Diffusion Interaction Research Articles

Dynamic Light Scattering Analysis of Lipid Nanoparticles: Effect of Salts on the Diffusion Interaction Parameter and Hydrodynamic Radius at Infinite Dilution.

The rise in the popularity of lipid nanoparticle (LNP)-based formulations necessitates the need for screening tools to quickly predict their colloidal stability in the presence of common excipients. Protein chemists have employed the diffusion interaction parameter (kD) determined using dynamic light scattering as an indicator of formulation stability, yet this approach has not been applied to particulate systems. Herein, kD measurements of LNPs revealed behavior dissimilar to that of proteins. LNP interactions were inherently weakly attractive and unaffected by increasing concentrations of NaCl. The small change in the value in the presence of different salts was dependent upon salt molecular identity and consistent with the Hofmeister series. In addition, calculation of the hydrodynamic radius at infinite dilution (RH,0) revealed a slight reduction in the LNP size with increasing NaCl concentration. Overall, while traditional kD measurements provide limited information about LNP stability, the assay provides insight into physical changes to LNP in the presence of excipients via extrapolation of the diffusion coefficient to infinite dilution.

Lattice-guided growth of dense arrays of aligned transition metal dichalcogenide nanoribbons with high catalytic reactivity.

Transition metal dichalcogenides (TMDs) exhibit unique properties and potential applications when reduced to one-dimensional (1D) nanoribbons (NRs), owing to quantum confinement and high edge densities. However, effective growth methods for self-aligned TMD NRs are still lacking. We demonstrate a versatile approach for lattice-guided growth of dense, aligned MoS2 NR arrays via chemical vapor deposition (CVD) on anisotropic sapphire substrates, without tailored surface steps. This method enables the synthesis of NRs with widths below 10 nanometers and longitudinal axis parallel to the zigzag direction, being also extensible to the growth of WS2 NRs and MoS2-WS2 heteronanoribbons. Growth is influenced by both substrate and CVD temperature, indicating the role of anisotropic precursor diffusion and substrate interaction. The 1D nature of the NRs was asserted by the observation of Coulomb blockade at low temperatures. Pronounced catalytic activity was observed at the edges of the NRs, indicating their promise for efficient catalysis.

Chromium adsorption using a composite adsorbent of corn waste and bentonite

Chromium, a highly toxic heavy metal, poses significant risks to both human health and environmental quality. Its adsorption in wastewater using low-cost, easily implementable technologies has emerged as a crucial solution for mitigating its harmful impact. This study explores the effectiveness of a composite adsorbent made from bentonite and corn waste for chromium adsorption. Experiments were conducted in a laboratory-scale batch system. The research examined the adsorption kinetics and equilibrium, process optimization, and the mechanisms of chromium adsorption. For optimization, a response surface methodology was applied considering three variables: adsorption time (min), adsorbent dosage (g/L), and initial chromium concentration (mg/L). The findings suggest that the adsorption kinetics fit best with the pseudo-first-order model (R2 = 0.968), and the adsorption equilibrium fits with the Freundlich model (R2 = 0.997). During optimization, the adsorbent dosage emerged as the most critical factor for chromium removal. The optimal operating conditions were determined to be 103 minutes, 29.71 g/L of adsorbent, and an initial chromium concentration of 31.13 mg/L. The results indicate that chromium adsorption is a multifaceted process involving diffusion and subsequent interaction at the surface and edges of the bentonite layers. Chemical analysis, coupled with changes in the FTIR spectrum, suggests an interaction between chromium and the silicon and aluminum components of the bentonite. These findings underscore the potential of the composite adsorbent for effective chromium removal.

An Underlying Cause and Solution to the Poor Size Exclusion Chromatography Performance of Antibody-Drug Conjugates.

