Process Parameters Research Articles

Magnetron-Sputtered Long-Term Superhydrophilic Thin Films for Use in Solid-State Cooling Devices

Pulse-magnetron-sputtered long-term superhydrophilic coatings have been synthesized to functionalize the surfaces of solid-state cooling devices, e.g., electrocaloric heat pumps, where not only a complete wetting of the surface by a fluid is intended, but also fast wetting and dewetting processes are required. The coatings consist of a (Ti,Si)O2 outer layer that provides lasting hydrophilicity thanks to the mesoporous structure, followed by an intermediate WO3 film that enables the reactivation of the wettability through visible light irradiation, and a W underlayer which can work as a top electrode of the electrocaloric components thanks to its suitable electrical and thermal conductivity properties. Process parameter optimization for each layer of the stack as well as the influence of the microstructure and composition on the wetting properties are presented. Finally, water contact angle measurements, surface energy evaluations, and a contact line dynamics assessment of evaporating drops on the coatings demonstrate that their enhanced wetting performance is attributed not only to their intrinsic hydrophilic nature but also to their porous microstructure, which promotes wicking and spreading at the nanometric scale.

Two-dimensional identification of time-varying batch nonlinear processes with input dead-zone nonlinearity

ABSTRACT In the time dimension, the batch process with input dead-zone nonlinearity often has the characteristics of short operation time and time-varying process parameters. A two-dimensional recursive least squares (2D-RLS) identification method for time-varying nonlinear systems with input dead zone is proposed. By mining system dynamic information from the time direction of the same batch and different batch directions, the identification parameters are updated. The proposed two-dimensional identification strategy converts the time-varying parameter estimation problem of time dimension into the equivalent time-invariant parameter estimation problem of batch dimension. Sufficient production data in batch dimension ensure that the proposed identification algorithm can eliminate the influence of random measurement noise. The identification strategy with unequal length of batch data is also given. The convergence of the proposed algorithm is analysed. Finally, numerical simulation and experimental tests are used to verify the effectiveness and superiority of the proposed algorithm.

Yield Stress and Elongation Prediction and Process Parameter Optimization of Two C-Mn Steel Based on XGBoost and Non-dominated Sorting Genetic Algorithm-IIization of C-Mn steel based on XGBoost algorithm

Yield Stress and Elongation Prediction and Process Parameter Optimization of Two C-Mn Steel Based on XGBoost and Non-dominated Sorting Genetic Algorithm-IIization of C-Mn steel based on XGBoost algorithm

Investigation of Micropattern Forming Process on Zr‐4 Alloy Surface Considering Plowing Effects

Micropattern forming process is an efficient and low‐cost process for fabricating multifunctional surfaces in electronics, energy, and biomedical products, but this process of creating microdimples on the surface of zirconium alloys has not been investigated. Currently, there are few models describing the micropattern forming process, and these existing models have not considered the effect of roughness on forming. The influence of roughness on micropattern forming process is not to be neglected due to the size effect, especially the plowing effects caused by asperities in surface roughness during sliding process. In this article, a micropattern forming process model is developed by combining a rough plane indentation model and a plowing effects model, and the experimental study of the forming process is conducted, which can quantitatively evaluate the effects of different process parameters and different roughness of forming die on forming process. The applicability range of the developed model is obtained, and the model is capable of predicting the forming process with various process parameters and surface roughness of forming die by comparing the experiment results with the model results, which is of great significance to the design of the forming die and the improvement of the forming process.

Experimental Analysis of Spiral Finishing Process on EDM Drilled Hole in Titanium

It is quite evident that some of the experimental research works have been carried out by researchers in the area of spiral polishing using abrasive for surface finishing improvement but most of the experiment has been employed on Steel or Alloy Steel as a material. Very few number of research works have been performed by researchers across the globe on the Spiral Polishing Method of Titanium holes made by Electrical Discharge Machining (EDM). Therefore, experimental investigations were carried out in the area of Spiral Polishing and Finishing of EDM-drilled holes of various materials to meet the desired goal of demands on the surface quality. This experimentation aims to develop a novel method with spiral polishing using abrasive flow finishing. To explore the search investigation and find out the better surface finishing for through holes made on EDM, the process parameters have been designed using the Taguchi L16 orthogonal array with input parameters such as Current (I), Pulse on time (Ton), and Pulse off time (Toff). The addition of Boron Carbide Powder with Handwash, Glycerine, Shampoo, and Liquid Soap is used to decrease the Surface Roughness (Ra) with a ratio of 5 : 1. The Taguchi technique is used to assess the P/M process parameter setting for a given signal to noise (S/N) ratio.

