Browse Articles

Comment on “Interaction confinement and electronic screening in two-dimensional nanofluidic channels” [J. Chem. Phys. 157, 114703 (2022)]

Toward improved descriptors by refining the complex reaction network in electrocatalysis

Electrocatalysis is one of the key technologies for developing sustainable and fossil resource free routes to produce fuels and chemicals. The limiting potential (UL), defined by the reaction free energy of the most difficult electrochemical step in a given pathway, is an effective descriptor for establishing the activity trend of a set of electrocatalysts, allowing high throughput screening of new catalysts. However, the reaction network of electrocatalytic processes is rather complex, especially for the reactions with necessary thermochemical steps, e.g., the synthesis of valuable C–N bond-containing chemicals. Thermochemical steps cannot be significantly enhanced by electrode potentials, where kinetics is a non-negligible issue at even high overpotentials. This makes it challenge by using limiting potential to accurately describe activity trends for the reactions with necessary thermochemical steps. To this end, we propose an effective scheme to determine an improved descriptor. We suggest refining the rather complex reaction network at first. In particular, it is suggested to decouple electro- and thermochemical steps and exclude the unfavorable pathways with an excessively high thermochemical barrier. Then, a global comparison among the other pathways can be made, to determine the optimal pathway and the improved descriptor (the reaction free energy of the most difficult step of the optimal pathway, defined as ΔGrRPD-limiting). In addition, the studies on reaction kinetics are also suggested to understand the exception of the best catalysts and provide the direction of experimental optimization. This scheme is of a great compromise between practical efficiency and the accuracy toward the rational design of electrocatalysts.

Microscopic roles of hydration on interfacial ion transfer after water finger break

During ion transfer through a water–oil interface, a water finger (WF) is transiently formed and breaks to leave hydrated ions in the oil phase. The present work investigated subsequent microscopic processes following WF by molecular dynamics (MD) simulation. The nascent ions tend to have excessive hydrating water as a consequence of unstable WF formation, implying subsequent relaxation. Subsequent kinetics of the ions including evaporation/condensation of hydrating water, diffusion, recapture of ions by WF, and ion pair formation were comprehensively examined with calculations of free energy surfaces and diffusion dynamics. The thickness of the interface associated with non-equilibrium hydration is estimated to be the order of ∼nm, and the WF recapture is a rather minor process in the range. The observed ion current through the liquid–liquid interface was shown to be sensitive to the water content in the oil because the concentration of ions including their hydrated clusters in the oil phase is sensitive to the trace amount of water concentration.

Rotational spectroscopy of 1,2-dihydronaphthalene, 1,4-dihydronaphthalene, and 1,2,3,4-tetrahydronaphthalene

The rotational spectra of 1,2-dihydronaphthalene (1,2-DHN), 1,4-dihydronaphthalene (1,4-DHN), and 1,2,3,4-tetrahydronaphthalene (1,2,3,4-THN) were measured and analyzed. A single conformation was detected for each molecule. The measurements for the parent isotopologues were extended to include the rotational spectra of all mono-substituted 13C isotopologues for 1,2-DHN and 1,4-DHN. Through the analysis of the experimental spectra, the rotational constants and quartic centrifugal distortion constants were accurately determined. The skeletal structures of 1,2-DHN and 1,4-DHN were derived based on the measured rotational constants. The precise spectroscopic parameters of the three molecules provided in this study enable future exploration of the chemistry of these species in the laboratory and interstellar medium.

Theoretical study of the excited states of NeH and of their non-adiabiatic couplings: A preliminary for the modeling of the dissociative recombination of NeH+

Potential energy curves and matrix elements of radial non-adiabatic couplings of the 2Σ+ and 2Π states of the NeH molecule are calculated using the electronic structure package MOLPRO, in view of the study of the reactive collisions between low-energy electrons and NeH+.

