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The magnetic performance of NdFeB permanent magnets rapidly decreases as their operation temperature increases. This limits the power output of electric motors as their internal temperature quickly increases with the power demand. This is particularly problematic for applications where high peak power is required for a short period of time, for example during automobile highway acceleration or during an airplane lift-off. With the advances in additive manufacturing, one can envision to fabricate more complex motor geometries and magnetic structures, without additional costs, allowing for enhanced functionalities such as better thermal management. In this context, this paper investigates the feasibility of using phase changing materials (PCMs) to mitigate the temperature rise in permanent magnets (PMs) fabricated by additive manufacturing. The potential of PCM and its relevance was validated by modeling the thermal response of an electric motor during a representative electric vehicle driving scenario. It was found that segmented magnets with embedded phase changing materials would allow to efficiently control temperature rise. To validate the simulation results, PM test pieces with and without embedded PCMs were fabricated using cold spray additive manufacturing and tested using a custom laser thermal cycling setup. [ABSTRACT FROM AUTHOR]

The correlated semiconductor vanadium dioxide (VO2) exhibits an insulator–metal transition (IMT) near room temperature, which is of interest in various device applications. Precise IMT temperature control is crucial to determine the use cases across technologies such as thermochromic windows, actuators for robots or neuronal oscillators. Doping the cation or anion sites can modulate the IMT by several tens of degrees and control hysteresis. However, modeling the effects of control parameters (e.g., doping concentration, type of dopants) is challenging due to complex experimental procedures and limited data, hindering the use of traditional data-driven machine learning approaches. Symbolic regression (SR) can bridge this gap by identifying nonlinear expressions connecting key input parameters to target properties, even with small data sets. In this work, we develop SR models to capture the IMT trends in VO2 influenced by different dopant parameters. Using experimental data from the literature, our study reveals a dual nature of the IMT temperature with varying tungsten (W) doping concentrations. The symbolic model captures data trends and accounts for experimental variability, providing a complementary approach to first-principles calculations. Our feature-driven analysis across a broader class of dopants informs selectivity and provides qualitative insights into tuning phase transition properties valuable for neuromorphic computing and thermochromic windows. [ABSTRACT FROM AUTHOR]

This study reports light narrowing in paraffin-coated vapor cells from room temperature 27 to 59 °C, where spin-exchange relaxation is suppressed. By means of a coating lock and eliminating the reservoir effect, an ultra-narrow magnetic resonance linewidth of 0.36 Hz and an atomic coherence lifetime of T 2 = 0.9 s are achieved. In cells free of buffer gas, the narrow linewidth over this broad temperature range is a result of enhanced spin polarization, which is facilitated by the effective suppression of radiation trapping benefiting from the stability of the vapor density. Using such cells in atomic magnetometers, the photon shot noise limit is estimated as 0.2 fT / Hz 1 / 2 and the spin-projection noise limit is estimated as 1.1 fT / Hz 1 / 2 . Also, a magnetometer system with the stable coated cell is identified, which demonstrates the potential for achieving relatively stable magnetometer sensitivity without precisely controlling the cell temperature. The long coherence lifetime and the broad operating temperature range expand the potential applications of quantum memory and other quantum sensors such as atomic clocks. [ABSTRACT FROM AUTHOR]

An accurate and efficient heat bath method plays a key role in atomic simulations of the thermal and mechanical properties of single-crystal silicon. Here, focusing on the single-crystal silicon (111) layer, which is a crucial lattice structure commonly employed as a substrate for chips, we propose a heat jet approach for finite temperature atomic simulations of silicon layers. First, we formulate the linearized dynamic equations for the silicon atoms and calculate the dispersion relation and lattice wave solutions. Then, an appropriate matching boundary condition is chosen for designing the two-way boundary condition, which allows incoming waves to inject into the lattice system while eliminating boundary reflections. Combining the two-way boundary condition and phonon heat source, the heat jet approach for the silicon (111) layer is proposed. Numerical tests illustrate the accuracy and effectiveness of the heat jet approach in simultaneously resolving thermal fluctuations and controlling temperature. Furthermore, we simulate the propagation of a Gaussian hump at a given temperature with the heat jet approach compared to the Nosé–Hoover heat bath. Numerical results demonstrate that the heat jet approach can well describe the movement of large structural deformations among thermal fluctuations without boundary reflections. [ABSTRACT FROM AUTHOR]

