Accurate and rapid identification of pathogens is essential for public health and infectious disease control. Despite notable advances, label-free, high-throughput, and sensitive bacterial detection in complex samples remains a significant challenge. An interpretable multimodal deep learning model, RaSizeNet, was developed by integrating surface-enhanced Raman spectroscopy (SERS) and inertial microfluidic size distribution for high-precision identification of complex bacterial populations. Fe@PCN-Au hybrid particles exhibiting strong SERS activity and magnetic responsiveness were synthesized and embedded into a dual-zone microfluidic chip to enable efficient bacterial enrichment, size-based separation, and signal enhancement. A large-scale multimodal dataset comprising nine representative bacterial species was constructed by combining SERS spectra and outlet distribution data. A size-guided cross-modal attention mechanism was introduced to improve spectral discriminability and model robustness while maintaining independent modality representations. RaSizeNet achieved an average accuracy of 96.22 % in complex samples, significantly outperforming unimodal (SERSNet, 82.23 %) and conventional multimodal (MultiNet, 92.81 %) models. The model also demonstrated superior adaptability and stability under extreme concentrations, varying flow rates, and diverse media conditions. This work establishes a promising framework for integrating microfluidic-SERS sensing with artificial intelligence, providing both theoretical and technical support for real-time multimodal pathogen detection.

Green crystallization technologies for energetic materials face significant challenges related to environmental pollution and crystal quality control. In this study, a zero-solvent discharge sustainable membrane crystallization process coupled with organic solvent nanofiltration (OSN) was developed. A novel hollow fiber module enabled precise separation of solvent and solute, allowing continuous solvent recovery and reuse while maintaining stable supersaturation conditions for crystallization. Through multi-index orthogonal design, the influences of permeation rate, feed rate, stirring rate and temperature on the crystal form, morphology and particle size distribution were investigated, and the optimal process conditions for preparing spherical CL-20 crystals were determined based on range analysis. On this basis, the crystallization kinetic characteristics were quantitatively described by combining the population balance model, revealing the kinetic mechanisms of nucleation and growth. Process sampling further clarified the microscopic evolution mechanisms of spherical epsilon-CL-20 crystals. Additionally, the separation performance and operational stability of the nanofiltration membrane were also characterized and evaluated. This research provides a theoretical basis and technical reference for the development of green crystallization processes for energetic materials, emphasizing high efficiency, safety and environmental sustainability, The proposed method demonstrates valuable insights for separation process design in chemical and environmental engineering.

Semi-batch nitration processes involve substantial heat release, and local reactant enrichment may induce hot-spot formation and increase the risk of thermal runaway. However, global indicators such as the volume-averaged reactor temperature cannot adequately characterize local thermal hazards or quantitatively describe the redistribution of reaction heat under practical flow conditions. In this study, a three-dimensional transient computational fluid dynamics (CFD) model coupled with reaction kinetics, fluid flow and heat transfer was established for the semi-batch nitration of 4-chlorobenzotrifluoride (4-Cl-BTF). On this basis, a CFD-based quantitative framework was proposed to characterize local heat distribution and hot-spot evolution directly from the predicted temperature field. The roles of feed location, stirring speed, feeding time, and impeller type were then investigated. The results show that hot-spot evolution is dominated by the spatial mismatch between local heat generation and heat transport rather than by the global thermal response alone. Insufficient mixing and excessive instantaneous feed flux intensified local reactant enrichment, thereby promoting early hot spot formation. In contrast, feed location and impeller type mainly affected the migration and connectivity of hot spots by reshaping the internal circulation pathway. The present work provides an initial quantitative description of hot spot propagation under realistic impeller-driven flow conditions, and offers a spatially resolved basis for local thermal risk assessment and operating condition optimization in semi-batch nitration reactors.

Oiling-out crystallization is a green, efficient route to spherical products with improved powder properties. However, key measurements and operational decisions often rely on offline tests and operator experience, causing low efficiency and high trial-and-error cost. Here, a deep learning workflow converts process images into quantitative metrics and decision triggers. Oiling-out crystallization of ethyl vanillin was online monitored and images of droplets and spherical particles were analyzed by deep learning model. By extracting droplet size and number, quenching was triggered when oiling-out equilibrium was detected, defining operation time. After spherical particles formed, particle size and 2-dimensional sphericity were extracted online for quality evaluation. Results show that higher stirring speed accelerated equilibrium and reduced product size, while early partial sodium dodecyl sulfate addition at the same speed yielded smaller spheres and better powder properties. This workflow provides a scalable template for online optimization and intelligent control of oiling-out crystallization.

