Determination of the Thermal Degradation Kinetic Parameters of Carbon Fibre Reinforced Epoxy Using TG

In this work, a kinetic study on the thermal degradation of carbon fibre reinforced epoxy is presented. The degradation is investigated by means of dynamic thermogravimetric analysis (TG) in air and inert atmosphere at heating rates from 0.5 to 20°C min⁻¹ . Curves obtained by TG in air are quite different from those obtained in nitrogen. A three-step loss is observed during dynamic TG in air while mass loss proceeded as a two step process in nitrogen at fast heating rate. To elucidate this difference, a kinetic analysis is carried on. A kinetic model described by the Kissinger method or by the Ozawa method gives the kinetic parameters of the composite decomposition. Apparent activation energy calculated by Kissinger method in oxidative atmosphere for each step is between 40–50 kJ mol⁻¹ upper than E _a calculated in inert atmosphere. The thermo-oxidative degradation illustrated by Ozawa method shows a stable apparent activation energy (E _a ≈130 kJ mol⁻¹ ) even though the thermal degradation in nitrogen flow presents a maximum E _a for 15% mass loss (E _a ≈60 kJ mol⁻¹ ). This revised version was published online in July 2006 with corrections to the Cover Date.     

Ab initio studies of the protonation of CO,N2 and NO+: Calculation of the minimum energy reaction paths

Ab initio molecular orbital calculations employing a 4-31G basis set have been used to study the minimum energy paths for the formation of HCO⁺, COH⁺, and HCOH²⁺ from CO by protonation. The protonation of N₂ to give NNH⁺ and HNNH²⁺ and of NO⁺ to form HNO²⁺ and NOH²⁺ have also been investigated. All species formed have linear equilibrium geometries and the minimum energy path for approach of the proton is along the line-of-centers of the heavy atoms. Energy barriers to the formation of the various species are given, where appropriate, and changes in geometry, ordering of molecular orbitals and orbital occupancy are discussed.     

动能歧视(KED)-电感耦合等离子体质谱(ICP-MS)法测定贵州沉积型稀土矿中16种稀土元素

贵州沉积型稀土矿主要含有高岭土-锐钛矿石等矿物,存在高含量Si、Al、Fe、Ti、Zr等难溶基体元素,采用高压密闭微波消解法处理难以将其完全溶解,易使测定结果偏低,需再次消解或进一步电热板敞开酸溶处理,方法耗时长,不利于大批量样品检测需求。同时电感耦合等离子体质谱法(ICP-MS)在测定稀土元素时存在基体效应和质谱干扰,影响了检测数据的准确性。本文采用过氧化钠熔融分解样品,熔融物冷却后引入三乙醇胺溶液,在碱性溶液中,大量基体元素与三乙醇胺形成稳定配合物,并与大量溶剂钠盐存于溶液中,稀土元素与Ca、Mg、Sr、Ba等留存于沉淀,经过滤,实现稀土元素与大量基体元素分离,随后沉淀用(1+1)硝酸复溶,并以103Rh和185Re为在线注入内标协同降低基体干扰;启用动能歧视(KED)模式以降低测定过程中潜在的质谱干扰。实验结果表明:高压密闭微波消解法消解液浑浊有残渣,溶矿耗时长,测试结果偏低,碱溶法酸化后溶液清亮透明,稀土元素测定值准确性高;经条件试验,采用10%三乙醇胺溶液提取能较大降低基体干扰;启用KED模式可降低测定过程中的质谱干扰,且准确度优于STD模式;碱溶法方法检出限为0.008μg/g~0.049μg/g,测定下限为0.034μg/g~0.195μg/g,相对标准偏差RSD在0.78%～10.2%之间,相对误差RE在0.0225%~13.5%之间。经实际样品验证,碱熔法较适用于贵州沉积性稀土矿中16种稀土元素的测定。     

Is Bitcoin’s Carbon Footprint Persistent? Multifractal Evidence and Policy Implications

The Bitcoin mining process is energy intensive, which can hamper the much-desired ecological balance. Given that the persistence of high levels of energy consumption of Bitcoin could have permanent policy implications, we examine the presence of long memory in the daily data of the Bitcoin Energy Consumption Index (BECI) (BECI upper bound, BECI lower bound, and BECI average) covering the period 25 February 2017 to 25 January 2022. Employing fractionally integrated GARCH (FIGARCH) and multifractal detrended fluctuation analysis (MFDFA) models to estimate the order of fractional integrating parameter and compute the Hurst exponent, which measures long memory, this study shows that distant series observations are strongly autocorrelated and long memory exists in most cases, although mean-reversion is observed at the first difference of the data series. Such evidence for the profound presence of long memory suggests the suitability of applying permanent policies regarding the use of alternate energy for mining; otherwise, transitory policy would quickly become obsolete. We also suggest the replacement of ‘proof-of-work’ with ‘proof-of-space’ or ‘proof-of-stake’, although with a trade-off (possible security breach) to reduce the carbon footprint, the implementation of direct tax on mining volume, or the mandatory use of carbon credits to restrict the environmental damage.     