Antibody-drug conjugate (ADC) size variants are frequently assessed by size exclusion chromatography (SEC). However, poor chromatography performance is often observed during SEC analysis. Existing studies have primarily focused on qualitatively describing non-specific interactions between ADCs and the column matrix. The purposes of the current study are to introduce an underlying cause from a novel perspective on the protein-protein interaction (PPI) mechanism, characterized by quantifying diffusion interaction parameter (kD) values, and to provide several strategies to reduce PPI and improve column performance during SEC analysis. Two kinds of ADCs with varying hydrophobicity properties and their corresponding monoclonal antibodies are used as models. The hydrophobicity of these products was verified using the relative calculated logarithm of the partition coefficient of a substance in n-octanol (oil) and water (rCLogP) and reversed-phase high performance liquid chromatography (RP-HPLC), and the size variants were analyzed using SEC. Finally, the PPI was characterized by kD values of these four products. The results of rCLogP and RP-HPLC indicated that ADC-1 is relatively hydrophobic, whereas ADC-2 is relatively hydrophilic. In the SEC analysis of the ADC-1, substituting sodium chloride with L-arginine hydrochloride or adding a specific concentration of acetonitrile as an organic solvent to the mobile phase resulted in reduced PPI and enhanced column performance. Conversely, the impact on ADC-2 was negligible. This study provides insights into improving the performance of SEC analysis for ADCs through strategies involving alterations in mobile phase composition. The changes in column performance can be quantitatively explained by the PPI mechanism.

Traveling waves in an ensemble of excitable oscillators: The interplay of memristive coupling and noise

Using methods of numerical simulation, we demonstrate the constructive role of memristive coupling in the context of the traveling wave formation and robustness in an ensemble of excitable oscillators described by the FitzHugh–Nagumo neuron model. First, the revealed aspects of the memristive coupling action are shown in an example of the deterministic model where the memristive properties of the coupling elements provide for achieving traveling waves at lower coupling strength as compared to non-adaptive diffusive coupling. In the presence of noise, the positive role of memristive coupling is manifested as significant, increasing a noise intensity critical value corresponding to the noise-induced destruction of traveling waves as compared to classical diffusive interaction. In addition, we point out the second constructive factor, the Lévy noise, whose properties provide for inducing traveling waves.

Asymptotic stability in a predator-prey system with density-dependent diffusion and indirect pursuit-evasion interaction in 2D

This paper deals with a predator-prey system with density-dependent diffusion and indirect pursuit-evasion interaction under homogeneous Neumann boundary conditions. By providing appropriate conditions, the asymptotic stability of solution is investigated.

Surface treatment of metal by combined particle beam

This work is related to modeling of metal surface modification process by combined particles beam. On the basis of thermodynamics of irreversible processes, including equations of state in differential form, a nonlinear model is formulated. The model takes into account the interaction of thermal, diffusion and mechanical waves and finiteness of relaxation times of thermal and diffusion processes. For the combined particle flow such model is proposed for the first time. The numerical algorithm is based on implicit difference schemes. The study of the interaction of waves of different nature is carried out on the example of a copper target treated with nickel and gold particles. It is shown that deformations take the maximal value at the left boundary, which is directly related to the presence of impurity concentration gradients. Depending on the pulse duration, the difference between the extrema on the elastic wave becomes less significant. With increasing temperature, obviously, the diffusion process accelerates. The propagation velocities of the interacting waves are different. The character of distributions of concentrations of introduced particles directly depends on the value of parameters proportional to relaxation times.

First-principles study of Re in BCC-Mo: Diffusion behavior and interaction with point defects