In this work, the solubility of epsilon-CL-20 in four binary solvents composed of ethyl acetate and halogenated hydrocarbons (bromobenzene, chlorobenzene, dibromomethane, 1,1,2,2-tetrachloroethane) was measured over the temperature range of 288.15-328.15 K at 0.101 MPa by gravimetric method. Under similar conditions, the order of solubility of epsilon-CL-20 is ethyl acetate + bromobenzene approximate to ethyl acetate + chlorobenzene > ethyl acetate + dibromomethane > ethyl acetate + 1,1,2,2-tetrachloroethane and the solubility decreases with the increase of halogenated hydrocarbon content. The results also reveal that the solubility is negatively correlated with temperature when the mole fraction of halogenated hydrocarbons is low, otherwise the result is opposite. The modified Apelblat model, van't Hoff model, CNIBS/R-K model, Jouyban-Acree model and Jouyban-Acree-van't Hoff model were used to correlate the experimental solubility data and all of the models perform well. The modified Apelblat model and Jouyban-Acree-van't Hoff model are relatively excellent. The dissolution thermodynamic properties of epsilon-CL-20 in four binary solvents were calculated and analyzed. The results show that the dissolution processes of epsilon-CL-20 are entropy-driven non-spontaneous processes. This work is significant to the design and optimization of the crystallization of epsilon-CL-20.

In this work, the effects of 12 novel binary green solvents on the crystal morphology of epsilon-CL-20 were systematically studied by a combination of molecular dynamics simulations and experiments. The interactions within the epsilon-CL-20 crystal structure were analyzed utilizing the Hirshfeld surface. The solvent-crystal layer interaction was examined by means of the modified attachment energy (MAE) model, which allowed for predictions of the crystal morphologies of epsilon-CL-20 in various binary green solvents. The corresponding crystals were prepared through dilution crystallization and compared with the simulation results, demonstrating excellent consistency. Additionally, the effect of solvent diffusion rate on different crystal surfaces was investigated by mean square displacement (MSD), and the composition of the solvent-crystal interaction was analyzed by radial distribution function (RDF), which suggested that the solvent molecules diffuse rapidly and interact strongly with the (1 1 0) crystal surfaces. This research offers novel insights and substantial support for green manufacturing and high-quality development of epsilon-CL-20.

In this work, an AlH3 passivation method is proposed to enhance its thermal stability. The method involves pretreatment by thermal activation, followed by a stearic acid (SA) coating. The optimal coating mass ratio was determined through the utilization of Scanning Electron Microscope, X-ray diffraction, X-ray photoelectron spectroscopy, and other analytical techniques, with a subsequent analysis of the coating mechanism. The results demonstrate that the initial dehydrogenation temperature increased by 2.7 degrees C, i.e. from 172.0 degrees C to 174.7 degrees C. The decomposition activation energy of the coated material AlH3-10%SA was found to be 84.57 kJ center dot mol-1, representing a 4.21 kJ center dot mol-1 increase compared to the raw sample (80.36 kJ center dot mol-1). The dehydrogenation kinetics of the AlH3-SA exhibited a transition from a 3-D nucleation and growth model to a 2-D nucleation and growth model. This indicates a strong coating effect, which slows the decomposition rate and enhances stability. This study provides new insights into the surface coating and stability of AlH3, facilitating its wider application in areas such as solid propellants, energetic materials, and fuel cells.

In this work, epsilon-CL-20 crystals with high sphericity, low sensitivity, and high true density were prepared in binary and ternary solvents using solvent-antisolvent recrystallization. The influence mechanisms of temperature, solvent type and solvent composition on crystal morphology were investigated through molecular dynamics simulations with modified attachment energy model. The results reveal that the crystals obtained in the ethyl acetate + chlorobenzene system at 313.15 K have the highest sphericity of 0.8630. The increase in temperature causes the crystals to become sharper. The crystals in ternary solvents retain morphological characteristics of those in the corresponding binary systems and the sphericities are between the two. In ternary systems, hydrogen bonding interactions are affected by the two antisolvents together, and van der Waals and electrostatic interactions can be influenced either by the combined effects of two antisolvents or predominantly by a single antisolvent. It is feasible to adjust interactions by changing growth environments. The temperature, solvent type and solvent composition can affect the diffusion behaviors of solvent molecules and the antisolvent molecules do not affect their mutual diffusion behaviors. This work provides valuable information for the design and optimization of the preparation process of spherical epsilon-CL-20 crystals.

