Precise Temperature Research Articles

Temperature and palaeolake evolution during a Middle Pleistocene interglacial–glacial transition at the Palaeolithic locality of Schöningen, Germany

The Middle Pleistocene Reinsdorf sequence at the Lower Palaeolithic sites of Schöningen offers the opportunity to reconstruct a rarely well‐preserved post‐Holsteinian environmental transition from an interglacial into a glacial phase along with its highly dynamic interjacent climatic oscillations. Combining biological proxies, element composition and stable isotope ratios of two lakeshore sequences at excavation site 13 II, we demonstrate repeated variations in climate, hydrology and catchment vegetation cover. New ostracod‐based quantitative mean summer and winter air temperature reconstructions with the Mutual Ostracod Temperature Range (MOTR) method provide the first detailed information about the temperature evolution. The interglacial temperature maximum, probably corresponding to Marine Isotope Stage 9e, is followed by a first dry phase and, during the younger part of the Reinsdorf sequence, by a second dry period. Both were marked by lower precipitation/evaporation ratios, reduced vegetation cover in the catchment and increased surface inflows from springs. Temperature reconstructions of these two steppe (open woodland) phases yield very narrow ranges for mean January (−4–0 °C) and July (+17–19 or +17–21 °C) air temperatures, demonstrating that, while summers were similar to those of today, winters were at least 1 °C colder, hinting at a more pronounced continental climate. Precise temperature estimates for the interjacent woodland and steppe (woodland) phase are hindered by generally wider ranges produced by the MOTR method (January mean −4–3 °C, July mean +15–21 °C). The development of a more extensive vegetation cover, reducing surface runoff and erosion in favour of increased river and groundwater discharge, as indicated by a shift in microfossil and stable isotope records, suggests generally more humid climates with higher precipitation/evaporation ratios as well as reduced seasonal temperature variations.

An innovative manifold microchannel heat sink for thermal management of high-power chips with multiple hotspots

In this study, we propose an innovative manifold microchannel heat sink (MMCHS) featuring perforated baffle structures, which is specifically engineered to address the thermal management challenges associated with chips that exhibit multiple hotspots. By enhancing the conventional Z-shaped MMCHS, we designed a cost-effective and efficient cooling solution tailored specifically for precise temperature regulation across multiple hotspots. We employed numerical simulation techniques to analyze the flow dynamics and heat transfer properties of the optimized manifold microchannel heat sink (OMMCHS) across various baffle configurations and perforation densities. The findings reveal that the OMMCHS significantly outperforms the traditional Z-shaped MMCHS, establishing it as a superior option for cooling of high-power chips with multiple hotspots. Notably, the OMMCHS configuration equipped with I-type baffles and a 50% perforation rate yields the most favorable results, ensuring temperature homogeneity across the hotspots at an inlet velocity of 1.9 m/s. Compared to the MMCHS, the OMMCHS reduces pump power consumption by up to 77.8% while maintaining the same peak temperature, highlighting its efficiency and effectiveness in thermal management.

Spline-based Abel Transform (SAT) radial property reconstruction for noise and trapping correction: Application to axisymmetric sooting flames

In combustion research, optical diagnostics often necessitate Abel inversion to deconvolve the measurements of axisymmetric flames, especially to determine local soot temperature fields from integrated flame radiative emission measurements. However, traditional Abel inversion methods can considerably amplify experimental noise, especially towards the flame centerline. Although various strategies exist to mitigate this issue, they typically do not address the correction of signal trapping within the flame. The present paper introduces an adapted Abel inversion tool that combines resistance to experimental noise with a mechanism to correct signal trapping effects. The tool employs noise-free Abel inversion using piecewise spline functions. Its effectiveness is validated through numerical comparisons with conventional methods. The practical application is demonstrated in the measurement of soot temperature in a canonical laminar diffusion ethylene flame. This is achieved by using multi-wavelength line-of-sight attenuation (LOSA) and emission measurements. The tool corrects for the signal trapping effect in emission data by integrating extinction profiles, thus enabling a more precise soot temperature analysis. The current study also compares two techniques of temperature measurement based on thermal emission: traditional two-color pyrometry and a calibrated emission and absorption ratio method. The study further explores the effects of signal trapping, scattering contribution, and the absorption function ratio on soot temperature determination based on experimental profiles. The findings suggest that signal trapping and scattering contributions have a negligible impact on measurements at the wavelengths examined. However, the choice of absorption function ratio significantly influences the outcomes of two-color pyrometry, highlighting the advantage of the one color emission/absorption technique for the determination of sooting flames temperature measurements.

