Hot Process Research Articles

Hot Carrier Trapping and It's Influence to the Carrier Diffusion in CsPbBr3 Perovskite Film Revealed by Transient Absorption Microscopy.

The defects in perovskite film can cause charge carrier trapping which shortens carrier lifetime and diffusion length. So defects passivation has become promising for the perovskite studies. However, how defects disturb the carrier transport and how the passivating affects the carrier transport in CsPbBr3 are still unclear. Here the carrier dynamics and diffusion processes of CsPbBr3 and LiBr passivated CsPbBr3 films are investigated by using transient absorption spectroscopy and transient absorption microscopy. It's found that there is a fast hot carrier trapping process with the above bandgap excitation, and the hot carrier trapping would decrease the population of cold carriers which are diffusible, then lower the carrier diffusion constant. It's proved that LiBr can passivate the defect and lower the trapping probability of hot carriers, thus improve the carrier diffusion rate. The finding demonstrates the influence of hot carrier trapping to the carrier diffusion in CsPbBr3 film.

Effects of Er addition on the hot deformation behavior and microstructure evolution of AZ31 alloy

AZ31 magnesium alloys typically have poor room temperature ductility after initial deformation. To address this disadvantage, rare earth element Er is introduced to regulate the structure, weaken texture, and promote non-basal slip to achieve plasticization. In this study, the deformation behavior and microstructure evolution during the hot compression process of Er added AZ31 alloy were systematically investigated. Hot compression stress-strain curves showed that the addition of Er reduced the deformation resistance. The constitutive equation and processing map were established. By combining the processing map with the microstructure analysis and texture evolution, an optimal processing area was determined to be 350–400 °C at a strain rate of 0.01 s−1. The influence of Er addition on the twinning behavior, recrystallization mechanism, and slip system of the AZ31 alloy were discussed. During the deformation process, the twinning behavior violates the maximum SF criterion, which is related to severe local stress. Continuous dynamic recrystallization, discontinuous dynamic recrystallization, and twinning induced recrystallization are all detected in the alloy. Through the in-grain misorientation axis and transmission electron microscopy, it can be confirmed that the addition of Er promoted the occurrence of pyramidal <c+a> slip. This is related to the modification of stacking fault energy by Er and the hindrance effect of the second phase containing Er on the basal dislocation.

Variety, growing conditions and processing method act on different structural and biochemical traits to modify viscosity in tomato puree

The texture of tomato products can be modified by choice of variety, their growing conditions and/or processing method, but no clear explanation exists of the mechanisms that transform fruit tissue, how they act on texture, or whether genetics and processing impact the same physical parameters. We therefore conducted a study that processed 4 varieties produced under low/high nitrogen supply, into puree using both hot and cold break processes. No specific rheological signature allows discrimination between cultivar-induced or process-induced textural changes, but that they can be distinguished by sensory analysis. Growth conditions impacted but was not sensory distinguished. Both caused significant variations in 7 of 11 physico-chemical parameters, but the order of importance of these traits controlling texture varied, depending on whether the cause was genetic or process-related. Analysis of alcohol insoluble solids revealed a specific signature in pectin composition and conformation that could be linked to particle aggregation in the presence of lycopene-rich particles.

Hot deformation, processing maps, and microstructural evolution of Ti/Ni/Ti layered composites

Ti/Ni/Ti layered composites, which combine the advantages of Ti and Ni, are widely used in sensor and biomedical applications due to their light weight, high strength, high conductivity, good stability and excellent corrosion resistance. However, it is difficult to control the structural parameters, microstructure, and mechanical properties of layered composites during co-deformation processing due to the distinct differences in the crystal structure, mechanical properties, and deformation behavior of Ti and Ni layers. In this paper, the hot deformation, processing maps, and microstructural evolution of Ti/Ni/Ti layered composites during hot deformation processing are investigated through hot compression tests at 550–850 °C/0.001–1.0 s−1, with a reduction of 65%. It is shown that the composites exhibit mainly dynamic recovery or similar dynamic recrystallization characteristics. Combined with the interface structure, processing maps and microstructure, the optimal parameters for Ti/Ni/Ti layered composites are 680–730 °C/0.007–0.015 s−1. During co-deformation, the microstructural evolution of the constituent layers is very complex. The deformation mechanism is mainly dynamic recovery (DRV), or DRV and dynamic recrystallization (DRX) in Ti layer, and work hardening (WH) or DRV in Ni layer.

