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A techno-economic and life cycle assessment for the production of green methanol from CO_(2): catalyst and process bottlenecks

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Journal of Energy Chemistry 2022年第5期31卷 255-266页

作者： Tomas Cordero-Lanzac Adrian Ramirez Alberto Navajas Lieven Gevers Sirio Brunialti Luis MGandía Andrés T.Aguayo S.mani sarathy Jorge Gascon Department of Chemical Engineering University of the Basque Country(UPV/EHU)PO Box 64448080 BilbaoSpain King Abdullah University of Science and Technology KAUST Catalysis Center(KCC)Advanced Catalytic MaterialsThuwal 23955Saudi Arabia Department of Science Public University of Navarre(UPNA)Arrosadía Campus s/n31006 PamplonaSpain Institute for Advanced Materials and Mathematics(InaMat2) Universidad Pública de Navarra(UPNA)Edificio Jerónimo de AyanzCampus de ArrosadiaPamplona-Iruña 31006Spain King Abdullah University of Science and Technology Clean Combustion Research Center(CCRC)Thuwal 23955Saudi Arabia

The success of catalytic schemes for the large-scale valorization of CO_(2) does not only depend on the development of active,selective and stable catalytic materials but also on the overall process *** we present a multidisciplinary study(from catalyst to plant and techno-economic/lifecycle analysis)for the production of green methanol from renewable H2 and CO_(2).We combine an in-depth kinetic analysis of one of the most promising recently reported methanol-synthesis catalysts(InCo)with a thorough process simulation and techno-economic *** then perform a life cycle assessment of the simulated process to gauge the real environmental impact of green methanol production from CO_(2).Our results indicate that up to 1.75 ton of CO_(2) can be abated per ton of produced methanol only if renewable energy is used to run the process,while the sensitivity analysis suggest that either rock-bottom H2 prices(1.5$kg1)or severe CO_(2) taxation(300$per ton)are needed for a profitable methanol ***,we herein highlight and analyze some critical bottlenecks of the *** attention has been paid to the contribution of H2 to the overall plant costs,CH4 trace formation,and purity and costs of raw *** addition to providing important information for policy makers and industrialists,directions for catalyst(and therefore process)improvements are outlined.

关键词： CO_(2) Methanol Kinetic modeling Process simulation Life cycle assessment

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丁烯/丁醇异构体低温氧化Waddington反应机制理论研究

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燃烧科学与技术 2022年第5期28卷 540-548页

作者：赵倩李阳 mani sarathy 黄佐华张英佳西安交通大学动力工程多相流国家重点实验室西安710049 西北工业大学燃烧、结构与内流场重点实验室西安710072 阿卜杜拉国王科技大学清洁燃烧研究中心图沃23955沙特阿拉伯

Waddington机理是烯烃和醇类异构体低温氧化机理建模的重要组成部分.针对丁烯/丁醇异构体,系统研究了低温氧化过程的Waddington动力学机制.基于量子化学原理,对该反应机制下的反应速率常数和物种热力学性质进行计算.基于过渡态理论,结合... 详细信息

Waddington机理是烯烃和醇类异构体低温氧化机理建模的重要组成部分.针对丁烯/丁醇异构体,系统研究了低温氧化过程的Waddington动力学机制.基于量子化学原理,对该反应机制下的反应速率常数和物种热力学性质进行计算.基于过渡态理论,结合RRKM/ME方法,获得目标体系温度-/压力依赖的速率系数.在统计热力学的基础上,计算了所有关键物种温度相关的内能、生成焓、熵和热容等热力学量.与文献结果比较发现,异丁烯(R4和R5体系)的动力学与热力学参数均与文献值吻合较好.该理论计算结果可直接用于丁烯和丁醇异构体低温氧化动力学模型构建.

关键词： Waddington机制丁烯/丁醇异构体从头算法速率系数热力学参数

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Predicting entropy and heat capacity of hydrocarbons using machine learning

能源与人工智能(英文)

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能源与人工智能(英文) 2021年第2期4卷 161-171页

作者： Mohammed N.Aldosari Kiran K.Yalamanchi Xin Gao S.mani sarathy Clean Combustion Research Center Physical Sciences and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955Saudi Arabia Computational Bioscience Research Center ComputerElectrical and Mathematical Sciences and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955Saudi Arabia

Chemical substances are essential in all aspects of human life,and understanding their properties is essential for developing chemical *** properties of chemical species can be accurately obtained by experiments or ab initio computational calculations;however,these are time-consuming and *** this work,machine learning models(ML)for estimating entropy,S,and constant pressure heat capacity,Cp,at 298.15 K,are developed for alkanes,alkenes,and *** training data for entropy and heat capacity are collected from the *** descriptors generated using alvaDesc software are used as input features for the ML *** vector regression(SVR),v-support vector regression(v-SVR),and random forest regression(RFR)algorithms were trained with K-fold cross-validation on two *** first level assessed the models’performance,and the second level generated the final *** the three ML models chosen,SVR shows better performance on the test *** SVR model was then compared against traditional Benson’s group additivity to illustrate the advantages of using the ML ***,a sensitivity analysis is performed to find the most critical descriptors in the property estimations.

关键词： Entropy Heat capacity Molecular descriptors Machine learning Supervised learning Hydrocarbons

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Clinical Profile of Carcinoma Breast Patients Treated with Trastuzumab: A Single Centre Study

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Advances in Breast Cancer Research 2020年第4期9卷 110-118页

作者： Srinivasa Belagutty Jayappa Bhanu Prakash Lalkota Veluswamy mani Reshma Elsa Jenny Kiran P. Krishnamurthi Vinu sarathy S. Thineshwaran Bayas Nithin Sumithra Martinovic Amritanshu Ram Shekar Patil Radheshyam Naik Department of Medical Oncology Healthcare Global Enterprises Ltd. Bangalore Karnataka India Center for Academics and Research HCG Foundation Bangalore India Department of Cytogenetics Healthcare Global Enterprises Ltd. Bangalore Karnataka India

Introduction: Breast cancer is the most common female cancer in India and accounting for almost 1 in 4 cancer cases in women worldwide. According to GLOBOCAN 2018: breast cancer incidence is increased to 162,468 in 2018 compared to 144,937 in 2012. Biosimilar drugs allow expanding access to the therapies in the form of cost savings and leading to better overall health outcomes. Our study evaluates the efficacy and safety of Trastuzumab biosimilars and assesses overall survival in the study population. Materials & Methods: This prospective study was conducted in Healthcare Global Enterprises Ltd., Bengaluru, India, and all female patients diagnosed with Her2 positive, metastatic (mBC) and Locally advanced breast cancer (LABC), between March 2013 and November 2014, with at least 4 years of post-treatment follow up. Results: A total of 65 patients diagnosed with Her2 positive breast cancer and satisfied the selection criteria were included for the study. Partial Response (PR) was observed in 42 (64.6%) patients, Stable Disease (SD) in 11 (16.9%) patients and Progressive Disease (PD) in 12 (18.5%) patients. The overall response rates were 46.1% PR, 30% SD, 23.8% PD in metastatic population and 76% PR, 7.2% SD, 15% PD observed in locally advanced disease. The mean overall survival of the study population was 20.75 ± 15.20 months

关键词： Breast Cancer Trastuzumab Biosimilars

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