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。     

纳米氧化镱对熔融石英析晶动力学机制的影响

本文研究引入纳米氧化镱对熔融石英析晶机制及动力学过程的影响.通过X射线衍射仪(XRD)测试结果分析了纳米氧化镱的引入对熔融石英陶瓷析晶率的影响,采用动力学方法分析了纳米氧化镱的引入对熔融石英陶瓷析晶机制的影响,同时探讨了其等温析晶动力学过程.研究表明,熔融石英陶瓷的晶粒向二维兼有一维及三维的方式生长,引入纳米氧化镱的熔...     

Dielectric Properties Investigation of Metal–Insulator–Metal (MIM) Capacitors

This study presents the construction and dielectric properties investigation of atomic-layer-deposition Al₂O₃/TiO₂/HfO₂ dielectric-film-based metal–insulator–metal (MIM) capacitors. The influence of the dielectric layer material and thickness on the performance of MIM capacitors are also systematically investigated. The morphology and surface roughness of dielectric films for different materials and thicknesses are analyzed via atomic force microscopy (AFM). Among them, the 25 nm Al₂O₃-based dielectric capacitor exhibits superior comprehensive electrical performance, including a high capacitance density of 7.89 fF·µm⁻², desirable breakdown voltage and leakage current of about 12 V and 1.4 × 10⁻¹⁰ A·cm⁻², and quadratic voltage coefficient of 303.6 ppm·V⁻². Simultaneously, the fabricated capacitor indicates desirable stability in terms of frequency and bias voltage (at 1 MHz), with the corresponding slight capacitance density variation of about 0.52 fF·µm⁻² and 0.25 fF·µm⁻². Furthermore, the mechanism of the variation in capacitance density and leakage current might be attributed to the Poole–Frenkel emission and charge-trapping effect of the high-k materials. All these results indicate potential applications in integrated passive devices.     

Precise Quantification of Molybdate In Vitro by the FRET-Based Nanosensor ‘MolyProbe’

Molybdenum (Mo) is an essential trace element in all kingdoms of life. Mo is bioavailable as the oxyanion molybdate and gains biological activity in eukaryotes when bound to molybdopterin, forming the molybdenum cofactor. The imbalance of molybdate homeostasis results in growth deficiencies or toxic symptoms within plants, fungi and animals. Recently, fluorescence resonance energy transfer (FRET) methods have emerged, monitoring cellular and subcellular molybdate distribution dynamics using a genetically encoded molybdate-specific FRET nanosensor, named MolyProbe. Here, we show that the MolyProbe system is a fast and reliable in vitro assay for quantitative molybdate determination. We added a Strep-TagII affinity tag to the MolyProbe protein for quick and easy purification. This MolyProbe is highly stable, resistant to freezing and can be stored for several weeks at 4 °C. Furthermore, the molybdate sensitivity of the assay peaked at low nM levels. Additionally, The MolyProbe was applied in vitro for quantitative molybdate determination in cell extracts of the plant Arabidopsis thaliana, the fungus Neurospora crassa and the yeast Saccharomyces cerevisiae. Our results show the functionality of the Arabidopsis thaliana molybdate transporter MOT1.1 and indicate that FRET-based molybdate detection is an excellent tool for measuring bioavailable Mo.