Wavelength-dependent photoactivity of ZnxCd1−xS and ZnCo2O4/ZnxCd1−xS for H2 and H2O2 production

Zinc cadmium sulfide (Zn_xCd_1?xS) is a good photocatalyst for hydrogen evolution reaction (HER), but an optimum x (x_m) at which a maximum HER rate is reached varies from one report to another. In this work, we examine the effect of light wavelength, not only for the HER to H₂ in the presence of Na₂S and Na₂SO₃, but also for oxygen reduction reaction (ORR) without addition of any sacrifices. For the HER under a 365 and 420 nm LED lamp, the x_m were 0.9 and 0.7, respectively. For the HER under a 330 and 395–515 nm cut-off xenon lamp, the x_m were 0.7 and 0.5, respectively. For the ORR under a 420 nm cut-off halogen lamp, a maximum production of H₂O₂ was observed at x = 0.3. Furthermore, after 4% ZnCo₂O₄ loading, Zn_xCd_1?xS had an increased activity and stability, either for the HER or for the ORR. Through a (photo)electrochemical measurement, it is proposed that the photocatalytic activity of Zn_xCd_1?xS is determined by its light absorptivity and electron reactivity. The improved performance of n-type Zn_xCd_1?xS by p-type ZnCo₂O₄ is due to formation of a p-n junction, promoting the HER (ORR) on Zn_xCd_1?xS, and the sulfide (water) oxidation on ZnCo₂O₄. This work highlights that Zn_xCd_1-xS is a promising photocatalyst for H₂ and H₂O₂ production, respectively.     

Lanthanide doped fluorosilicate glass-ceramics:A review on experimental and theoretical progresses

Significant developments have been made in the past few decades for lanthanide(Ln)ions doped fluorosilicate glass-ceramics(Flusi-GCs).As novel generation of luminescence materials with a wide range of applications,Flusi-GCs as a single host combine the advantages of glass and ceramics/crystals as well as fluorides and silicates.In this review,the chemical design principles and experimental procedures of Flusi-GCs are summarized in detail.Flusi-GCs are categorized as those containing PbxCd_1-xF₂,RF₃(R=Y,La,Gd),MF₂(M=Ca,Sr,Ba),xMF₂-yRF₃(R=Y,La-Lu),mAF-nRF₃(A=Li,Na,K),KTF₃(T=Zn,Mn)and K2 SiF6 nanocrystals(NCs).Theoretical breakthroughs mainly by molecular dynamic(MD)simulation have been recapitulated as efficient routes for composition-design,nano-crystallization-prediction,and performance-optimization of Flusi-GCs containing target fluoride NCs.Essential research progresses pertaining photonic applications have been made in random lasers,communication amplifiers,optical fibers,spectral converters,white light-emitting-diodes(WLEDs),and thermal sensors.In the end,we propose three future research directions for Flusi-GCs.     

A Highly Sensitive,Reversible, and Bidirectional Humidity Actuator by Calcium Carbonate Ionic Oligomers Incorporated Poly(Vinylidene Fluoride)

Sensitivity and multi-directional motivation are major two factors for developing optimized humidity-response materials, which are promising for sensing, energy production, etc. Organic functional groups are commonly used as the water sensitive units through hydrogen bond interactions with water molecules in actuators. The multi-coordination ability of inorganic ions implies that the inorganic ionic compounds are potentially superior water sensitive units. However, the particle forms of inorganic ionic compounds produced by classical nucleation limit the number of exposed ions to interact with water. Recent progress on the inorganic ionic oligomers has broken through the limitation of classical nucleation, and realized the molecular-scaled incorporation of inorganic ionic compounds into an organic matrix. Here, the incorporation of hydrophilic calcium carbonate ionic oligomers into hydrophobic poly(vinylidene fluoride) (PVDF) is demonstrated. The ultra-small calcium carbonate oligomers within a PVDF film endow it with an ultra-sensitive, reversible, and bidirectional response. The motivation ability is superior to other bidirectional humidity-actuators at present, which realizes self-motivation on an ice surface, converting the chemical potential energy of the humidity gradient from ice to kinetic energy.     