Prediction of adsorption energies of CmHnOp (m ≤ 2, n ≤ 6, p ≤ 2) on transition metals and alloys with machine learning methods

Metal-based catalysts are widely used in many kinds of reactions, including the hydrogenation of CO2 to alcohols. Adsorption energies of key intermediates have often been used as descriptors in high-throughput catalyst screening. However, establishing machine learning models to accurately predict adsorption energies of widely spanned species is still challenging. In the present article, we explored the predictive power of sure independence screening and sparsifying operator (SISSO), multilayer perceptron regression (MLPR), random forest regression (RFR), kernel ridge regression (KRR), support vector regression (SVR), eXtreme Gradient Boosting (XGBoost), and 20 ensemble machine learning (ML) methods for adsorption energies of 57 species involved in CO2 hydrogenation to ethanol using surface features, adsorbate features, and adsorption site features. The results show that SISSO and the five base ML methods cannot furnish models with the maximum absolute error (MAX) comparable to DFT errors. On the other hand, the MAX of most two-component and three-component ensemble ML methods is less than 0.3 eV, and the KRR+MLPR+XGBoost ensemble ML model performs the best, with the mean absolute error being 0.03 eV and MAX of only 0.17 eV. Feature importance analysis reveals that the condensed local softness is the most important feature, and there are linear relations between the condensed local softness and adsorption energies of 10 C1 species on all considered surfaces. The present work shows that ensemble ML methods outperform the base ML methods for predicting adsorption energies of widely ranged species with satisfactory accuracy and deserve further studies.

Kinetic frustration enables single-molecule computation

A fundamental challenge in physical systems is implementing computation at the microscopic scale where thermal fluctuations dominate. While biological systems achieve this through complex molecular networks, the physical principles enabling simpler systems to process temporal information remain unclear. Here we demonstrate how non-equilibrium dynamics can enable single molecules to perform sophisticated computation through thermal-kinetic frustration—a principle that creates a controlled discrepancy between thermodynamic stability and kinetic accessibility. By engineering this frustration in a linear polymer with N binary-state units, we create a physical realization of a deterministic finite automaton capable of accessing 2N configurations through non-equilibrium driving, far exceeding the N + 1 configurations available at equilibrium. Despite operating in a thermal environment, the molecule’s dominant configuration evolves deterministically, enabling recognition of complex temporal patterns through mechanical control signals. Our framework establishes how stochastic microscopic dynamics can give rise to deterministic computation, providing new insights into non-equilibrium statistical mechanics and information processing in physical systems. The theoretical predictions can be tested using DNA nanotechnology, with potential applications in biosensing and adaptive materials.

Active learning regression quality prediction model and grinding mechanism for ceramic bearing grinding processing

The study aims to explore quality prediction in ceramic bearing grinding processing, with particular focus on the effect of grinding parameters on surface roughness. The study uses active learning regression model for model construction and optimization, and empirical analysis of surface quality under different grinding conditions. At the same time, various deep learning models are utilized to conduct experiments on quality prediction in grinding processing. The experimental setup covers a variety of grinding parameters, including grinding wheel linear speed, grinding depth and feed rate, to ensure the accuracy and reliability of the model under different conditions. According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. In addition, the experiment also found that increasing the grinding wheel linear velocity and moderately adjusting the grinding depth can significantly improve the machining quality. For example, when the grinding wheel linear velocity is 45 m/s and the grinding depth is 0.015 mm, the Ra value drops to 0.1876 μm. The results of the study not only provide theoretical support for the grinding processing of ceramic bearings, but also provide a basis for the optimization of grinding parameters in actual production, which has an important industrial application value.