Calibrating cryogenic temperature of TEM specimens using EELS

Cryogenic Scanning/Transmission Electron Microscopy has been established as a leading method to image sensitive biological samples and is now becoming a powerful tool to understand materials' behavior at low temperatures. However, achieving precise local temperature calibration at low temperatures remains a challenge, which is especially crucial for studying phase transitions and emergent physical properties in quantum materials. In this study, we employ electron energy loss spectroscopy (EELS) to measure local cryogenic specimen temperatures. We use the temperature-dependent characteristics of aluminum's bulk plasmon peak in EEL spectra, which shifts due to changes in electron density caused by thermal expansion and contraction. We successfully demonstrate the versatility of this method by calibrating different liquid nitrogen cooling holders in various microscopes, regardless of whether a monochromated or non-monochromated electron beam is used. Temperature discrepancies between the actual temperature and the setpoint temperatures are identified across a range from room temperature to 100 K. This work demonstrates the importance of temperature calibrations at intermediate temperatures and presents a straightforward, robust method for calibrating local temperatures of cryogenically-cooled specimens in electron microscopes.

Model Validation and Real-Time Process Control of a Continuous Flow Ohmic Heater

Ohmic heating is a highly efficient method for rapid fluid heating, with applications in fields such as food processing, pharmaceuticals, and chemical engineering. Prior to its industrial application, thorough analysis and modeling are crucial to ensure safe and efficient operations. Therefore, this research focuses on the development and validation of a transfer function-based model for a continuous flow ohmic heater (CFOH). Validation metrics include root mean square error (RMSE) and mean absolute percentage error (MAPE). The developed model achieves an RMSE of ±1.48 and a MAPE of ±2.58% compared to experimental results, demonstrating its accuracy. Furthermore, the research presents the implementation of robust real-time applications of advanced process controllers, including PID, MPC, and AMPC. These controllers were first simulated using the developed model and subsequently deployed in the pilot plant ohmic heater system to achieve precise temperature control and optimised input voltage. The reliability of this procedure was affirmed through a comparison between simulated results and empirical data obtained from the CFOH pilot plant. The study concludes by suggesting potential applications in fault diagnosis, educational training, system identification, and controller design.

Temperature-Dependent Sex Determination in Crocodilians and Climate Challenges.

The sex of crocodilians is determined by the temperature to which the eggs, and hence the developing embryo are exposed during critical periods of development. Temperature-dependent sex determination is a process that occurs in all crocodilians and numerous other reptile taxa. The study of artificial incubation temperatures in different species of crocodiles and alligators has determined the specific temperature ranges that result in altered sex ratios. It has also revealed the precise temperature thresholds at which an equal number of males and females are generated, as well as the specific developmental period during which the sex of the hatchlings may be shifted. This review will examine the molecular basis of the sex-determination mechanism in crocodilians elucidated during recent decades. It will focus on the many patterns and theories associated with this process. Additionally, we will examine the consequences that arise after hatching due to changes in incubation temperatures, as well as the potential benefits and dangers of a changing climate for crocodilians who display sex determination based on temperature.