We examine structural and magnetic properties of a series of La–Fe–Si alloys in the region of concentrations where they naturally form two-phase LaFeSi–LaFe13−xSix composites with variable content and connectivity of LaFe13−xSix grains distributed within the LaFeSi matrix. Theoretical calculations confirm that the LaFeSi constituent is magnetically and structurally inert below room temperature and at pressures between −10 and 10 GPa. The LaFe13−xSix constituent, on the other hand, is magnetically and structurally active: it exhibits first-order magnetostructural transformations that, in addition to xSi, can be controlled with temperature, magnetic field, and pressure. In composites where the concentration of the inactive constituent is ∼70 wt. % or greater, the standard, single-step, LaFe13−xSix first-order phase transformation proceeds in two steps separated by over 30 K in a zero magnetic field. Increasing the magnetic field recouples the two steps and restores the single-step phase transformation pathway. We analyze the roles of stresses caused by both thermal expansion mismatch and the first-order magnetic phase transition in LaFe13−xSix to rationalize the observed physical behaviors that emerge as the temperature or/and magnetic field vary. [ABSTRACT FROM AUTHOR]

Thermoelectric coolers (TECs) offer a promising solution for direct cooling of local hotspots and active thermal management in advanced electronic systems. However, TECs present significant trade-offs among spatial cooling, heating, and power consumption. The optimization of TECs requires extensive simulations, which are impractical for managing actual systems with multiple hotspots under spatial and temporal variations. In this study, we present a novel machine learning-assisted optimization algorithm for thermoelectric coolers that can achieve global optimal temperature by individually controlling TEC units based on real-time multi-hotspot conditions across the entire domain. We train a convolutional neural network with a combination of the inception module and multi-task learning approach to comprehend the coupled thermal-electrical physics underlying the system and attain accurate predictions for both temperature and power consumption with and without TECs. Due to the intricate interaction among passive thermal gradient, Peltier effect and Joule effect, a local optimal TEC control experiences spatial temperature trade-off which may not lead to a global optimal solution. To address this issue, we develop a backtracking-based optimization algorithm using the machine learning model to iterate all possible TEC assignments for attaining global optimal solutions. For any m × n matrix with NHS hotspots (n, m ≤ 10, 1 ≤ NHS ≤ 20), our algorithm is capable of providing 52.4% peak temperature reduction and its corresponding TEC array control within an average of 1.64 s while iterating through tens of temperature predictions behind-the-scenes. This represents a speed increase of over three orders of magnitude compared to traditional finite element method strategies which take approximately 27 min. [ABSTRACT FROM AUTHOR]

Enhanced sampling algorithms are indispensable when working with highly disconnected multimodal distributions. An important application of these is the conformational exploration of particular internal degrees of freedom of molecular systems. However, despite the existence of many commonly used enhanced sampling algorithms to explore these internal motions, they often rely on system-dependent parameters, which negatively impact efficiency and reproducibility. Here, we present fully adaptive simulated tempering (FAST), a variation of the irreversible simulated tempering algorithm, which continuously optimizes the number, parameters, and weights of intermediate distributions to achieve maximally fast traversal over a space defined by the change in a predefined thermodynamic control variable such as temperature or an alchemical smoothing parameter. This work builds on a number of previously published methods, such as sequential Monte Carlo, and introduces a novel parameter optimization procedure that can, in principle, be used in any expanded ensemble algorithms. This method is validated by being applied on a number of different molecular systems with high torsional kinetic barriers. We also consider two different soft-core potentials during the interpolation procedure and compare their performance. We conclude that FAST is a highly efficient algorithm, which improves simulation reproducibility and can be successfully used in a variety of settings with the same initial hyperparameters. [ABSTRACT FROM AUTHOR]

PtS2, a member of the group 10 transition metal dichalcogenides (TMDs), has received extensive attention because of its excellent electrical properties and air stability. However, there are few reports on the preparation of single-crystal PtS2 in the literature, and the growth mechanism of single crystal PtS2 is not well elucidated. In this work, we proposed a method of preparation that combines magnetron sputtering and chemical vapor transport to obtain monocrystalline PtS2 on a SiO2/Si substrate. By controlling the growth temperature and time, we have synthesized a single crystalline PtS2 of hexagonal shape and size of 1–2 μm on a silicon substrate. Combining the molecular dynamics simulation, the growth mechanism of single crystal PtS2 was investigated both experimentally and theoretically. The synthesis method has a short production cycle and low cost, which opens the door for the fabrication of other TMDs single crystals. [ABSTRACT FROM AUTHOR]

We demonstrate modulation of insulator metal transition (IMT) of VO2 films grown on single crystalline substrates through the effect of in-plane compression with crystallization of capping chalcogenide layer on the targeted VO2 films. Chalcogenide germanium–antimony–telluride (Ge2Sb2Te5: GST), which shows large volume reduction of 6.8% with its phase change from amorphous to crystal, was deposited on VO2 films grown on Al2O3 (001) and TiO2 (001) substrates, where V–V atoms along the cR-axis in the tetragonal VO2 phase align parallel and perpendicular to the substrate surfaces, respectively. As a result, counter shifts in temperature-dependence of resistance characteristics, to lower and higher directions, were observed for VO2 films on Al2O3 (001) and TiO2 (001), consistent with the lattice modulation of VO2 films by the in-plane compression introduced by GST crystallization. The obtained results open a way to realize large resistance change of IMT under constant temperature by controlling GST phases. [ABSTRACT FROM AUTHOR]

