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Quanta of the magnetic monopole entering the Oersted–Ampere law 磁单极子的量子进入奥斯特-安培定律
Pub Date : 2018-08-01 DOI: 10.15406/mseij.2018.02.00043
S. Olszewski
The paper demonstrates that quantization of the magnetic monopole, much similar to that concerning the magnetic flux in superconductors, can occur also in a non–superconducting case represented by the Oersted–Ampere law. This result can occur on condition the Joule–Lenz law for the action quanta of electrons participating in the effect is taken into account. The quantum result obtained for a monopole can be confirmed with the aid of the uncertainty principle applied to the energy and time period characteristic for the current involved in the Oersted–Ampere phenomenon.
本文证明了磁单极子的量子化,与超导体中磁通量的量子化非常相似,也可以发生在用奥斯特-安培定律表示的非超导情况下。这一结果可以在考虑参与效应的电子的作用量子的焦耳-伦茨定律的条件下发生。单极子的量子结果可以借助应用于奥斯特-安培现象中电流的能量和周期特性的不确定性原理加以证实。
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引用次数: 0
Electron structure and thermodynamics of solid solutions in Ni–H system Ni-H体系中固溶体的电子结构和热力学
Pub Date : 2018-07-23 DOI: 10.15406/mseij.2018.02.00042
Gavriljuk Vg
The widespread concept of nickel hydride in the Ni–H system is discussed based on the first–principle atomic calculations and experimental X–ray diffraction data. The total cohesion energy in Ni–H solid solution has been determined using the density functional theory and program package Wien2k. Its dependence on hydrogen concentration is shown to be linear, which suggests the absence of any energy barrier for precipitation reaction. Moreover, the second derivative of the calculated solution enthalpy is negative within the hydrogen–to–nickel ratios, H/Ni, of 0.03 to 0.75, which is a sign of spinodal decomposition. These hydrogen concentrations are consistent with the measurements of X–ray diffraction, of which results are traditionally interpreted in terms of Ni hydride. The density of electron states has been calculated, and its non–monotonous concentration dependence correlates with that of solution enthalpy, which is also expected for spinodal decomposition. The obtained results are interpreted as miscibility gap in the Ni–H system with spinodal decomposition having the electron origin. In addition, using mechanical spectroscopy, the strain dependent internal friction has been observed in the hydrogen–charged nickel with H/Ni ratio of about 0.7. This effect is controlled by irreversible plastic deformation, which is typical for solid solutions, not for brittle chemical compounds. Finally, the “hydrides” in a number of metals are discussed in terms of two Gibb’s types of precipitation reactions. Keywords: nickel, hydrogen, ab initio calculations, spinodal decomposition, hydride
基于第一性原理原子计算和实验x射线衍射数据,讨论了Ni-H体系中广泛存在的氢化镍概念。利用密度泛函理论和Wien2k程序包计算了Ni-H固溶体的总内聚能。它对氢浓度的依赖是线性的,这表明沉淀反应不存在任何能垒。此外,在氢镍比(H/Ni)为0.03 ~ 0.75的范围内,计算得到的溶液焓二阶导数为负,这是旋量分解的标志。这些氢浓度与x射线衍射的测量结果一致,x射线衍射的结果传统上用氢化镍来解释。计算了电子态的密度,其非单调的浓度依赖关系与溶液焓的浓度依赖关系相关联,这也是spinodal分解所期望的。所得结果可以解释为Ni-H体系中具有电子源的独立分解的混相间隙。此外,在H/Ni比约为0.7的含氢镍中,利用力学谱法观察到应变相关的内摩擦。这种效应是由不可逆的塑性变形控制的,这是典型的固溶体,而不是脆性化合物。最后,根据两种吉布类型的沉淀反应,讨论了许多金属中的“氢化物”。关键词:镍,氢,从头计算,旋多分解,氢化物
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引用次数: 1
Garbage classification using convolutional neural networks (CNNs) 基于卷积神经网络的垃圾分类
Pub Date : 1900-01-01 DOI: 10.15406/mseij.2023.07.00217
Al Mahmud Al Mamun, Rasel Hossain, Mst. Mahfuza Sharmin, E. Kabir, Md. Ashik Iqbal
Proper garbage classification is essential for effective waste management and environmental sustainability. This research paper presents a comprehensive study of garbage classification using Convolutional Neural Networks (CNNs). The objective is to develop an accurate and automated garbage classification system leveraging the power of deep learning. The proposed CNN model achieves an impressive accuracy of 98.45%, demonstrating its efficacy in classifying different waste categories. The research encompasses data collection, preprocessing, model architecture, training methodology, and evaluation. The results indicate the potential of CNNs in revolutionizing waste management practices and paving the way for a more sustainable future.
正确的垃圾分类对有效的废物管理和环境的可持续性至关重要。本文提出了一种基于卷积神经网络(cnn)的垃圾分类方法。目标是利用深度学习的力量开发一个准确和自动化的垃圾分类系统。本文提出的CNN模型达到了令人印象深刻的98.45%的准确率,证明了其对不同垃圾类别进行分类的有效性。研究内容包括数据收集、预处理、模型架构、训练方法和评估。研究结果表明,cnn在彻底改变废物管理实践和为更可持续的未来铺平道路方面具有潜力。
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引用次数: 0
Gradualism and collaboration must still be extoled as universal academic and societal values 渐进主义和合作仍然必须作为普遍的学术和社会价值加以颂扬
Pub Date : 1900-01-01 DOI: 10.15406/mseij.2023.07.00216
Patrick Ajwang 
.
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引用次数: 0
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Material Science &amp; Engineering International Journal
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