Visible Light-Driven Alkyne-Grafted Ethylene-Bridged Azobenzene Chromophores for Photothermal Utilization

Molecular photoswitches are considered to be important candidates in the field of solar energy storage due to their sensitive and reversible bidirectional optical response. Nevertheless, it is still a daunting challenge to design a molecular photoswitch to improve the low solar spectrum utilization and quantum yields while achieving charging and discharging of heat without solvent assistance. Herein, a series of visible-light-driven ethylene-bridged azobenzene (b-Azo) chromophores with different alkyne substituents which can undergo isomerization reactions promoted in both directions by visible light are reported. Their visible light responsiveness improves their solar spectrum utilization while also having high quantum yields. In addition, as the compounds are liquids, there is no need to dissolve the compounds in order to exploit this switching. The photoisomerization of b-Azo can be adjusted by alkyne-related substituents, and hexyne-substituted b-Azo is able to store and release photothermal energy with a high density of 106.1 J·g⁻¹, and can achieve a temperature increase of 1.8 °C at a low temperature of −1 °C.     

Joint Optimization of Control Strategy and Energy Consumption for Energy Harvesting WSAN

With the rapid development of wireless sensor technology, recent progress in wireless sensor and actuator networks (WSANs) with energy harvesting provide the possibility for various real-time applications. Meanwhile, extensive research activities are carried out in the fields of efficient energy allocation and control strategy design. However, the joint design considering physical plant control, energy harvesting, and consumption is rarely concerned in existing works. In this paper, in order to enhance system control stability and promote quality of service for the WSAN energy efficiency, a novel three-step joint optimization algorithm is proposed through control strategy and energy management analysis. First, the optimal sampling interval can be obtained based on energy harvesting, consumption, and remaining conditions. Then, the control gain for each sampling interval is derived by using a backward iteration. Finally, the optimal control strategy is determined as a linear function of the current plant states and previous control strategies. The application of UAV formation flight system demonstrates that better system performance and control stability can be achieved by the proposed joint optimization design for all poor, sufficient, and general energy harvesting scenarios.     

Optimal Energy-Storage Configuration for Microgrids Based on SOH Estimation and Deep Q-Network

Energy storage is an important adjustment method to improve the economy and reliability of a power system. Due to the complexity of the coupling relationship of elements such as the power source, load, and energy storage in the microgrid, there are problems of insufficient performance in terms of economic operation and efficient dispatching. In view of this, this paper proposes an energy storage configuration optimization model based on reinforcement learning and battery state of health assessment. Firstly, a quantitative assessment of battery health life loss based on deep learning was performed. Secondly, on the basis of considering comprehensive energy complementarity, a two-layer optimal configuration model was designed to optimize the capacity configuration and dispatch operation. Finally, the feasibility of the proposed method in microgrid energy storage planning and operation was verified by experimentation. By integrating reinforcement learning and traditional optimization methods, the proposed method did not rely on the accurate prediction of the power supply and load and can make decisions based only on the real-time information of the microgrid. In this paper, the advantages and disadvantages of the proposed method and existing methods were analyzed, and the results show that the proposed method can effectively improve the performance of dynamic planning for energy storage in microgrids.     

氦原子及类氦离子基态的二参数变分法研究

提出了一种计算氦原子及类氦离子基态能量和波函数的二参数变分法,包括试探波函数的设计和基态能量表达式的推导,并用Mathematica 5.0软件的优化计算功能方便快捷地计算出基态能量,将计算结果与实验结果和部分所列文献的结果进行对比.结果表明,本文所得精度较高,变分参数个数较少.同时强调交换对称性和量子态的交缠在双电子原子体系问题中的重要性.     

Feature of Low-Lying States of a Planar Three-Boson System

The energy spectrum of the low-lying states of a system of three charged bosons confined in a two-dimensional harmonic trap is investigated as a function of the confinement strength ω₀ by means of the exact diagonalization of the Hamiltonian. The important feature of the low-lying states of three charged bosons in two-dimensional space is obtained via an analysis of the energy spectrum.     

Te溶剂Bridgman法CdMnTe晶体核辐射探测器的制备和表征

碲锰镉(CdMnTe)作为性能优异的室温核辐射探测器材料,可用于环境监测和工业无损检测领域。本文中采用Te溶剂Bridgman法生长In掺杂Cd_0.9Mn_0.1Te晶体,制备成10 mm×10 mm×2 mm大小的室温单平面探测器,研究了该探测器对²⁴¹Am@59.5 keV γ射线源的能谱响应。通过表征红外透过率、电阻率以及探测器能谱响应等参数,综合评定了探测器用CdMnTe晶体的质量、电学和探测器性能。结果表明,晶片的红外透过率均在55%以上,最好可达到60%。采用湿法钝化,100 V偏压下的漏电流由钝化前的9.48 nA降为钝化后的7.90 nA,钝化后的电阻率为2.832×10¹⁰ Ω·cm。在-400 V反向偏压下,CdMnTe探测器对²⁴¹Am@59.5 keV γ射线源的能量分辨率在钝化前后分别为13.53%和12.51%,钝化后的电子迁移率寿命积为1.049×10^-3 cm²/V。研究了探测器的能量分辨率随电压的变化特性,当偏压≤400 V时,探测器的能量分辨率主要由载流子的收集效率决定,而当偏压>400 V时,能量分辨率由漏电流决定。本文研究结果表明,Te溶剂Bridgman法生长的CdMnTe晶体质量较好,电阻率和电子迁移率寿命积满足探测器制备需求。