类球形低硫磷酸铁的制备技术研究

磷酸铁（FePO₄）是锂电池正极材料磷酸铁锂（LiFePO₄）的核心前驱体,FePO₄形貌及硫含量对合成的LiFePO₄材料性能有重要影响。为得到类球形低硫FePO₄产品,在传统液相沉淀法技术基础上做了改进优化,添加十六烷基三甲基溴化铵（CTAB）作为形貌助剂提高产品球形度,添加氨水作为配体形成磷酸铁铵配合物改善结晶过程,降低产品硫含量。结果表明：所制备的FePO₄产品硫质量分数低,达到2.6×10 ^-5,形貌为均一的微米类球形颗粒,D₅₀=11.4 μm,振实密度达到1.22 g/cm ³,有望成为制备高压实密度LiFePO₄材料的核心前驱体。     

模态描述逻辑MALC模型的几个代数性质

本文定义了MALC模型间的同构、同态等关系,并讨论了合式公式在这些关系下的不变性等代数性质。最后定义了MALC的拓扑语义及基于拓扑语义互模拟,得到MALC的合式公式在拓扑互模拟下具有不变性。     

随机正则(k,r)-SAT问题的可满足临界

研究k-SAT问题实例中每个变元恰好出现r=2s次,且每个变元对应的正、负文字都出现s次的严格随机正则（k,r）-SAT问题.通过构造一个特殊的独立随机实验,结合一阶矩方法,给出了严格随机正则（k,r）-SAT问题可满足临界值的上界.由于严格正则情形与正则情形的可满足临界值近似相等,因此得到了随机正则（k,r）-SAT问题可满足临界值的新上界.该上界不仅小于当前已有的随机正则（k,r）-SAT问题的可满足临界值上界,而且还小于一般的随机k-SAT问题的可满足临界值.因此,这也从理论上解释了在相变点处的随机正则（k,r）-SAT问题实例通常比在相应相变点处同规模的随机k-SAT问题实例更难满足的原因.最后,数值分析结果验证了所给上界的正确性.     

Analyses and improvement of a broadcasting multiple blind signature scheme based on quantum GHZ entanglement

A broadcasting multiple blind signature scheme based on quantum GHZ entanglement has been presented recently. It is said that the scheme’s unconditional security is guaranteed by adopting quantum key preparation, quantum encryption algorithm and quantum entanglement. In this paper, we prove that each signatory can get the signed message just by an intercept–resend attack. Then, we show there still exist some participant attacks and external attacks. Specifically, we verify the message sender Alice can impersonate each signatory to sign the message at will, and so is the signature collector Charlie. Also, we demonstrate that the receiver Bob can forge the signature successfully, and with respect to the external attacks, the eavesdropper Eve can modify the signature at random. Besides, we discover Eve can change the signed message at random, and Eve can impersonate Alice as the message sender without being discovered. In particular, we propose an improved scheme based on the original one and show that it is secure against not only the attacks mentioned above but also some collusion attacks.     

金属酞菁/卟啉分子电催化CO2还原的研究进展

大气中日益增加的CO₂浓度导致了气候变化等环境问题。将CO₂催化转化为有价值的化学品具有重要意义。利用太阳能、风能等可再生能源产生的电能,通过电化学方法将CO₂还原转化为有价值的碳基化合物是最具有应用前景的方式。分子催化剂具有明确的结构和清晰的活性位点,可实现基于机理的性能优化。综述了近年来金属酞菁/卟啉分子在电催化CO₂还原为CO的实验和理论方面的最新研究进展。首先,介绍了金属酞菁/卟啉分子电催化CO₂还原为CO的详细机理。然后,重点介绍了如何通过分子分散和配体修饰提升金属酞菁/卟啉分子电催化CO₂还原为CO的活性和选择性。最后,讨论了金属酞菁/卟啉分子电催化CO₂还原存在的挑战及其可能的解决方案。     