Cooling and heating innovations: exploring the diverse applications of heat pumps

Heat pumps are versatile and energy efficient devices that play a crucial role in modern heating, cooling, and refrigeration applications. This paper provides a concise overview of the diverse applications and benefits of heat pumps across residential, commercial, industrial, and transportation sectors. The paper discusses the principles of heat pump operation, emphasizing their capability to transfer heat from one location to another using thermodynamic processes. The work highlights key applications such as residential heating, ventilation, and air conditioning systems, commercial refrigeration, hot water heating, process cooling, and renewable energy integration. The energy efficiency and environmental benefits of heat pumps are also emphasized, showcasing their potential to reduce carbon emissions and contribute to sustainable energy practices. By understanding the broad scope of heat pump applications outlined in this work, researchers, engineers, policymakers, and industry stakeholders can gain insights into the significance of heat pump technology in advancing energy efficiency and addressing climate change challenges.

Effects of service stress on the deformation behavior and microstructures of Zn-0.5Mg-0.05Fe alloy from ambient to high temperatures

To overcome challenges in the traditional melt casting process of zine alloys, such as oxidative burnout, compositional segregation, and grain coarsening, this study carried out hot compression deformation tests on Zn-0.5Mg-0.05Fe alloys prepared by powder metallurgy. The results show that increasing deformation temperature and decreasing strain rate reduce rheological stress. The hot compression deformation process exhibits three phases, as rheological stress increases, work hardening, dynamic softening, and steady-state fluidization are observed, respectively. An intrinsic equation for the hot compression process is derived as = 1.334 × 1010 × [sinh(0.0053σ)]7.62947exp(-109.931691/RT). Processing conditions for Zn-0.5Mg-0.05Fe alloy are determined from a processing map, suggesting that a safe zone of 25°C–130 °C deformation temperatures with 0.13s−1-0.36s−1 strain rates, and 120°C–200 °C deformation temperatures with 0.01s−1-0.6s−1 strain rates. Electron Back-scattering Patterns (EBSD) and Transmission Electron Microscope (TEM) results show both discontinuous dynamic recrystallization (DDRX) and continuous dynamic recrystallization (CDRX) during the hot deformation compression process. DRX reduces deformation resistance, refines the grains, and improves the mechanical properties of the alloys. This study provides theoretical insights and process guidance for preparing degradable zinc alloys with excellent mechanical properties.

Investigation on effect of high-efficiency solid solution and hot stamping process on microstructure evolution and mechanical properties of high-strength aluminum alloy

Aluminum alloy has become an important lightweight material in the automotive industry due to its excellent performance. The development of hot stamping technology has effectively promoted the application of high-strength aluminum alloys in auto parts. However, aluminum alloy hot stamping requires a long time for solid solution and aging heat treatment, which hinders its mass production application in the existing mature hot stamping production line. Therefore, this paper studies the effect of a high-efficiency solid solution and hot stamping process on the microstructure and mechanical property strengthening mechanism of high-strength aluminum alloy. The contact heating and hot stamping experiment device was designed. It was found that the temperature rise rate of the sheet during the contact heating process could reach 44.51 °C/s. The experiment results show that contact heating treatment with a solution temperature of 480 °C and a solution time of 20s can achieve the high-efficient solution treatment of the sheet metal. The high-temperature deformation behavior of 7075-T6 at different temperatures (300-450 °C) and different strain rates (0.01∼1/s) under the condition of high-efficiency solid solution rapid heating was studied.

