Purpose Nucleic acid amplification forms the core of molecular diagnostics, with its efficiency dependent upon rapid and precise temperature control. Sensor-based closed-loop control serves as a key approach, whilst microfluidic chips provide an ideal platform for efficient thermal regulation. This paper aims to review recent advances in microfluidic chip temperature control technologies and explores their application prospects and challenges in point-of-care testing. Design/methodology/approach Through systematic analysis of thermal heating, optical heating, semiconductor thermoelectric cooling (TEC) and fluid-driven fixed-temperature-zone strategies, this study compares their performance in heating rates, temperature uniformity, and system integration. Application discussions are supplemented with recent research examples. Findings Different temperature control methods possess distinct advantages: electrical heating offers simplicity but higher power consumption; optical heating provides rapid temperature rise yet is constrained by light source coupling; TEC enables bidirectional temperature regulation but requires complex heat dissipation design; while fixed-temperature-zone fluid-driven systems demonstrate outstanding performance in continuous-flow PCR. Originality/value This review paper assesses the efficacy, advantages, disadvantages and clinical feasibility of various temperature control solutions incorporating temperature sensors, based on the requirements of microfluidic nucleic acid amplification. It aims to provide design references for future high-efficiency molecular diagnostic systems.

PSMA RNA aptamer A10-3.2 conjugated with indocyanine green for rapid intraoperative imaging and effective mild photothermal therapy of prostate cancer.

ABSTRACT The rapid advancement of artificial intelligence technologies has imposed unprecedented demands on high‐density and energy‐efficient optical interconnects. Silicon photonic (SiPh) chips offer a promising solution by enabling the integration of hundreds of photonic devices within a millimeter‐scale footprint using standard semiconductor fabrication processes. However, the high thermo‐optic coefficient of silicon (Si) poses a significant challenge to achieving energy‐efficient operation, especially under varying thermal conditions. Therefore, athermal designs that eliminate the need of active temperature control are highly desirable. Here, we design and experimentally demonstrate an athermal silicon photonic optical transmitter, realized through heterogeneous integration of graphene on a silicon nitride (SiN) photonic integrated circuit fabricated in a standard 200 mm SiPh pilot line. The transmitter supports data transmission rates exceeding 100 Gbps over a temperature range from 20°C to 60°C, with temperature‐induced relative bandwidth fluctuations remaining below 3%. Our work paves the way for scalable and cost‐effective SiPh solutions with enhanced thermal stability, meeting the growing interconnect demands of next‐generation computing infrastructure.

Prompt recognition of these intrapartum features allows early intervention through maternal temperature control, antibiotic therapy, and timely delivery when indicated. Early identification and management of fetal inflammation are essential to mitigate inflammation-mediated neonatal morbidity and adverse neurological outcomes. • Intra-amniotic inflammation and infection during labor are common at term and are major contributors to fetal and neonatal morbidity. • Traditional intrapartum cardiotocography (CTG) interpretation is primarily focused on detecting hypoxia-related fetal compromise and may fail to recognize non-hypoxic inflammatory insults. • Fetal exposure to intra-amniotic inflammation during labor can be identified antenatally through specific intrapartum cardiotocographic patterns, even in the absence of maternal clinical signs of infection. • The recognition of CTG features suggestive of fetal inflammation provides an opportunity for earlier intrapartum intervention, with potential to reduce neonatal sepsis, encephalopathy, and long-term neurological injury.

Regulating open pores to engineer closed pores in ZIF-8-derived hard carbon for high-plateau-capacity sodium-ion batteries.