On the Method of temperature Measurements in Borehole Using Precision thermometers

Precise autonomous borehole thermometers (loggers) allow measuring temperature anomalies of small amplitude (up to 1 mK). It significantly expands the range of problems that borehole thermometry can solve in exploration geophysics, hydrogeology, engineering geology, and geoecology. However, thermal logging techniques remain outdated that hinders the effective implementation of the capabilities of these devices. The paper discusses methodological issues of precision temperature measurements in water-filled boreholes. Experimental studies with an autonomous thermometer rBrsolo³ T (RBR Ltd., Canada) showed that the device’s response to changes in ambient temperature (relaxation) is complex. Within a few seconds after the immersing of device in a borehole, it registers a temperature close to the fluid temperature. However, this temporary “window” closes soon, and after 15–20 seconds the measured temperature begins to deviate more and more from the undisturbed temperature. Next time measured temperature returns to the undisturbed temperature after 1000–6000 sec. In addition, the temperature response in the interval of 20–600 sec is complicated by non-periodic fluctuations with an amplitude of 0.02–0.05 K associated with thermal convection. The presence of a time “window” on the relaxation curve makes it possible to measure fluid temperature quickly and accurately in stop-and-go mode. The design parameters of thermometers determining the width of the “window” were assessed using mathematical modeling. Recommendations for conducting precision temperature logging of boreholes in both continuous and stop-and-go modes have been provided.

Physics-Informed Online Learning for Temperature Prediction in Metal AM.

In metal additive manufacturing (AM), precise temperature field prediction is crucial for process monitoring, automation, control, and optimization. Traditional methods, primarily offline and data-driven, struggle with adapting to real-time changes and new process scenarios, which limits their applicability for effective AM process control. To address these challenges, this paper introduces the first physics-informed (PI) online learning framework specifically designed for temperature prediction in metal AM. Utilizing a physics-informed neural network (PINN), this framework integrates a neural network architecture with physics-informed inputs and loss functions. Pretrained on a known process to establish a baseline, the PINN transitions to an online learning phase, dynamically updating its weights in response to new, unseen data. This adaptation allows the model to continuously refine its predictions in real-time. By integrating physics-informed components, the PINN leverages prior knowledge about the manufacturing processes, enabling rapid adjustments to process parameters, geometries, deposition patterns, and materials. Empirical results confirm the robust performance of this PI online learning framework in accurately predicting temperature fields for unseen processes across various conditions. It notably surpasses traditional data-driven models, especially in critical areas like the Heat Affected Zone (HAZ) and melt pool. The PINN's use of physical laws and prior knowledge not only provides a significant advantage over conventional models but also ensures more accurate predictions under diverse conditions. Furthermore, our analysis of key hyperparameters-the learning rate and batch size of the online learning phase-highlights their roles in optimizing the learning process and enhancing the framework's overall effectiveness. This approach demonstrates significant potential to improve the online control and optimization of metal AM processes.

Construction of multifunctional core-shell structure nanoprobe integrating NIR dual-mode optical thermometer and nuclear magnetic imaging

Precise temperature regulation and imaging are critical for in vivo photothermal treatment. The goal of this work is to realize non-contact temperature measurement and imaging in biological tissues by building a multifunctional nano-platform using optical temperature probes and imaging for biological diagnosis and therapy. Here, NIR dual-mode temperature probes of NaYF4: Nd/Yb/Gd@NaNdF4 were designed according to the LIR-I of 4F3/2 → 4I9/2/2F5/2 → 2F7/2 levels in 850 – 1025 nm and LIR-II of 2F5/2 → 2F7/2/4F3/2 → 4I11/2 in 950 – 1100 nm from the emissions of Nd3+/Yb3+. Transmission electron microscope (TEM) and X-ray diffraction (XRD) data of the sample demonstrate its superior dispersibility and accurate structure. The integrated intensity ratio centered around various luminescence intensity peaks is used as a temperature sensor since luminescence intensity is temperature-dependent. Additionally, the temperature sensing capabilities of two ratio temperature sensors were examined under 808 nm laser excitation, utilizing LIR (luminescence intensity ratio) technology. Furthermore, the MRI test indicated that the sample exhibited good imaging capacity when Gd3+ was added. These results assure the auspicious application prospects of the samples in temperature sensing, photothermal therapy, and biomedical imaging.