Design and Fabrication of Multifunctional E-Textiles by Upcycling Waste Cotton Fabrics through Carbonization

The merging of electronic materials and textiles has triggered the proliferation of wearables and interactive surfaces in the ubiquitous computing era. However, this leads to e-textile waste that is difficult to recycle and decompose. Instead, we demonstrate an eco-design approach to upcycle waste cotton fabrics into functional textile elements through carbonization without the need for additional materials. We identify optimal parameters for the carbonization process and develop encapsulation techniques to improve the response, durability, and washability of the carbonized textiles. We then configure these e-textiles into various 'design primitives' including sensors, interconnects, and heating elements, and evaluate their electromechanical properties against commercially available e-textiles. Using these primitives, we demonstrate several applications, including a haptic-transfer fabric, a joint-sensing wearable, and an intelligent sailcloth. Finally, we highlight how the sensors can be composted, re-carbonized and coated onto other fabrics, or repurposed into different sensors towards their end-of-life to promote a circular manufacturing process.

A Practical Method for Synthesizing Iptacopan.

Iptacopan, the first orally available small-molecule complement factor B inhibitor, was developed by Novartis AG of Switzerland. Iptacopan for the treatment of PNH was just approved by the FDA in December 2023. Other indications for treatment are still in phase III clinical trials. Iptacopan is a small-molecule inhibitor targeting complement factor B, showing positive therapeutic effects in the treatment of PNH, C3 glomerulonephritis, and other diseases. Although Iptacopan is already on the market, there has been no detailed synthesis process or specific parameter report on the intermediates during the synthesis of its compounds except for the original research patent. In this study, a practical synthesis route for Iptacopan was obtained through incremental improvement while a biosynthesis method for ketoreductase was used for the synthesis of the pivotal intermediate 12. Moreover, by screening the existing enzyme library of our research group on the basis of random as well as site-directed mutagenesis methods, an enzyme (M8) proven to be of high optical purity with a high yield for biocatalectic reduction was obtained. This enzyme was used to prepare the compound benzyl (2S,4S)-4-hydroxy-2-(4-(methoxycarbonyl)-phenyl)-piperidine-1-carboxylate) white powder (36.8 g HPLC purity: 98%, ee value: 99%). In the synthesis of intermediate 15, the reaction was improved from two-step to one-step, which indicated that the risk of chiral allosterism was reduced while the scale was expanded. Finally, Iptacopan was synthesized in a seven-step reaction with a total yield of 29%. Since three chiral intermediate impurities were synthesized directionally, this paper lays a solid foundation for the future of pharmaceutical manufacturing.

Microbiological safety of dry-aged meat: a critical review of data gaps and research needs to define process hygiene and safety criteria

Dry-aged meat is gaining popularity among food business operators and private consumers. The process is carried out in aerobic conditions by hanging beef carcasses or placing subprimal or primal cuts in a dedicated cabinet for several weeks or even months while controlling the environment through the management of process parameters such as temperature, relative humidity, and airflow. In this review, we present a critical evaluation of the literature to evaluate tools to manage the process to guarantee food safety and identify critical control points, as well as good hygienic and manufacturing practices. In controlled aging conditions, only Listeria monocytogenes and Yersinia enterocolitica can multiply, while a reduction in the number of Salmonella spp. and Escherichia coli O157:H7 is generally reported. Enterobacteriaceae usually decrease on the surface of the meat during maturation; thus, for the purpose of the hygienic evaluation of the production process, a count no higher than that of unmatured meat is expected. Besides, various studies report that the total bacterial count and the spoilage microorganisms significantly increase on the surface of the meat, up to 5-6 Log CFU/g in the absence of visible spoilage. Bacteria of the Pseudomonas genus tend to progressively replace other microorganisms during maturation; thus, the total mesophilic or psychrophilic bacterial load is not a good indicator of process hygiene for matured meat. Critical parameters for the control of the process are temperature, relative humidity, and ventilation, which should be monitored during the process. For this reason, equipment designed and certified for dry aging must be used, and the manufacturer must validate the process. Food business operators must apply general good manufacturing practices (GMP) and good hygiene practices (GHP) for meat processing and some GMP and GHP specific for dry aging. Several research needs were identified, among them the evolution of the populations of L. monocytogenes and Y. enterocolitica and the microbiology of the inner parts of the dry-aged meat.