Abstract Organ transplantation is the only effective therapeutic modality for end-stage organ diseases. However, short preservation windows (several hours) and donor scarcity limit the development of transplantation. Clinical studies have confirmed that machine perfusion is a more effective approach for organ preservation and repair compared with traditional static cold storage technology. It has been demonstrated that a reduction in temperature can further diminish organ metabolic rates, thus minimizing consumptive injury. Currently, machine perfusion devices for organs above 0 °C are available, but those for sub-zero temperatures and suitable for multiple organs remain underdeveloped. In this study, a multi-thermic machine perfusion (MTMP) system is developed, which enables programmed regulation over a wide temperature range from normothermia, hypothermia to supercooling. The core engineering design incorporates a dual-channel temperature control module, a closed-loop perfusion unit, a pressure feedback unit, and an organ chamber adaptable to diverse organs (1-200 cm3). Our results show that the device is capable of precisely regulating temperature, pressure, and flow rate. We successfully perform perfusion on rat hearts, rabbit kidneys and pig kidneys using the designed MTMP system, achieving stable multi-thermic perfusion preservation. Moreover, stepwise loading of cryoprotective agent is realized by the system, providing a critical pretreatment platform for subsequent organ vitrification. This MTMP system addresses critical gaps in organ preservation technology, offering multi-scale applicability and compatibility with vitrification pretreatment. Its engineering robustness and clinical adaptability lay a foundation for extending preservation duration and accelerating translation to transplant clinics.

Development and evaluation of an advanced wire-arc directed energy deposition process with integrated temperature control and in-situ heat treatment

Abstract To further optimize the overall combustion performance of combustion-type tear gas mixtures and improve the effective utilization rate of the tear gas agent OC, various nanomaterials and composite nanomaterials were incorporated into the combustion-type tear gas mixture system. Using specialized equipment for measuring physical property parameters and thermal analysis instruments, changes in the physical property parameters and thermal decomposition behavior of six modified mixtures were investigated. The microstructure of these mixtures was characterized and analyzed, and the mechanism by which nanomaterial addition influences the thermal decomposition process of the mixture system was explored via the Starink method, Flynn-Wall-Ozawa method, and Coats-Redfern method. The results revealed that the maximum decomposition temperature (T max ) of samples NP2, NP5, and NP6 exhibited the most significant reduction (approximately 40 °C), while the average combustion rate increased by nearly 17%. Correspondingly, the OC release efficiency (ω OC ) rose by 8.2% to 10.2%, and the smoke concentration increased by approximately 10%. Comprehensive analysis of sample pyrolysis behavior, calculation of kinetic parameters, fitting of reaction models, and examination of combustion residues demonstrated that the activation energy of the first-stage reaction for samples NP1–NP6 varied with the conversion degree (α). This indicates that the addition of nanomaterials transformed the reaction process at this stage from a single-step to a multi-step mechanism, which is consistent with the findings from pyrolysis behavior analysis.The most probable reaction models were predicted using the Coats-Redfern method, revealing that the reaction models corresponding to each stage of samples NP1–NP6 underwent certain changes. Notably, during the first two pyrolysis stages of the samples, the models shifted from the diffusion model (D3) and nucleation model (A4) to the reaction order model (F1/F2). Additionally, this study reproduced the pyrolysis process of the tear gas mixture as it enters the combustion zone through thermodynamic simulation. The reaction processes occurring within these specific temperature ranges provide a critical foundation for further investigating precise temperature control technologies and enhancing the overall combustion efficiency of such mixtures.

Thermal comfort and energy efficiency are two main goals of heating, ventilation, and air conditioning (HVAC) systems, which use about 40% of the total energy in buildings. This paper aims to predict optimal room temperature, enhance comfort, and reduce energy consumption while avoiding extra energy use from overheating or overcooling. Six Machine Learning (ML) models were tested to predict the optimal temperature in the classroom based on the occupancy characteristic detected by a Deep Learning (DL) model, You Only Look Once (YOLO). The decision tree achieved the highest accuracy at 97.36%, demonstrating its effectiveness in predicting the preferred temperature. To measure energy savings, the study used RETScreen software version 9.4 to compare intelligent temperature control with traditional operation of HVAC. Genetic algorithm (GA) was further employed to optimize HVAC energy consumption while keeping the thermal comfort level by adjusting set-points based on real-time occupancy. The GA showed how to balance comfort and efficiency, leading to better system performance. The results show that adjusting from default HVAC settings to preferred thermal comfort levels as well controlling the HVAC to work only if the room is occupied can reduce energy consumption and costs by approximately 76%, highlighting the substantial impact of even simple operational adjustments. Further improvements achieved through GA-optimized temperature settings provide additional savings of around 7% relative to preferred comfort levels, demonstrating the value of computational optimization techniques in fine-tuning building performance. These results show that intelligent, data-driven HVAC control can improve comfort, save energy, lower costs, and support sustainability in buildings.

