Actual Temperature Research Articles

Effects of water temperature increase on gene expression, biochemical, and histopathological responses of the bivalve species Mytilus galloprovincialis to the antineoplastic drug 5-fluorouracil.

Effects of water temperature increase on gene expression, biochemical, and histopathological responses of the bivalve species Mytilus galloprovincialis to the antineoplastic drug 5-fluorouracil.

Rapid Intensification of Hurricane Ian (2022) in High Shear

Abstract Initially a Category 3 storm, Hurricane Ian (2022) rapidly intensified on the West Florida Shelf reaching Category 5 over the course of about 12 hr. Intensification occurred despite inhibiting factors such as high axial tilt, high vertical wind shear, low atmospheric moisture, and transit over a relatively shallow continental shelf. Using a high‐resolution simulation of Hurricane Ian from the Hurricane Weather Research Forecasting (HWRF) model, we examine the factors that both hindered and supported rapid intensification (RI) by blending various methods. We show that an increase in diabatic heating in the eyewall led to an inward radial advection of momentum, seen in both the absolute angular momentum budget and in the azimuthal wind budget. Analysis of the moist static energy budget indicates that the substantial latent heat flux from the surface was enough to balance heat losses through storm outflow. For instance, surface latent heat fluxes exceeded 1,500 W m−2 on the West Florida Continental Shelf. As suggested by actual ocean temperature observations that substantially exceeded those in the HWRF simulation, the latent heating may have even been larger. Physical explanations for discrepancies between the simulated Hurricane Ian and observations are provided, particularly those pertaining to the coastal ocean at the time of Ian's passage. This research provides a comprehensive explanation of the RI of a hurricane using momentum budget analyses as part of a coupled air‐sea analysis. Our findings demonstrate the importance of in situ oceanic air‐sea measurements in evaluating the performance of coupled models, especially for hurricanes.

Improved African Vulture Optimization Algorithm for Optimizing Nonlinear Regression in Wind-Tunnel-Test Temperature Prediction

The thermal data of the hypersonic wind tunnel field accurately reflect the aerodynamic performance and key parameters of the aircraft model. However, the prediction of the temperature in hypersonic wind tunnels has problems such as a large delay, nonlinearity and multivariable coupling. In order to reduce the influence brought by temperature changes and improve the accuracy of temperature prediction in the field control of hypersonic wind tunnels, this paper first combines kernel principal component analysis (KPCA) with phase space reconstruction to preprocess the temperature data set of wind tunnel tests, and the processed data set is used as the input of the temperature-prediction model. Secondly, support vector regression is applied to the construction of the temperature prediction model for the hypersonic wind-tunnel temperature field. Meanwhile, aiming at the problem of difficult parameter-combination selection in support vector regression machines, an Improved African Vulture Optimization Algorithm (IAVOA) based on adaptive chaotic mapping and local search enhancement is proposed to conduct combination optimization of parameters in support vector regression. The improved African Vulture Optimization Algorithm (AVOA) proposed in this paper was compared and analyzed with the traditional AVOA, PSO (Particle Swarm Optimization Algorithm) and GWO (Grey Wolf Optimizer) algorithms through 10 basic test functions, and the superiority of the improved AVOA algorithm proposed in this paper in optimizing the parameters of the support vector regression machine was verified in the actual temperature data in wind-tunnel field control.

A view on recent ice-nucleating particle intercomparison studies: why the uncertainty of the activation temperature matters