P-156 Ultra-fast warming of blastocysts yields better survival rates for D5 non-PGT and similar survival rates for D5/D6 PGT blastocysts

Abstract Study question Can an ultra-fast single-step warming of vitrified blastocysts yield similar survival rates and post-warming development compared to the standard multi-step rehydration protocol? Summary answer Ultra-fast warming, shows significantly better rates of survival and post-warming development in vitro for non-PGT blastocysts and similar rates for PGT blastocysts. What is known already Excellent survival rates have been reported since the introduction of human blastocyst vitrification. Typically, most warming procedures involve three steps with decreasing concentrations of non-penetrating cryoprotectants. Recently, few studies have evaluated the effectiveness of simplifying the procedure to a single step for rehydration, while maintaining comparable survival and pregnancy rates. Adopting simpler procedures can optimize laboratory protocols, workflow, and safety, supporting further advancements in Assisted Reproduction Technologies (ART). Study design, size, duration This validation study ultra-fast warmed 246 vitrified blastocysts [129 non-PGT day5 (cryopreservation period 23/01/2017-24/04/2018 VIT-kit, Fujifilm), 57 PGT day5 (25/01/2023-31/03/2023 VIT-KitNX, Fujifilm), 60 PGTday6 (03/02/2023-22/08/2023 Vit-KitNX, Fujifilm)] and compared survival rates with 379 blastocysts [240 non-PGT day5, 97 PGT day5, 42 PGT day6] vitrified in the same time-periods and warmed for clinical application using the standard multi-step protocol. Ultra-fast warmed blastocysts were cultured for 24h in a time-lapse incubator and subjected to a viability staining. Participants/materials, setting, methods Blastocysts, originating from 111 patients that were donated to validation studies after the legal storage period(n = 129) or deemed non-transferable after PGT(n = 117), were ultra-fast warmed by immersing the straw in a 37 °C thawing solution (1M trehalose; Vit-kitwarmNX; Fujifilm) for 1 minute. Survival rates [total (≥50% intact) and fully (100% intact) ], transfer rates (2h post-warming, ≥50% intact), re-expansion time and the number of damaged cells (Live/Dead kit L-3224, Invitrogen) were analysed. Fisher’s Exact Test (p < 0.05). Main results and the role of chance Overall, the immediate post-warming survival rates (≥50% intact) were comparable between ultra-fast and multi-step warming, 98.4% vs 96.8% respectively (p = 0.3041). However, the fully intact survival rate immediately post-warming was significantly higher with ultra-fast warming (85.4% vs 76.3%; p = 0.0058) as well as the percentage of blastocysts considered transferable (96.7% vs 91.2%; p = 0.0076). Sub-group analysis demonstrated significantly better results for non-PGT blastocysts following ultra-fast warming. Higher immediate survival post-warming (100% vs 96.6%; p = 0.036) and transfer rates (100% vs 90%; p = 0.0002) were achieved. Similar results were observed for PGT blastocysts on both day 5 and day 6, with no significant differences in total, fully intact, and transfer rates observed between the two warming procedures [PGT Day5: 96.5%, 80.7%, and 93.0% vs. 97.9%(p = 0.6270), 69.1%(p = 0.1334), and 93.8%(p = 1.0000)] [PGT Day6: 96.7%, 68.3%, and 93.3% vs. 95.2%(p = 1.0000), 64.3%(p = 0.6761), and 92.8%(p = 1.0000)]. Ultra-fast warmed blastocysts showed a total re-expansion rate of 93.3% in 3.3h±2.7h on average. Viability staining demonstrated very few cells damaged. Zero cell damage was observed in 31.5% of the blastocysts, 59.0% had 1-10 cells damaged, 9.5% >10 cells damaged, and only 4 blastocysts were completely degenerated. Limitations, reasons for caution In order to limit the amount of embryos needed in this validation study, ultra-fast warming outcome parameters were compared with retrospective clinical results of blastocysts vitrified in the same time periods. Ultra-fast warming is a single-step process where precise temperature control(37 °C) of the warming medium is crucial for success. Wider implications of the findings Minimizing handling steps leads to an overall risk reduction in potential exposure to suboptimal warming conditions and operator/handling-related stress. This optimization brings huge efficiency to the busy work schedule that is characteristic for an IVF lab without dropping cryopreservation quality indicators. Trial registration number Not applicable