Understanding and modulating the spin-pair correlation of conjugated polymer materials in π-conjugated polymer light-emitting devices (PLEDs) plays a crucial role in the development of their applications. We investigated the relationships between the internal hyperfine interactions (HFIs), triplet–triplet annihilation (TTA), and triplet–charge annihilation (TCA) spin evolution processes in π-conjugated PLED. Research has shown that in a unipolar π-conjugated PLED, the "M" shaped ultra-small magnetic field effect is due to the HFI between hole polarons and the spin-mixing process of charge carriers. Under high magnetic fields (15 mT<|B|<350 mT), the TCA process dominates the negative magneto-conductance (MC), and its intensity and sign are not controlled by temperature. In polar π-conjugated PLED, excess carriers can provide conditions for the generation of TCA. Moreover, π-conjugated polymers (emission layers) have relatively strong electron–phonon coupling, which can capture triplet excitons into adjacent organic layers to obtain higher triplet exciton concentrations, resulting in the TTA process. Under low-temperature conditions, excess carriers induce the magneto-electroluminescence (MEL) effect to undergo TTA and form P-type delayed fluorescence. This study can provide a new mechanism explanation for the HFI in PLED devices and a new approach for the effective utilization of triplets. [ABSTRACT FROM AUTHOR]

Molecular dynamics simulations have been widely used in exploring the nucleation behavior of many systems, including gas hydrates. Gas hydrates are ice-like solids in which gas molecules are trapped in water cages. During hydrate formation, a considerable amount of heat is released, and previous work has reported that the choice of temperature control scheme may affect the behavior of hydrate formation. The origins of this effect have remained an open question. To address this question, extensive NVE simulations and thermostatted (NPT and NVT) simulations with different temperature coupling strengths have been performed and compared for systems where a water nanodroplet is immersed in a H2S liquid. Detailed analysis of the hydrate structures and their mechanisms of formation has been carried out. Slower nucleation rates in NVE simulations in comparison to NPT simulations have been observed in agreement with previous studies. Probability distributions for various temperature measures along with their spatial distributions have been examined. Interestingly, a comparison of these temperature distributions reveals a small yet noticeable difference in the widths of the distributions for water. The somewhat reduced fluctuations in the temperature for the water species in the NVE simulations appear to be responsible for reducing the hydrate nucleation rate. We further conjecture that the NVE-impeded nucleation rate may be the result of the finite size of the surroundings (here the liquid H2S portion of the system). Additionally, a local spatial temperature gradient arising from the heat released during hydrate formation could not be detected. [ABSTRACT FROM AUTHOR]

We report on both the electrical and thermoelectric transport properties as a function of temperature in poly(3,4-ethylene dioxythiophene) (PEDOT)–poly(styrene sulfonate) conducting polymers for a wide range of dimethyl sulfoxide (DMSO) additives. Whereas an insulating-like electrical behavior is found over the whole temperature range, a metallic-like thermopower is mainly observed. We show that the resistivity appears to be governed by a three-dimensional variable range hopping mechanism due to disordered regions with a decreasing localization temperature T 0 and an increasing scaling factor ρ 0 as a function of the DMSO ratio. The correlation between T 0 and ρ 0 demonstrates that they are both controlled by the localization length ξ 0 , which is strongly enhanced by the DMSO in agreement with the morphological evolution of the PEDOT chains with the additive. On the other hand, the high-T positive metallic-like thermopower seems rather unaffected by the additive in contrast to its low-T counterpart, which appears negative below a characteristic temperature T s w i t c h . By showing that the latter is closely related to the localization temperature, we propose to ascribe this sign switch to the thermoelectric contribution originating from disordered regions, which competes with the metallic ones due to ordered domains. While still controlled by the localization temperature, this negative contribution appears to be consistent with a phonon-drag component with a scaling behavior as T 0 T − 3 . These analyses allow us to discuss the overall temperature dependent thermoelectric properties in a consistent way by considering a heterogeneous structure with both ordered and disordered domains. By relating explicitly the electrical resistivity to the thermopower, our results do not only reconcile these transport coefficients, but they also provide a unified picture of the properties of the conducting polymers. [ABSTRACT FROM AUTHOR]