Waste heat utilization is a critical aspect of enhancing energy efficiency and sustainability in various systems. This study investigates the recovery of waste heat using a heat exchanger installed at the outlet of a small-sized engine, demonstrating significant temperature control capabilities. The introduction of hot air from the heat exchanger effectively increased the ambient room temperature from 20 °C to 48 °C within 90 minutes. The heat exchanger's effectiveness improved with higher initial exhaust gas temperatures, as demonstrated across three test cases. In Case I, the room temperature rose to 33 °C with an initial exhaust temperature of 61 °C. Cases II and III showed further increases to 43 °C and 45.7 °C, respectively, corresponding to higher exhaust temperatures of 77 °C and 84 °C. A notable achievement was the consistent improvement in heat exchanger performance, evidenced by increased outlet temperatures and decreased exhaust temperatures, indicating efficient heat transfer. The effectiveness of the device improved from 0.31 to 0.55, highlighting its potential for energy-efficient ambient temperature regulation. However, the study also identified certain limitations. The temperature rise plateaued after 90 minutes, suggesting a limit to the heat exchanger’s capacity due to its size. Additionally, the minimal temperature difference between 60 and 90 minutes in Case III indicated that the engine had reached its peak efficiency, thereby limiting further heat recovery.

A hydroxylamine-O-sulfonic acid (HOSA)-enabled, switchable C-H functionalization/annulation of acetophenones with α,β-unsaturated ketones is disclosed, providing a tunable one-pot route to either quinoline or isoquinoline derivatives. The identity of the HOSA-derived transient directing group, coupled with solvent and temperature control, dictates the divergent reaction pathway with high selectivity. This strategy features a broad substrate scope and excellent functional group tolerance. Its utility is demonstrated by a significantly streamlined three-step synthesis (formerly nine) of the antianemic drug roxadustat. This work establishes HOSA as a powerful catalytic transient directing group for selective C-H annulation, offering a new paradigm for heterocycle synthesis.

This paper presents a practical thermal control strategy to enhance the output performance of oxide-based all-solid-state batteries (ASSBs), which typically exhibit low ionic conductivity at room temperature. A lightweight polyimide (PI) film heater was designed, fabricated, and integrated into the cell stack to locally maintain the optimal operating temperature range (≈65–75 °C) for electrolyte activation. Unlike previous studies limited to liquid or sulfide-based batteries, this work demonstrates the direct integration and coupled numerical–experimental validation of a PI film heater within oxide-based ASSBs. The proposed design achieves high heating efficiency (~92%) with minimal thickness (<100 μm) and long-term stability, enabling reliable and scalable thermal management. Finite-element simulations and experimental verification confirmed that the proposed heater achieved rapid and uniform heating with less than a 10 °C temperature deviation between the cell and heater surfaces. These findings provide a foundation for smart battery management systems with distributed temperature sensing and feedback control, supporting the development of high-performance and reliable solid-state battery platforms.

The roasting process significantly impacts coffee's aroma and flavor profile, making it crucial in coffee processing. This study developed a rotating drum coffee roasting machine at laboratory scale with 2.0 - 2.5 kg batch capacity. Heat is provided by an LPG-powered pressure cooker burner. The research aimed to evaluate machine performance and assess roasted coffee quality. The roasting process is classified into light, medium, and dark levels. Tests show roasting temperatures from 192°C to 225°C, with times between 12 and 17 min. Moisture content of roasted coffee ranges from 2% to 7%, lower than SNI-7465:2008 standards. The motor requires 23.34 watts of electrical power to operate. Energy consumption for light and medium roasts is 4708.93 kJ, while dark roast needs 9417.86 kJ. Roasted coffee uniformity exceeds 90% at all roasting levels. The weight loss does not exceed 20%. The performance test results indicate the machine's suitability for small-scale coffee industries or laboratories to improve roasting efficiency. Future improvements should focus on better temperature and time control for enhanced flavor profiling.