Assessment of NIR-triggered PEG-coated NaGdF4:Tm3+/Yb3+ bio-compatible upconversion nanoparticles for contrast enhancement in OCT imaging and optical thermometry

In this investigation, we embarked on the synthesis of polyethylene glycol coated NaGdF4:Tm3+/Yb3+ upconversion nanoparticles (UCNPs), aiming to assess their utility in enhancing image contrast within the context of swept source optical coherence tomography (OCT) and photo-thermal OCT imaging. Our research unveiled the remarkable UC emissions stemming from the transitions of Tm3+ ions, specifically the 1G4 → 3H6 transitions, yielding vibrant blue emissions at 472 nm. We delved further into the UC mechanism, meticulously scrutinizing decay times and the nanoparticles′ capacity to convert radiation into heat. Notably, these nanoparticles exhibited an impressive photo-thermal conversion efficiency of 37.5%. Furthermore, our investigations into their bio-compatibility revealed a promising outcome, with more than 90% cell survival after 24 h of incubation with HeLa cells treated with UCNPs. The nanoparticles demonstrated a notable thermal sensitivity of 4.7 × 10−3 K−1 at 300 K, signifying their potential for precise temperature monitoring at the cellular level.

Real-time temperature control in rubber extrusion lines: a neural network approach

In rubber extrusion, precise temperature control is critical due to the process’s sensitivity to fluctuating parameters like compound behavior and batch-specific material variations. Rapid adjustments to temperature deviations are essential to ensure stable throughput and extrudate surface integrity. Based on our previous research, which initiated the development of a feedforward neural network (FNN) without real-world empirical application, we now present a real-time control system using artificial neural networks (ANNs) for dynamic temperature regulation. The underlying FNN was trained on a dataset comprising different ethylene propylene diene monomer (EPDM) rubber compounds, totaling 14,923 measurement points for each temperature value. After training, the FNN achieves remarkable precision, evidenced by a mean absolute percentage error (MAPE) of 0.68% and a mean squared error (MSE) of 0.63°C2 in predicting temperature variations. Its integration into the control system enables real-time responsiveness, allowing for adjustments to temperature deviations within an average timeframe of 68 ms. A key advantage over proportional-integral-derivative (PID) controllers is the ability to continuously learn and adjust to complex, non-linear, and batch-specific process dynamics. This adaptability results in enhanced process stability, as evidenced by inline manufacturing validation. Our paper presents the first ANN-based rubber extrusion control, demonstrating how machine learning techniques can be effectively leveraged for real-time, adaptive temperature control. Beyond rubber extrusion, this strategy has potential applications in various polymer processing and other industries requiring precise temperature control. Future trends may involve the integration of online learning techniques and the expansion of interconnected manufacturing processes.

