Enhance cycling performance of LiMn2O4 cathode by Sr2+ and Cr3+ doping

Spinel LiSr_0·1Cr_0·1Mn_1·8O₄ was synthesised by high temperature solid state method in order to enhance the electrochemical performance. The LiSr_0·1Cr_0·1Mn_1·8O₄ (LSCMO) materials were characterised by X-ray diffraction (XRD), scanning electron microscopy (SEM) and electrochemical tests. The XRD and SEM studies confirm that LSCMO had spinel crystal structure with a space group of Fd3m, and the particle of LSCMO shows irregular shape. The cyclic voltammetry data illustrated that the heavy current charge–discharge performance of LMO was improved by Sr²⁺ and Cr³⁺ doping. The galvanostatic charge–discharge of LSCMO cathode materials was measured at 1, 5, 10 and 20 C. The results indicated that LSCMO improved the capacity retention.     

An overview on fault diagnosis and nature-inspired optimal control of industrial process applications

Fault detection, isolation and optimal control have long been applied to industry. These techniques have proven various successful theoretical results and industrial applications. Fault diagnosis is considered as the merge of fault detection (that indicates if there is a fault) and fault isolation (that determines where the fault is), and it has important effects on the operation of complex dynamical systems specific to modern industry applications such as industrial electronics, business management systems, energy, and public sectors. Since the resources are always limited in real-world industrial applications, the solutions to optimally use them under various constraints are of high actuality. In this context, the optimal tuning of linear and nonlinear controllers is a systematic way to meet the performance specifications expressed as optimization problems that target the minimization of integral- or sum-type objective functions, where the tuning parameters of the controllers are the vector variables of the objective functions. The nature-inspired optimization algorithms give efficient solutions to such optimization problems. This paper presents an overview on recent developments in machine learning, data mining and evolving soft computing techniques for fault diagnosis and on nature-inspired optimal control. The generic theory is discussed along with illustrative industrial process applications that include a real liquid level control application, wind turbines and a nonlinear servo system. New research challenges with strong industrial impact are highlighted.     

A review study on titanium niobium oxide-based composite anodes for Li-ion batteries: Synthesis,structure, and performance

The growing demands for Li-ion batteries (LIBs) in the electrification revolution, require the development of advanced electrode materials. Recently, intercalating titanium niobium oxide (TNO) anode materials with the general formula of TiNb_xO_2+2.5x have received lots of attention as an alternative to graphite and Li₄Ti₅O₁₂ commercial anodes. The desirability of this family of compounds stems from their high theoretical capacities (377–402 mAh/g), high safety, high working voltage, excellent cycling stability, and significant pseudocapacitive behavior. However, the rate performance of TNO-based anodes is poor owing to their low electronic and ionic conductivities. TNO-based composites generally are prepared with two aims of enhancing the conductivity of TNO and achieving a synergic effect between the TNO and the other component of the composite. Compositing with carbon matrices, such as graphene and carbon nanotubes (CNTs) are the most studied strategy for improving the conductivity of TNO and optimizing its high-rate performance. Also, for obtaining anode materials with high capacity and high long-term stability, the composites of TNO with transition metal dichalcogenides (TMDs) materials were proposed in previous literature. In this work, a comprehensive review of the TNO-based composites as the anodes for LIBs is presented which summarizes in detail the main recent literature from their synthesis procedure, optimum synthesis parameters, and the obtained morphology/structure to their electrochemical performance as the LIBs anode. Finally, the research gaps and the future perspective are proposed.     

Human responses to high levels of carbon dioxide and air temperature

In this study, 30 subjects were exposed to different combinations of air temperature (T_a: 24, 27, and 30°C) and CO₂ level (8000, 10 000, and 12 000 ppm) in a high-humidity (RH: 85%) underground climate chamber. Subjective assessments, physiological responses, and cognitive performance were investigated. The results showed that as compared with exposure to T_a = 24°C, exposure to 30°C at all CO₂ levels caused subjects to feel uncomfortably warm and experience stronger odor intensity, while increased mental effort and greater intensity of acute health symptoms were reported. However, no significant effects of T_a on task performance or physiological responses were found. This indicated that subjects had to exert more effort to maintain their performance in an uncomfortably warm environment. Increasing CO₂ from 8000 to 12 000 ppm at all T_a caused subjects to report higher rates of headache, fatigue, agitation, and feeling depressed, although the results were statistically significant only at 24 and 27°C. The text typing performance and systolic blood pressure (SBP) decreased significantly at this exposure, whereas diastolic blood pressure (DBP) and thermal discomfort increased significantly. These effects suggest higher arousal/stress. No significant interaction effect of T_a and CO₂ concentration on human responses was identified.     

