We present simulation results for the Donnan equilibrium between a homogeneous bulk reservoir and inhomogeneous confining geometries with varying number of restricted dimensions, . Planar slits ( = 1), cylindrical pores ( = 2), and spherical cavities ( = 3) are considered. The walls have a negative surface charge density. Because different dielectric constants are used in the reservoir and confined system, we used the Donnan grand canonical Monte Carlo method [Boda and Gillespie, J. Mol. Liq. , 123372 (2023)] to simulate the equilibrium. The systems with larger confining dimensionality produce greater adsorption of counterions (cations) into the confinements, so cation selectivity increases with increasing dimensionality. The systems with smaller dielectric constants produce more effective coion (anion) exclusion, so cation selectivity increases with decreasing dielectric constant. The combined effect of a more confining space and solvation penalty produces even more efficient anion exclusion and cation selectivity than each separately.

Diffusive adsorption/association is a fundamental step in almost all chemical reactions in diluted solutions, such as organic synthesis, polymerization, self-assembly, biomolecular interactions, electrode dynamics, catalysis, chromatography, air and water environmental dynamics, and social and market dynamics. However, predicting the rate of such a reaction is challenging using the equations established over 100 years ago. Several orders of magnitude differences between the theoretical predictions and experimental measurements for various systems, from self-assembled monolayers to protein-protein aggregations, make such calculations meaningless in many situations. I believe the major problem is that the time-dependent evolution curve of Fick's gradient is an ideal assumption in most cases, and its slope is significantly overestimated. This paper digs into Fick's gradient problem for 3D cases and provides a solution using the single-molecule diffusion probability density function discretely.

Scalable electronic brain implants with long-term stability and low biological perturbation are crucial technologies for high-quality brain-machine interfaces that can seamlessly access delicate and hard-to-reach regions of the brain. Here, we created "NeuroRoots," a biomimetic multi-channel implant with similar dimensions (7 m wide and 1.5 m thick), mechanical compliance, and spatial distribution as axons in the brain. Unlike planar shank implants, these devices consist of a number of individual electrode "roots," each tendril independent from the other. A simple microscale delivery approach based on commercially available apparatus minimally perturbs existing neural architectures during surgery. NeuroRoots enables high density single unit recording from the cerebellum and . NeuroRoots also reliably recorded action potentials in various brain regions for at least 7 weeks during behavioral experiments in freely-moving rats, without adjustment of electrode position. This minimally invasive axon-like implant design is an important step toward improving the integration and stability of brain-machine interfacing.

We investigated the interaction of DNA nucleobases [adenine (A), guanine (G), thymine (T), and cytosine (C)] with single-layer TiC MXene using Van der Waals (vdW)-corrected density functional theory and non-equilibrium Green's function methods. All calculations were benchmarked against graphene. We showed that depending on the initial vertical height of a nucleobase above the TiC surface, two interaction mechanisms are possible, namely, physisorption and chemisorption. For graphene, DNA nucleobases always physisorbed onto the graphene surface irrespective of the initial vertical height of the nucleobase above the graphene sheet. The PBE+vdW binding energies for graphene are high (0.55-0.74 eV) and follow the order G > A > T > C, with adsorption heights in the range of 3.16-3.22 Å, indicating strong physisorption. For TiC, the PBE+vdW binding energies are relatively weaker (0.16-0.20 eV) and follow the order A > G = T > C, with adsorption heights in the range of 5.51-5.60 Å, indicating weak physisorption. The binding energies for chemisorption follow the order G > A > T > C, which is the same order for physisorption. The binding energy values (5.3-7.5 eV) indicate very strong chemisorption (∼40 times larger than the physisorption binding energies). Furthermore, our band structure and electronic transport analysis showed that for physisorption, there is neither significant variation in the band structure nor modulation in the transmission function and device density of states. The relatively weak physisorption and strong chemisorption show that TiC might not be capable of identifying DNA nucleobases using the physisorption method.

In this work, we describe the formation of geometric phases during nonadiabatic frequency swept (FS) radio frequency (RF) pulses with sine amplitude modulation and cosine frequency modulation functions. The geometric phases during the FS pulse were analyzed using a Schrödinger equation formalism, and the unified analytical expression for the geometric phase was derived. We present the solutions for sub-geometric phase components incorporated in spinor wavefunctions for the RF Hamiltonian of spin ½ nuclei. We demonstrate that the geometric phases during sine/cosine RF pulses are opposite in signs for different initial conditions of the spinor and that geometric phases can accumulate in correspondence to different magnetization trajectories. The derived formalism could be extended for the evaluation of the geometric phases during a wide class of amplitude- and frequency-modulated pulses used in MRI and in high-resolution NMR.

