with a coarse-grained model of the polymer to capture certain aspects of the dimerization process. At separations d0 much shorter than the length of the monomeric polymer, the dimerization could happen fast and irreversibly from the partly extended polymer state itself. At an initial separation larger than a critical distance, dc, the polymer collapse precedes dimerization, and a significant number of single polymers do not dimerize within the time scale of simulations. To quantify these competitions, we introduce several time-dependent order parameters, namely, (i) the time-dependent radius of gyration RG(t) of individual polymers describing the conformational state of the polymer, (ii) a center-to-center of mass distance parameter RMM, and (iii) a time dependent overlap function Q(t) between the two monomeric polymers, mimicking the contact order parameter popular in protein folding. In order to better quantify the findings, we perform a theoretical analysis to capture the stochastic processes of collapse and dimerization by using the dynamical disorder model.
Frequency, predictors and outcomes of intradialytic complications in patients on maintenance haemodialysis in Dar es Salaam: Prospective longitudinal study
Introduction Hemodialysis is a crucial renal replacement therapy option for end stage renal disease (ESRD) patients. Currently, there is a rise of patients who require hemodialysis with concurrent rise in intradialytic complications which can potentiate several outcomes some of which are life threatening. This study assessed the frequency, predictors, and outcomes of intradialytic complications amongst ESRD patients on maintenance hemodialysis. Methodology Prospective longitudinal study using self-designed questionnaires including patient’s demographic data and relevant past medical history, pre-hemodialysis assessment and intra-dialysis monitoring was done for 2 months at Aga Khan Hospital and Muhimbili National Hospital, in Dar es salaam, Tanzania. Results 215 patients were enrolled, of which 138(64.2%) were males with mean age 57(SD 15.37), height 1.64(SD 0.08) and weight 69.27(SD 12.62). Most patients 197(91.6%), were on thrice weekly schedule of which the duration of each session in most patients 206(95.8%) was 4 hours. Diabetes mellitus was the most common etiology of ESRD 126 (58.6%), ArterioVenous fistula (AVF) was the most common vascular access for the procedure 90(41.9%) and mostly, high flux dialyzers were used, FX100 & FX80, (211, 98.2%). There was a statistically significant association between pre-dialysis vital signs, blood flow rate and sex (p value < 0.05) with intradialytic hypertension and hypotension. Interestingly, male sex appeared to elicit a protective effect on intradialytic hypotension (p value < 0.001). Conclusion Hemodialysis is a life-saving procedure with multiple complications of which some have detrimental outcomes. Nonetheless, having a good understanding of the factors associated with the complications, appropriate management and ways of preventing them will remarkably improve the procedure and make it a safer renal replacement modality. Carefully, monitoring pre-dialysis vitals and taking necessary measures when deranged, individualized proper machine settings, sufficient fluid removal and standard blood flow rate may improve the dialysis procedure.
Memory, hysteresis, and kinetic cooperativity in stochastic mnemonic networks
Mnemonic networks are cyclic catalytic networks of monomeric enzymes that exhibit kinetic cooperativity as departures of the mean velocity from the hyperbolic, Michaelis–Menten-like response. In addition, such networks admit a hysteretic response when conformational fluctuations are slow compared to the catalytic rate. Here, we show how these fluctuation-driven effects emerge from the underlying stochasticity in the network. We use the chemical master equation to study the stochastic kinetics of mnemonic networks, which, in their minimal form, include a pair of conformers and triangular reaction pathways. We introduce statistical measures that are conditional on the turnovers to comprehensively analyze molecular fluctuations in the transient and stationary states of these networks. In the transient state, temporal correlations between enzyme turnovers lead to an inequivalence between number and temporal fluctuations, yielding a hysteretic response of the mean velocity to substrates. The transient relaxes to a stationary state with independent and identically distributed turnovers and equality between number and temporal fluctuations. This state is a non-equilibrium stationary state (NESS) when the Kolmogorov loop criterion is not satisfied, leading to the emergence of kinetic cooperativity. The symmetry of the number correlation functions allows us to distinguish between the absence of cooperativity in equilibrium and the accidental vanishing of cooperativity in a NESS. We conclude that memory and hysteresis are transient effects while kinetic cooperativity emerges as the macroscopic manifestation of the microscopic irreversibility of the NESS in a network with cyclic reaction pathways.