Abstract. Ice-nucleating particles (INPs) play a crucial role in cloud formation, influencing cloud phase, lifetime, and the onset of precipitation. Consequently, microphysical processes involving INPs strongly affect the radiative properties of clouds. However, when multiple INP counters are operated simultaneously, notoriously high deviations between instruments in the range of 1 order of magnitude are commonly observed. These differences occur in ambient atmospheric measurements as well as in laboratory studies. A potential reason for these discrepancies that deserves more consideration may be related to uncertainties and errors in the temperature measurement. As the activation of INPs is a strong function of the nucleation conditions, relatively small inaccuracies in the temperature measurement may lead to significant over- or underestimations of the INP concentration. In this study, we have explored this effect as a potential reason for the differences observed among INP counters by analyzing 10 INP intercomparison studies that were published within the last 10 years with a novel quantitative estimate of the temperature uncertainty effect on heterogeneous ice nucleation. The stated temperature uncertainty of instruments used in these experiments ranged from ±0.1 to ±1.5 °C, and was most commonly specified as ±0.5 °C. Potential deviations resulting from typical temperature errors were compared with the reported level of agreement for intercompared methods. As a measure of the potential INP error due to nucleation temperature error, we defined the temperature error factor (TEF) as the quotient of the ice nucleation activity at the actual nucleation temperature divided by the ice nucleation activity at a potentially erroneously measured temperature. Respective TEFs were calculated for five distinct activation spectra based on four INP parameterizations and one compilation of atmospheric INP data. TEFs were between 1.1 and 3.2 for temperature errors of ±0.5 °C, and between less than 2 and larger than 10 for temperature errors of ±1.5 °C. TEFs calculated from parameterizations of aerosols that are highly ice nucleation active were significantly larger than those derived from atmospheric data; although the effect was found to be still as large as a factor of 10 for certain temperature ranges in atmospheric activation spectra at a temperature error of ±2 °C. When comparing two INP instruments, measurement biases may be of opposite direction, thus resulting in expected differences of up to the product of both TEFs. We found that opposite biases of +0.5 and −0.5 °C can therefore typically explain differences of a factor of 2, while opposite biases of +1 and −1 °C can theoretically explain differences of factors up to 5 or even 10, which is of the order of discrepancies typically reported in the literature on INP intercomparisons. These results highlight the need to carefully assess and report on uncertainties of the ice nucleation activation temperature.

Heat transfer model for non-invasive leakage detection in heating pipes

Typical leak detection equipment requires the excavation, installation, and reconstruction of heating pipes, which interrupt production and daily activities of nearby residents. This study proposes a heat transfer model for detecting underground heating pipes by analyzing the temperature of the ground surface boundary layer, thereby eliminating the interruption needs. A sandbox test rig, incorporating hot water and wind circulation, was constructed, and six sets of tests were conducted to verify the model’s accuracy, which was determined to be 99.805% by varying the air flow rate and water temperature in the pipes. Moreover, leakage scenarios were simulated. Non-invasive leak detection of heating pipes was achieved by comparing the accuracy of the model for leaking and non-leaking conditions. The results show that after 1 h of leakage, the calculated temperature was 0.207 ℃ lower than the actual temperature, confirming that the model can detect leakage within 1 h. This paper presents a novel approach for non-invasive leak detection in heating pipe networks, providing valuable data for future applications of the model.

Therapeutic hypothermia for acute ischemic stroke: from preclinical studies to clinical trials.

Therapeutic hypothermia (TH) is acknowledged as a promising neuroprotective strategy in clinical settings. However, its application in managing acute ischemic stroke (AIS) remains unclear due to variable clinical outcomes in bench and bedsides. A comprehensive review of original studies concerning hypothermia in ischemic stroke was conducted, sourcing data from PubMed, Web of Science, Embase, and Ovid Medicine databases covering the period from January 1, 1990 to October 31, 2023. Our search strategy yielded 1,218 articles from PubMed, 1,094 from Web of Science, 3,083 from Embase, and 2,841 from Ovid Medicine. After removing duplicates, review articles, meta-analyses, and in vitro studies focusing on hypoxic-ischemic encephalopathy or global cerebral ischemia, a total of 304 articles out of 5,669 papers were ultimately selected for in-depth analysis. Overall, we have found that there are significant differences in depth, duration, and delay between bench and bedside studies. We want to introduce the concepts of "actual brain temperature", "hypothermia initiation time", and "effective hypothermic duration" as crucial for the optimization of hypothermic therapy in AIS. We recommend critical parameters for the clinical translation of hypothermia, including a target temperature range of 34-35°C, a duration of 2-4 h, immediate initiation post-insult, and natural rewarming processes. We also advocate for selective brain cooling when reperfusion therapy is achieved. We find great differences in administrating TH for AIS between bench and bedsides. More efforts are still needed to enhance the likelihood of successful clinical translation and deepen the understanding of hypothermia's role in AIS treatment.