Computational modeling of neuroactivity plays a central role in our effort to understand brain dynamics in the advancements of neural engineering such as deep brain stimulation, neuroprosthetics, and magnetic resonance electrical impedance tomography. However, analytic solutions do not capture the fundamental nonlinear behavior of an action potential. What is needed is a method that is not constrained to only linearized models of neural tissue. Therefore, the objective of this study is to establish a robust, straightforward process for modeling neurodynamic phenomena, which preserves their nonlinear features. To address this, we turn to decomposition methods from homotopy analysis, which have emerged in recent decades as powerful tools for solving nonlinear differential equations. We solve the nonlinear ordinary differential equations of three landmark models of neural conduction-Ermentrout-Kopell, FitzHugh-Nagumo, and Hindmarsh-Rose models-using George Adomian's decomposition method. For each variable, we construct a power series solution equivalent to a generalized Taylor series expanded about a function. The first term of the decomposition series comes from the models' initial conditions. All subsequent terms are recursively determined from the first. We show rapid convergence, achieving a maximal error of with only eight terms. We extend the region of convergence with one-step analytic continuation so that our complete solutions are decomposition splines. We show that this process can yield solutions for single- and multi-variable models and can characterize a single action potential or complex bursting patterns. Finally, we show that the accuracy of this decomposition approach favorably compares to an established polynomial method, B-spline collocation. The strength of this method, besides its stability and ease of computation, is that, unlike perturbation, we make no changes to the models' equations; thus, our solutions are to the problems at hand, not simplified versions. This work validates decomposition as a viable technique for advanced neural engineering studies.

Faraday rotation is considered a gold standard measurement of the electronic spin polarization of an alkali metal vapor produced under optical pumping. However, during the production of large volumes of hyperpolarized xenon gas, transmission monitoring measurements, otherwise known as field cycling measurements, are generally employed to measure the spin polarization of alkali metal atoms as this method is easier to implement than Faraday rotation on standard polarizer setups. Here, we present a simple, low-cost experimental setup to perform Faraday rotation measurements of the electronic spin polarization of alkali metal atoms that can be easily implemented on standard polarizer setups. We then compare Rb polarization measurements obtained with the Faraday rotation method to those obtained with the transmission monitoring method. To our knowledge, a direct comparison of these methods has never been made. Overall, we found good agreement between the two methods, but at low Rb density and high laser power, we found evidence of nonlinear magneto-optical effects that may prevent Faraday rotation from being used under these conditions.

The present paper investigates droplet and aerosol emission from the human respiratory function by numerical and experimental methods, which is analyzed at the worst-case scenario, a violent sneeze without a face covering. The research findings develop the understanding of airborne disease transmission relevant to COVID-19, its recent variants, and other airborne pathogens. A human sneeze is studied using a multiphase Computational Fluid Dynamics (CFD) model using detached eddy simulation coupled to the emission of droplets that break up, evaporate, and disperse. The model provides one of the first experimental benchmarks of CFD predictions of a human sneeze event. The experiments optically capture aerosols and droplets and are processed to provide spatiotemporal data to validate the CFD model. Under the context of large random uncertainty, the studies indicate the reasonable correlation of CFD prediction with experimental measurements using velocity profiles and exposure levels, indicating that the model captures the salient details relevant to pathogen dispersion. Second, the CFD model was extended to study the effect of relative humidity with respect to the Wells curve, providing additional insight into the complexities of evaporation and sedimentation characteristics in the context of turbulent and elevated humidity conditions associated with the sneeze. The CFD results indicated correlation with the Wells curve with additional insight into features, leading to non-conservative aspects associated with increased suspension time. These factors are found to be associated with the combination of evaporation and fluid-structure-induced suspension. This effect is studied for various ambient air humidity levels and peaks for lower humidity levels, indicating that the Wells curve may need a buffer in dry climates. Specifically, we find that the increased risk in dry climates may be up to 50% higher than would be predicted using the underlying assumptions in Wells' model.