Digital twin-based analysis of volumetric error mapping procedures

The evaluation of the volumetric accuracy of a machine tool is an open challenge in the industry, and a wide variety of technical solutions are available in the market and at research level. All solutions have advantages and disadvantages concerning which errors can be measured, the achievable uncertainty, the ease of implementation, possibility of machine integration and automation, the equipment cost and the machine occupation time, and it is not always straightforward which option to choose for each application. The need to ensure accuracy during the whole lifetime of the machine and the availability of monitoring systems developed following the Industry 4.0 trend are pushing the development of measurement systems that can be integrated in the machine to perform semi-automatic verification procedures that can be performed frequently by the machine user to monitor the condition of the machine. Calibrated artefact based calibration and verification solutions have an advantage in this field over laser based solutions in terms of cost and feasibility of machine integration, but they need to be optimized for each machine and customer requirements to achieve the required calibration uncertainty and minimize machine occupation time.This paper introduces a digital twin-based methodology to simulate all relevant effects in an artefact-based machine tool calibration procedure, from the machine itself with its expected error ranges, to the artefact geometry and uncertainty, artefact positions in the workspace, probe uncertainty, compensation model, etc. By parameterizing all relevant variables in the design of the calibration procedure, this simulation methodology can be used to analyse the effect of each design variable on the error mapping uncertainty, which is of great help in adapting the procedure to each specific machine and user requirements. The simulation methodology and the analysis possibilities are illustrated by applying it on a 3-axis milling machine tool.     

High performance H2 sensor based on rGO-wrapped SnO2–Pd porous hollow spheres

Hydrogen (H₂) sensors based on metal oxide semiconductors (MOS) are promising for many applications such as a rocket propellant, industrial gas and the safety of storage. However, poor selectivity at low analyte concentrations, and independent response on high humidity limit the practical applications. Herein, we designed rGO-wrapped SnO₂–Pd porous hollow spheres composite (SnO₂–Pd@rGO) for high performance H₂ sensor. The porous hollow structure was from the carbon sphere template. The rGO wrapping was via self-assembly of GO on SnO₂-based spheres with subsequent thermal reduction in H₂ ambient. This sensor exhibited excellently selective H₂ sensing performances at 390 °C, linear response over a broad concentration range (0.1–1000 ppm) with recovery time of only 3 s, a high response of ～8 to 0.1 ppm H₂ in a minute, and acceptable stability under high humidity conditions (e. g. 80%). The calculated detection limit of 16.5 ppb opened up the possibility of trace H₂ monitoring. Furthermore, this sensor demonstrated certain response to H₂ at the minimum concentration of 50 ppm at 130 °C. These performances mainly benefited from the special hollow porous structure with abundant heterojunctions, the catalysis of the doped-PdO_x, the relative hydrophobic surface from rGO, and the deoxygenation after H₂ reduction.     

Gaussian process regression approach for robust design and yield enhancement of self-assembled nanostructures

Self-assembled nanostructures are increasingly used for nanoelectronic and optoelectronic applications due to their high surface area to volume ratio and their ability to break traditional lithography limits. However, they suffer due to poor yield and repeatability as the growth process is often not well studied or optimized. Gaussian process regression (GPR) is a machine learning technique that can be used for both regression and classification purpose. In the GPR framework, a probability measure is defined according to one prior belief about the response surface and the Bayesian rule is applied to combine the observations with prior beliefs to form a posterior distribution of the response surface, which is known as the “surrogate model”. We propose here the use of GPR as an effective statistical tool to optimize the growth conditions of nanostructures so as to improve their yield, controllability and repeatability ensuring at the same time that the yield is not affected by process variations at the identified optimum process conditions. In effect, we are proposing a design for reliability and robust design strategy for optimization of self-assembled nanostructure growth. We present here a case study of cadmium selenide nanostructures making use of an extensive design of experiment result (available open source) to illustrate the proposed methodology. The prediction accuracy of GPR is compared with two other commonly used statistical models → binomial and multinomial logistic regression. The use of the GPR method resulted in much better accuracy of probabilistic prediction of the different nanostructures with fewer fitting parameters than the logistic regression method.     