Achieving a High Thermally Conductive One Micron AlN Deposition by High Power Impulse Magnetron Sputtering plus Kick.

High-power impulse magnetron sputtering (HiPIMS) plus kick is a physical vapor deposition method that employs bipolar microsecond-scale voltage pulsing to precisely control the ion energy during sputter deposition. HiPIMS plus kick for AlN deposition is difficult since nitride deposition is challenged by low surface diffusion and high susceptibility to ion damage. In this current study, a systematic examination of the process parameters of HiPIMS plus kick was conducted. Under optimized main negative pulsing conditions, this study documented that a 25 V positive kick biasing for AlN deposition is ideal for optimizing a high quality film, as shown by X-ray diffraction and transmission electron microscopy as well as optimal thermal conductivity while increasing high speed deposition (25 nm/min) and obtaining ultrasmooth surfaces (rms roughness = 0.5 nm). HiPIMS plus kick was employed to deposit a single-texture 1 μm AlN film with a 7.4° rocking curve, indicating well oriented grains, which correlated with high thermal conductivity (121 W/m·K). The data are consistent with the optimal kick voltage enabling enhanced surface diffusion due to ion-substrate collisions without damaging the AlN grains.

Study of the Dynamic Recrystallization Behavior of Mg-Gd-Y-Zn-Zr Alloy Based on Experiments and Cellular Automaton Simulation

The exploration of the relationship between process parameters and grain evolution during the thermal deformation of rare-earth magnesium alloys using simulation software has significant implications for enhancing research and development efficiency and advancing the large-scale engineering application of high-performance rare-earth magnesium alloys. Through single-pass hot compression experiments, this study obtained high-temperature flow stress curves for rare-earth magnesium alloys, analyzing the variation patterns of these curves and the softening mechanism of the materials. Drawing on physical metallurgical theories, such as the evolution of dislocation density during dynamic recrystallization, recrystallization nucleation, and grain growth, the authors of this paper establish a cellular automaton model to simulate the dynamic recrystallization process by tracking the sole internal variable—the evolution of dislocation density within cells. This model was developed through the secondary development of the DEFORM-3D finite element software. The results indicate that the model established in this study accurately simulates the evolution process of grain growth during heat treatment and the dynamic recrystallization microstructure during the thermal deformation of rare-earth magnesium alloys. The simulated results align well with relevant theories and metallographic experimental results, enabling the simulation of the dynamic recrystallization microstructure and grain size prediction during the deformation process of rare-earth magnesium alloys.

Synergy between Fe-Co oxide catalysts supported over HZSM-5 for direct conversion of methane to methanol