Meteorological data from Badwater, Death Valley National Park 1998 to 2019

AbstractWe installed a meteorological recording system at Badwater (elev. −75 m), the lowest point in Death Valley, California and recorded data over the period 1998–2019. A second station (the Outhouse Station) was established nearby from 2014 to 2019. Here, we report on and publicly archive the data from these two stations. Of interest was the comparison between two air temperature measurements at the Badwater Station, the first with an aspirated platinum resistance temperature device and the second with a thermistor probe in a passive sun shield. During the hottest periods of the summer when temperatures were typically between 30°C at night and 50°C daily peak, the passively shielded sensor indicated up to 0.5°C warmer than the aspirated temperature sensor due to radiative effects. The data suggest a correction for radiative heating of (T–35)/30, for T > 35°C, where, T, is the uncorrected temperature reading of a passively shielded sensor subtracted after any calibration at lower temperatures. Our station was the first precision temperature measurements at Badwater. A longer record exists for the reporting station near the visitor's centre at the Furnace Creek. The summer temperature maxima at the Badwater site correlate well with the values the same day from the Furnace Creek site. The daily maximum temperatures in winter at the Badwater site appear to be about 1°C lower than at the Furnace Creek site. The largest differences are in the minimum temperatures for which the Badwater site averages about 2–3°C warmer than the Furnace Creek site.

Unraveling the complexity of Fe-based bulk metallic glasses: Insights into dynamic mechanical relaxation in atomic-scale

This research conducts a thorough investigation into the structural and mechanical evolution of Fe74B20Nb2Hf2Si2 bulk metallic glass (BMG) subjected to thermal aging. Utilizing X-ray diffraction (XRD) and selected area electron diffraction (SAED), the study verifies the amorphous structure of the as-cast BMG, highlighting evidence of short-range ordering (SRO). Thermal aging conducted between 342 and 570 K induces substantial changes, notably the formation of Fe23B6 and α-Fe phases and reduced defect concentrations. During dynamic mechanical analysis, a significant shift was observed, which is characterized by a decrease in the intensity of β-relaxation and an increase in β-activation energy from 333.3±2.1 kJ/mol (for the sample aged at 342 K) to 384.6±5.6 kJ/mol (for the sample aged at 570 K). Nanoindentation evaluations reveal an increase in hardness from 11.85±0.22 GPa (for the as-cast BMG) to 14.65±0.41 GPa (for the sample aged at 570 K), accompanied by an increase in Young’s modulus from 211.61±3.00–244.24±2.00 GPa. These changes imply tighter atomic packing and diminished free volume due to aging, suggesting an advanced stage of structural relaxation. Additionally, the material demonstrates a decrease in plastic strain from 0.0052 in its as-cast state to 0.0026 at 342 K, progressing to brittle behavior with further aging. This study shows the pivotal role of precise aging temperature control in optimizing BMGs for diverse applications, illustrating the intricate interplay between thermodynamics and kinetics in material science.

A Precise Temperature Control Method for Lithium-ion Battery Pack based on the Nonlinear Model Predictive Control Algorithm

Abstract To utilize the maximum performance of the battery while ensuring its thermal safety, a battery thermal management system is used to control the battery maximum temperature within a safe range. This paper centres on the establishment of a temperature prediction model and the development of the nonlinear-based model predictive control (MPC) strategy. First, to address the need of predicting battery temperature, this paper develops a distributed parameter thermal resistance model to predict battery temperature quickly and accurately. Secondly, the open-loop formulation of the nonlinear-based MPC is derived based on the established state space equations. Then the soft and hard constraints of the model are established based on the actual current conditions, pump conditions, temperature difference and temperature rise indexes, so as to establish the objective function of the MPC algorithm. Finally, the established temperature nonlinear MPC algorithm is embedded on the board and the hardware platform of battery liquid cooling system is established. The experiment test result shows that the maximum error of temperature control is less than 0.1°C, and the effectiveness of the temperature control strategy of lithium-ion battery is verified through experiments.