Copper selenide nanomaterial mediated light-driven RPA-SDA cascade amplification combined with photothermal test strips for methicillin-resistance gene mecA detection.

Accelerating quantitative polymerase chain reaction (qPCR) without compromising analytical fidelity remains a significant challenge in molecular diagnostics, primarily due to the thermal lag between heating elements and reagents. Here, we report a high-speed qPCR platform that overcomes this limitation using a reagent-centric cascade control strategy. The system employs a planar PCB-based copper heater that functions as both a heating element and a temperature sensor, ensuring low-latency, sensor-efficient thermal feedback. To overcome this thermal delay, a virtual temperature sensor-derived from system identification-is used to estimate the real-time reagent temperature, which drives an outer-loop fuzzy PID controller with feedforward compensation. Inner cascaded loops stabilize the heater current and surface temperature. The system achieves reagent-phase average heating and cooling rates of 24.1 °C s-1 and 19 °C s-1, respectively. Furthermore, the reagent temperature is controlled with an accuracy of ±0.2 °C and an overshoot of less than 0.2 °C. A complete 45-cycle amplification is achieved in as little as 4.4 minutes. Crucially, this speed is attained without analytical compromise, demonstrating excellent quantitative accuracy (R2 = 0.9965) and amplification efficiency (109.8%). The proposed reagent-centred control framework offers a scalable pathway for developing high-throughput PCR and molecular diagnostic instruments, supporting fast, accurate, and scalable nucleic acid testing.

Energy efficiency in water heaters is a crucial factor in ship operational environments due to limited electricity resources that rely on generators. This study aims to design and build an IoT-based water heater monitoring system with an innovative heat storage medium in the form of a mixture of silica sand and paraffin wax to improve thermal efficiency. Although previous studies have developed temperature monitoring and control systems in IoT-based water heaters, this study specifically fills this gap by analyzing the performance of adding silica sand to overcome the low thermal conductivity of paraffin wax. Using the Research and Development (R&D) method, this system was built with an ESP32 microcontroller as the control center, a DS18B20 temperature sensor for accurate measurements, and the Blynk and Google Sheets platforms for real-time monitoring and data recording. Performance testing was conducted by comparing the water heating rate between pure paraffin wax media and the mixed media. The results showed that the monitoring system functioned reliably, and the main finding proved that the addition of silica sand to paraffin wax significantly increased heating efficiency. This was clearly seen from the reduction in time required to raise the water temperature to 40°C, from 2.5 hours to only 1 hour in the second heating cycle. The results of this study indicate that the integration of silica sand and paraffin wax media with IoT technology can increase the efficiency of water heaters and provide an innovative solution for energy-efficient and environmentally friendly temperature control.

Improved biostimulant production through solid-state fermentation of green waste using low-temperature strategy in tray bioreactors.

Efficacy of cleaning of unbrushable endoscope channels in automated endoscope reprocessors: evidence of non-compliance in real-world practice.

Abstract Modern electronic devices are prone to overheating due to their miniaturised design, so effective thermal management and temperature control are critical to ensuring they perform and operate safely. The fin heatsinks are widely used for the cooling of electronic components. The present study systematically investigated the influence of fin height, gap dimensions, and gap quantity on the thermal performance of forced-air cooling radiators through a combined approach of numerical simulation and experimentation. The three-dimensional numerical simulation of the heatsink was performed with FLUENT based on the semiconductor refrigeration model. The results showed that the maximum heat dissipation of the heatsink was attained when the fin height was 20 mm, the gap size was 4.5 mm, and the number of gaps was 4. The response surface method was used to optimise the heatsink structure, and the maximum heat dissipation of the heatsink was 193.48 W when the gap size was 4.8 mm, and the number of gaps was 4. It is 4.25 % higher than the original heat dissipation. The system pressure drop decreased by 24.21%, the volumetric flow rate increased by 9.80%, the fan power consumption reduced by 16.88%, and the net thermal efficiency improved by 4.35%. The results of this study had a theoretical basis and practical value. They provided a scientific basis and theoretical guidance for the actual thermal design and application of heatsinks.

Analysis on direct and additional temperature spectra of skin: A near-infrared diffuse reflectance spectroscopy study with temperature control