Family’s perceptions of their members who use nyaope in Tshwane, South Africa
Introduction Over the last two decades, nyaope use has evolved to become a prominent substance use disorder in South Africa, posing a significant public health burden. The majority of users are young people who are solely concerned with their next nyaope joint. This study aimed to explore the perception of family members on the factors associated with the use of and dependency on nyaope. Methods This was a descriptive exploratory qualitative study conducted in Tshwane, South Africa. Data were collected from 32 family members of Nyaope users via three focus group interviews conducted by a retired psychologist nurse in the three townships of Tshwane. Results The findings revealed a complex and interconnected web of elements that shape the journey of individuals from the onset of nyaope use to the point of dependence and eventual departure from their family homes. Rather than following a linear path of events, this pathway is characterised by a dynamic interplay of seven distinct themes, namely concealed nyaope use, family concerns and suspicions regarding nyaope use, confirmation of nyaope use, possible reasons for using nyaope, barriers to obtaining assistance for nyaope users, family distress, and the transition from home to a life on the streets. Conclusion Most users ended up being disconnected from their families. Family members’ opinions noted that the problem is perceived to be a web of elements working together rather than a linear path of events. The findings have implications for substance use services, social services, health and police services as well as schools.
Relativistic energy transfer
Energy transfer processes are ubiquitous in nature and intensely investigated. The investigations concentrate on the transfer of small to intermediate sized energies. Here, we pose the question of whether the transfer of large energies, where relativistic effects play a central role, can be efficient. At large energies, the process leads to ionization of the environment, i.e., it is the interatomic (or intermolecular) Coulombic decay (ICD) process. To that end, we derive asymptotic expressions for the ICD amplitude by employing the Dirac–Breit Hamiltonian and expanding the frequency dependent Coulomb–Breit interaction between the electrons of the donor and those of the acceptor in powers of the inverse distance between their centers of mass. Expressions are separately derived for the two popular Feynman and Coulomb gauges. At long range, the two expressions have a different appearance but are proven to be equivalent. The derived energy transfer rate at long range shows that when the donor is embedded in an environment, the transfer can be highly efficient. A key is that the radiative lifetime of the donor is extremely short (it can be in the attosecond, 10−18 s, regime), and the x-ray emission typically dominates by far Auger decay (also called Auger–Meitner decay), and the ICD can quench this emission. This contrasts with the situation at small to intermediate sized energies, where the radiative lifetime is much smaller and Auger decay (if the channel is open) dominates. In these cases, the major contribution to ICD comes from the neighbors nearby.
Time-resolved nonlinear microspectroscopy with Gaussian beams
Time-resolved nonlinear microspectroscopy bridges high-resolution imaging and ultrafast spectroscopy, enabling the investigation of spatially localized molecular excited state and exciton dynamics on ultrafast timescales. By integrating ultrafast techniques such as pump–probe and coherent multidimensional spectroscopy with microscopy techniques utilizing high numerical aperture objective lenses and structured beams, these approaches provide label-free chemical contrast and reveal transient phenomena critical to understanding complex systems. Recent advancements, including adaptive optics and tailored beam profiles, have further enhanced spatial and temporal control, unlocking new possibilities for studying heterogeneous systems. This work explores time-resolved nonlinear microspectroscopy using Laguerre–Gaussian beams with orbital angular momentum. Analytical expressions for pump–probe microspectroscopy signals are derived to elucidate how beam parameters influence nonlinear responses reflecting spatial diffusion and ultrafast relaxation processes. The results demonstrate the potential of customized ultrafast pulses and spatial light fields to improve both resolution and sensitivity, advancing dynamic studies in materials science, chemistry, and biology.
High-pressure and high-temperature thermoelasticity of tantalum: An <i>ab initio</i> study
We present the thermoelastic properties of the body-centered cubic tantalum calculated within the quasi-harmonic approximation (QHA) and compare them with those given by the quasi-static approximation (QSA) and those measured experimentally. We find that the QHA temperature dependent elastic constants (TDECs) follow the experiment very well from 5 K up to 500 K, and in this range of temperatures are in better agreement with the experiment than the QSA TDECs. At higher temperatures, our QHA results are linear with temperature and fail to follow the measured change in slope of C(T) and C44(T) that become parallel to the QSA results. We also present our QHA pressure dependent elastic constants at 5, 300, 1000, and 1500 K.