磷矿对牙舟陶土煅烧性能的影响研究

牙舟陶在陶瓷业界具有举足轻重的地位,陶土对牙舟陶性能具有重要的影响。为加强对牙舟陶的研究,采用化学分析法、激光粒度仪、X射线衍射仪、综合热分析仪、数显白度仪等测试手段对牙舟陶土的化学组成、粒度分布、晶相组成、热性能及白度进行了检测。结果表明：牙舟陶土主要由石英和珍珠石组成,石英质量分数为59.34%、珍珠石质量分数为34.78%。牙舟陶土颗粒分布广泛,粒径小于6.5 μm的颗粒质量分数达到58.67%,粒径越小石英含量越低。在此基础上,结合贵州黔南丰富的磷矿资源,研究加入磷矿后牙舟陶土在煅烧过程中白度、硬度及物相组成的变化规律。研究表明：牙舟陶土的白度随着温度的升高先增大后减小,在1 100 ℃时达到最大值45.5%;加入磷矿组分后,在1 100 ℃时牙舟陶土的白度增加至54%,且煅烧时固熔体形成温度下降、烧结温度降低,并伴随钙长石矿物的产生。     

Rapid Determination of Volatile Compounds in <Emphasis Type="Italic">Gymnotheca involucrata</Emphasis> Pei. by MAE–HS-SPME Followed by GC–MS

Microwave-assisted extraction (MAE) and headspace solid-phase microextraction (HS-SPME) followed by gas chromatography–mass spectrometry (GC–MS) was developed for the rapid determination of the volatile chemical compositions of Gymnotheca involucrata Pei. The experimental parameters of the MAE–HS-SPME were optimized by orthogonal experimental design. The results indicated that the optimal experimental parameters for determination of the volatile constituents of Gymnotheca involucrata Pei. were: sample weight 2.0 g, microwave power of 400 W and irradiation time of 3.0 min. Employing these conditions, 106 volatile constituents in the dry stems and 103 volatile constituents in the dry leaves of Gymnotheca involucrata Pei. were separated and identified, amounting to 93.58 and 98.53% of the total peak areas, respectively. The major components found in the oil extracted from the stems and leaves were nerolidol (16.57, 17.50%), sabinene (3.35, 3.65%), cis, cis, cis-1,1,4,8-tetramethyl-4,7,10-cycloundecatriene (4.64, 5.03%), α-copaene-8-ol (6.01, 6.33%) and phytol (2.92, 3.03%), respectively. Relative standard deviation (RSD) values of <9.0% showed that the MAE–HS-SPME method followed by GC–MS has good precision. The experimental results demonstrated that this solvent-free method is simple, time-efficient, and is a potentially suitable analytical tool for the determination of volatile compounds from vegetative and other materials.     

Improved fish migration optimization method to identify PEMFC parameters

In a worldwide environment context where the emergency need to decrease pollutant emissions is an important issue, the research for solutions is increasing. Fuel cell technology is anticipated to become a practicable approach for solving the problem of pollution due to its environmentally friendly characteristics. In this work, a novel problem formulation is suggested for the efficient recognition of PEMFC parameters which the solving is by using the Improved Fish Migration Optimizer (IFMO) technique. After coding the steps of the algorithm in MATLAB, the objective function is resolved for the fuel cell. Comprehensive simulations evaluate the formulation performance with the suggested and traditional objective functions; then, the outcomes are compared. To confirm the suggested formulation ascendancy compared to the traditional curve-fitting method, a complete assessment based on convergence rate, the value of the objective function, and the value of absolute voltage error are performed. The achieved value of the objective function, absolute voltage error, and average time of computation is 0.005, 0.4, and 1.63, respectively. Environmentally, the combustion of hydrogen and its use in PEMFC produce no carbon dioxide.     

A generalized method for the inherent energy performance modeling of machine tools

Machine tools (MTs), as the key equipment of manufacturing systems, have enormous quantities and consume a great amount of energy. However, the diversity of both machines and their energy consumption properties make it difficult to transfer the energy-saving knowledge and services among different MT. To facilitate the initialization configuration of energy-saving services, the inherent energy performance (IEP) is investigated to describe the differences in energy consumption among MTs, and a generalized method for modeling the IEP of MT and its electrical subsystems is proposed. Three key enablers, including generalized experimental design rules, automatic coding, and data processing algorithms, are presented and integrated into a supporting system to reduce the modeling efforts and knowledge requirements. Case studies of an offline manufacturing scenario and an Internet of Things (IoT)-enabled manufacturing scenario were carried out to verify the effectiveness and convenience of the proposed method. The results show that the proposed method can provide essential modeling support for large-scale energy-saving service configurations and energy-efficient MT development.