Drug-resistant bacteria pose a severe threat to global public health. Therefore, developing new, efficient, and safe antibacterial strategies not based on antibacterial drugs is crucial. This study designed and synthesized a core-shell heterojunction material PCN-224@ZIF-8 for photocatalytic and photothermally enhanced antibacterial treatment and wound healing. The PCN-224 nanoparticles were prepared using a solvothermal method, with subsequent in situ growth of a ZIF-8 shell to form a core-shell structure. Characterization of PCN-224@ZIF-8 demonstrated a large specific surface area and a stable heterojunction interface, facilitating photogenerated charge carrier separation and migration, thereby boosting reactive oxygen species generation and photothermal effects. Photoelectrochemical analysis and in vitro tests confirmed excellent antibacterial activity against Escherichia coli and Staphylococcus aureus under 660 nm light, with sterilization rates of 99.71% and 99.52%, respectively. In vivo mouse studies demonstrated that PCN-224@ZIF-8 significantly promoted wound healing in Methicillin-resistant S. aureus (MRSA) infected wounds, showing excellent biocompatibility and tissue repair potential.

In this work, the efficient crystallization of ε-CL-20 was achieved through precise reduced pressure evaporation, enabling the preferential separation of the good solvent. This novel method, compared with previous techniques, resulted in a more gradual change in CL-20 concentration, a more uniform particle size distribution, and excellent crystallization efficiency ensured by the high driving force. Additionally, the ASL model was employed to accurately describe the size-dependent growth behavior of the ε-CL-20 crystals. Nonlinear fitting methods were used to determine the nucleation and growth kinetic equations of the crystals under reduced pressure evaporation in three binary solvent systems (ethyl acetate + bromobenzene/dibromomethane/1,1,2,2-tetrachloroethane). Process experiments validated the kinetic equations: 1,1,2,2-tetrachloroethane system produced crystals with the highest growth rate and most uniform particle size distribution; the bromobenzene system exhibited the highest nucleation rate, yielding the smallest crystal size, while the dibromomethane system was the least sensitive to external influences and produced the largest crystal size. A moderate increase in the stirring rate was found to enhance mass transfer and crystal growth. These findings provide new insights into the production of ε-CL-20, offering theoretical guidance and data support for solvent system selection, experimental parameter optimization, and particle size distribution control.

In this study, the γ → α phase transition and decomposition of AlH3 were probed using integrated hot-stage polarized microscopy, in situ XRD, DSC, and fluorescence analysis. Phase coexistence at 100 °C and complete transition at 140 °C were demonstrated by in situ XRD. Meanwhile, synchronized fluorescence decay (ImageJ-quantified) and XRD evolution analysis confirmed the temperature-dependent kinetics, with the isothermal γ → α durations decreasing from 225 min (100 °C) to 5 min (180 °C). The transition involved competing surface nucleation and bulk diffusion, which was accelerated by the reduced diffusion resistance at elevated temperatures. Above 160 °C, α → Al decomposition dominated via interfacial reactions and H2 release, accompanied by gas-induced crystalline fracturing. DSC analysis revealed heating-rate-dependent core–shell thermal gradients, which caused hysteresis. At the same time, the experiment also shows that the surface oxidation of γ-AlH3 may have hindered transitions through passivation layer formation. This work validates Gao et al.’s core–shell model, demonstrating that combined fluorescence and conventional techniques elucidate kinetic laws in metastable systems.

CFD simulations of annular coolers have often been performed on a single trolley, making it difficult for the method to provide reliable and accurate data for the optimum design of annular coolers. The present paper establishes a three-dimensional model of the entire annular cooler, uses sliding mesh to approach the actual working conditions, and through UDF, realizes the simulations of the continuous feeding process of the annular cooler, and obtains complete data for one run of the annular cooler. By comparing the simulated data with the actual measured data, the reliability of the model was verified. The temperature distribution inside the annular cooler and the temperature variation at the outlet of the waste heat recovery as well as the flow rate are also explored in detail. Subsequently, the temperature distribution inside the annular cooler, the flue gas flow, and the changes in temperature at each outlet were studied under different material layer thicknesses, and the discharge temperature under different thicknesses was obtained. Based upon the proposed method, a lot of data that cannot be obtained by traditional calculation methods can be obtained, thus shortening the cycle of optimizing the design and development of the structure and operating parameters of annular coolers.

Acer truncatum seed oil, extracted from the samaras of the yuanbaofeng (A. truncatum Bunge) tree, is rich in oleic acid, palmitic acid (PA), erucic acid (EA), and nervonic acid (NA). The melt crystallization is a crucial way to isolate NA. In this present study, the solid–liquid equilibrium of erucic acid/palmitic acid (EA– +PA), erucic acid/nervonic acid (EA–NA), and nervonic acid/palmitic acid (NA–PA) binary systems was investigated by differential scanning calorimetry. The solid–liquid phase diagrams of binary systems were constructed by thermodynamic analysis and model simulations, which illustrated the influence of molecular interaction on the melting point change of binary systems. The solid–liquid phase and the enthalpy change diagrams together demonstrated eutectic phenomenon. The eutectic behavior appeared in the EA–NA and EA–PA binary systems at the EA concentration more than 50

In amino acid/amphiphilic mixed micelle-polymer systems, the coecervate process and properties are shaped by mixed micelle ratio, dilution ratio, and salt concentration, which alter intermolecular interactions within the coacervates.