Photo-mediated ultrasound therapy (PUT) is a novel technique utilizing synchronized ultrasound and laser to generate enhanced cavitation inside blood vessels. The enhanced cavitation inside blood vessels induces bio-effects, which can result in the removal of micro-vessels and the reduction in local blood perfusion. These bio-effects have the potential to treat neovascularization diseases in the eye, such as age-related macular degeneration and diabetic retinopathy. Currently, PUT is in the preclinical stage, and various PUT studies on rabbit eye models have shown successful removal of micro-vessels. PUT is completely non-invasive and particle-free as opposed to current clinical treatments such as anti-vascular endothelial growth factor therapy and photodynamic therapy, and it precisely removes micro-vessels without damaging the surrounding tissue, unlike laser photocoagulation therapy. The stresses produced by oscillating bubbles during PUT are responsible for the induced bio-effects in blood vessels. In our previous work, stresses induced during the first phase of PUT due to combined ultrasound and laser irradiation were studied using a 2D model. In this work, stresses induced during the third or last phase of PUT due to ultrasound alone were studied using a 3D finite element method-based numerical model. The results showed that the circumferential and shear stress increased as the bubble moves from the center of the vessel toward the vessel wall with more than a 16 times increase in shear stress from 1.848 to 31.060 kPa as compared to only a 4 times increase in circumferential stress from 211 to 906 kPa for a 2 m bubble placed inside a 10 m vessel on the application of 1 MHz ultrasound frequency and 130 kPa amplitude. In addition, the stresses decreased as the bubble was placed in smaller sized vessels with a larger decrease in circumferential stress. The changes in shear stress were found to be more dependent on the bubble-vessel wall distance, and the changes in circumferential stress were more dependent on the bubble oscillation amplitude. Moreover, the bubble shape changed to an ellipsoidal with a higher oscillation amplitude in the vessel's axial direction as it was moved closer to the vessel wall, and the bubble oscillation amplitude decreased drastically as it was placed in vessels of a smaller size.

The dispersion of cough-generated droplets from a person going up- or downstairs was investigated through a laboratory experiment in a water tunnel. This experiment was carried out with a manikin mounted at inclination angles facing the incoming flow to mimic a person going up or down. Detailed velocity measurements and flow visualization were conducted in the water tunnel experiments. To investigate the influence of the initial position on the motion of particles, a virtual particle approach was adopted to simulate the dispersion of particles using the measured velocity field. Particle clustering, which is caused by the unsteadiness of the flow, was observed in both flow visualization and virtual particle simulation. For the case of going upstairs, particles are concentrated below the person's shoulder and move downward with a short travel distance. For the case of going downstairs, particles dispersing over the person's head advect over for a long distance. We also found that the motion of the particles is closely related to the initial position. According to the results in this study, suggestions for the prevention of respiratory infectious disease are made.

The COVID19 infection is known to disseminate through droplets ejected by infected individuals during coughing, sneezing, speaking, and breathing. The spread of the infection and hence its menace depend on how the virus-loaded droplets evolve in space and time with changing environmental conditions. In view of this, we investigate the evolution of the droplets within the purview of the Brownian motion of the evaporating droplets in the air with varying weather conditions under the action of gravity. We track the movement of the droplets until either they gravitationally settle on the ground or evaporate to aerosols of size 2 m or less. Droplets with radii 2 m or less may continue to diffuse and remain suspended in the air for a long time. The effects of relative humidity and temperature on the evaporation are found to be significant. We note that under strong flowing conditions, droplets travel large distances. It is found that the bigger droplets fall on the ground due to the dominance of gravity over the diffusive force despite the loss of mass due to evaporation. The smaller evaporating droplets may not settle on the ground but remain suspended in the air due to the dominance of the diffusive force. The fate of the intermediate size droplets depends on the weather conditions and plays crucial roles in the spread of the infection. These environment dependent effects indicate that the maintenance of physical separation to evade the virus is not corroborated, making the use of face masks indispensable.

This report uses Monte Carlo simulations to connect stochastic single-molecule and ensemble surface adsorption of molecules from dilute solutions. Monte Carlo simulations often use a fundamental time resolution to simulate each discrete step for each molecule. The adsorption rate obtained from such a simulation surprisingly contains an error compared to the results obtained from the traditional method. Simulating adsorption kinetics is interesting in many processes, such as mass transportation within cells, the kinetics of drug-receptor interactions, membrane filtration, and other general reaction kinetics in diluted solutions. Thus, it is important to understand the origin of the disagreement and find a way to correct the results. This report reviews the traditional model, explains the single-molecule simulations, and introduces a method to correct the results of adsorption rate. For example, one can bin finer time steps into time steps of interest to simulate the fractal diffusion or simply introduce a correction factor for the simulations. Then two model systems, self-assembled monolayer (SAM) and biosensing on the patterned surface, are simulated to check the accuracy of the equations. It is found that the adsorption rate of SAM is highly dependent on the conditions and the uncertainty is large. However, the biosensing system is relatively accurate. This is because the concentration gradient near the interface varies significantly with reaction conditions for SAMs while relatively stable for the biosensing system.

