Can semi-empirical models describe HCl dissociation in water?

We discuss the failure of commonly used AM1 and PM3 semiempirical methods to correctly describe acid dissociation. We focus our analysis on HCl because of its physicochemical importance and its relevance in atmospheric chemistry. The structure of non-dissociated and dissociated HCl – (H₂O) _n clusters is accounted for. The very bad results obtained with PM3 (and also with AM1) are related to large errors in gas-phase proton affinity of water and gas-phase acidity of HCl. Indeed, estimation of pKa values shows that neither AM1 nor PM3 are able to predict HCl dissociation in liquid water since HCl is found to be a weaker acid than H₃O⁺. We have proposed in previous works a modified PM3 approach (PM3-MAIS) adapted to intermolecular calculations. It is derived from PM3 by reparameterization of the core–core functions using ab initio data. Since parameters for H–Cl and O–Cl core–core interactions were not yet available, we have carried out the corresponding optimization. Application of the PM3-MAIS method to HCl dissociation in HCl–(H₂O) _n clusters leads to a huge improvement over PM3 results. Though the method predicts a slightly overestimated HCl acidity in water environment, the overall agreement with ab initio calculations is very satisfying and justifies efforts to develop new semiempirical methods.     

The dissociation quotients of formic acid in sodium chloride solutions to 200°C

The dissociation quotients of formic acid were measured potentiometrically from 25 to 200°C in NaCl solutions at ionic strengths of 0.1, 0.3 1.0, 3.0, and 5.0 mol-kg^–1. The experiments were carried out in a concentration cell with hydrogen electrodes. The resulting molal acid dissociation quotients for formic acid, as well as a set of infinite dilution literature values and a calorimetrically-determined enthalpy of reaction, were fitted by an empirical equation involving an extended Debye Hückel term and seven adjustable parameters involving functions of temperature and ionic strength. This regressional analysis yielded the following thermodynamic quantities for 25°C: logK=–3.755±0.002, H^o=–0.09±0.15 kJ-mol^–1, S^o=–72.2±0.5 J-K^–1-mol^–1, and C _p ^o =–147±4 J-K^–1-mol^–1. The isocoulombic form of the equilibrium constant is recommended for extrapolation to higher temperatures.     

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.     

Interpretation of Strengthening Mechanism of Densified Wood from Supramolecular Structures

In this study, densified wood was prepared by hot pressing after partial lignin and hemicellulose were removed through alkaline solution cooking. The tensile strength and elastic modulus of densified wood were improved up to 398.5 MPa and 22.5 GPa as compared with the original wood, and the characterization of its supramolecular structures showed that the crystal plane spacing of the densified wood decreased, the crystallite size increased, and the maximum crystallinity (CI) of cellulose increased by 15.05%; outstandingly, the content of O(6)H⋯O(3′) intermolecular H-bonds increased by approximately one-fold at most. It was found that the intermolecular H-bond content was significantly positively correlated with the tensile strength and elastic modulus, and accordingly, their Pearson correlation coefficients were 0.952 (p < 0.01) and 0.822 (p < 0.05), respectively. This work provides a supramolecular explanation for the enhancement of tensile strength of densified wood.     

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.