The direct conversion of methane to methanol over iron and cobalt oxide based composite catalysts supported over HZSM-5 was carried out in a fixed-bed micro reactor under changing process parameters and catalyst compositions. The prepared catalysts were well characterized by various techniques including N2 adsorption desorption, X-ray diffraction (XRD), Fourier transformed infrared spectroscopy (FTIR), pyridine FTIR, X-ray photoelectron spectroscopy (XPS), UV–vis spectroscopy and temperature programmed reduction (H2-TPR). The characterization results revealed the presence of various reducible iron and cobalt oxide species depending on the Fe/Co molar ratio and total metal oxide loading. Moreover, the XPS and UV–vis spectroscopic results also confirmed the variation of Fe2+/Fe3+ and Co2+/Co3+ species depending on the Fe-Co molar ratio which had strong influence on the performance of the composite catalysts. It was found that the cobalt species favours the formaldehyde formation whereas the iron species promotes the formic acid formation in their respective pure supported oxide catalysts. However, the synergistic effect of iron and cobalt oxide in equimolar ratio in composite catalysts appeared as effective for achieving highest yield of methanol. The methanol selectivity was also influenced by the alteration of various studied process parameters. The higher reaction temperature favoured the overoxidation of methanol to CO2 whereas the methanol selectivity increased with increasing the methane to oxygen ratio. The lattice to adsorbed oxygen ratio also had strong influence on the activity of composite catalysts and methanol selectivity. The highest methanol yield of 1.87% was achieved at the methane conversion of 42.81 % with the 20Fe1Co1Z catalyst at 873 K reaction temperature with CH4/O2 ratio of 2:1 and WHSV of 1030 ml hr−1 gcat−1.

Manufacturing motor core lamination from thin non-oriented silicon steel sheet direct by pulsed laser cutting using multi-quality optimized process parameters

Manufacturing motor core lamination from thin non-oriented silicon steel sheet direct by pulsed laser cutting using multi-quality optimized process parameters

Modelling and Prediction of Process Parameters with Low Energy Consumption in Wire Arc Additive Manufacturing Based on Machine Learning

Wire arc additive manufacturing (WAAM) has attracted increasing interest in industry and academia due to its capability to produce large and complex metallic components at a high deposition rate. One of the basic tasks in WAAM is to determine appropriate process parameters, which will directly affect the morphology and quality of the weld bead. However, the selection of process parameters relies heavily on empirical data from trial-and-error experiments, which results in significant time and cost expenditures. This paper employed different machine learning models, including SVR, BPNN, and XGBoost, to predict process parameters for WAAM. Furthermore, the SVR model was optimized by the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithms. A 3D laser scanner was employed to obtain the weld bead’s point cloud, and the weld bead size was extracted using the point cloud processing algorithm as the training data. The K-fold cross-validation strategy was applied to train and validate machine learning models. The comparison results showed that PSO–SVR predicted process parameters with the highest precision, with the RMSE, R2, and MAE being 1.1670, 0.9879, and 0.8310, respectively. Based on the process parameters produced by PSO–SVR, an optimal process parameter combination was chosen by taking into comprehensive consideration the impacts of power consumption and efficiency. The effectiveness of the process parameter optimization method was proved through three groups of validation experiments, with the energy consumption of the first two groups decreasing by 10.68% and 11.47%, respectively.

From laboratory to industrial use: Understanding process variation during enzymatic protein hydrolysis with dry film fourier-transform infrared spectroscopy

Industries are continuously looking for dedicated sensor solutions for evaluating the chemical composition of products that can provide valuable insights into process control, process optimization, and product quality. A rapid and robust analytical method, Fourier-Transform Infrared (FTIR) spectroscopy, holds significant potential in this regard as it provides detailed compositional values of food nutrients. The main aim of the present study was to use dry film FTIR spectroscopy as an analytical tool to characterize products from an industrial enzymatic protein hydrolysis process and link this to understand industrial process variations. For this purpose, 463 protein hydrolysate samples were obtained from an industrial enzymatic protein hydrolysis plant. In the same period, systematic variations in process parameters such as raw material composition, enzyme type, and water addition, were performed. All samples were analyzed using dry film FTIR spectroscopy. Two subsets containing 200 and 68 hydrolysate samples were chosen for measuring average molecular weight (AMW) and collagen content respectively, providing reference data for constructing calibration models based on partial least squares regression (PLSR). The percentage of low molecular weight constituents was derived from the molecular weight distribution of size exclusion chromatograms of protein hydrolysates and also used in the modeling. Calibration models for the prediction of AMW, low molecular weight constituents, and collagen content were obtained with a good fit and lower estimation errors. Principal component analysis (PCA) of protein hydrolysates' FTIR spectra effectively differentiated process variations (enzyme types and raw materials) without extensive reference analysis. One-factor analysis of variance (ANOVA) tests was used to observe the impact of process variation on product quality. FTIR proved to be a sensitive method for liquid protein analysis and process control with a significant potential in process optimization approaches. To the authors’ knowledge, this is the first time dry film FTIR spectroscopy has been used to evaluate an industrial bioprocess with designed process variations.