Моделирование реальных условий холодильной цепи и ее влияние на микробиологическую безопасность мяса птицы

Соблюдение температурного режима в звеньях холодильной цепи является одним из основных факторов, сохраняющих качество и обеспечивающих безопасность скоропортящихся пищевых продуктов. Принимая во внимание фактические температурные режимы в реальной холодильной цепи, авторами на экспериментальном стенде было смоделировано 6 режимов, включающих имитацию нахождения продукции в распределительном центре, в процессе транспортировки до точки реализации и хранения, с целью оценки ее хранимоспособности на различных этапах холодильной цепи. 3 серии из 6 были обеспечены режимами при стабильной температуре воздушной среды на протяжении всего срока хранения: минус 1±1 °С, 1±1 °С, 3±1 °С (условия хранения, указанные производителем). Еще для 3 серий опытов были смоделированы режимы с различными колебаниями температуры, характерными для реальной цепи поставок: повышение температуры при отгрузке и разгрузке до 10 °С, при транспортировании – до 13 °С, при приемке в магазине – до 20 °С. Установлено, что при обеспечении необходимого температурного режима минус 1±1 °С и 1±1 °С на всех этапах холодильной цепи возможна пролонгация сроков годности продукции мяса птицы. Установлена хранимоспособность охлажденного мяса птицы на различных этапах холодильной цепи и режимы, обеспечивающие наилучшее качество и безопасность продукта. Полученные результаты исследования позволят внедрить риск-ориентированный подход при организации трофологической цепи поставок скоропортящихся продуктов. Работа проведена в рамках выполнения исследований по государственному заданию ФГБНУ «ФНЦ пищевых систем им. В. М. Горбатова» РАН. Maintaining the temperature conditions in the links of the cold chain is one of the main factors preserving the quality and ensuring the safety of perishable food products. Taking into account the actual temperature conditions in a real cold chain, the authors simulated six conditions on the experimental stand, including imitation of the location of products in the distribution center, during transportation to the point of sale and storage, in order to assess their shelf life at various stages of the cold chain. Three of the six series were provided with conditions at a stable air temperature throughout the shelf life: minus 1±1 °С, 1±1 °С, 3±1 °С (storage conditions specified by the manufacturer). For three more series of experiments, conditions with various temperature fluctuations typical of a real supply chain were simulated: an increase in temperature during shipment and unloading up to 10 ° C, during transportation – up to 13 °С, during acceptance in the store – up to 20 °С. It has been established that by ensuring the required temperature conditions of minus 1±1 °С and 1±1 °С at all stages of the cold chain, it is possible to extend the shelf life of poultry products. The shelf life of chilled poultry meat at various stages of the cold chain and the modes that ensure the best quality and safety of the product have been established. The obtained research results will allow the introduction of a risk-oriented approach in organizing the trophological supply chain of perishable products. The research was carried out as part of the fulfillment of research under the state assignment of the of V. M. Gorbatov Federal Scientific Center of Food Systems of the RAS.

Improving Geometric Uniformity in Dynamic Chemical Vapor Deposition of Carbon Nanotube Forests.

Geometric nonuniformities are often observed in the catalytic chemical vapor deposition (CVD) of vertically aligned carbon nanotubes (VACNTs), known as CNT forests. These nonuniformities typically occur in the form of sloped heights and empty regions within the catalyst-covered substrate. To realize the true potential of carbon nanotube forests in unidirectional mass and energy transport applications, it is critical to develop robust manufacturing processes to produce geometrically uniform CNT forests on large-scale substrates in a repeatable manner. Our custom-designed reactor with an IR heating multizone furnace with rapid thermal processing capability allows the programming of dynamic recipes with the catalyst formation temperature decoupled from the CNT nucleation and growth temperature. In this work, we present an approach for tuning the geometric uniformity of CNT forests based on the combined effects of substrate holder design and dynamic recipes during CVD. We propose a mechanism that explains the observed geometric nonuniformities based on both the temperature profile across the catalyst chip, which depends on the substrate holder design, and the temperature range for CNT growth, which depends on the catalyst formation temperature. We performed a comparative study of the properties of alumina layers after annealing with two different substrate holder designs. We found that the actual temperature experienced by the sample depends on the substrate holder, which supports our proposed mechanism. Our work provides insight into the growth of CNT forests with large-scale spatial uniformity and high structural quality.

Digital twinning of temperature fields for modular multilayer multiphase pipeline structures

The temperature field of oil and gas wells in the field of petroleum engineering presents a core problem and challenge in the digital twin framework due to its ultra-long-distance and highly variable structural characteristics. The varying wellbore cross-sectional structures with depth make it difficult to establish an effective and generalized analytical model for heat transfer. In this study, we propose, for the first time, a method to automate the construction of multi-layered and multi-component heat transfer models by using a general computational model based on non-steady-state single-phase structural modules. This method enables the automated generation of complex multi-layered and multi-component heat transfer models, thereby achieving the construction of a generalized model for temperature field characterization with varying wellbore cross-sectional structures over ultra-long distances. Utilizing this modeling approach, we validate the proposed method through case studies using actual wellbore temperature field data. The results demonstrate the lightweight and efficient computational analysis of temperature field information under non-steady-state conditions.