Slow and fluctuating dynamics in high concentration BSA protein solutions

We present a study on globular bovine serum albumin (BSA) protein solutions using particle tracking microrheology and dynamic light scattering over a wide concentration range (1–55 g/dl). We measured the expected drastic increase in viscosity and relaxation times with concentration, highlighting the slowing down of the dynamics associated with collective molecular motions as concentration increases. A novel aspect of our study emerged at very high concentrations, where the slow relaxation times exhibit only a mild increase with concentration, resembling the behavior observed in very soft colloids. Upon quenching the temperature to induce very slow dynamics, we observe fluctuating dynamics, suggesting a mild aging regime characterized by micro-rearrangements of BSA proteins. We use protein concentration (mass per volume) as the control parameter due to the precision of Bradford assay measurements, facilitating straightforward comparisons with other studies. Our work offers new insights into the phase behavior of BSA solutions across a wide concentration range, with implications for understanding protein solution dynamics at high concentrations.

Frontispiece: An Amorphous Donor‐Acceptor Conjugated Polymer with Both High Charge Carrier Mobility and Luminescence Quantum Efficiency

Comparison between bupivacaine-lidocaine, dexamethasone mixture and bupivacaine alone for motor recovery after axillary brachial plexus block in distal radius surgery: A prospective randomized trial

Background Prolonged motor block, known as “dead arm,” which can cause patient discomfort and anxiety, is a serious concern that is often overlooked in ambulatory surgery, particularly in elderly patients. The purpose of this study was to examine the recovery time of motor blockade with bupivacaine and a mixture of bupivacaine-lidocaine-dexamethasone in axillary brachial plexus block. Methods A prospective, randomized, double-blinded controlled trial was conducted with 70 patients scheduled for distal end radius fixation under axillary brachial plexus block. A local anesthetic mixture group (LA-mixture group) received a 21 ml mixture of 0.2% bupivacaine with 1.2% lidocaine and 5 mg of dexamethasone (n =  35). A bupivacaine group received 20 ml of 0.5% bupivacaine with 1 ml of normal saline (n =  35). The primary outcome was the duration of the motor blockade. Secondary outcomes included the duration of sensory blockade, postoperative pain score, and the incidence of rebound pain. Results The demographic data were similar between the two groups. The mean times for recovery of hand grips and sensation were 13.5 ±  7.3 and 12.6 ±  6.2 hours in the LA-mixture group and 15.3 ±  6.7 and 14.6 ±  6.2 hours in the bupivacaine group. Pain scores were not significantly different between the two groups, but the incidence of rebound pain was lower in the LA-mixture group (8.6% and 28.6%, p =  0.031). Conclusion The bupivacaine-lidocaine, dexamethasone mixture failed to enhance motor recovery compared to 0.5% bupivacaine alone. However, patients in the mixture group appeared to experience a lower incidence of rebound pain. Trial registration Thai Clinical Trials Registry TCTR20200114003

Sn9C15 monolayer with desirable bandgap, high carrier mobilities, and broadband light absorption for photovoltaic devices

Two-dimensional carbon-based materials show considerable promise for applications in a wide range of fields, including aerospace, energy storage, and catalysis, due to their great advantages of abundant carbon resources, relatively low-cost, non-toxicity, and excellent physical and chemical properties. However, their applications in photovoltaics remain limited. Here, we first theoretically predict a stable Sn9C15 monolayer (space group P321). The Sn9C15 monolayer exhibits numerous advantages, which make it an ideal candidate for photovoltaic applications: (1) The Sn9C15 monolayer is a direct bandgap semiconductor with a bandgap of 1.70 eV, which is closer to the optimal bandgap of 1.50 eV for photovoltaic devices; (2) the Sn9C15 monolayer exhibits electron mobilities in excess of 2 × 103 cm2 V−1 s−1; (3) the Sn9C15 monolayer shows a direct bandgap of 1.50 eV under a 3% compressive biaxial strain; (4) the Sn9C15 monolayer shows a benign light absorption in the whole visible region (380–780 nm); (5) the Sn9C15 monolayer possesses an optical bandgap of 0.97 eV and an exciton binding energy of 1.63 eV; and (6) the Sn9C15/TMD heterostructures are predicted to have a power conversion efficiency of 9%–23%. In terms of its formation energy, we expect that the Sn9C15 monolayer will be fabricated similarly to the synthesized Si9C15 monolayer. Importantly, the target bandgap of the Sn9C15 monolayer is achieved by the synergistic mechanism of the crystal lattice spacing and the atomic contribution of band edges (referred to as lattice-band edge synergistic mechanism). We anticipate that this synergistic mechanism will facilitate the design of a great number of new materials with targeted bandgaps.