[Display omitted] • A spatial-time-dual-resolved PL switching system based on 0D Mn-based metal halides. • Excellent reversible phase conversion properties between crystalline and molten states. • Superior PL switching with short response times and ultrahigh cyclic reversibility. • Screen printing fluorescent security labels with high spatial resolution and convenience. • Versatile multi-level information encryption-decryption and anti-counterfeiting. While spatial and time-resolved anti-counterfeiting technologies have gained increasing attention owing to their excellent tunable photoluminescence, achieving high-security-level anti-counterfeiting remains a challenge. Herein, we developed a spatial-time-dual-resolved anti-counterfeiting system using zero-dimensional (0D) organic–inorganic Mn(II) metal halides: (EMMZ) 2 MnBr 4 (named M−1 , EMMZ=1-Ethyl-3-Methylimidazolium Bromide) and (EDMMZ) 2 MnBr 4 (named M−2 , EDMMZ=1-Ethyl-2,3-Dimethylimidazolium Bromide). M−1 shows a bright green emission with a quantum yield of 78 %. It undergoes a phase transformation from the crystalline to molten state with phosphorescence quenching at 350 K. Reversible phase and luminescent conversion was observed after cooling down for 15 s. Notably, M−2 exhibits green light emission similar to M−1 but undergoes phase conversion and phosphorescence quenching at 390 K, with reversible conversion observed after cooling down for 5 s. The photoluminescence switching mode of on(green)-off–on(green) can be achieved by temperature control, demonstrating excellent performance with short response times and ultra-high cyclic reversibility. By leveraging the different quenching temperatures and reversible PL conversion times of M−1 and M−2 , we propose a spatial-time-dual-resolved photoluminescence (PL) switching system that combines M−1 and M−2. This system enables multi-fold tuning of the PL switch for encryption and decryption through cationic engineering strategies by modulating temperature and cooling time. This work presents a novel and feasible design strategy for advanced-level anti-counterfeiting technology based on a spatial-time-dual-resolved system. [ABSTRACT FROM AUTHOR]

[Display omitted] • Temperature regulation enables flexible transformation of non-radical degradation pathways in MIL-88B(Fe)-derived catalysts. • Increased carbonization temperature transforms the catalyst structure from amorphous to carbon nanotubes. • DFT theoretical calculations verified FeNP, pyrrole N and C=N as key active sites. • Decreased toxicity of byproducts produced in the carbamazepine degradation pathway. • The MN@C-9/PMS system has good anti-interference ability and low iron ion solubility. Temperature modulation of the synthesis process of MOF-derived composites is not well understood for changes in the peroxymonosulfate catalytic domain. This study synthesized a carbon-based nitrogen-doped (MN@C) MOF-derived composite catalyst derived from MIL-88B(Fe) (Materials Institute Lavoisier) by modulating temperature changes and calcination. Combined with density-functional theory calculations (DFT) analyses showed that changes in iron nanoparticles (FeNP) and C N content caused the alterations of the degradation pathways. MN@C-9 exhibited outstanding activation performance (100 % carbamazepine (CBZ) removal within 10 min). The system maintained efficient operation in different aqueous environments and a wide pH range and demonstrated efficient removal of many pollutants typical of pharmaceuticals and personal care products (PPCPs). After comprehensively analyzing the results of liquid chromatography mass spectrometry (LC-MS) and toxicity prediction, the possible degradation pathways were reasonably speculated, and the toxicity of the byproducts was greatly reduced. This study provides a potential and efficient catalyst preparation strategy for water purification. [ABSTRACT FROM AUTHOR]

Embryo culture is crucial to achieve successful outcomes in in vi tro production-embryo transfer for cattle. This study explored the innovative use of dry incubators for bovine embryo culture, building on their advantages in human medicine, such as reduced contamination risk, stable temperature control, and lower gas consumption. In this study, we examined changes in osmotic pressure, the in vi tro developmental potential of IVP embryos including the cleavage rate, blastocyst development rate, blastocyst diameter, and blastocyst cell number, morphokinetics, and the transcriptional profile of the blastocysts between humidified and dry incubators. Our research demonstrates the feasibility of this approach, showing that although the osmotic pressure gradually increases over the culture period (on day 8: 271.7 vs. 299.0, respectively; P = 0.09), it did not negatively affect the blastocyst formation rate (62.4 % vs. 69.8 %) and the morphological quality of blastocysts (diameter: 237.4 vs. 242.8, total cell number: 189.2 vs. 242.8). Embryos cultured in dry incubators exhibited morphokinetics comparable to those cultured in conventional humidified incubators. Furthermore, RNA-seq revealed that while a few genes showed changes, the transcriptomic profiles of blastocysts cultured in dry incubators were largely similar to those of blastocysts cultured in humidified incubators. These findings highlight the considerable potential of dry incubators for the in vi tro production of bovine embryos. • Embryos in dry incubators showed in vitro development and morphokinetics similar to those in humidified incubators. • RNA-seq analysis revealed blastocysts in dry incubator had transcriptomic profiles similar to those in humidified incubators. • Dry incubators offer potential for advancing bovine embryo production, providing an alternative to traditional methods. [ABSTRACT FROM AUTHOR]