Enhancement of Photovoltaic Systems Using Plasmonic Technology

The rise in temperature worldwide, especially in hot regions with extreme weather conditions, has made climate change one of the critical issues that degrades the solar photovoltaic (PV) system performance. In this paper, a new design of solar cells based on plasmonic thin-film Silver (Ag) technology is introduced. The new design is characterized by enhancing thermal effects, optical power absorption, and output power significantly, thus compensating for the deterioration in the solar cells efficiency when the ambient temperature rises to high levels. The temperature distribution on a PV solar module is determined using a three-dimensional computational fluid dynamics (CFD) model that includes the front glass, crystalline cells, and back sheet. Experimental and analytical results are presented to validate the CFD model. The parameters of temperature distribution, absorbed optical power, and output electrical power are considered to evaluate the device performance during daylight hours in summer. The effects of solar radiation falling on the solar cell, actual temperature of the environment, and wind speed are investigated. The results show that the proposed cells’ temperature is reduced by 1.2 °C thanks to the plasmonic Ag thin-film technology, which leads to enhance 0.48% real value as compared to that in the regular solar cells. Consequently, the absorbed optical power and output electrical power of the new solar cells are improved by 2.344 W and 0.38 W, respectively.

Analytical investigation on resolution calculation method for nonlinear temperature load of steel-concrete composite girders

This study establishes a thermo-mechanical coupling framework to elucidate the contribution mechanisms of nonlinear thermal loads in composite girders through thermal effect decomposition. A novel decomposition methodology for nonlinear temperature fields is developed based on the thermal effect equivalence principle, integrating cross-sectional deformation compatibility conditions to characterize the dynamic coupling between thermal responses and temperature loads. The proposed approach enables systematic decomposition of actual nonlinear temperature fields into three equivalent components: uniform, linear, and nonlinear temperature gradients. A computational framework incorporating statically indeterminate structural effects is subsequently formulated for comprehensive thermal response analysis. Four thermal loading models are comparatively investigated: field-measured temperature gradients, two theoretical thermal loading models (TLM-I and TLM-II), and the standardized gradient in Chinese Code JTG D60-2015. The analysis encompasses temperature-induced self-restraint stresses, secondary stresses, and axial deformation in variable-section continuous composite girders. Key findings reveal that code-specified thermal stresses exhibit opposing polarity characteristics at specific locations compared to other models. Quantitative decomposition demonstrates that self-restraint stresses primarily derive from equivalent uniform and nonlinear temperature components, while secondary stresses predominantly originate from equivalent linear and uniform temperature contributions. Axial deformations show 89%–94% dependence on equivalent uniform temperature effects. The developed methodology provides theoretical foundations for refined thermal design of composite bridge structures, addressing critical limitations in current code-specified thermal analysis approaches.

Unraveling the Thermal Effects of High-Intensity Ultrasound: A Practical Guide to Acoustic Power Determination and Heat Management.

This study provides a practical guide for determining acoustic power, the actual energy delivered during high-intensity ultrasound (HIUS) processing, which is critical for the effective design of ultrasound-assisted processes. Acoustic energy is fundamental for ensuring precise process scaling and optimization. Additionally, we address a key misconception in the literature, challenging the view that HIUS is a strictly nonthermal treatment. While HIUS has been widely explored for enhancing process efficiency, reducing energy consumption, lowering costs, and minimizing environmental impact in food and beverage processing, its thermal effects have often been overlooked. HIUS is employed in various applications, including the extraction of bioactive compounds, inactivation of microorganisms and enzymes, and modification of proteins and carbohydrates. However, one of the primary challenges in HIUS processing is temperature control, which is essential for maintaining food stability, quality, and safety. Uncontrolled temperature increases can jeopardize these attributes. In this study, we assessed actual temperature conditions during HIUS treatments by analyzing thermal histories and investigating strategies for minimizing heat generation, such as pulsed ultrasound, ice baths, and combining sonication with external heating. We also evaluated the temperature profiles in fluids with varying thermophysical properties. While heat minimization techniques are effective in mitigating excessive heating, failure to account for thermal histories can lead to underestimations of the thermal effects. Accurate temperature monitoring provides critical insights into optimizing process design. Moreover, we observed potential solvent phase changes at the microscale during high-intensity treatments. These findings offer valuable guidance for improving heat management in HIUS applications and propose standardized methods for reporting thermal conditions and energy parameters in studies that utilize this technology.