Quenching optimization of a hot stamping line for aluminum automotive components

The rising cost of fuel and harder environmental regulations driving the need for more eco-friendly vehicles have compelled automotive manufacturers to search for innovative lightweight solutions. Consequently, hot stamped aluminum alloys are gaining prominence due to their exceptional specific strength and improved formability compared to cold formed components. Unfortunately, the current state of knowledge in the field lacks the necessary depth to establish a reliable, fast and optimized process for aluminum hot forming. To address this gap, a collaborative effort between Mondragon Unibertsitatea (knowledge provider), Fagor Arrasate (hot stamping line supplier), and Batz (tool manufacturer) has been initiated. The collaborative endeavour aims to conduct semi-industrial trials involving the hot stamping of an authentic automobile bumper employing high-strength 6xxx and 7xxx aluminum alloys. The hot stamping trials have been performed under different in-die quenching times and mechanical properties of the stamped bumpers have been empirically tested. These results have helped to define the optimal quenching time. With that aim, first, a thermophysical and rheological characterization of the aluminum has been performed, followed by the development of a model to predict mechanical properties of aluminum alloys. This predictive model, together with the aluminum material data, has been then integrated into the simulation framework to enable accurate forecasting of mechanical properties and, consequently, the identification of the optimal quenching duration. The results revealed that quenching times as brief as 1 second could be employed while maintaining acceptable mechanical properties in a rapid cycle hot stamping process. These expedited quenching times have the potential to boost production by an impressive 70 % when compared to the conventional hot stamping process applied to the equivalent steel bumper.

Hot deformation behavior and hot working map of Mn–Cr–Ni–Co steel for ball mill liner forging process

To explore the thermoformability of Mn–Cr–Ni–Co steel for ball mill liner, isothermal compression tests were performed on Mn–Cr–Ni–Co steel using a Gleeble-3800 thermal compressive testing machine. Flow stress curves at 900 °C–1200 °C and 0.01s−1∼10s−1 were obtained. Results show Mn–Cr–Ni–Co steel has obvious positive strain rate sensitivity, with peak stress decreasing with increasing temperature. A constitutive equation for Mn–Cr–Ni–Co steel was established using the Arrhenius model based on strain compensation, and fitted values were compared to experimental values. A hot working map for Mn–Cr–Ni–Co steel was established and analyzed. Hot working process parameters are: deformation temperature of 980∼1200 °C, strain rate of 0.04–1.78s−1, providing a basis for selecting the hot forging process of the ball mill liner. Forging and forming experiments of the ball mill liner were carried out using the optimal parameters of Mn–Cr–Ni–Co steel from the hot working map. The ball mill liner has good forming quality with a relatively uniform martensitic structure inside. Tensile and impact tests were performed on the ball mill liner. Compared to the mechanical properties of traditional cast Mn13 ball mill liners, results show the tensile strength increased by 159.75%, elongation by 18.8%, and impact capacity by about 16.7%.

Influence of gradual stress relieving on the microstructure, texture development, grain structure and orientation of the hot-rolled Ti6Al4V–5Cu alloy

In order to investigate the influence of gradual stress relieving treatment on the microstructure, texture evolution, grain structure, and misorientation distribution of the hot-rolled Ti6Al4V–5Cu (α+β) alloy deformed in various thickness reduction ratios (TRR's) of 15%, 58%, and 73% to maintain the burger orientation relationship (BOR), different stress reliving treatment was specially designed for relieving the residual stresses occurred due to the hot deformation process. Using IPF maps, the majority of the α grains, specifically the elongated ones were found nearly at 45 ° with respect to the rolling and transverse direction. The study also show that the heat treatment schedule on the 58% deformed alloy significantly promote the transformation of β to α phase and a special microstructure with an equiaxed grains is produced. The local misorientation angle distribution due to stress reliving treatment has also discussed. Using EBSD analysis, the alloy processed under highest TRR's (i.e., 73%) and subsequent stress relieving treatment could result a serious internal crystalline instability with various degree of element diffusion rate, which promote a severe and ease of alloy coarsening. Thus, coarsening encourage the formation of grains with the highest softening potential, comparatively. It is obvious that the stress-relived treatment does not result a change in microstructure. However the internal residual stresses on the hot deformation were relieved, the texture intensity had increased quietly. A significant textural behavior could be achieved on the 73% hot-rolled alloys by the stress-relieving process to align the α/β fiber texture interface in parallel coincidence to maintain the BOR.