Induction of zinc conjugated with Doxorubicin for the prevention of aggregating β-catenin in the Wnt signaling pathway investigated through computational approaches

Canonical Wnt signaling plays a key role in tumor cell proliferation which correlates with the accumulation of β-catenin resulting inactivation of the network of targets such as GSK3β, Axin, CK1. Uncontrolled expression of β-catenin leads to different types of cancers and other diseases such as sarcoma and mesenchymal tumor formation. However, β-catenin is an attractive target for cervical cancer. In the present study, the compounds such as Doxorubicin and Zinc conjugated with Doxorubicin were screened against β-catenin using Molecular Docking, Molecular Dynamics Simulation, MM/GBSA, and DFT approaches to explore their insights. The study further demonstrated that the binding energy of Zn conjugated with Doxorubicin has shown -7.2 kcal/mol and Doxorubicin registers -5.9 kcal/mol against β-catenin. The disruption between the β-catenin/Tcf-4 complex was observed through the Zinc-Doxorubicin complex, both the proteins are separated about 12 Å. The Zn-Doxorubicin was stabilized with the hydrophobic residues such as Val349 of β-catenin and Phe21 of Tcf-4. The DFT analysis using the B3LYP/6-31g(d,p) method explores that Zn-doxorubicin in complex with the binding site residues has shown the HOMO-LUMO gap of 2.55 eV. The binding free energy calculations exhibit the Zn conjugated Doxorubicin favors in the study by showing ~ 3 kcal/mol difference with Doxorubicin. The Zn-conjugated Doxorubicin will be discussed in the context of cervical cancer with the hope of improving drug efficacy and reducing toxicities for the betterment of the patient’s quality of life.

Ion velocity map imaging study of the charge transfers from N2+/N+ to H2O

Considering important roles of ion–molecule collision in planetary atmospheres, here we investigate the charge transfer dynamics of N2+/N+ + H2O → N2/N + H2O+ in the collision energy range of 0.42–2.09 eV. In the collisions with N2+, the H2O+ yield is populated in the bending-motion vibrational states of the A 2A1 state and its production efficiency is enhanced monotonously with the decrease in collision energy. The H2O+ velocity images recorded with the three-dimensional ion velocity map imaging technique exhibit two categories of spatial distributions: at relatively high energies, the narrow and forward-scattered distribution corresponds to the resonant or prompt charge transfer in large-impact-parameter collisions; small-impact-parameter or intimate collisions are preferred at the lower energies, leading to the H2O+ distribution closer to the center of masses. The charge transfers from N+ exhibit similar dynamics; by contrast, an intermediate complex (N⋯H2O)+ is more likely to be experienced in the low-energy intimate collision.

Comparison of COVID-19 testing strategies and costs for professional sports teams: A case study of J. League clubs

Professional sports teams are entertainment groups that earn income through performances, and they recognize that efforts to prevent the within-team spread of infection that could lead to performance cancellation are important. Infectious disease control involves several costs, some of which are in a trade-off relationship. For example, frequent testing can reduce the spread of infection, but it also leads to increased costs. On the other hand, limiting the number of tests can reduce testing costs, but it increases the revenue loss from players becoming infected and the loss from canceling games. Therefore, a methodology that strikes a reasonable balance between the cost of control measures and the risk of infection is needed. The relationship between infection control measures and the number of infected individuals was investigated through simulations using the susceptible-exposed-infected-recovered (SEIR) model. Two types of testing scenarios as control measures were principally considered: rapid antigen testing or the slower PCR testing (regular-testing scenarios); and regular testing with more frequent, additional testing after the appearance of an infected individual (additional-testing scenarios). Testing fees, revenue loss due to player or staff inactivity as a result of infection, and expenses for postponement or cancelation of matches were considered as costs. Regular antigen testing was found to be more effective than PCR testing in reducing the number of infected individuals and associated costs. There are two main reasons why antigen testing was more efficient: It is less expensive than PCR testing; and the results are available sooner (immediately, versus at least a day of waiting time for the PCR results). This was shown to markedly reduce the number of infected individuals.