A theoretical model of gas diffusivity in graphene nanochannels
Gas diffusion in graphene nanochannels is pivotal for applications such as gas sensing and membrane separation, where nanoscale confinement introduces unique transport phenomena. Unlike bulk-phases, diffusion in graphene nanochannels is significantly influenced by adsorption, which modifies density distributions and alters diffusivity behavior. In this study, molecular dynamics simulations are combined with a theoretical framework to comprehensively investigate gas diffusion under varying pressures and channel heights. A modified Chapman–Enskog model, derived from atomistic Lennard-Jones potential parameters, is proposed to account for the effects of confinement. Simulation results reveal that gas diffusivity decreases with increasing gas-phase pressure and decreasing channel height due to enhanced density in the nanochannels. Interestingly, for ultra-narrow channels (h ≲ 0.7 nm), the diffusivity correction factor exhibits non-monotonic behavior, initially decreasing but subsequently increasing due to overlapping repulsive potential fields. The proposed model integrates adsorption effects through density predictions based on the Boltzmann distribution and effectively predicts gas diffusivities with relative errors of less than 13%, even under strong confinement. These findings highlight the critical interplay between adsorption and confinement in shaping gas transport within graphene nanochannels. The theoretical model provides a predictive tool for designing graphene-based gas separation and sensing devices, offering fundamental insights for optimizing their performance.
Stretching and twisting of double-stranded RNA under forces: Unwinding mechanism and base-pair dependent elasticity
We used all-atom molecular dynamics simulations to investigate the mechanical response of double-stranded RNA (dsRNA) by applying various forces. We used the helical rise and helical twist, as well as a newly defined helical diameter, to characterize the stretching and twisting of dsRNA. The results indicate that dsRNA unwinds when stretched, accompanied by a linear increase in helical rise and helical diameter. Then, we utilized the normal modes, which are linear combinations of helical modes, to elucidate the underlying mechanism of dsRNA unwinding from an energetic perspective. On the other hand, we employed a stiffness matrix based on a rigid base pair model to examine the base-pair dependence of twist elasticity for dsRNA, as well as stretch elasticities with respect to the helical rise and helical diameter. The results show that the force induces variations in the local elasticities and their couplings of dsRNA, which are closely related to the distributions of base pairs. The mean stretch and twist elasticities can be considered as constants within the measurement uncertainties; however, their couplings demonstrate a slight linear dependency on applied force.
Iterative charge equilibration for fourth-generation high-dimensional neural network potentials
Machine learning potentials allow performing large-scale molecular dynamics simulations with about the same accuracy as electronic structure calculations, provided that the selected model is able to capture the relevant physics of the system. For systems exhibiting long-range charge transfer, fourth-generation machine learning potentials need to be used, which take global information about the system and electrostatic interactions into account. This can be achieved in a charge equilibration step, but the direct solution of the set of linear equations results in an unfavorable cubic scaling with system size, making this step computationally demanding for large systems. In this work, we propose an alternative approach that is based on the iterative solution of the charge equilibration problem (iQEq) to determine the atomic partial charges. We have implemented the iQEq method, which scales quadratically with system size, in the parallel molecular dynamics software LAMMPS for the example of a fourth-generation high-dimensional neural network potential (4G-HDNNP) intended to be used in combination with the n2p2 library. The method itself is general and applicable to many different types of fourth-generation MLPs. An assessment of the accuracy and the efficiency is presented for a benchmark system of FeCl3 in water.
Solvation free energies from neural thermodynamic integration
We present a method for computing free-energy differences using thermodynamic integration with a neural network potential that interpolates between two target Hamiltonians. The interpolation is defined at the sample distribution level, and the neural network potential is optimized to match the corresponding equilibrium potential at every intermediate time step. Once the interpolating potentials and samples are well-aligned, the free-energy difference can be estimated using (neural) thermodynamic integration. To target molecular systems, we simultaneously couple Lennard-Jones and electrostatic interactions and model the rigid-body rotation of molecules. We report accurate results for several benchmark systems: a Lennard-Jones particle in a Lennard-Jones fluid, as well as the insertion of both water and methane solutes in a water solvent at atomistic resolution using a simple three-body neural-network potential.
Quantum corrections to the kinetic energy and the <i>ab initio</i>-based prediction of the thermodynamic properties and vapor–liquid equilibria of hydrogen
The ability of ab initio-based intermolecular potentials to predict the vapor–liquid-equilibria (VLE) and thermodynamic properties of hydrogen is investigated via Monte Carlo simulation. The combination of a simplified ab initio atomic potential (SAAP) and first order Feynman–Hibbs (FH-1) interactions closely reproduces the VLE phase envelope, providing a good estimate of the critical point. The SAAP + FH-1 combination also improves the prediction of other thermodynamic properties. However, the accurate determination of enthalpy, heat capacity, isothermal compressibility, isochoric pressure coefficient, and isobaric thermal expansion coefficient requires the addition of a quantum correction to the kinetic energy (QCKE). The QCKE is a post-simulation contribution to the thermodynamic properties of quantum fluids and, as such, can be used to improve the accuracy of any predictions using an intermolecular potential. The addition of QCKE to the SAAP + FH-1 potential results in values for the thermodynamic properties that are close to reference data for hydrogen at temperatures greater than 40 K and pressures up to 100 MPa.