Investigation of hot deformation behavior and microstructure evolution of TC18 alloy and establishment of constitutive equation under friction-temperature correction

The effects of deformation temperature and strain rate on the microstructure evolution of TC18 alloy are studied by hot compression experiment and EBSD test, based on the double correction of friction and temperature rise in hot compression, a more accurate constitutive equation and thermal processing diagram are established. Recrystallization grain is the main microstructure of TC18 alloy during deformation from 810 °C to 930 °C. Higher deformation temperature and lower strain rate are beneficial to the occurrence of dynamic recrystallization and grain size growth. The strain rate has no significant effect on volume fraction of large and small angle boundary. After double correction of temperature rise and friction, it is found the activation energy of TC18 titanium alloy in β region and α/β region are 485.895 kJ/mol and 355.337 kJ/mol, respectively. The ideal hot working conditions of TC18 titanium alloy are 812 °C ∼ 840 °C, 0.01 s−1 ∼ 0.018 s−1 and 878 °C ∼ 915 °C, 0.178 s−1 ∼ 1.0 s−1, respectively. The unevenness of microstructure, the large size difference among grains and the large orientation difference among grains lead to the instability of hot working process. The conclusions of this paper can provide more accurate guidance for the determination of hot working parameters and the prediction of microstructure evolution during hot working of TC18 alloy.

Perovskite quantum laser with enhanced population inversion driven by plasmon-induced hot electron transfer under potential shift polarization conditions

The hot electron transfer resulting in fluorescence enhancement is significantly meaningful for theory and experiment of the study on photoelectric devices. However, the laser emission based on direct hot electron transfer is difficult to realize because of the low transfer efficiency. To achieve a laser with a new-generation mechanism based on hot electron transfer, the photoelectric co-excitation is proposed for improving the efficiency of hot electron transfer. The lasing behavior at 532 nm is realized with a threshold of 5 kw cm−2 and 1 μA, which can be considered as the hot electron transfer resulting in population inversion enhancement. Meanwhile, the lasing output power is 0.3 mW. The hot electrons transfer process was described via the transient absorption spectrum according to the improved ground-state bleaching and excited-state absorption signal in device ON. Through comparison with the optical pump only, the quantum efficiencies of hot electron generation (HEG) and hot electron transfer (HET) were increased ∼31% and 31%, respectively. Most importantly, a triple gain mode coupling device including local surface plasmon, hot electron transfer, and array oscillation was presented. Two modes of population inversion enhancement are proposed. This study can provide theoretical and experimental reference for the research of hot electron lasers and devices.

Optimization of thermal deformation process parameters of 2219 Al matrix composites

To investigate the deformation behavior and optimize the hot processing parameters for 2219 aluminum matrix composite, the constitutive equation and hot processing maps were established. Initially, hot compression experiments on 2219 aluminum alloy (2219A) were conducted using a Gleeble-3500 thermal simulation tester to obtain high-temperature rheological data. The deformation temperatures tested were 573, 623, 673, 723, and 773 K, with strain rates of 0.01, 0.1, 1, and 10 s−1, and a maximum deformation of 60 %. Subsequently, material parameters such as the activation energy, Zener–Hollomon parameter, power dissipation efficiency, and instability coefficient for 2219A were calculated. Analytical expressions for these material and deformation parameters were formulated, and a hot processing map for 2219A was constructed. The hot processing map, along with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and the Entropy Weight Method (EWM), were used to optimize the thermal deformation process parameters. The stability processing area and the optimal processing area identified by both methods were largely consistent. According to the hot processing map, the stability processing areas were identified in the temperature ranges of 580–660 K and 690–773 K with strain rates of 0.01 s−1 and 0.01–0.6 s−1, respectively. Using the TOPSIS and EWM methods, the stability processing areas were defined between 573 and 640 K and 0.01 s−1, 640–690 K and 0.01–0.1 s−1, and 690–773 K and 0.01–1 s−1. The consistency and accuracy of these optimization results were confirmed through microstructure analysis.