Spontaneous single-molecule dissociation in infrared nanocavities

Ultrastrong light–matter interaction with molecular vibrations in infrared cavities has emerged as a tool for manipulating and controlling chemical reactivity. By studying the wavepacket dynamics of an individual polar diatomic molecule in a quantized infrared electromagnetic environment, we show that chemical bonds can efficiently dissociate in the absence of additional thermal or coherent energy sources, provided that the coupled system is prepared in a suitable diabatic state. Using hydrogen fluoride as a case study, we predict dissociation probabilities of up to 35% in less than 200 fs for a vibration-cavity system that is rapidly initialized with a low number of bare vibrational and cavity excitations. We develop a simple and general analytical model based on the multipolar formulation of quantum electrodynamics to show that the Bloch–Seigert shift of the bare vibrational ground state is a predictor of a threshold coupling strength below which no spontaneous dissociation is expected. The role of state-dependent permanent dipole moments in the light–matter interaction process is clarified. Our work paves the way toward the development of vacuum-assisted chemical reactors powered by ultrastrong light–matter interaction at the single-molecule level.

Deciphering insights into commercial Myrrh species authenticity from the psbA-trsnH genetic region

Objective The genetic analysis, particularly focusing on the psbA-trnH region, aims to tackle the challenges linked to myrrh identification and improve quality control in medicinal and aromatic plant sectors. This process reveals the genetic diversity inherent in myrrh species, identifies adulterants, and assesses consistency with pharmacopoeia-designated species. Methods A meticulous investigation was conducted, involving twenty-five myrrh samples sourced from diverse origins and one adulterant sample. The methodology encompassed precise execution of DNA extraction, PCR amplification targeting the psbA-trnH region, sequencing, and subsequent data analysis. Additionally, the integration of GenBank data was employed to enrich the genetic analysis. Results The psbA-trnH region demonstrated 100% amplification efficiency across all myrrh samples, accurately identifying three distinct species—Commiphora gileadensis, Commiphora myrrha, and Commiphora edulis. Only 8% of samples aligned with pharmacopoeia-specified species, revealing a significant misalignment. The identified adulterant, Liquidambar formosana, underscored the efficacy of the genetic approach. Genetic distances and haplotype analysis offered insights into myrrh species diversity. Intraspecific and interspecific distances highlighted the discriminatory potential of the psbA-trnH region. A phylogenetic tree illustrated distinct genetic clusters among Commiphora species and Liquidambar formosana. Conclusions It affirms the robustness of the psbA-trnH region for authenticating myrrh and emphasizes the necessity of adapting pharmacopoeial standards to accurately mirror genetic diversity. An avenue for exploring therapeutic variations within myrrh species and advocates collaboration among researchers, regulatory agencies, and industry stakeholders to fortify comprehensive quality management measures within the context of agronomy-focused herbal products.