Fractal Circuit Architectures for Spatially Controlled Heating and Multi-Modal Shape Programming of Electro-Active Shape Memory Polymers

Shape memory polymers (SMPs) are commonly activated through external heating or rigid embedded heaters, which lack precise temperature control and restrict programmable shape transformations. This study demonstrates integrating thin films of hard electronic materials patterned in fractal designs into SMPs yields novel thermomechanical responses, enabling flexible implementation of stretchable electronic functionality. Space-filling Hilbert, Moore and Peano fractal curves generate distributed electronic circuitry patterns within the SMP matrices. To investigate the coupled electro-thermal-mechanical behavior, a multi-physics modeling approach is adopted. A nonlinear thermo-visco-hyperelastic constitutive model captures the SMP’s shape memory characteristics. Governing equations for the multi-physics problem are formulated. Experimental data validates the model’s predictions of the SMP’s nonlinear material response under uniaxial loading. This validated framework analyzes SMP composites with integrated fractal circuits. Findings reveal composites with higher-order fractal circuits’ exhibit faster, more uniform resistive heating and smaller electrical resistance changes during stretching, enabling consistent and predictable shape recovery under various deformations. Notably, these advantageous heating and resistance characteristics enhance the force recovery rate during the shape memory cycle. Furthermore, the composites demonstrate excellent shape recovery under bending. Remarkably, uniaxial stretching can induce controlled out-of-plane shape transformations, enabling novel actuation modalities. This work provides insights into leveraging fractal circuit integration to enhance SMP performance and expand capabilities, enabling multi-functional actuators, sensors and programmable soft grippers.

SPECIFICS OF DESIGNING AN INFRARED PYROMETER-REFLECTOMETER FOR SEMICONDUCTOR HETEROSTRUCTURE FABRICATION

There are general technical requirements for all types of reactors for chemical vapour deposition technology using AIII- BV metalorganic compounds. Among them, it is worth highlighting the large temperature gradients that cause the origin of convection loops, which in turn, taking into account the high speed of the gas flow, lead to turbulence in the reactor instead of the expected laminar flow. It is also important to take into account the change in parameters of the wafer surface during the growth process and the need for signal separation between the useful signal from the wafer surface and the background signal from the wafer carrier, which rotates at fixed speed for uniform deposition of compounds. To obtain high-quality heterostructures with reproducible parameters, it is important to have a system of precise temperature control on the wafer surface directly in the deposition area, since the deposition process for many complex semiconductor devices (for example, laser diodes, LEDs, photodiodes, transistors on heterojunctions) is very sensitive to temperature changes. The method of optical pyrometry is a non-contact method that allows to precisely determine the temperature of the wafer surface and meets the technical requirements of CVD epitaxy growth reactors. This article is devoted to the analysis of the features of the development of optoelectronic systems for precise temperature measurement during epitaxial growth in order to determine the criteria for the selection or development of components of the optoelectronic system of the pyrometer-reflectometer. The main physical processes, electro-optical characteristics of Si photodiode, AlGaAs/GaAs LED and parameters of bandpass interference filters were investigated. Based on the analysis of the obtained research and measurement results, scientific recommendations have been developed. The recommendations aimed at the selection and optimization of the parameters of the components of the pyrometer-reflectometer (photodetectors, light emitting diodes, optical filters) in order to improve the accuracy and temperature stability of measurements in the pyrometer’s operation conditions, which take into account the compensation of emissivity change from the surface of the wafer.

Advancements in Nanomaterial Dispersion and Stability and Thermophysical Properties of Nano-Enhanced Phase Change Materials for Biomedical Applications.