A novel soft sensing modelling approach for sulphur content estimation in hot metal pretreatment process

In the hot metal pretreatment desulphurisation process, the sulphur content needs to be controlled precisely. A novel soft sensing modelling method is proposed to address the problem that sulphur content cannot be directly measured online. Firstly, the main desulphurisation behaviour is represented with the proposed simplified mechanism model for boosting computational efficiency. Moreover, the complex influence of the changing operation condition on the parameters of the simplified mechanism model is described with neural networks to compose a hybrid structured hz. Then, for training this hybrid model, a conjoint learning scheme is designed to ensure stability and reliablity. The experimental results show that the proposed hybrid model obtains higher prediction accuracy and better robustness compared with the pure mechanism modelling technique and the existing benchmark data-driven modelling methods. In addition, the proposed method is able to provide real-time prediction ability, which is substantial to the optimisation control of the hot metal pretreatment process.

A spatiotemporal synergetic operating performance assessment based on reconstructed correlation matrix and dissimilarity analytics for plant-wide hot strip mill process

Operating performance assessment (OPA) of process industries plays a significant role in improving the product quality and pursuing the best economic benefits. With the continuous improvement of industrial intelligence, massive data has been collected. Variable time-delay issue is brought by the different spatial and temporal distributions of production units, which affects the actual causal relationship of collected data and assessment accuracy. Therefore, a spatiotemporal synergetic operating performance assessment (SSOPA) method is proposed in this paper. First, a reconstructed correlation matrix is carefully crafted in both time and space, leveraging the intricate multi-correlated spatiotemporal-delay (MCSD) parameters. To precisely quantify the multi-correlated relationships, a mixed gray relation analysis (MGRA) is employed. Subsequently, a predatory search-based genetic algorithm (PSGA) is utilized to meticulously search for the optimal MCSD parameters. Once these parameters are determined, an OPA model is formulated for each subsystem, drawing upon aligned process data and a distributed dissimilarity analysis (DISSIM). Finally, based on the subsystem-level OPA, a comprehensive assessment of the global operating performance level is conducted. The feasibility and effectiveness of the proposed method are verified by the plant-wide hot strip mill process (PHSMP).

Hot deformation behavior and processing maps for an Al-Mg-Si-Zr-Mn alloy

Isothermal compression tests were executed on an Al-Mg-Si-Zr-Mn alloy using a Gleeble-3800 thermo-mechanical simulator at temperatures from 400 to 550 °C and strain rates ranging from 1 to 0.001 s⁻¹. By analyzing the flow curves and characterizing the deformed microstructure, this study aimed to gain insights into the hot deformation behavior and hot workability. Utilizing the hyperbolic-sine sinusoidal model, a constitutive equation was derived, revealing an activation energy of hot deformation of 274 kJ/mol. The processing maps were constructed utilizing the dynamic material model, which highlighted the secure range of hot working conditions between 480 to 550 °C and 0.01–0.001 s−1. The softening mechanism observed at relatively low deformation temperatures and high strain rates was primarily dynamic recovery, whereas the safe domain exhibited a combination of dynamically recovered (DRV) and recrystallized (DRX) grain structures. The results of the FEM simulation indicated a non-homogeneous distribution of stress and strain fields, with the highest effective values focused at the center of the sample. Furthermore, the FEM simulation unveiled a clear correlation between the evolution of DRV and DRX and the strain.

Hot deformation behavior and process optimization of TC4-DT alloy fabricated by wire and arc additive manufacturing with in-situ forging