The development of efficient, durable, and resource-efficient electrocatalysts is critically important for the sustainable advancement of water splitting technologies. In particular, exploring non-precious metal electrocatalysts for hydrogen evolution reactions (HER) in high-pH environments is a critical research question within the field of renewable energy sources. In this study, we present the successful synthesis of a bimetallic oxide heterojunction material, achieved through the reduction of a single-phase bimetallic structure, CoMoO 4 , to CoMoO 4 /Co 2 Mo 3 O 8. The tunable electronic structure not only enhances the traditional water dissociation capabilities of metal oxides but also optimizes hydrogen adsorption. As a result, the meticulously engineered CoMoO 4 /Co 2 Mo 3 O 8 , synthesized on Ni foam, exhibits exceptional HER performance in alkaline condition, achieving overpotentials of approximately 24 mV and 88 mV at current densities of 10 mA cm−2 and 100 mA cm−2, respectively in 1 M KOH solution. Furthermore, it demonstrates stability exceeding 100 h at a current density of 100 mA cm−2. In comparison to single-phase CoMo oxides loaded with Pt, the bimetallic oxides heterojunction exhibits superior performance. We hypothesize that CoMo oxides possess an electronic structure analogous to that of Pt, which facilitates the generation of a greater quantity of H 3 O+ during the high-pH HER process. This finding provides new perspectives on improving the inherent electrocatalytic properties of non-precious metal oxides. • CoMo oxide heterojunctions were prepared via one-step temperature control method. • The oxide heterojunction samples exposed more active sites. • The oxide heterojunction shows better performance than the Pt-loaded CoMo oxide. • Creating a local acidic environment that enhances alkaline HER. [ABSTRACT FROM AUTHOR]

Carbon fiber‐reinforced thermoplastic composites have the advantages of lightweight and high strength and have broad application prospects in automotive lightweighting. This study uses the Overmolding process to mold carbon fiber‐reinforced nylon 6 composite materials. By using laser surface treatment and preheating technology, the interfacial bonding performance of the composite material is emphasized. By optimizing the embedding temperature, it was observed that the in‐plane shear strength increased by 13 times to 70 MPa, and the tensile strength increased by 10 times to 44 MPa. Similarly, by adjusting the melting temperature, the in‐plane shear strength was significantly improved, and the mechanical interlock and interfacial bonding were effectively enhanced by laser surface treatment, achieving the same effect as embedding preheating. By establishing a finite element model, the in‐plane tensile and in‐plane shear at the interface were accurately simulated, and the progressive failure process of the interface layer was successfully predicted. Highlights: Laser energy density strengthens the overmolding interface.Optimizing insert, mold, and melt temperatures enhances interface bonding.Shear and tensile tests reveal differences in interface failure behavior.Finite element model accurately simulates overmolding interface failure.Laser treatment and temperature control are key to stronger interfaces. [ABSTRACT FROM AUTHOR]

In the article, for air-handling units (AHUs), an almost disturbance decoupling temperature and humidity tracking controller is constructed directly based on dynamic nonlinear models by backstepping. Compared with model-free techniques such as proportion integration differentiation (PID) and so on, the proposed scheme uses the known information effectively in the model to ensure control accuracy. Different from linearisation methods, the almost disturbance decoupling method is employed to attenuate the impact of disturbances. Without fuzzy logics, the proposed controller requires less computation since the exponential explosion of computation caused by the increase of fuzzy rules can be avoided. To show the practicability, the outdoor temperature and humidity, strength of humidity source, and heat load are considered to be time-varying. Finally, compared with PID, feedback linearisation and fuzzy controllers, the effectiveness and superiority of the constructed controller are proved. [ABSTRACT FROM AUTHOR]

The heat generation problem of axle box bearing during churning phase leads to abnormal temperature rise and temperature alarm, which affects the normal operation of high-speed train. Aiming at this problem, the temperature characteristics of bearing initial lubrication phase is studied, and the multi-speed grade cycle running schemes are used in tests to run multiple bearings for multiple times. The temperature data and friction data in tests are collected by using non-destructive testing method, and characteristic extraction is carried out. Under the premise of not destroying the internal structure and lubrication state of the bearing, the lubrication state inside the bearing is reflected by the change of the characteristic values. A 118 min scheme is proposed, and the bearing using this scheme to run on the test rig is used in the actual operation. The results show that the temperature of the bearing with running-in test is lower than that of the bearing without running-in test, which indicates the effectiveness of the proposed temperature control strategy. [ABSTRACT FROM AUTHOR]