Efficient dynamical field-theoretic simulations for multi-component systems

Understanding the phase behavior and dynamics of multi-component polymeric systems is essential for designing materials used in applications ranging from biopharmaceuticals to consumer products. While computational tools for understanding the equilibrium properties of such systems are relatively mature, simulation platforms for investigating non-equilibrium behavior are comparatively less developed. Dynamic self-consistent field theory (DSCFT) is a method that retains essential microscopic thermodynamics while enabling a continuum-level understanding of multi-component, multi-phase diffusive transport. A challenge with DSCFT is its high computational complexity and cost, along with the difficulty of incorporating thermal fluctuations. External potential dynamics (EPD) offers a more efficient approach to studying inhomogeneous polymers out of equilibrium, providing similar accuracy to DSCFT but with significantly lower computational cost. In this work, we introduce an extension of EPD to enable efficient and stable simulations of multi-species, multi-component polymer systems while embedding thermodynamically consistent noise. We validate this framework through simulations of a triblock copolymer melt and spinodally decomposing binary and ternary polymer blends, demonstrating its capability to capture key features of phase separation and domain growth. Furthermore, we highlight the role of thermal fluctuations in early stage coarsening. This study provides new insights into the interplay between stochastic and deterministic effects in the dynamic evolution of polymeric fluids, with the EPD framework offering a robust and scalable approach for investigating the complex dynamics of multi-component polymeric materials.

Monitoring physical behavior in pediatric physical therapy: A mixed methods feasibility study to evaluate a newly developed toolkit and training

Introduction Pediatric physical therapists (PPTs) aim to enhance active physical behavior but lack feasible accelerometry devices to assess and evaluate physical activity (PA). We developed an activity monitoring prototype toolkit (AM-p Toolkit) consisting of a wearable, a docking station, a digital tool for data analysis, and physical tools for communication with children and parents. A training for PPTs was also created. We aim to explore the feasibility of the AM-p Toolkit from the perspectives of PPTs, children, and parents and to assess if training improved PPTs’ knowledge, skills, and confidence in using the Toolkit. Participants and methods Using an explanatory sequential mixed methods design, we collected data through questionnaires, individual interviews, and focus groups, guided by Bowen’s dimensions of ‘acceptability,’ ‘demand,’ and ‘practicality.’ We included children with the ability to walk, their parents, and their PPTs. The training was evaluated by analyzing PPTs’ knowledge, skills, and confidence using the AM-p Toolkit. Quantitative results were analyzed descriptively (mean [SD] and median [interquartile range] when appropriate and qualitative data were analyzed thematically. Results Fifteen PPTs, 17 parents, and 20 children completed the study. PPTs rated overall satisfaction on a 10-point scale with the AM-p Toolkit at 6.3 (SD 1.2), and parents rated it 7.3 (SD 1.6). The following themes emerged for acceptability, demand, and practicality respectively: for acceptability: 1) expected added value, 2) quality and usability, and 3) design; for demand: 1) use and non-use, 2) further development, and 3) willingness for future use; and for practicality: 1) time constraints and 2) integration. Conclusion The AM-p Toolkit shows promise in PPT, with generally positive acceptability among all end-users. PPTs see potential for certain groups of children who can benefit from the AM-p Toolkit. Practicality requires improvements in the web application and refinement of the strap. Training is important and can be strengthened by emphasizing the analysis of assessment results, clinical reasoning, and functional goal-setting.

Tuning configurations and orbitals of vanadyl phthalocyanine on transition metals via surface alloy effect

Fabrication of well-ordered molecular films and further tuning their structural and electronic properties is crucial in enhancing the performance of the on-based organic devices. Herein, by high-resolution scanning tunneling microscopy and density functional theory calculation, we demonstrate the on-surface fabrication of well-organized vanadyl phthalocyanine (VOPc) membranes with diverse characteristics on the binary alloy monolayer. The molecular configurations, structures, and orbitals are clearly clarified in the submolecular level. On Ag2Sb/Ag(111), the VOPc membrane exhibits the fourfold symmetric unit cell comprising one centered and four cornered O-up molecules with two distinct stacking orientations. On the contrary, on Cu2Sb/Cu(111), all VOPc molecules adopt the O-down configuration and uniform orientations. The tunneling conductance spectra unveil a semiconductor signature but with different occupied orbitals for both VOPc membranes. These contrasting features are resulted from the diverse molecule–substrate interaction relating to the different charge transfer of alloy surfaces. Our study may open up a new route for modifying the structures and electronic states of the molecular films by applying surface alloy effects.