Research on the effects of surface modification of ceramic powder on cure performance during digital light processing (DLP)

Digital light processing (DLP) is one of the most important additive manufacture technologies to fabricate ceramic parts with complex geometries. Compared with pure photosensitive resin, the cure performance of ceramic suspensions is obviously different due to the optical property change after the addition of ceramic powders. In this paper, a unique oxidation process was used to modify the optical properties of nitride powders including AlN and Si₃N₄. The properties of oxidized ceramics were investigated and the cure performance of ceramic suspensions was then characterized. The effect of oxidation time on cure performance was evaluated. The results showed that for AlN, oxidation process leads to the smaller cure depth and smaller excess cure width as compared with non-oxidized AlN and for Si₃N₄, oxidation process leads to the larger cure depth and larger excess cure width as compared with non-oxidized Si₃N₄, indicating that both refractive index and light absorbance of ceramic powders have obvious effects on cure behaviors. Additionally, the cure behavior of oxidized ceramic suspension in this study shows that the relationship of cure depth vs. incident energy agrees well with Beer- Lambert model, but the excess cure width vs. incident energy is not consistent with quasi Beer-Lambert model due to the nature of digital micromirror device (DMD).     

Parameter estimation for a morphochemical reaction-diffusion model of electrochemical pattern formation

The process of electrodeposition can be described in terms of a reaction-diffusion partial differential equation (PDE) system that models the dynamics of the morphology profile and the chemical composition. Here we fit such a model to the different patterns present in a range of electrodeposited and electrochemically modified alloys using PDE constrained optimization. Experiments with simulated data show how the parameter space of the model can be divided into zones corresponding to the different physical patterns by examining the structure of an appropriate cost function. We then use real data to demonstrate how numerical optimization of the cost function can allow the model to fit the rich variety of patterns arising in experiments. The computational technique developed provides a potential tool for tuning experimental parameters to produce desired patterns.     

An automated treatment planning strategy for highly noncoplanar radiotherapy arc trajectories

Radiation therapy is a technology-driven cancer treatment modality that has experienced significant advances over the last decades, due to multidisciplinary contributions that include engineering and computing. Recent technological developments allow the use of noncoplanar volumetric modulated arc therapy (VMAT), one of the most recent photon treatment techniques, in clinical practice. In this work, an automated noncoplanar arc trajectory optimization framework designed in two modular phases is presented. First, a noncoplanar beam angle optimization algorithm is used to obtain a set of noncoplanar irradiation directions. Then, anchored in these directions, an optimization strategy is proposed to compute an optimal arc trajectory. The computational experiments considered a pool of twelve difficult head-and-neck tumor cases. It was possible to observe that, for some of these cases, the optimized noncoplanar arc trajectories led to significant treatment planning quality improvements, when compared with coplanar VMAT treatment plans. Although these experiments were done in a research environment treatment planning software (matRad), the conclusions can be of interest for a clinical setting: automated procedures can simplify the current treatment workflow, produce high-quality treatment plans, making better use of human resources and allowing for unbiased comparisons between different treatment techniques.     

Revisiting the Parallel Strategy for DOACROSS Loops

Journal of Computer Science and Technology - DOACROSS loops are significant parts in many important scientific and engineering applications, which are generally exploited pipeline/wave-front...     

APP软件性能效率研究

性能效率是APP软件的重要质量属性，但目前缺乏APP软件性能效率的通用模型。分析了APP软件的性能特征，基于ISO/IEC 25010标准提出了APP软件的性能效率模型，定义了APP软件性能效率的子特性和度量指标。基于提出的APP软件性能效率模型，通过实验对APP软件的性能效率进行了度量及相关分析。