Due to their some beneficial properties, molybdenum-based alloys, such as Mo-Re alloys, are recognized as potential structural materials for nuclear power reactors. Irradiation induced precipitation of rhenium (Re) atoms causes hardening and embrittlement of Mo-Re alloys, restricting their application. The interaction of rhenium (Re) atoms with point defects (PDs), as well as the diffusion behavior of Re atoms in BCC-Mo (Body Center Cubic-molybdenum), were investigated using first-principles methods. The results revealed that Re atoms exhibited high binding energies with both vacancy (Vac) and interstitial dumbbells. Furthermore, the binding energies increased with the number of Re atoms. The binding energies of Re with self-interstitial dumbbell (SIA, ie., Mo-Mo) and mixed interstitial dumbbell (Mo-Re) were quite close to. Due to the high exchange barrier between Vac and Re, the diffusion of rhenium through the vacancy-drag mechanism was difficult. Due to the low migration and rotation barrier of Mo-Re mixed interstitial dumbbell, the diffusion of Re atoms in Mo was dominated by the interstitial-mediated mechanism. From the perspective of diffusion dynamics, only interstitial dumbbells can promote the aggregation of Re atoms. By comparing the binding energy of interstitial dumbbell with interstitial dumbbell and interstitial dumbbell with Re atoms, pairs of Mo-Re interstitial dumbbell was suggested to be the nucleation sites to attract more interstitial dumbbells, thereby promoting the precipitation of Re clusters. It was because they had high binding energy and were difficult to decompose once combined.

Floating Photothermal Hydrogen Production.

Solar-to-hydrogen (STH) is emerging as a promising approach for energy storage and conversion to contribute to carbon neutrality. The lack of efficient catalysts and sustainable reaction systems is stimulating the fast development of photothermal hydrogen production based on floating carriers to achieve unprecedented STH efficiency. This technology involves three major components: floating carriers with hierarchically porous structures, photothermal materials for solar-to-heat conversion and photocatalysts for hydrogen production. Under solar irradiation, the floating photothermal system realizes steam generation which quickly diffuses to the active site for sustainable hydrogen generation with the assistance of a hierarchically porous structure. Additionally, this technology is endowed with advantages in the high utilization of solar energy and catalyst retention, making it suitable for various scenarios, including domestic water supply, wastewater treatment, and desalination. A comprehensive overview of the photothermal hydrogen production system is present due to the economic feasibility for industrial application. The in-depth mechanism of a floating photothermal system, including the solar-to-heat effect, steam diffusion, and triple-phase interaction are highlighted by elucidating the logical relationship among buoyant carriers, photothermal materials, and catalysts for hydrogen production. Finally, the challenges and new opportunities facing current photothermal catalytic hydrogen production systems are analyzed.

Flow Activation Energy of High-Concentration Monoclonal Antibody Solutions and Protein-Protein Interactions Influenced by NaCl and Sucrose.

The solution viscosity and protein-protein interactions (PPIs) as a function of temperature (4-40 °C) were measured at a series of protein concentrations for a monoclonal antibody (mAb) with different formulation conditions, which include NaCl and sucrose. The flow activation energy (Eη) was extracted from the temperature dependence of solution viscosity using the Arrhenius equation. PPIs were quantified via the protein diffusion interaction parameter (kD) measured by dynamic light scattering, together with the osmotic second virial coefficient and the structure factor obtained through small-angle X-ray scattering. Both viscosity and PPIs were found to vary with the formulation conditions. Adding NaCl introduces an attractive interaction but leads to a significant reduction in the viscosity. However, adding sucrose enhances an overall repulsive effect and leads to a slight decrease in viscosity. Thus, the averaged (attractive or repulsive) PPI information is not a good indicator of viscosity at high protein concentrations for the mAb studied here. Instead, a correlation based on the temperature dependence of viscosity (i.e., Eη) and the temperature sensitivity in PPIs was observed for this specific mAb. When kD is more sensitive to the temperature variation, it corresponds to a larger value of Eη and thus a higher viscosity in concentrated protein solutions. When kD is less sensitive to temperature change, it corresponds to a smaller value of Eη and thus a lower viscosity at high protein concentrations. Rather than the absolute value of PPIs at a given temperature, our results show that the temperature sensitivity of PPIs may be a more useful metric for predicting issues with high viscosity of concentrated solutions. In addition, we also demonstrate that caution is required in choosing a proper protein concentration range to extract kD. In some excipient conditions studied here, the appropriate protein concentration range needs to be less than 4 mg/mL, remarkably lower than the typical concentration range used in the literature.

Study on the Impact of Pole Spacing on Magnetic Flux Leakage Detection under Oversaturated Magnetization.