The near net shape forging of a preform fabricated using additive manufacturing (AM) technique has attracted significant attention due to its exceptional material utilization rate. However, the complexity of the parts hinders its further development. This study investigated the hot deformation behavior of TC4-DT titanium alloy fabricated by wire and arc additive manufacturing (WAAM) with in-situ forging. The isothermal compression samples underwent homogenizing treatment to eliminate layer bright lines before being subjected to deformation at temperatures ranging from 800 to 950 °C and strain rates ranging from 0.01 to 1 s−1 with the height reduction of 60%. Subsequently, the hot deformation constitutive equations and hot processing map were established to analyze the characteristics of hot deformation and microstructure evolution. The results demonstrate that the hyperbolic sine constitutive equation considering strain can accurately predict flow stress under arbitrary deformation conditions, with an average relative error of 7.23%. Furthermore, microstructure analysis under different deformation conditions validated the applicability of the hot processing map, which identified preferable and easily achievable in-situ hot forging regions at temperatures between 900 and 950 °C and strain rates between 0.05 and 1 s−1 with the strain exceeded 0.4. Finally, WAAM combined with optimized in-situ hot deformation processing enables the production of macrostructures consisting of fully equiaxed prior-β grains while maintaining isotropy in mechanical properties, thereby providing a solid foundation for direct additive manufactured complex forgings featuring uniformly fine equiaxed grains and highly comprehensive properties.

An adaptive strategy for time‐varying batch process fault prediction based on stochastic configuration network

AbstractFault prediction ensures safe and stable production, and cuts maintenance costs. Due to the changing operating conditions that lead to the changes in the characteristics of industrial processes, there is a need to monitor the fault state of batch processes in real‐time and to accurately predict fault trends. An adaptive slow feature analysis‐neighborhood preserving embedding‐improved stochastic configuration network (SFA‐NPE‐ISCN) algorithm for batch process fault prediction is proposed. Firstly, SFA is used to extract the time‐varying features of process data and establish the update index of the NPE model. Then, to extract local nearest‐neighbor features and reconstruct them by the NPE model with adaptive update capability, square prediction error (SPE) statistics are constructed as fault state features based on the reconstructed error. Further, the hunter‐prey optimization (HPO) algorithm optimizes the weights and biases in the stochastic configuration network, and the singular value decomposition (SVD) and QR decomposition of column rotation are introduced to solve the ill‐posed problem of SCN and obtain the prediction model of ISCN. Finally, the obtained statistics SPE is formed into a time series, and the ISCN model is used to predict the process state trend. The effectiveness of the proposed algorithm is verified by case studies of industrial‐scale penicillin fermentation processes and the Hot strip mill process.

Design of melting parameters for safety airbag labels based on hot air welding technology: CFD simulation and experimental validation

This paper focuses on researching the various factors that influence the material melting rate during the hot air melting process. To achieve this purpose, the paper proposes a melting model for Acrylonitrile-Butadiene-Styrene (ABS) plastic under hot air heating based on Computational Fluid Dynamics (CFD). Orthogonal experiments were conducted based on the parameter range of each factor obtained in the pre-experiment. The results showed that the outlet distance, hot air velocity, hot air temperature, and their interaction items are important factors that affect the melting rate of ABS materials. Based on the simulation results, a multiple nonlinear regression model was constructed to predict the melting rate under different parameters. Comparing the simulation values with the predicted values of the multiple nonlinear regression model, the error between the two was no >10%, indicating the effectiveness of the prediction model. The research results can help guide the hot air welding melting process for different materials and characteristics, and provide a certain reference value for the development of hot air welding technology.

A novel process monitoring framework combined temporal feedback autoencoder and multilevel correlation analysis for large-scale industrial processes

Modeling and monitoring generally face numerous challenges such as complex characteristics of multi-unit, temporal correlations and strong interaction among subblocks in large-scale industrial processes. To handle those challenges, a novel process monitoring framework combined temporal feedback autoencoder and multilevel correlation analysis is proposed in this paper. Firstly, large-scale industrial processes are decomposed into multiple subblocks in spatial and temporal order based on process knowledge. Secondly, an improved autoencoder with temporal feedback mechanism is constructed as local monitoring model to capture the important latent variables of each subblock. Then, considering the sequential transmission and correlations among subblocks in series, a multilevel correlation analysis method is employed to efficiently extract the unique features of each subblock and the joint features of the whole process. Finally, the irregular contribution indices of the unique features and the joint features are designed for hierarchical process monitoring. The superiority of the proposed framework can be verified by Tennessee Eastman process and a real hot strip mill process.