Science and Technology of Advanced Materials最新文献

Polymeric materials can boost their performances by strategically incorporating inorganic substances. Heat dissipators are a representative class of such composite materials, where inorganic fillers and matrix polymers contribute to high thermal conductivity and strong adhesion, respectively, resulting in excellent heat dissipation performance. However, due to the complex interaction between fillers and polymers, even slight differences in structural parameters, e.g. dispersion/aggregation degree of fillers and crosslink density of polymers, may significantly impact material performance, complicating the quality management and guidelines for material developments. Therefore, we introduce pyrolysis mass spectra (MS) as material descriptors. On the basis of these spectra, we construct prediction models using a data-driven approach, specifically focusing on thermal conductivity and adhesion, which are key indicators for heat dissipating performance. Pyrolysis-MS observes thermally decomposable polymers, which occupy only 0.1 volume fraction of the heat dissipators; nevertheless, the physical states of non-decomposable inorganic fillers are implicitly reflected in the pyrolyzed fragment patterns of the matrix polymers. Consequently, pyrolysis-MS provides sufficient information to construct accurate models for predicting heat dissipation performance, simplifying quality management by substituting time-consuming performance evaluations with rapid pyrolysis-MS measurements. Furthermore, we elucidate that higher crosslinking density of the matrix polymers enhances thermal conductivity. This data-driven method promises to streamline the identification of key functional factors in complex composite materials.

The hydrogen evolution reaction (HER) is an important phenomenon in water splitting. Consequently, the development of an active, earth-abundant, and inexpensive HER catalyst is highly desired. MoS₂ has drawn considerable interest as an HER catalyst because it is composed of non-precious metal and exhibits high catalytic activity in the nanosheet form. In this study, size-controlled MoS₂ particles were synthesized by ball milling. The as-prepared samples exhibited significantly enhanced electrochemical and catalytic properties compared to those of pristine bulk MoS₂. Furthermore, the HER activity improved further upon the introduction of graphene into the as-prepared ball-milled samples. In particular, the MoS₂ sample ball-milled for 12 h mixed with graphene exhibited optimal performance, showing an overpotential (160 mV at 10 mA cm^-2) that was ~ 335 mV lower than that of pristine bulk MoS₂. The superior catalytic activity was ascribed to the exposed edge sites, sulfur vacancies, and 1T phase of MoS₂, as well as the noteworthy fortifying effect of the electronically conductive flexible material, graphene. The results provide a promising strategy for its application as an efficient and stable HER catalyst.

This current study investigates the effect of Direct Energy Deposition (DED) process conditions on the properties and microstructure of M300 maraging steel samples. The investigation centers on two key factors: laser power and deposition environment. The microstructure of this tool steel is analyzed by computing the Primary Cellular Arm Spacing. The findings revealed a significant influence of both inert atmosphere and laser power on cooling conditions. These different cooling rates influence the phase content as demonstrated by X-Ray Diffraction and Electron Backscatter Diffraction measurements. It was demonstrated the presence of different content of residual austenite at cell boundaries. These distinct microstructural features caused variations in the hardness values of the printed samples. Furthermore, a direct aging heat treatment was implemented, that was chosen from Differential Scanning Calorimetry measurements results. This heat treatment proves effective in achieving consistent hardness increases and eliminated the differences among samples built in different process conditions. This outcome suggests the possibility of selecting the most economically viable DED parameters for optimal results.