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Crystallisation of water in a series of precious opal samples with opal-A and opal-CT morphologies has been characterised using low-temperature differential scanning calorimetry (DSC) and temperature-dependent terahertz/far-infrared (THz/Far-IR) spectroscopy. The melting temperature for the crystallisable water in the opals was observed to be depressed reflecting a microporous environment and was found to be consistent for both DSC and THz spectroscopy. Based on melt temperature depression, the size range of the pores for the opal-CT was estimated to be in the range 3–6 nm while for opal-A the range was 4 to >50 nm, indicating differing microstructures between opal-A and -CT. The THz/Far-IR spectroscopy indicated the presence of both crystalline and amorphous ice on solidification of the water, although phase identification of the crystalline ice was not possible. Notably, to the authors knowledge, this paper represents the first use of THz/Far-IR spectroscopy in the temperature-dependent characterisation of water and ice encapsulated in micropores.

Temperature segregation during the paving of asphalt pavements is one of the causes of asphalt pavement distress. Therefore, controlling the paving temperature is crucial in the construction of asphalt pavements. To quickly evaluate the road performance of asphalt mixtures during paving, in this work, we used unmanned aerial vehicle infrared thermal imaging technology to monitor the construction work. By analyzing the temperature distribution at the paving site, and conducting laboratory tests, the relationship between the melt temperature, high-temperature stability, and water stability of the asphalt mix was assessed. The results showed that the optimal temperature measurement height for an unmanned aerial vehicle (UAV) with an infrared thermal imager was 7–8 m. By coring the representative temperature points on the construction site and then conducting a Hamburg wheel tracking (HWT) test, the test results were verified through the laboratory test results in order to establish a prediction model for the melt temperature and high-temperature stability of y = 10.73e0.03x + 1415.78, where the predictive model for the melt temperature and water was y = −19.18e−0.02x + 98.03. The results showed that using laboratory tests combined with UAV infrared thermography could quickly and accurately predict the road performance of asphalt mixtures during paving. We hope that more extensive evaluations of the roadworthiness of asphalt mixtures using paving temperatures will provide reference recommendations in the future.

Highly reliable and accurate melt temperature measurements in the barrel are necessary for stable injection molding. Conventional sheath-type thermocouples are insufficiently responsive for measuring melt temperatures during molding. Herein, machine learning models were built to predict the melt temperature after plasticizing. To supply reliably labeled melt temperatures to the models, an optimized temperature sensor was developed. Based on measured high-quality temperature data, three machine learning models were built. The first model accepted process setting parameters as inputs and was built for comparisons with previous models. The second model accepted additional measured process parameters related to material energy flow during plasticizing. Finally, the third model included the specific heat and part weights reflecting the material energy, in addition to the features of the second model. Thus, the third model outperformed the others, and its loss decreased by more than 70%. Meanwhile, the coefficient of determination increased by about 0.5 more than those of the first model. To reduce the dataset size for new materials, a transfer learning model was built using the third model, which showed a high prediction performance and reliability with a smaller dataset. Additionally, the reliability of the input features to the machine learning models were evaluated by shapley additive explanations (SHAP) analysis.

A method for measuring the temperature of the silicon melt during plasma-chemical electron-beam refining is proposed. The method is based on measuring the radiation intensity from the melt in the infrared range and comparing it with the temperature. It is established that changing the refining conditions, in particular, the electron beam current allows a controlled change in the temperature refined silicon from 1500 K to 2600 K.

Au-20Sn (mass fraction) eutectic alloy is a key lead-free solder material for high reliability microelectronics and optoelectronics packaging. The refinement of initial solidification structure can improved the processing performance of Au-20Sn alloy. This paper reported the research progresses on refining solidification structure of Au-20Sn alloy in our research group. The results indicated that the solidification structure of alloy can be effectively refined by rapid solidification with the increasing of cooling rate. The solidification structure can also be refined by incubated nucleation treatment with Au or Sn or by proper melt temperature treatment. The refinement mechanisms of solidification structure by the three types of solidification methods were thoroughly discussed.

De novo enzyme design has sought to introduce active sites and substrate-binding pockets that are predicted to catalyse a reaction of interest into geometrically compatible native scaffolds 1 , 2 , but has been limited by a lack of suitable protein structures and the complexity of native protein sequence–structure relationships. Here we describe a deep-learning-based ‘family-wide hallucination’ approach that generates large numbers of idealized protein structures containing diverse pocket shapes and designed sequences that encode them. We use these scaffolds to design artificial luciferases that selectively catalyse the oxidative chemiluminescence of the synthetic luciferin substrates diphenylterazine 3 and 2-deoxycoelenterazine. The designed active sites position an arginine guanidinium group adjacent to an anion that develops during the reaction in a binding pocket with high shape complementarity. For both luciferin substrates, we obtain designed luciferases with high selectivity; the most active of these is a small (13.9 kDa) and thermostable (with a melting temperature higher than 95 °C) enzyme that has a catalytic efficiency on diphenylterazine ( k cat / K m  = 10 6  M −1  s −1 ) comparable to that of native luciferases, but a much higher substrate specificity. The creation of highly active and specific biocatalysts from scratch with broad applications in biomedicine is a key milestone for computational enzyme design, and our approach should enable generation of a wide range of luciferases and other enzymes. A deep-learning-based strategy is used to design artificial luciferases that catalyse the oxidative chemiluminescence of diphenylterazine with high substrate specificity and catalytic efficiency.