This research looks at the impact of dielectric fluids and fluid speeds on cell temperature control in innovative cylindrical lithium‐ion batteries during high‐rate discharges (C‐rate) using the multiscale multidomain battery model. The goal is to improve the battery thermal management system to increase battery performance, longevity, and safety. The present study includes reducing thermal strains, enhancing efficacy, and forestalling overheating risks across various applications in electrified systems. The assessment focuses on four dielectric fluids—ester, mineral, kerosene, and Novec 7200—flowing at 0.01 m/s to gauge their efficiency in managing cell temperatures. Results demonstrate the criticality of effective thermal management in maintaining optimal battery performance and longevity. Ester oil emerges as the most efficient coolant, maintaining cell temperatures at 305.84 K and showcasing a 44% reduction compared with scenarios without coolant. In contrast, kerosene oil, mineral oil, and Novec 7200 yield temperature reductions of 42.86%, 42.51%, and 43.11%, respectively. Furthermore, combining 1% v/v. MXene nanoparticles with ester oil enhance cooling capabilities, with remarkable cell temperature reductions of 50% at 0.01 m/s velocity. Subsequent increments in flow velocity lead to enhanced cooling effects: at 0.05 and 0.1 m/s, reductions reach 51.89% and 52.155%, escalating to 52.58% and 54% at 0.5 and 1.0 m/s, correspondingly. [ABSTRACT FROM AUTHOR]

The drying process of agro-industrial products such as kiwi, avocado, banana, kale, and red chili is described. Additionally, it proposes the design of a new control technique based on active disturbance rejection to regulate the temperature required for the dehydration of these products in a hybrid solar-LP gas tunnel-type dryer. The simulation results confirm the effectiveness of the control technique in regulating the temperature during the process. Furthermore, they demonstrate that the developed control not only ensures optimal plant operation but also mitigates the risks of rejecting batches of dried products due to non-compliance with quality specifications. [ABSTRACT FROM AUTHOR]

Polymer-based zeolite imidazolate framework composite membrane (TAPP-ZIF-60). [Display omitted] • Antibacterial TAPP-ZIF-6 h membrane was prepared using temperature regulation and PEI bridging strategies. • The introduction of PEI and MOF enhance the antimicrobial ability of the membrane. • PEI reduces the size of ZIF-8 crystals by inhibiting the Ostwald ripening effect. • CDA is performed to deeply analyze the interaction between ZIF-8 and uranyl ion. • Coordination-driven and covalent-driven PEI-bridging assembly was employed. Extraction uranium (VI) (U(VI)) from wastewater and seawater is highly important for environmental protection and life safety, but it remains a great challenge. In this work, the growth of the zeolitic imidazolate framework-8 (ZIF-8) nanoparticles on the tannic acid (TA)-3-aminopropyltriethoxysilane (APTES) modified PVDF (TAP) membrane was designed to obtain an excellent U(VI) adsorbent. The zeolite imidazolate framework composite membrane (TAPP-ZIF-60) was prepared through polyethyleneimine (PEI) bridging strategy and temperature regulation strategy in solvothermal method. The coordination bond between PEI and ZIF-8 and the covalent bond between PEI and TAP are essential in forming stable composite membrane. TAPP-ZIF with different properties was synthesized through a temperature regulation process and the TAPP-ZIF prepared at 60 °C has the uniform morphology and good performance. The adsorption capacity of TAPP-ZIF-60 is 153.68 mg/g (C 0 = 95.01 mg/L and pH = 8.0) and water permeability is 5459 L m−2 h−1 bar−1. After ten adsorption–desorption cycles, it is proved that TAPP-ZIF-60 has good repeatability and stability. In addition, the TAPP-ZIF-60 composites membrane has a good inhibitory effect on Staphylococcus aureus and Escherichia coli. X-ray photoelectron spectroscopy (XPS) and density functional theory (DFT) analysis reveal that the coordination between TAPP-ZIF-60 and uranyl ions is the primary factor contributing to the high adsorption capacity. [ABSTRACT FROM AUTHOR]

The optimal temperature control strategy in extracorporeal cardiopulmonary resuscitation (ECPR) patients is unknown, and several trials have reported conflicting results regarding its effectiveness. We aimed to conduct a systemic review and network meta-analysis (NMA) to assess the efficacy of temperature control in ECPR patients. Database searching of studies reporting data on temperature control strategy during ECPR in MEDLINE, EMBASE, Scopus, and Cochrane Library was performed. Primary outcomes were overall survival and neurological outcome. Pairwise meta-analysis and Bayesian NMA were performed on studies comparing outcomes among groups of moderate hypothermia (32–34 °C), mild hypothermia (34.1–36 °C) and normothermia (36.1–37.5 °C). Nineteen retrospective studies were included (5622 patients). Statistically significant differences in good neurological outcome were observed in the direct comparison of moderate hypothermia and mild hypothermia (OR, 1.73; 95 % CI: 1.07–2.81) as well as moderate hypothermia and normothermia (OR, 2.14; 95 % CI: 1.24–3.67), but no significant differences were found in the NMA result. There was no difference in either survival outcome or the incidence of bleeding complications among any groups according to direct or indirect analysis. Direct evidence suggests that moderate hypothermia might be associated with improved neurological outcomes in ECPR patients. However, no significant differences in survival outcomes were observed in either the direct or NMA results. Given the lower level of the evidence, interpretation should be made with caution. [ABSTRACT FROM AUTHOR]