Phase change materials (PCMs) are materials that exhibit thermal response characteristics, allowing them to be utilized in the biological field for precise and controllable temperature regulation. Due to considerations of biosafety and the spatial limitations within human tissue, the amount of PCMs used in medical applications is relatively small. Therefore, researchers often augment PCMs with various materials to enhance their performance and increase their practical value. The dispersion of nanoparticles to modify the thermophysical properties of PCMs has emerged as a mature concept. This paper aims to elucidate the role of nanomaterials in addressing deficiencies and enhancing the performance of PCMs. Specifically, it discusses the dispersion methods and stabilization mechanisms of nanoparticles within PCMs, as well as their effects on thermophysical properties such as thermal conductivity, latent heat, and specific heat capacity. Furthermore, it explores how various nano-additives contribute to improved thermal conductivity and the mechanisms underlying enhanced latent heat and specific heat. Additionally, the potential applications of PCMs in biomedical fields are proposed. Finally, this paper provides a comprehensive analysis and offers suggestions for future research to maximize the utilization of nanomaterials in enhancing the thermophysical properties of PCMs for biomedical applications.

In situ monitoring of cycling characteristics in lithium-ion battery based on a two-cavity cascade fiber-optic Fabry-Perot interferometer

The state characterization inside the lithium-ion battery during charge/discharge cycling is extremely crucial for understanding the electrochemical reaction mechanism. However, current methods exhibit a challenge to overcome the specific battery environment obstacles, including strong redox properties, strong electromagnetic interference, and fast reaction processes. Hence, more efforts are still needed to monitor the actual state inside the battery accurately and reliably. To address this issue, we designed and developed a compact two-cavity cascade fiber-optic Fabry-Perot interferometer (FPI) sensor that can be safely implanted in batteries to measure internal temperature and pressure simultaneously. With its high pressure and temperature sensitivity of 26.6 ​nm/kPa and 107 ​nm/°C, this sensor exhibits an ultra-low cross-sensitivity of −40 ​Pa/°C. During charge/discharge cycling tests, regular cyclic pressure and temperature signals are obtained at various rates cycling in real-time and in situ, revealing details about the actual state characterization inside the battery. From the experiment results, the pressure inside the battery is divided into reversible changes caused by respiration effects and irreversible changes caused by trace gas production. Furthermore, the FPI sensor provides a more precise temperature than thermocouples that measure the surface temperature of the battery, reflecting the internal/external temperature difference to a maximum of 3.5 ​°C at 1 ​C rate cycling. This operando FPI sensor provides a valuable technological tool for battery performance testing and safety monitoring.

Development of Focused Ultrasound-Assisted Nanoplexes for RNA Delivery.

RNA-based therapeutics, including siRNA, have obtained recognition in recent years due to their potential to treat various chronic and rare diseases. However, there are still limitations to lipid-based drug delivery systems in the clinical use of RNA therapeutics due to the need for optimization in the design and the preparation process. In this study, we propose adaptive focused ultrasound (AFU) as a drug loading technique to protect RNA from degradation by encapsulating small RNA in nanoliposomes, which we term nanoplexes. The AFU method is non-invasive and isothermal, as nanoplexes are produced without direct contact with any external materials while maintaining precise temperature control according to the desired settings. The controllability of sample treatments can be effectively modulated, allowing for a wide range of ultrasound intensities to be applied. Importantly, the absence of co-solvents in the process eliminates the need for additional substances, thereby minimizing the potential for cross-contaminations. Since AFU is a non-invasive method, the entire process can be conducted under sterile conditions. A minimal volume (300 μL) is required for this process, and the treatment is speedy (10 min in this study). Our in vitro experiments with silencer CD44 siRNA, which performs as a model therapeutic drug in different mammalian cell lines, showed encouraging results (knockdown > 80%). To quantify gene silencing efficacy, we employed quantitative polymerase chain reaction (qPCR). Additionally, cryo-electron microscopy (cryo-EM) and atomic force microscopy (AFM) techniques were employed to capture images of nanoplexes. These images revealed the presence of individual nanoparticles measuring approximately 100-200 nm in contrast with the random distribution of clustered complexes observed in ultrasound-untreated samples of liposome nanoparticles and siRNA. AFU holds great potential as a standardized liposome processing and loading method because its process is fast, sterile, and does not require additional solvents.