Monitoring and optimization of temperature field of pre-oxidation furnace using CFD and surrogate model

Abstract The temperature distribution in the pre-oxidation furnace has a great influence on the stabilization stage of carbon fiber production. The actual temperature of the pre-oxidation furnace is measured by fiber Bragg grating temperature sensors in this study. Moreover, the error caused by friction to the FBG temperature sensor is compensated so that the accuracy of the temperature sensor is improved. Considering that it is difficult to get the influence of process parameters on the temperature field in production, a numerical calculation model of the pre-oxidation furnace is established by computational fluid dynamics. The effect of the heat release from the polyacrylonitrile precursors on the temperature field is considered. Considering the high calculation cost of the CFD method in an optimization environment, this study established a radial basis function model instead of numerical calculation. The results demonstrate that the surrogate model is valid and the suggested optimization approach significantly enhances the thermal distribution uniformity in the pre-oxidation furnace.

Measurement of active region temperature in THz quantum cascade lasers by micro-photocurrent spectroscopy

To accurately monitor the actual temperature of a terahertz quantum cascade laser (THz-QCL) under operating conditions, this study proposes a method utilizing micro-photocurrent spectroscopy to determine the active region temperature. Micro-photocurrent spectra of THz-QCL devices with cavity lengths of 0.5 and 1 mm are measured at various bias voltages. The results demonstrate that the peak of the photocurrent spectrum exhibits a linear shift with the bias voltage below 10 V, while presenting a sharp redshift as the voltage increases further. Additionally, micro-photocurrent spectra are investigated at multiple locations on the device facet. Further analysis of the temperature effect and quantum confinement Stark effect on the bandgap change reveals the temperature distributions of the THz-QCL. It indicates that at 15 V, the temperature gradient of the active region along the material growth direction is approximately 0.4 K/μm. The proposed method, based on photocurrent spectroscopy, achieves about 3 K resolution for temperature measurement of THz-QCL, facilitating the optimization of device thermal management and failure analysis.

Sistem Monitoring Temperatur Mesin Dies Molding

PT. Yasunli Abadi Utama Plastik is a company operating in the manufacturing sector that produces motor vehicle body products. Using the Root Cause Analysis (RCA) research method, a problem was found in one of the production processes in injection molding, the plastic injection section with the product COVER R FR IDE K1Z where there was no reference to the actual temperature of the mold so that operators often started the production process before molding. reaches standard temperature according to work instructions, which causes production defects in the form of NG Silver. NG Silver is a product defect caused by bubbles trapped in the product forming cone lines. This problem will disrupt the daily production planning that has been determined and has the potential to increase production costs due to overtime work by employees to achieve production targets. The solution to this problem Shaking Water Bath Temperature and speed control have been made with using heater 1500 W, 220 V and termocouple sensor type K. This heater use a receiver (keypad) for controlling and viewing the valve of rotation speed (rpm) and temperature (˚C) by set in set point (SP). Way of rotation speed regulation is with controll the width of pulse (PWM). With maximum power, will have the temperature only 98˚C with maximum speed 600 rpm..

Cold memories control whole-body thermoregulatory responses.

Environmental thermal challenges trigger the brain to coordinate both autonomic and behavioural responses to maintain optimal body temperature1-4. It is unknown how temperature information is precisely stored and retrieved in the brain and how it is converted into a physiological response. Here we investigated whether memories could control whole-body metabolism by training mice to remember a thermal challenge. Mice were conditioned to associate a context with a specific temperature by combining thermoregulatory Pavlovian conditioning with engram-labelling technology, optogenetics and chemogenetics. We report that if mice are returned to an environment in which they previously experienced a 4 °C cold challenge, they increase their metabolic rates regardless of the actual environmental temperature. Furthermore, we show that mice have increased hypothalamic activitywhen they are exposed to the cold, and that a specific network emerges between the hippocampus and the hypothalamus during the recall of a cold memory. Both natural retrieval and artificial reactivation of cold-sensitive memory engrams in the hippocampus mimic the physiological responses that are seen during a cold challenge. These ensembles are necessary for cold-memory retrieval. These findings show that retrieval of a cold memory causes whole-body autonomic and behavioural responses that enable mice to maintain thermal homeostasis.