The powder bed fusion (PBF) process is increasingly employed by industry to fabricate complex parts with stringent standard criteria. However, fabricating parts "free of defects" using this process is still a major challenge. As reported in the literature, thermally induced abnormalities form the majority of generated defects, and are mainly the result of thermal evolution. Monitoring & controlling the temperature and its distribution throughout a layer under fabrication is an effective and efficient proxy to controlling such an evolution. In this paper, we introduce a novel online thermography and closed-loop hybrid-control (NOTCH)©, a practical control approach, to modify the scan strategy in metal PBF real-time. This system employs different mathematical thermophysical -based models, designed to optimize the printing sequence of different zones throughout a printing layer as well as the islands or stripes within each zone. Moreover, NOTCH uses artificial neural network (ANN) to optimize the energy density applied on each zone in order to avoid or mitigate some prevalent thermal anomalies. NOTCH strategy has two aims. First, producing a uniform temperature distribution throughout an entire layer to mitigate the thermally induced residual stress and its related distortion. In this step, we optimize the printing sequence of islands or stripes in their respective scan strategies. This paper expands on three potential models, explains pros and cons of these models, and presents preliminary results for a printed prototype. Second, controlling the laser specifications in order to avoid heat affected zones (HAZ) and mitigate thermal abnormalities such as the balling phenomenon. This step enables a smart adjustment of energy density by using ANN to avoid or mitigate HAZs, generate uniform microstructure with minimum porosity, and contribute to a more uniform temperature distribution. The completion of the latter step is part of the ongoing research which should be reported in future publications. [ABSTRACT FROM AUTHOR]

Copyright of Metal Working (1674-165X) is the property of Metal Working Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Metal Working (1674-165X) is the property of Metal Working Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The accuracy of laser gas detection technology is influenced by the temperature of the optical cavity. Traditional control methods suffer from inadequacies in fully considering the coupling effects between features and the time delay in heat transfer. To address these issues, a method combining Transformer and reinforcement learning (RL) has been proposed. By using Transformer, this method generates enhanced features that are then used by the RL algorithm for iterative learning, aiming to optimize the control strategy. Additionally, a dual attention mechanism is introduced to enhance the model’s comprehension of the complex dynamics within the optical cavity. This study represents the first application of Transformer in the field of temperature control, paving the way for the utilization of advanced machine-learning techniques in optical cavity temperature regulation. Experimental results confirm the proposed method’s efficiency and long-term effectiveness in ensuring precise temperature control, demonstrating its potential in managing the complex cross-coupling effects within temperature control systems. [ABSTRACT FROM AUTHOR]

Many models predict changes in the distribution and incidence of diseases associated with climate change. However, studies exploring the effect of microclimatic changes on host–parasite relationships are scarce. In this study, we increased temperature or humidity in Eurasian Blue Tit Cyanistes caeruleus nestboxes during the breeding season, to analyse the effect of each variable on the abundance of ectoparasites and, also, on the body condition of the hosts. Temperature and humidity were experimentally increased on average by about 2°C and 15%, respectively. The abundance of blowfly Protocalliphora azurea pupae was significantly reduced in nests with increased temperature compared with control nests and those with increased humidity, and was also significantly reduced in nests with increased humidity compared with control nests. The abundance of mites Dermanyssus spp. was significantly reduced in nests with increased humidity. However, there was no significant effect of the experiment on the abundance of flea Ceratophyllus gallinae larvae, biting midges (Culicoides spp.) and blackflies (Simuliidae). The body condition of nestlings was lower in nests with increased humidity and slightly lower in heated nests. However, the body condition of adults was not significantly affected by the experiment. In addition, blowfly pupae and biting midge abundance were negatively related to the body condition of the nestlings, and biting midge abundance was also negatively related to the body condition of the adults. Overall, an increase in temperature and humidity reduces the abundance of ectoparasites, which suggests that these parasites are sensitive to sudden changes in the microclimate in which they develop. Moreover, these fluctuations negatively affect the body condition of Blue Tit nestlings despite the concurrent decrease of parasites in nests. In other words, the expected benefit to the nestlings from the reduction in parasites does not occur because the microclimate also adversely affects nestlings, probably affecting their heat exchange with the nest environment. [ABSTRACT FROM AUTHOR]