In this study, lithium was recovered from spent lithium-ion batteries through the crystallization of lithium carbonate. The influence of different process parameters on lithium carbonate precipitation was investigated. The results indicate that under the conditions of 90 °C and 400 rpm, a 2.0 mol/L sodium carbonate solution was added at a rate of 2.5 mL/min to a 2.5 mol/L lithium chloride solution, yielding lithium carbonate with a recovery rate of 85.72% and a purity of 98.19%. The stirring rate and LiCl solution concentration significantly impact the particle size of lithium carbonate aggregates. As the stirring rate increases from 200 to 800 rpm, the average particle size decreases from 168.694 μm to 115.702 μm. Conversely, an increase in the LiCl solution concentration reduces the lithium carbonate particle size, with an average particle size of only 97.535 μm being observed at a LiCl solution concentration of 2.5 mol/L. It was also observed that nickel and cobalt ions become incorporated into the crystal lattice of lithium carbonate, thereby affecting the growth and morphology of lithium carbonate.

This study introduces a novel approach combining Raman spectroscopy's unique 'fingerprint' features with colorimetric techniques, offering dual functionality and exceptional convenience for bacterial detection.

In order to apply precipitated calcium carbonate (PCC) in the detergent industry, its ability to deposit calcium ions in hard water is an important process. In this work, the calcium ion deposition in the presence of PCC from different sources is investigated to reveal the influencing factors and mechanism of nucleation and crystal growth of CaCO3. SEM, XRD, Malvern particle size analysis, and calcium electrodes are used to evaluate the effects of PCC morphology, saturation of Ca2+, and PCC additive amount on the deposition behavior of CaCO3. Through SEM and Malvern particle size analysis, it is found that the precipitation of calcium ions is obviously accelerated by PCC acting as seeds. Moreover, calcium ions are effectively adsorbed on (211) crystal facets, thus prismatic and scalenohedral PCC crystals exhibit better adsorption performance than irregular cubic PCC ones. In addition, XRD demonstrates that PCC reduces or even eliminates the formation of crystals such as vaterite, displaying high deposition capacity under complex water conditions (slightly acidic or highly alkaline pH, low magnesium ion concentration (<0.01 M), and temperatures of 0–60 °C), forming thermodynamically stable calcite in water, which significantly controls the instability of the washing process.

Here, a dimensionless empirical parameter is proposed to comprehensively evaluate the foaming properties of high-viscosity non-Newtonian surfactant fluids. Rheological measurements were used to probe the viscosity, viscoelasticity, and viscous flow activation energies of the materials. Additionally, an advanced Focused Beam Reflectance Measurement (FBRM) online characterization technique, in conjunction with traditional microscopic observations, was used to quantitatively examine the generation, distribution, and destabilization of bubbles during the foaming process. This is the first time that the FBRM technique has been used for online quantitative analysis of bubble distribution. Three dimensionless parameters were proposed to describe the foaming properties of the fluids, namely the volume fraction of gas, Phi, the coefficient of dispersion of the bubble size distribution, c, and the fraction of span change for 10 min, Delta s. These properties represent the foam generativity, dispersibility, and stability, respectively. A dimensionless parameter, the foaming property index (FPI), is proposed to provide an overall evaluation of the foaming behavior based on the intrinsic properties of the fluid. Finally, the results of foaming experiments under the same mixing conditions demonstrated that the index provides a simple and reliable estimate of foaming performance, which is expected to aid in the industrial design of foaming unit operations for non-Newtonian fluids.

Design and working principle of bacterial capture and identification using a ZnO/Ag microfluidic SERS sensor array.

3-D numerical simulations based on diffusion combustion technology were employed to optimize the multi-stage air/gas supply system in a coke oven battery with 7.1 m coking chambers. In the heating flues, the Eddy-Dissipation Concept (EDC) model and the ideal gas model were utilized to numerically investigate diffusion combustion. What is more, the radiation between the flue gas and the silicon brick was calculated using the Discrete Ordinates (DO) model. After validating the reliability of the model with field-measured data, insights into the temperature field and gas flow in the heating flue, and heat flux distribution over the heating wall were obtained. To characterize the vertical heating uniformity, an index of the standard deviation of the heat flux over the vertical heating walls was proposed. By optimizing the multi-stage air/gas supply design of heating flues, the vertical heating uniformity was improved by 60% according to the index values. The approach developed in this work can be a useful tool for the design of large-capacity coke oven batteries at different scales.