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Titlebook: Microbially Induced Corrosion and its Mitigation; Ajay K. Singh Book 2020 The Author(s), under exclusive license to Springer Nature Singap

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發(fā)表于 2025-3-21 16:22:01 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Microbially Induced Corrosion and its Mitigation
編輯Ajay K. Singh
視頻videohttp://file.papertrans.cn/634/633076/633076.mp4
叢書名稱SpringerBriefs in Materials
圖書封面Titlebook: Microbially Induced Corrosion and its Mitigation;  Ajay K. Singh Book 2020 The Author(s), under exclusive license to Springer Nature Singap
描述.This brief covers case studies on Microbial Induced Corrosion (MIC) and its mitigation. After reviewing the basics of corrosion, it focuses on MIC. MIC is a special type of electrochemical corrosion in which the presence of microbes and bacteria alters the chemistry of liquid media so as to make them more corrosive. These changes are harmful to metallic equipment, processing machinery, marine vessels, etc. in an environment that is host to a wealth of microorganisms. A 2007 US survey estimated corrosion-related damages to cost $276 billion a year, roughly 50% of which are due to MIC. The industries most affected by MIC are power production, oil exploration, transportation and storage, water distribution and more generally all industries involving marine environments. However, means for effectively preventing and controlling MIC are poorly understood. As such, the book’s later chapters address various mechanisms/processes that show promise with regard to MIC mitigation. Lastly, the book discusses the strategies currently being explored to mitigate MIC using green technologies..
出版日期Book 2020
關(guān)鍵詞Bioleaching; Bioremediation; Biosorption; Electrochemical Crrosion; Metabolic Engineering; Microbial Indu
版次1
doihttps://doi.org/10.1007/978-981-15-8019-2
isbn_softcover978-981-15-8017-8
isbn_ebook978-981-15-8019-2Series ISSN 2192-1091 Series E-ISSN 2192-1105
issn_series 2192-1091
copyrightThe Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020
The information of publication is updating

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沙發(fā)
發(fā)表于 2025-3-21 21:22:51 | 只看該作者
板凳
發(fā)表于 2025-3-22 03:27:07 | 只看該作者
Microbial Induced Corrosion and Industrial Economy,only chemicals, weakens the material strength prematurely and thus results in unscheduled shutdown of plants, catastrophic failure pf machinery, leakage of chemicals etc. This needs maintenance of machinery or its replacement. Other factors are also involved which together results in extra expenditu
地板
發(fā)表于 2025-3-22 06:46:15 | 只看該作者
Experimental Details and Strategies to Control Corrosion,estigation on MIC. First of these is microbiology work, e.g., isolation of bacteria from natural resources, studying the growth cycle of bacteria, and biofilm characterization, and second of these is related to investigating corrosion due to bacteria. In this later case, details have been discussed
5#
發(fā)表于 2025-3-22 10:28:27 | 只看該作者
Industrial Cases of Microbial Induced Corrosion,tance if such type of work can be used in controlling MIC experienced by the construction materials used in various industries or elsewhere. This chapter, therefore, deals with different industries where MIC is observed and pose problems. This chapter discusses about corrosion problems due to MIC in
6#
發(fā)表于 2025-3-22 14:53:27 | 只看該作者
Mitigation of Microbial Induced Corrosion,rrosion of metals, it is obvious to talk about the ways and means for mitigating MIC. This chapter deals with this aspect in two parts, the first part dealing with the conventional/currently undergoing techniques while the second part dealing with newer/green technology approach for MIC mitigation.
7#
發(fā)表于 2025-3-22 17:38:40 | 只看該作者
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發(fā)表于 2025-3-22 23:23:27 | 只看該作者
Ajay K. Singhxisting camera based approaches relies on hand crafted rules, image based classification and supervised learning. In a real world intrusion detection system, we need to learn spatio-temporal features unsupervisely (as annotated data are very difficult to obtain) and use these features to detect intr
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發(fā)表于 2025-3-23 02:42:14 | 只看該作者
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發(fā)表于 2025-3-23 06:14:10 | 只看該作者
Ajay K. Singh-dependent sentiment analysis in Slavic languages in specific cultural context, as well as the software implementation of the resulting network. Convolutional neural networks are easy to train and implement. To train them, a standard error back propagation algorithm is used, and because the filter w
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