Slow dynamical modes from static averages
In recent times, efforts have been made to describe the evolution of a complex system not through long trajectories but via the study of probability distribution evolution. This more collective approach can be made practical using the transfer operator formalism and its associated dynamics generator. Here, we reformulate in a more transparent way the result of Devergne et al. [Adv. Neural Inform. Process. Syst. 37, 75495–75521 (2024)] and show that the lowest eigenfunctions and eigenvalues of the dynamics generator can be efficiently computed using data easily obtainable from biased simulations. We also show explicitly that the long time dynamics can be reconstructed by using the spectral decomposition of the dynamics operator.
Morphology regulation during mechanochemistry synthesis activating nanostructured aluminum lithium storage behavior
Aluminum (Al) is a potential anode material for lithium-ion batteries due to its high theoretical capacity and low volume expansibility. However, scalable fabrication of nanostructured Al still faces a great challenge. In addition, the lithium storage performance of Al anode materials always encounters a severe strike within a dozen discharge/charge cycles, and such an abnormal behavior of the Al anode material remains enigmatic. Herein, a mechanochemistry method without using any solvent is developed to achieve scalable production of Al nanoparticles and the morphology of the obtained Al nanoparticles could be regulated using Ketjen black (KB). KB with a chain-like structure could regulate the Al crystal growth process and the aggregation of Al nanoparticles during the solid-phase reaction, shortening the electron transfer path among Al crystals, ultimately activating the lithium storage behavior of nanostructured Al. Initial discharge/charge capacities of 630.6 and 402.0 mA h g−1 were achieved at 50 mA g−1; unfortunately, the nanostructured Al still suffered from rapid deterioration of lithium storage performance. Comprehensive analysis demonstrated that the raised energy barrier of LiAl formation and the slow lithium diffusion kinetics in the Al matrix may be the main factors destroying the lithium storage performance of the Al anode material. This work provided more evidence for illustrating the lithium storage behavior of the Al anode.
Constrained dipole moment density functional theory for the calculation of the charge-transfer energy in non-covalent complexes
The original constrained dipole moment density functional theory allows one to control the magnitude of the molecular dipole moment in a variational and non-empirical way. In this work, we extend this methodology to control the three Cartesian components of the molecular dipole moment. The new theoretical development is suitable for the calculation of the charge-transfer energy contributions to the total interaction energies in non-covalent complexes. To test the reliability of the theoretical development, we form three sets of non-covalent complexes from the literature with a total of fifty-one systems. The former set of complexes includes many different types of non-covalent interactions, the second set consists of prototypical non-covalent complexes and three biologically relevant interactions between DNA base pairs, and the third set comprises halogen bonding complexes. We determined the charge-transfer energy contributions and the total interaction energies of all these complexes. The calculated charge-transfer energies are in very good agreement with the ones calculated using the fragment-based Hirshfeld methodology, which has been proven to be reliable. Nevertheless, the new procedure relies on the molecular dipole moment, which is observable, while the fragment-based Hirshfeld methodology relies on a definition of a population analysis.
Radical scavenging rate constants determined by spin relaxation times of electron spin polarized radicals as measured by free induction decay signals
Radical scavenging reaction rate constants were measured by monitoring the free induction decay (FID) of the unpaired electron of radicals by using laser-synchronized pulsed-EPR. This method probes large electron spin magnetization arisen from dynamic electron spin polarization (DEP), which remarkably enhances the EPR signal. DEP decays with the longitudinal spin relaxation time, which was observed by using the FID detection method. In the presence of a radical scavenger, the DEP decay time depends on both spin-lattice relaxation and the chemical reaction with the scavenger, the latter of which reduces radical concentration. The plots of DEP decay rates against the radical scavenger concentrations gave the pseudo-first-order reaction rate constants for various radicals. This procedure was applied to determine the radical scavenging reaction rate constants of hydroxycyclohexyl, 2-hydroxypropyl, diphenylphosphinoyl, and α,α-dimethoxybenzyl radicals. The measured rate constants show good agreement with the previously reported values determined by using another method monitoring electron spin echo (ESE) decays of the radicals. We discussed the advantageous and disadvantageous characters of the FID detection method with respect to the existing ESE method in the viewpoints of signal intensity, selectivity of radicals, the simpleness of the measurements, and so on.