Climate Change Impacts in Eastern Mediterranean Sea: Trends and Extremes

Abstract This study examines the impacts of climate change on Eastern Mediterranean Sea coastal environment using long-term in situ data. Specifically, it explores three decades of previously inaccessible data on surface waves and sea surface temperature, obtained from two buoys moored off the Israeli coastline, augmented with data from several coastline temperature sensors, and sea level measurements. Our findings reveal a moderate increase in sea surface temperature of 2.65 °C per century, contradicting the current local scientific consensus of faster warming trends, and showing that the reanalysis models grossly overestimate the multiannual trends while underestimating the actual temperature values. We found alteration in the seasonal cooling-warming cycles, with shrinking transitional season periods that are replaced by prolonged summer and winter periods. Marine heatwaves have become more frequent and severe, which may result in significant ecological impacts. Maritime storm activity was observed to intensify, with a sharp increase in storms’ intensity during the early 2000s. The study also documented a rise in the occurrence of Rogue waves, including a notable 11.5-m wave near Haifa in February 2015. The sea level rise trend was found to be 2.3 mm per year. In summary, our study demonstrates the intensification in the occurrence of extreme ocean weather events which may increasingly threaten marine life in the Levant coastal zone.

Optimization and Performance Evaluation of Diesel Oxidation Catalysts for Methane Removal in Dual-Fuel Diesel–CNG Engines

Compressed natural gas (CNG) in dual-fuel diesel engines offers environmental benefits but significantly increases unburned methane (CH4) emissions, especially at low engine loads. This study investigates the effectiveness of different catalytic converters in methane oxidation under transient test conditions (WHTC). Three types of catalysts (Pt-, Rh-, and Pd-based) were evaluated using a combined approach of empirical engine bench tests and mathematical modelling. The results showed that, under actual exhaust gas temperature conditions, the average methane conversion efficiencies were 3.7% for Pt, 17.7% for Rh, and 31.3% for Pd catalysts. Increasing the exhaust gas temperature by 50% improved the conversion efficiencies to 7.3%, 51.8%, and 69.2%, respectively. Despite this enhancement, none of the catalysts reached the 90% efficiency threshold required to increase the CNG content of the fuel beyond 6% without exceeding emission limits. The results highlight the need for high-activity Pd-based catalysts and optimised thermal management strategies to enable the broader adoption of dual-fuel engines, while complying with Euro VI standards.

Exploring the impact of textural and intrinsic properties of coal on the devolatilization and low-temperature char gasification of low-rank Indian coal

ABSTRACT A notably sustainable method of coal utilization is its gasification to produce syngas, a chemical precursor. Despite process significance, studies of the effect of the properties of Indian coal used in industrial gasification on the kinetics of pyrolysis and subsequent low-temperature char gasification are relatively scarce. There is also a dearth of studies that look at the determination of such kinetics for the same coal feed. This study endeavors to bridge such gaps by employing an experiment-modeling approach to calculate the kinetic parameters and draw conclusions based on the results. The apparent kinetic parameters for pyrolysis were determined by considering four stages- stage 0, stage 1, stage 2 and onset-offset rapid region of devolatilization. Notably, the results underline the influence of properties like pore size, volatile matter and oxygenate on the devolatilization process. The inferential thermodynamic study showed positive enthalpy change with incrementing conversion indicative of the endothermicity and non-spontaneity of the process. In succession, the kinetics of the low-temperature CO2-char gasification at actual gasification inception temperatures was determined, culminating in activation energy values in the range 88–101 kJ/mol. The results illuminate the influence of textural and intrinsic properties, particularly the alkali index on the kinetics of the reaction.

Laser Annealing of Si Wafers Based on a Pulsed CO2 Laser

Laser annealing plays a significant role in the fabrication of scaled-down semiconductor devices by activating dopant ions and rearranging silicon atoms in ion-implanted silicon wafers, thereby improving material properties. Precise temperature control is crucial in wafer annealing, particularly for repeated processes where repeatability affects uniformity. In this study, we employ a three-dimensional time-dependent thermal simulation model to numerically analyze the multiple static laser annealing processes based on a CO2 laser with a center wavelength of 9.3 μm and a pulse repetition rate of 10 kHz. The heat transfer equation is solved using a multiphysics coupling approach to accurately simulate the effects of different numbers of CO2 laser pulses on wafer temperature rise and repeatability. Additionally, a pyrometer is used to collect and convert the surface temperature of the wafer. Radiation intensity is converted to temperature via Planck’s law for real-time monitoring. Post-processing is performed to fit the measured temperature and the actual temperature into a linear relationship, aiding in obtaining the actual temperature under small beam spots. According to the simulation conditions, a wafer annealing device using a CO2 laser as the light source was independently built for verification, and a stable and uniform annealing effect was realized.