Metals that are active catalysts for methane (Ni, Pt, Pd), when dissolved in inactive low–melting temperature metals (In, Ga, Sn, Pb), produce stable molten metal alloy catalysts for pyrolysis of methane into hydrogen and carbon. All solid catalysts previously used for this reaction have been deactivated by carbon deposition. In the molten alloy system, the insoluble carbon floats to the surface where it can be skimmed off. A 27% Ni–73% Bi alloy achieved 95% methane conversion at 1065°C in a 1.1-meter bubble column and produced pure hydrogen without CO₂ or other by-products. Calculations show that the active metals in the molten alloys are atomically dispersed and negatively charged. There is a correlation between the amount of charge on the atoms and their catalytic activity.

Ziegler-Natta and Metallocene Catalysis isotactic polypropylene with different chemical defects were isothermally crystallized at various crystallization temperatures. The crystal thickness and their corresponding melting behavior were studied using small angle X-ray scattering, atomic force microscopy, optical microscopy, and differential scanning calorimetry. The equilibrium melt temperature of the samples was calculated from the Hofmann-Weeks extrapolation for the supercooling. Two lamellar populations were distinctly observed in all cases during the crystallization process. Relatively thicker and stable lamellar crystals which melt at higher temperatures were observed with lowering the supercooling and found catalysis dependence in these crystals. During melting, no significant recrystallization of the samples has been detected for higher crystallization temperature where recrystallization processes enhance the lamellae thickness. The melting of the crystals has found strong dependence with the crystallization temperatures, the catalysis process and the nature of the defects present in the isotactic polypropylene. The increase of the crystal lamellae thickness and their melting temperature might be presumably related with the chain folding mechanism as well as the stability of the crystals formed during the isothermal crystallization process. A combined plot of SAXS and DSC results is demonstrated for the equilibrium melting temperature followed by critical analysis of the results.

Single-atom metal catalysts have sparked tremendous attention, but direct transformation of cheap and easily obtainable bulk metal oxide into single atoms is still a great challenge. Here we report a facile and versatile gas-transport strategy to synthesize isolated single-atom copper sites (Cu ISAS/NC) catalyst at gram levels. Commercial copper (I) oxide powder is sublimated as mobile vapor at nearly melting temperature (1500 K) and subsequently can be trapped and reduced by the defect-rich nitrogen-doped carbon (NC), forming the isolated copper sites catalyst. Strikingly, this thermally stable Cu ISAS/NC, which is obtained above 1270 K, delivers excellent oxygen reduction performance possessing a recorded half-wave potential of 0.92 V vs RHE among other Cu-based electrocatalysts. By varying metal oxide precursors, we demonstrate the universal synthesis of different metal single atoms anchored on NC materials (M ISAS/NC, where M refers to Mo and Sn). This strategy is readily scalable and the as-prepared sintering-resistant M ISAS/NC catalysts hold great potential in high-temperature applications. Single-atom catalysts attract lots of attention, but direct transformation of bulk metal oxide into single atoms remains challenging. Here the authors report a gas-transport route to transform monolithic copper (I) oxide into copper single-atoms catalyst with a high activity for oxygen reduction.

Recent advances in two-dimensional semiconductors, particularly molybdenum disulfide (MoS 2 ), have enabled the fabrication of flexible electronic devices with outstanding mechanical flexibility. Previous approaches typically involved the synthesis of MoS 2 on a rigid substrate at a high temperature followed by the transfer to a flexible substrate onto which the device is fabricated. A recurring drawback with this methodology is the fact that flexible substrates have a lower melting temperature than the MoS 2 growth process, and that the transfer process degrades the electronic properties of MoS 2 . Here we report a strategy for directly synthesizing high-quality and high-crystallinity MoS 2 monolayers on polymers and ultrathin glass substrates (thickness ~30 µm) at ~150 °C using metal–organic chemical vapour deposition. By avoiding the transfer process, the MoS 2 quality is preserved. On flexible field-effect transistors, we achieve a mobility of 9.1 cm 2  V −1  s −1 and a positive threshold voltage of +5 V, which is essential for reducing device power consumption. Moreover, under bending conditions, our logic circuits exhibit stable operation while phototransistors can detect light over a wide range of wavelengths from 405 nm to 904 nm. Using metal–organic chemical vapour deposition, high-crystallinity MoS 2 monolayers are grown directly on polymers and thin glass substrates at about 150 °C, thus avoiding any transfer process, preserving the electronic properties of MoS 2 .