Bioinspired soft-hard interfaces fabricated by multi-material additive manufacturing: A fracture mechanics investigation using essential work of fracture

This study employs the Essential Work of Fracture (EWF) concept to evaluate the interfacial fracture toughness of bioinspired interfaces between soft and hard polymer phases. The experimental framework utilizes a model material system with Polylactic Acid (PLA) as the hard phase and Thermoplastic Polyurethane (TPU) as the soft phase. Employing the Fused Filament Fabrication (FFF) technique, bioinspired sutural interfaces are created, characterized by interpenetrating soft and hard protrusions. The modulation of a critical parameter in the FFF process enables the variation of interpenetration length of protrusions at the interface, thereby achieving a spectrum of interfacial strength and toughness. The determination of essential work of fracture from double edge notch tension samples, with varied ligament sizes, allows for the specific EWF measurement. This specific EWF is found to align with the initiation value of plane strain interfacial fracture toughness obtained through the Double Cantilever Beam (DCB) test. Therefore, the proposed approach asserts the elimination of the need for complex interfacial fracture tests, such as DCB. A noteworthy discovery is the establishment of a correlation between specific plastic energy dissipation and protrusion length. This correlation suggests an increased plastic dissipation with longer protrusions within the investigated bioinspired interface. Due to this heightened plastic energy dissipation, the shape of the interfacial nominal stress-displacement curves demonstrates substantial dependence on interface morphology, shifting from a triangular to a trapezoidal shape as protrusion length increases. These findings offer valuable insights into the mechanics of bioinspired interfaces, presenting a more efficient and nuanced approach to characterizing their fracture properties.

Parameters Optimization and Physicochemical Properties Characterization of Nanobiochar Prepared from Apple Branches by Ball Milling

Nanobiochar exhibits promising applications across a spectrum of fields due to its exceptional physicochemical properties. Ball milling, a prominent nanobiochar synthesis method, is influenced by process factors and biochar pretreatments, yet dominant controls still remain uncertain. In this study, the apple branch bulk biochar (pyrolyzed under 350[Formula: see text] C) was ball milled under different milling speeds, ball-to-powder mass ratios, and milling durations to investigate the optimal process parameter combinations for ball milling method. Then, we evaluated the impact of pyrolysis temperature and pretreatment temperature of bulk biochar on ball milling effect using optimized parameter combinations. Subsequently, the physicochemical properties of the bulk biochar and nanobiochar were measured. The results showed that high speed with low ball-to-powder mass ratio, low speed with high ball-to-powder mass ratio, and high pyrolysis temperature could significantly decrease the particle sizes of nanobiochar. Ball milling duration and pretreatment temperature had no significant effect on the particle sizes of biochar. The optimal combination of the rotational speed, ball-to-powder mass ratio and milling duration was 400 RPM, 100:1, 2 h and 700 RPM, 20:1, 2 h. The bulk biochar pyrolyzed at 550[Formula: see text] C could be milled into biochar nanoparticles with an average particle size smaller than 100 nm via above parameters. Nanobiochar shows improved properties such as specific surface area, cation exchange capacity, and surface functional groups over bulk biochar. This study provides a scientific basis for the widespread application of ball milling in the field of preparing nanobiochar.

Aliquat 336 in Solvent Extraction Chemistry of Metallic ReO4- Anions.