Magnetic flux leakage (MFL) inspection employs leakage magnetic fields to effectively detect and locate pipeline defects. The spacing between magnetic poles significantly affects the leakage magnetic field strength. While most detectors typically opt for moderate pole spacing for routine detection, this study investigates the propagation characteristics of MFL signals at small pole spacings (under specimen oversaturated magnetization) and their impact on MFL detection. Through finite element simulation and experiments, it reveals a new signal phenomenon in the radial MFL signal By at small pole spacings, the double peak-valley (DPV) phenomenon, characterized by outer and inner peaks and valleys. Theoretical analysis based on the simulation results elucidates the mechanisms for this DPV phenomenon. Based on this, the impact of defect size, pipe wall thickness, and magnetic pole and rigid brush height on MFL signals under small magnetic pole spacings is examined. It is demonstrated that, under a smaller magnetic pole spacing, a potent background magnetic field manifests in the air above the defect. This DPV phenomenon is generated by the magnetic diffusion and compression interactions between the background and defect leakage magnetic fields. Notably, the intensity of the background magnetic field can be mitigated by reducing the height of the rigid brush. In contrast, the pipe wall thickness and magnetic pole height exhibit a negligible influence on the DPV phenomenon. The emergence of the DPV precipitates a reduction in the peak-to-valley difference within the MFL signal, constricting the depth range of detectable defects. However, the presence of DPV increases the identification of defects with smaller opening sizes. These findings reveal the characterization of the MFL signal under small pole spacing, offering a preliminary study on identifying specific defects using unconventional signals. This study provides valuable guidance for MFL detection.

Direct Visualization of Defect-Controlled Diffusion in van der Waals Gaps.

Diffusion processes govern fundamental phenomena such as phase transformations, doping, and intercalation in van der Waals (vdW) bonded materials. Here, the diffusion dynamics of W atoms by visualizing the motion of individual atoms at three different vdW interfaces: hexagonal boron nitride (BN)/vacuum, BN/BN, and BN/WSe2, by recording scanning transmission electron microscopy movies is quantified. Supported by density functional theory (DFT) calculations, it is inferred that in all cases diffusion is governed by intermittent trapping at electron beam-generated defect sites. This leads to diffusion properties that depend strongly on the number of defects. These results suggest that diffusion and intercalation processes in vdW materials are highly tunable and sensitive to crystal quality. The demonstration of imaging, with high spatial and temporal resolution, of layers and individual atoms inside vdW heterostructures offers possibilities for direct visualization of diffusion and atomic interactions, as well as for experiments exploring atomic structures, their in situ modification, and electrical property measurements of active devices combined with atomic resolutionimaging.

Cumulative asparagine to aspartate deamidation fails to perturb γD-crystallin structure and stability.

Deamidation frequently is invoked as an important driver of crystallin aggregation and cataract formation. Here, we characterized the structural and biophysical consequences of cumulative Asn to Asp changes in γD-crystallin. Using NMR spectroscopy, we demonstrate that N- or C-terminal domain-confined or fully Asn to Asp changed γD-crystallin exhibits essentially the same 1H-15N HSQC spectrum as the wild-type protein, implying that the overall structure is retained. Only a very small thermodynamic destabilization for the overall Asn to Asp γD-crystallin variants was noted by chaotropic unfolding, and assessment of the colloidal stability, by measuring diffusion interaction parameters, yielded no substantive differences in association propensities. Furthermore, using molecular dynamics simulations, no significant changes in dynamics for proteins with Asn to Asp or iso-Asp changes were detected. Our combined results demonstrate that substitution of all Asn by Asp residues, reflecting an extreme case of deamidation, did not affect the structure and biophysical properties of γD-crystallin. This suggests that these changes alone cannot be the major determinant in driving cataract formation.