Large diurnal temperature changes (ΔT) (or the diurnal temperature range (DTR)) in surface soils, ranging from 5°C to often greater than 20°C, are generally acknowledged to occur yet largely disregarded in studies that seek to understand how temperature affects microbially-mediated carbon and nitrogen cycling processes. The soil DTR is globally significant at depths of 30 cm or less, occurring from spring through summer in temperate biomes, during summer periods in the arctic, and year-round in the tropics. Thus, although temperature has long been considered an important factor in controlling microbial processes, our understanding of its effects remains incomplete when considering natural soil temperature cycles. Here we show: (1) documented impacts of diurnal temperature changes on microbial respiration rates; (2) documented observations of surface soils with large DTR (>5°C) that affect soil microbial mineralization rates and redox potentials of important biogeochemical reactions; and (3) direct evidence that the constant temperature regime typically used in laboratory soil incubation studies may therefore lead to mischaracterization of in situ temperature controls on microbially influenced processes in the environment. The overall effect is that the DTR yields process rates that are often higher than what has been observed under experimental mean temperature incubation. We suggest that overlooked genetic mechanisms, such as the presence of a circadian clock or thermophilic activity during summer months, are likely contributing to the observed effects of the DTR. To improve our understanding of climate change effects on soil greenhouse gas emissions, nutrient cycling, and other biogeochemical soil processes, we propose a paradigm shift in approach to temperature-inclusive process modeling and laboratory incubation studies that accounts for the important role of natural diurnal temperature fluctuations. [ABSTRACT FROM AUTHOR]

AbstractStructured high-dimensional streaming data offers abundant information that are crucial for process feedback control. Nevertheless, traditional control models predominantly emphasize the global patterns of spatiotemporal correlation within responses, often neglecting the local correlation structure. This oversight can be problematic in applications where local correlations play a significant role, such as temperature control of composite plates. Additionally, these models typically fail to incorporate local patterns within the spatial influence of control variables, an essential aspect considering the location-sensitive nature of control impact. Moreover, in practice, the suboptimal uniform placement of control variables can significantly impact the effectiveness of control strategies under insufficient control resources. To address these issues, we propose a tensor-based feedback control model for locally structured high-dimensional (LSHD) streaming data under limited control capabilities. For system modeling, we employ kernel distributions to capture the local structure within (i) the response autocorrelation and (ii) the spatial impact of location-sensitive control variables. For online control, we develop a dynamic control strategy to optimize controller placement, enhancing control efficiency despite resource constraints. Finally, we validate the effectiveness of our proposed framework through simulations and a case study. [ABSTRACT FROM AUTHOR]

Process modeling is an indispensable tool for establishing a foundation for process optimization and enhancing the quality of products. Analyzing the thermoforming process of polymer matrix composites presupposes the acquisition of accurate thermal histories. This paper introduces a numerical solution based on the finite difference (FD) model to predict the temperature field of angle‐ply composite structures during automated fiber placement (AFP) process along the machining trajectory. The proposed method incorporates three‐dimensional hybrid boundary conditions and considers temperature‐dependent material properties, significantly improving efficiency compared to the finite element (FE) model and overcoming challenges related to complex boundary conditions and anisotropic heat transfer in analytical solutions. Real‐time temperature measurement experiments were conducted to validate predictions, and further a specific temperature control strategy that meets process requirements was explored. In summary, the paper introduces a novel approach to address the temperature field in complex composite structure manufacturing processes. Highlights: A novel 3D finite difference model predicts the temperature field in automated fiber placement.Improved prediction accuracy by managing complex boundary conditions.Effectively handled anisotropic heat transfer in complex composite structures.Superior efficiency over existing numerical methods.Developed a model‐based strategy for optimal temperature control within ±5°C. [ABSTRACT FROM AUTHOR]

Liquid alkaline water electrolysis has gained considerable interest in recent years due to its promising role in an energy sector based on renewable energy sources. Its main advantage is the low investment cost of industrial alkaline water electrolyzers compared to other electrolysis technologies. A challenge remains in developing cost-efficient materials, stable in corrosive electrolytes, and offering competitive cell performance. Although there are many publications in liquid alkaline electrolysis, there is insufficient standardization of experimental conditions and procedures, reference materials, and hardware. As a result, comparability and reproducibility suffer, significantly slowing down research progress. This manuscript presents the initial efforts towards the development of such reference hardware and procedures within the framework of Task 30 Electrolysis in the Technology Collaboration Programme on Advanced Fuel Cells (AFC TCP) of the International Energy Agency (IEA). For this purpose, a homogenized setup including the electrolysis cell, functional materials, experimental conditions, and a test protocol was developed. The protocol and hardware were tested simultaneously at eleven different institutions in Europe and North America. To evaluate the success of this approach, polarization and run-in data were collected and analyzed for comparison, and performance differences were calculated. Significant disparities between the laboratories were observed and some key influence factors were identified: iron content in the electrolyte resulted to be a main source of deviation between experiments, along with temperature control and the conditioning of the cells. The results suggest that additional attention to detailed experimental conditions should be paid to obtain meaningful performance data in future research. [Display omitted] • Alkaline water electrolysis round robin tests were performed at 11 different laboratories. • A harmonized electrolysis cell and testing protocol was developed. • Significant inter-laboratory deviations were observed, up to 610 mV at 1000 mA cm−2. • Iron content in electrolyte and temperature control are key improvement parameters. [ABSTRACT FROM AUTHOR]