Semiclassical transition state theory/master equation kinetics of HO + CO: Performance evaluation

Previously, master equation (ME) simulations using semiclassical transition state theory (SCTST) and high-accuracy extrapolated ab initio thermochemistry (HEAT) predicted rate constants in excellent agreement with published experimental data over a wide range of pressure and temperatures ≳250 K, but the agreement was not as good at lower temperatures. Possible reasons for this reduced performance are investigated by (a) critically evaluating the published experimental data and by investigating; (b) three distinct ME treatments of angular momentum, including one that is exact at the zero- and infinite-pressure limits; (c) a hindered-rotor model for HOCO that implicitly includes the cis- and trans-conformers; (d) possible empirical adjustments of the thermochemistry; (e) possible empirical adjustments to an imaginary frequency controlling tunneling; (f) including or neglecting the prereaction complex PRC1; and (g) its possible bimolecular reactions. Improvements include better approximations to factors in SCTST and using the Hill and van Vleck treatment of angular momentum coupling. Evaluation of literature data does not reveal any specific shortcomings, but the stated uncertainties may be underestimated. All ME treatments give excellent fits to experimental data at T ≥ 250 K, but the discrepancy at T < 250 K persists. Note that each ME model requires individual empirical energy transfer parameters. Thermochemical adjustments were unable to match the experimental H/D kinetic isotope effects. Adjusting an imaginary frequency can achieve good fits, but the adjustments are unacceptably large. Whether PRC1 and its possible bimolecular reactions are included had little effect. We conclude that none of the adjustments is an improvement over the unadjusted theory. Note that only one set of experimental data exists in the regime of the discrepancy with theory, and data for DO + CO are scanty.     

Molecularly engineering polymeric membranes for H2/CO2 separation at 100–300 °C

Over the last two decades, polymers with superior H₂/CO₂ separation properties at 100–300 °C have gathered significant interest for H₂ purification and CO₂ capture. This timely review presents various strategies adopted to molecularly engineer polymers for this application. We first elucidate the Robeson's upper bound at elevated temperatures for H₂/CO₂ separation and the advantages of high-temperature operation (such as improved solubility selectivity and absence of CO₂ plasticization), compared with conventional membrane gas separations at ~35 °C. Second, we describe commercially relevant membranes for the separation and highlight materials with free volumes tuned to discriminate H₂ and CO₂, including functional polymers (such as polybenzimidazole) and engineered polymers by cross-linking, blending, thermal treatment, thermal rearrangement, and carbonization. Third, we succinctly discuss mixed matrix materials containing size-sieving or H₂-sorptive nanofillers with attractive H₂/CO₂ separation properties.     

Activation of α-Fe2O3 for Photoelectrochemical Water Splitting Strongly Enhanced by Low Temperature Annealing in Low Oxygen Containing Ambient

Photoelectrochemical (PEC) water splitting is a promising method for the conversion of solar energy into chemical energy stored in the form of hydrogen. Nanostructured hematite (α-Fe₂O₃) is one of the most attractive materials for a highly efficient charge carrier generation and collection due to its large specific surface area and the short minority carrier diffusion length. In the present work, the PEC water splitting performance of nanostructured α-Fe₂O₃ is investigated which was prepared by anodization followed by annealing in a low oxygen ambient (0.03 % O₂ in Ar). It was found that low oxygen annealing can activate a significant PEC response of α-Fe₂O₃ even at a low temperature of 400 °C and provide an excellent PEC performance compared with classic air annealing. The photocurrent of the α-Fe₂O₃ annealed in the low oxygen at 1.5 V vs. RHE results as 0.5 mA cm⁻², being 20 times higher than that of annealing in air. The obtained results show that the α-Fe₂O₃ annealed in low oxygen contains beneficial defects and promotes the transport of holes; it can be attributed to the improvement of conductivity due to the introduction of suitable oxygen vacancies in the α-Fe₂O₃. Additionally, we demonstrate the photocurrent of α-Fe₂O₃ annealed in low oxygen ambient can be further enhanced by Zn-Co LDH, which is a co-catalyst of oxygen evolution reaction. This indicates low oxygen annealing generates a promising method to obtain an excellent PEC water splitting performance from α-Fe₂O₃ photoanodes.     

室温铁磁性Sr3YCo4O10.5+δ多晶有序化的烧结工艺及电磁性能

采用固相反应法制备了不同烧结温度(950~1 180 ℃)、烧结时间、烧结次数共7种工艺的Sr₃YCo₄O_10.5+δ多晶块材,通过热分析、XRD、SEM确定了有序化相变和最佳烧结工艺(1 180 ℃/24 h+1 180 ℃/24 h),并研究了多晶的电磁性能。结果表明,964 ℃完全晶化的四方相Sr₃YCo₄O_10.5在1 042 ℃吸氧(δ)完成有序化,生成Sr₃YCo₄O_10.5+δ,而1 100 ℃和1 180 ℃烧结的样品均出现(103)、(215)超结构峰,验证了其结构的有序性。块材均呈半导体电输运行为,二次烧结晶格完整性提高,晶粒长大,300 K时电阻率仅为0.06 Ω·cm,居里温度(T_c)~335 K,零场冷曲线(ZFC)上的Hopkinson峰源于低温时被冻结的磁矩随温度升高转向磁场方向,磁化强度在298 K达到最大,随后受热扰动的影响减小。室温铁磁性源于有序结构导致的中自旋或高自旋态Co³⁺的e_g轨道有序。     

Deficiency zero for random reaction networks under a stochastic block model framework

Journal of Mathematical Chemistry - Deficiency zero is an important network structure and has been the focus of many celebrated results within reaction network theory. In our previous paper...     

Review on the Use of Artificial Intelligence to Predict Fire Performance of Construction Materials and Their Flame Retardancy

The evaluation and interpretation of the behavior of construction materials under fire conditions have been complicated. Over the last few years, artificial intelligence (AI) has emerged as a reliable method to tackle this engineering problem. This review summarizes existing studies that applied AI to predict the fire performance of different construction materials (e.g., concrete, steel, timber, and composites). The prediction of the flame retardancy of some structural components such as beams, columns, slabs, and connections by utilizing AI-based models is also discussed. The end of this review offers insights on the advantages, existing challenges, and recommendations for the development of AI techniques used to evaluate the fire performance of construction materials and their flame retardancy. This review offers a comprehensive overview to researchers in the fields of fire engineering and material science, and it encourages them to explore and consider the use of AI in future research projects.     

Efficacy of incorporating PCMs into the commercial wall on the energy-saving annual thermal analysis

Journal of Thermal Analysis and Calorimetry - In this study, the efficacy of incorporating phase change material (PCM) into the building walls on the annual heat transfer reduction is examined....     

General one-loop formulas for $$H\rightarrow f\bar{f}\gamma $$ H → f f ¯ γ and its applications

The European Physical Journal C - Considering supergravity theory is a natural step in the development of gravity models. This paper follows the “algebraic“ path and constructs possible...     

Chitosan hydrogel,as a biological macromolecule-based drug delivery system for exosomes and microvesicles in regenerative medicine: a mini review

Cellulose - Extracellular vesicles are membrane-packed entities that are involved in various physiological and pathological processes. Recently, the role of exosomes and microvesicles in...