YOLO-FMDI: A Lightweight YOLOv8 Focusing on a Multi-Scale Feature Diffusion Interaction Neck for Tomato Pest and Disease Detection

At the present stage, the field of detecting vegetable pests and diseases is in dire need of the integration of computer vision technologies. However, the deployment of efficient and lightweight object-detection models on edge devices in vegetable cultivation environments is a key issue. To address the limitations of current target-detection models, we propose a novel lightweight object-detection model based on YOLOv8n while maintaining high accuracy. In this paper, (1) we propose a new neck structure, Focus Multi-scale Feature Diffusion Interaction (FMDI), and inject it into the YOLOv8n architecture, which performs multi-scale fusion across hierarchical features and improves the accuracy of pest target detection. (2) We propose a new efficient Multi-core Focused Network (MFN) for extracting features of different scales and capturing local contextual information, which optimizes the processing power of feature information. (3) We incorporate the novel and efficient Universal Inverted Bottleneck (UIB) block to replace the original bottleneck block, which effectively simplifies the structure of the block and achieves the lightweight model. Finally, the performance of YOLO-FMDI is evaluated through a large number of ablation and comparison experiments. Notably, compared with the original YOLOv8n, our model reduces the parameters, GFLOPs, and model size by 18.2%, 6.1%, and 15.9%, respectively, improving the mean average precision (mAP50) by 1.2%. These findings emphasize the excellent performance of our proposed model for tomato pest and disease detection, which provides a lightweight and high-precision solution for vegetable cultivation applications.

Measuring the Adsorption Cross Section of YOYO-1 to Immobilized DNA Molecules.

Many interactions between small molecules and particles occur in solutions. They are surrounded by other molecules that do not react, for example, biological processes in water, chemical reactions in gas or liquid solutions, and environmental reactions in air and water. However, predicting the rate of such diffusive interactions remains challenging, due to the random motion of molecules in solutions, as exampled by the famous Brownian motion of pollen particles. In this report, we experimentally confirmed that a disruptive rate equation we have published before can predict the association rate of typical adsorption at interfaces, which has a surprising fraction order of 4/3 that has not been considered before. This could be an important step toward a generalized method to predict the adsorption rate of many reactions.

Unfolding the interaction of radioactive Cs and Sr with polyethylene-derived microplastics in marine environment

To unveil the interaction of radioactive Cs and Sr with polyethylene-derived microplastics in the marine environment, a mesocosm study was conducted in a stepwise manner by investigating the uptake capability of microplastics at three different stages: pristine, radiation-exposed, and marine-exposed microplastics. The study demonstrates that the physio-chemical properties of microplastics undergo significant alterations upon exposure to the environment, leading to the emergence of biofilm formation upon marine exposure, while radiation exposure induces surface roughness and cracks. Biofilm growth enhances the uptake of radionuclides by microplastics. However, the growth of biofilms increases the density of microplastics through aggregation, leading to a buoyancy transition from positive to negative buoyancy. Various interaction mechanisms, such as electrostatic, ion–dipole, and physical diffusion interactions, were identified as important mechanisms playing key roles in radionuclide binding to polyethylene-derived microplastics. Despite the significantly lower apparent distribution coefficients observed for radio Cs (in the range of 7.3–23.6 L/kg) and Sr (in the range of 4.3–8.06 L/kg) in the marine system, typically 2–3 orders of magnitude lower than those on marine suspended sediment, this study offers compelling evidence that microplastics in marine environments are capable of sequestering radio Cs and Sr. Consequently, microplastics can potentially accumulate these radionuclides, highlighting their role as potential reservoirs as well as vectors of radionuclides in marine environments.

Insight into the Manipulation Mechanism of Polymorphic Transformation by Polymers: A Case of Cimetidine.