Aerosol particles are one of the main routes of transmission of COVID-19. Mobile air purifiers are used to reduce the risk of infection indoors. We focus on an air purifier that generates a defined volumetric air flow through a highly efficient filter material. We investigate the transport of aerosol particles from an infected dummy equipped with an aerosol generator to receiving thermal dummies. For analysis, we use up to 12 particle sensors to monitor the particle concentration with high spatial resolution. Based on the measurement data, a computational fluid dynamics (CFD) model is set up and validated. The experimental and numerical methods are used to investigate how the risk of infection suggested by the particle exposure in an exemplary lecture hall can be reduced by a clever choice of orientation of the air purifier. It turns out that obstructing the outlet stream of the air purifier may be particularly advantageous. The particle concentration at the head height deviates by 13% for variations of the location and orientation. At an air change per hour of 5, the cumulated PM1 mass at the head level was reduced by 75%, independently of the location of the infected dummy, compared to the "natural decay" case, showing that filtration is an effective means of reducing aerosol particle concentrations. Finally, CFD simulation was used to monitor the particle fates. The steady simulation results fit quite well with the experimental findings and provide additional information about the particle path and for assessing the comfort level due to air flow.

The structural evolution of a Pt thin film following photo-thermal excitation by 1 ps optical laser pulses was studied with a time resolution of 100 ps over a total time period of 1 ms. Laser pulse fluences below 50 mJ/cm were insufficient to relax the residual stress state of the as-prepared film even after 10 000 pulses. In this fluence regime, a rapid initial lattice expansion and a decrease in the lattice coherence length due to ultrafast photo-thermal heating were observed. The lattice expansion reached a maximum, and the coherence length reached a minimum, 100-200 ps after excitation before monotonically decaying back to their initial values in about 1 s. Laser pulse fluences greater than 50 mJ/cm produced irreversible stress relaxation within the first 10 optical pulses. In this regime, the lattice expansion was qualitatively similar to that in the low fluence regime, except that the initial structural state was not recovered. The evolution in the coherence length, however, was more complex. Following an initial decrease similar to that observed at low fluence, the coherence length then increased to a broad maximum greater than the initial value, before recovery.

We propose a theoretical model to elucidate intermolecular electrostatic interactions between a virus and a substrate. Our model treats the virus as a homogeneous particle having surface charge and the polymer fiber of the respirator as a charged plane. Electric potentials surrounding the virus and fiber are influenced by the surface charge distribution of the virus. We use Poisson-Boltzmann equations to calculate electric potentials. Then, Derjaguin's approximation and a linear superposition of the potential function are extended to determine the electrostatic force. In this work, we apply this model for coronavirus or SARS-CoV-2 case and numerical results quantitatively agree with prior simulation. We find that the influence of fiber's potential on the surface charge of the virus is important and is considered in interaction calculations to obtain better accuracy. The electrostatic interaction significantly decays with increasing separation distance, and this curve becomes steeper when adding more salt. Although the interaction force increases with heating, one can observe the repulsive-attractive transition when the environment is acidic.

The COVID-19 pandemic has caused a high demand for filtering facepiece respirators (FFRs), which has brought global challenges in sustaining the supply chain for FFRs. Because respirators are basic personal protective equipment to protect frontline healthcare workers against COVID-19, the chronic, global shortage of N95/N99 masks is one of the most urgent threats to our collective ability to save lives from the coronavirus. The reuse of masks may need to be considered as a crisis capacity strategy to ensure continued availability even though most of the masks are considered one-time use. Moreover, environmentalists warn that single-use masks add to the glut of plastic pollution, threatening the health of oceans and marine life. In this study, we develop a method to decontaminate respirators to reuse filtering facepiece respirators. Samples of SARS-CoV-2 are applied to the 4 × 4 cm samples of FFP2 and FFP3 respirator materials. The filtration efficiency of plasma treated samples is measured using a planar particle image velocimetry technique with a neutrally charged polydisperse aerosol particle of NaCl. The measured viral decontamination and filtration efficiencies show that the developed plasma decontamination system can achieve a 4-log reduction for the coronavirus without reducing the filtration efficiency of masks after 5-min plasma exposure. The developed plasma decontamination system demonstrates the feasibility to tackle the acute shortages of FFRs in many countries and their environmental and economic burdens against discarding reusable masks.