Synthesis of Ionic Ultramicroporous Polymers for Selective Separation of Acetylene from Ethylene

The design of highly stable and efficient porous materials is essential for developing breakthrough hydrocarbon separation methods based on physisorption to replace currently used energy-intensive distillation/absorption technologies. Efforts to develop advanced porous materials such as zeolites, coordination frameworks, and organic polymers have met with limited success. Here, a new class of ionic ultramicroporous polymers (IUPs) with high-density inorganic anions and narrowly distributed ultramicroporosity is reported, which are synthesized by a facile free-radical polymerization using branched and amphiphilic ionic compounds as reactive monomers. A covalent and ionic dual-crosslinking strategy is proposed to manipulate the pore structure of amorphous polymers at the ultramicroporous scale. The IUPs exhibit exceptional selectivity (286.1–474.4) for separating acetylene from ethylene along with high thermal and water stability, collaboratively demonstrated by gas adsorption isotherms and experimental breakthrough curves. Modeling studies unveil the specific binding sites for acetylene capture as well as the interconnected ultramicroporosity for size sieving. The porosity-engineering protocol used in this work can also be extended to the design of other ultramicroporous materials for the challenging separation of other key gas constituents.     

Effect of nano-vanadium nitride on microstructure and properties of sintered Fe-Cu-based diamond composites

With FeCu₃₀ pre-alloy powder as the main component of the bond, a new type of nano‑vanadium nitride (VN) additive with different concentrations was introduced into Fe-Cu-based diamond composites to investigate the effect of nano-VN on the microstructure and properties of Fe-Cu-based diamond composites. The hardness, relative density, bending strength and wear loss weight of the fabricated specimens were tested, and then the fracture surfaces and worn surfaces of those specimens were analyzed using scanning electron microscopy (SEM) and energy dispersive spectrometry (EDS). The results show that the Fe-Cu-based diamond composites with nano-VN addition exhibited an improvement in the mechanical properties, plasticity and wear resistance, which can be attributed to the dispersion strengthening and grain refinement caused by nano-VN. And the nano-VN can also activate sintering, which can significantly improve the wettability of the binder to diamonds, resulting in more binder elements wetting and diffusion on the diamond surface during the sintering process. Besides, the diamond composites showed the best properties with the addition of 2% nano-VN. That is, the bending strength and the HRB hardness of the diamond composites increased by 25% and 20%, respectively, and the wear resistance of the matrix and holding force coefficient of the matrix to diamond were improved significantly. But an excessive amount of nano-VN was detrimental to the mechanical properties of Fe-Cu-based diamond composites.     

Elasticity solution for the casing under linear crustal stress

The integrity of the casing is crucial for oil and gas well. Based on stress function method, a three-dimensional model of the casing-cement sheath-formation system subjected to linear crustal stress is proposed. And then an analytical solution of the model was obtained. In the process of calculation, the casing and cement sheath are simplified as the perfect cylinder. The cement sheath is closely bonded with the casing and formation. The formation is considered to be an isotropic material without the layer-block structure. And the crustal stress is assumed to be linearly increasing with the depth of the well. The analytical solution strictly meets the stress and displacement continuity condition and boundary condition, and exhibits good agreement with finite element method. The results imply that an analytical method to capture the stress and displacement field of the casing under linear crustal stress along the axis is presented. Next, a benchmark for numerical and approximate solutions is provided. In addition, a new idea about solving the casing under the non-linear loads along the axis in some special stratum (such as heterogeneity stratum, salt rock) is proposed. Finally, our understanding for the casing under complex loads will be deepened.