Employing polymer additives is an effective strategy to realize the manipulation of polymorphic transformation. However, the manipulation mechanism is still not clear, which limit the precise selection of polymeric excipients and the development of pharmaceutical formulations. The solubility of cimetidine (CIM) in acetonitrile/water mixtures were measured. And the polymorphic transformation from CIM form A to form B with the addition of different polymers was monitored by Raman spectroscopy. Furthermore, the manipulation effect of polymers was determined based on the results of experiments and molecular simulations. The solubility of form A is consistently higher than that of form B, which indicate that form B is the thermodynamically stable form within the examined temperature range. The presence of polyvinylpyrrolidone (PVP) of a shorter chain length could have a stronger inhibitory effect on the phase transformation process of metastable form, whereas polyethylene glycol (PEG) had almost no impact. The nucleation kinetics experiments and molecular dynamic simulation results showed that only PVP molecules could significantly decrease the nucleation rate of CIM, due to the ability of reducing solute molecular diffusion and solute-solute molecular interaction. A combination of crystal growth rate measurements and calculations of the interaction energies between PVP and the crystal faces of CIM indicate that smaller molecular weight PVP can suppress crystal growth more effectively. PVP K16-18 has more impact on the stabilization of CIM form A and inhibition of the phase transformation process. The manipulation mechanism of polymer additives in the polymorphic transformation of CIM was proposed.

Modification of the Model of Mixed Infection Dynamics with Regard for the Diffusion Perturbations and Interactions Between Antigens

Modification of the Model of Mixed Infection Dynamics with Regard for the Diffusion Perturbations and Interactions Between Antigens

Modeling drag coefficients of spheroidal particles in rarefied flow conditions

Transport of particles in flows is often modeled in a combined Eulerian–Lagrangian framework. The flow is evaluated on an Eulerian grid, while particles are modeled as Lagrangian points whose positions and velocities are evolved in time, resulting in particle trajectories embedded in the time-dependent flow field. The method essentially resolves the flow field in complex geometries in detail but uses a closure model for the particle dynamics aimed at including the essential particle–fluid interactions at the cost of detailed small-scale physics. Rarefaction effects are usually included through the phenomenological Cunningham correction on the drag force experienced by the particles. In this Lagrangian point-particle approach, any explicit reference to the finite size and the shape of the particles, and their local orientation in the flow field, is typically ignored. In this work we aim to address this gap by deriving, from fully-resolved Direct Simulation Monte Carlo (DSMC) studies, heuristic or closure models for the drag force acting on prolate and oblate spheroidal particles with different aspect ratios, and a fixed orientation, in uniform ambient rarefied flows covering the transition regime between the continuum and free-molecular limits. These closure models predict the drag in the transition regime for all considered parameter settings (validated with DSMC data). The continuum limit is enforced a priori and we retrieve the free-molecular limit with reasonable accuracy (based on comparisons with literature data). We also include in the models the capability to predict effects related to basic gas-surface interactions via the tangential momentum accommodation coefficient. We furthermore assess the validity of the proposed closure model for particle dynamics in proximity to solid walls. This investigation extends our previous work, which focused on small aspect ratio spheroids with exclusively diffusive gas-surface interactions [see Livi et al. (2022)]. The derived models are obtained for isothermal, subsonic flows relevant for particle contamination control in semiconductor manufacturing.

Synthesis and Characterization of Silica-Biochar Composite as Rhodamine B Dye Adsorbent

Composites are synthesized by combining different materials, resulting in properties suitable for use as adsorbents due to the combination of pores and functional groups within the constituent materials. This study developed a silica-biochar composite to serve as an adsorbent for rhodamine B dye, utilizing silica derived from red mud and biochar obtained from oil palm empty fruit bunches (OPEFB). This research focused on analyzing the characteristics and effectiveness of the composite as an adsorbent by varying its composition. Silica from red mud exhibited a purity of 80.05% and possessed silanol (Si-OH) and siloxane (Si-O-Si) functional groups on its surface, whereas biochar from OPEFB had a carbon content of 95.91% and included functional groups such as -OH, C=O, C=C, C-H, and C-O. The combination of silica and biochar yielded a composite surface consisting of -OH, C=O, C=C, C-O, C-H, and Si-O-Si functional groups. The silica-biochar composite demonstrated a greater surface area than its individual components, with silica at 69.824 m²/g and biochar at 95.452 m²/g. The composite with a 1:2 (% w/w) ratio exhibited the largest surface area at 102.371 m²/g, achieving a maximum adsorption capacity of 1.550 mg/g and an efficiency of 88.463%. The adsorption process encompasses physical interactions via pore diffusion and chemical interactions through functional groups.