Cold atmospheric plasma (CAP), regarded as a powerful physics technology, displays antimicrobial, antitumor, and even antiviral properties, but the underlying mechanism is rarely studied. In this study, four CAP exposure doses (30, 60, 120, and 240 s) were applied to inactivate a severe acute respiratory syndrome coronavirus 2 like pseudovirus on a stainless steel disk, which comprised spike protein on its membrane and can express a green fluorescent protein. In order to unravel the potential effects of CAP irradiation on pseudovirus, infection assay, optical emission spectra analysis, transmission electron microscopy (TEM), sodium dodecyl sulfate polyacrylamide gel electrophoresis, ELISA, and qPCR experiments were carried out. As a result, our study indicated that CAP irradiation can significantly decrease the infectivity of pseudovirus in a dose dependent manner through destroying the cell membrane and further damaging viral RNA, with the molecular weight and conformation of spike receptor binding domain protein unchanged.

The transport of virus-laden aerosols from a host to a susceptible person is governed by complex turbulent airflow and physics related to breathing, coughing and sneezing, mechanical and passive ventilation, thermal buoyancy effects, surface deposition, masks, and air filtration. In this paper, we study the infection risk via airborne transmission on an urban bus using unsteady Reynolds-averaged Navier-Stokes equations and a passive-scalar model of the virus-laden aerosol concentration. Results from these simulations are directly compared to the widely used well-mixed model and show significant differences in the concentration field and number of inhaled particles. Specifically, in the limit of low mechanical ventilation rates, the well-mixed model will overpredict the concentration far from the infected passenger and substantially underpredict the concentration near the infected passenger. The results reported herein also apply to other enclosed spaces.

This work introduces a method for co-localized multi-modal imaging of sub-m features in an additively manufactured (AM) titanium alloy. Ti-6Al-4V parts manufactured by electron beam melting powder bed fusion were subjected to hot isostatic pressing to seal internal porosity and machined to remove contour-hatch interfaces. Electron microscopy and atomic force microscopy-based techniques (electron backscatter diffraction and scanning Kelvin probe force microscopy) were used to measure and categorize the effects of crystallographic texture, misorientation, and phase content on the relative differences in the Volta potential of -Ti and -Ti phases. Given the tunability of additive manufacturing processes, recommendations for texture and phase control are discussed. In particular, our findings indicate that the potential for micro-galvanic corrosion initiation can be regulated in AM Ti-6Al-4V parts by minimizing both the total area of {111} prior-β grains and the number of contact points between {111} β grains and laths that originate from {001} prior-β grains.

Lithium niobate (LN) is used in diverse applications such as spectroscopy, remote sensing, and quantum communications. The emergence of lithium-niobate-on-insulator (LNOI) technology and its commercial accessibility represent significant milestones. This technology aids in harnessing the full potential of LN's properties, such as achieving tight mode confinement and strong overlap with applied electric fields, which has enabled LNOI-based electro-optic modulators to have ultra-broad bandwidths with low-voltage operation and low power consumption. Consequently, LNOI devices are emerging as competitive contenders in the integrated photonics landscape. However, the nanofabrication, particularly LN etching, presents a notable challenge. LN is hard, dense, and chemically inert. It has anisotropic etch behavior and a propensity to produce material redeposition during the reactive-ion plasma etch process. These factors make fabricating low-loss LNOI waveguides (WGs) challenging. Recognizing the pivotal role of addressing these fabrication challenges for obtaining low-loss WGs, our research focuses on a systematic study of various process steps in fabricating LNOI WGs and other photonic structures. In particular, our study involves (i) careful selection of hard mask materials, (ii) optimization of inductively coupled plasma etch parameters, and finally, (iii) determining the optimal post-etch cleaning approach to remove redeposited material on the sidewalls of the etched photonic structures. Using the recipe established, we realized optical WGs with total (propagation and coupling) loss value of -10.5 dB, comparable to established values found in the literature. Our findings broaden our understanding of optimizing fabrication processes for low-loss lithium-niobate waveguides and can serve as an accessible resource in advancing LNOI technology.

Hyperspectral luminescence imaging adds high-resolution spectral data to electroluminescence and photoluminescence images of photovoltaic materials and devices. This enables absolute calibration across a range of spectra, and subsequently enhances the information that can be gained from such measurements. We present a temperature-dependent luminescence hyperspectral imaging study of dilute InGaAs solar cells. We are able to identify the cause of dark spots on the device as local areas with increased defect-related recombination and identify a likely candidate for the type of defect. Hyperspectral images also reveal a device-wide pattern in low-energy-tail luminescence and In alloy fraction, which corresponds with increased nonradiative recombination. This pattern would not be identifiable with conventional imaging methods. Detailed information on such features is useful as, paired with knowledge of fabrication processes and device design features, it can help identify ways to reduce associated non-radiative recombination and improve device performance.