A study of the liquid-liquid extraction of ReO4- anions from hydrochloric acid solutions using the ionic liquid Aliquat 336 (QCl: trialkyl(C8-C10)methylammonium chloride) via the well-known method of slope analysis along with the determination of the process parameters is presented. This study employs CCl4, CHCl3 and C6H12 as diluents. This study was carried out at room temperature (22 ± 2) °C and an aqueous/organic volumetric ratio of unity. The ligand effect on the complexation properties of ReO4- is quantitatively assessed in different organic media. The organic extract in chloroform media is examined through 1H, 13C and 15N NMR analysis as well as the HRMS technique and UV-Vis spectroscopy in order to view the anion exchange and ligand coordination in the organic phase solution. Final conclusions are given highlighting the role of the molecular diluent in complexation processes and selectivity involving ionic liquid ligands and various metal s-, p-, d- and f-cations. ReO4- ions have shown one of the best solvent extraction behaviors compared to other ions. For instance, the Aliquat 336 derivative bearing Cl- functions shows strongly enhanced extraction as well as pronounced separation abilities towards ReO4-.

Model-Based input energy control for reproducible AISI 316L laser deposited tracks

In the Directed Energy Deposition (DED) process, when the mass flow of metal particles is relatively high, the thickness of the layers increases, leading to a more productive process. The higher the mass flow is, the more difficult it becomes to get a stable melt pool. The accumulation of residual heat in the previously consolidated material constitutes a thermal input affecting the balance at the laser-material interaction zone. An accurate control of the temperature of the laser-material interaction zone is critical to maintain the dynamic viscosity of the liquid metal within the narrow margin in which it can be managed in a stable way. The present work introduces a thermal model in which domains with tunable properties are considered to reproduce the growing of the manufactured sample. Concurrently, a virtual closed-loop PID regulator has been implemented in order to calculate suitable values of laser power to compensate the heat accumulated in the material, offering the results from the model as input process parameters to be directly applied in the real process. The levels of laser power proposed by the model have been experimentally applied, leading to a stable process capable of carrying out in reality the desired component.

Enhanced pulse electrocatalytic reductive-oxidative degradation of chlorinated organic pollutants based on a synergistic effect from Pd single atoms and FeCo2O4 nanowire

Targeting complete dechlorination and decomposition of chlorinated organic pollutants in an environmentally friendly and resource efficient manner. In this investigation, a three-dimensional multi-structured electrode (Pd-NC@Fe/CoCF) comprising Pd monatomic and nitrogen-doped carbon-coated FeCo2O4 nanowire cluster arrays were effectively synthesized. This electrode demonstrated efficient generation of H* and the production of •OH through a (2+1) e- oxygen reduction mechanism under the synergistic action of Pd single atoms and FeCo2O4 nanowire. When integrated with a square-wave pulsed electrocatalytic system, the chlorinated organic pollutants could be fully degraded within 45 min under the most favorable process parameters, which include a pulse voltage of −0.7 V, a duty cycle of 50 %, and a pulse frequency of 0.1 Hz. This results in a removal rate of 92.3 % for TOC and an energy consumption of 1.27 kWh·kg−1. This study presents a sustainable and environmentally friendly approach to the electrochemical degradation of chlorinated organic pollutants.

Optimization of Mechanical Properties and Evaluation of Fatigue Behavior of Selective Laser Sintered Polyamide-12 Components.

In this paper, a comprehensive study of the mechanical properties of selective laser sintered polyamide components is presented, for various different process parameters as well as environmental testing conditions. For the optimization of the static and dynamic mechanical load behavior, different process parameters, e.g., laser power, scan speed, and build temperature, were varied, defining an optimal parameter combination. First, the influence of the different process parameters was tested, leading to a constant energy density for different combinations. Due to similarities in mechanical load behavior, the energy density was identified as a decisive factor, mostly independent of the input parameters. Thus, secondly, the energy density was varied by the different parameters, exhibiting large differences for all levels of fatigue behavior. An optimal parameter combination of 18 W for the laser power and a scan speed of 2666 mm/s was determined, as a higher energy density led to the best results in static and dynamic testing. According to this, the variation in build temperature was investigated, leading to improvements in tensile strength and fatigue strength at higher build temperatures. Furthermore, different ambient temperatures during testing were evaluated, as the temperature-dependent behavior of polymers is of high importance for industrial applications. An increased ambient temperature as well as active cooling during testing was examined, having a significant impact on the high cycle fatigue regime and on the endurance limit.