Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Golshan Mazloom"'
Autor:
Jafar Abdi, Golshan Mazloom, Fahimeh Hadavimoghaddam, Abdolhossein Hemmati-Sarapardeh, Seyyed Hamid Esmaeili-Faraj, Akbar Bolhasani, Soroush Karamian, Shahin Hosseini
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-21 (2023)
Abstract Light olefins, as the backbone of the chemical and petrochemical industries, are produced mainly via steam cracking route. Prediction the of effects of operating variables on the product yield distribution through the mechanistic approaches
Externí odkaz:
https://doaj.org/article/c9359b41483142ccb49e62ceb324362b
Autor:
Jafar Abdi, Golshan Mazloom
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-13 (2022)
Abstract Arsenic in drinking water is a serious threat for human health due to its toxic nature and therefore, its eliminating is highly necessary. In this study, the ability of different novel and robust machine learning (ML) approaches, including L
Externí odkaz:
https://doaj.org/article/3466e215b9d8485eb9ff466bb48f0b9d
Autor:
Golshan Mazloom, Sheida Esmaeili
Publikováno v:
مجله مدل سازی در مهندسی, Vol 17, Iss 57, Pp 55-68 (2019)
Kinetic modeling was used to determine the type of the oxygen function in partial oxidation of propane to AA over Mo1V0.3Te0.23Nb0.12Ox catalyst. Experimental data was collected under different operating conditions in a fixed bed tubular reactor. A r
Externí odkaz:
https://doaj.org/article/ecb9a52c240149e69f31f30378c3227c
Publikováno v:
شیمی کاربردی روز, Vol 13, Iss 46, Pp 101-122 (2018)
Role of water vapor in propane selective oxidation to acrylic acid over Mo1V0.3Te0.23Nb0.12Ox has been investigated using kinetic study. The catalyst was produced by slurry method and two sets of experiments have been designed: reactions in the prese
Externí odkaz:
https://doaj.org/article/bce2de8422de491ea04b19c35638b0be
Publikováno v:
Biomass Conversion and Biorefinery.
Publikováno v:
Industrial & Engineering Chemistry Research. 60:9729-9738
Autor:
Rafael Abargues, Jafar Abdi, Saurabh Ahalawat, Faheem Ahamad, Md. Ahmaruzzaman, Charu Arora, Anu Bharti, Brij Bhushan, Rakesh Bhutiani, Manish Biyani, Vladimir Bogoslovskiy, Alexandr Burakov, Irina Burakova, Monika Chaudhary, Shubham Chaudhary, Parul Chauhan, Jorge Alberto Vieira Costa, Mohammad Hadi Dehghani, Alejandro Dorazco-González, Partha Dutta, Aleksander Ejsmont, Seyyed Hamid Esmaeili-Faraj, Ali Fakhri, Aleksandra Galarda, Evgeny Galunin, Kajol Goria, Joanna Goscianska, Agata Jankowska, Rama Rao Karri, Richa Kothari, Shreya Kotnala, Gagandeep Kour, Nupur Kukretee, Ankur Kumar, Ravinder Kumar, Vikas Kumar, Vinod Kumar, Yogendra Kumar, Tarun Kumar Kumawat, Varsha Kumawat, Suelen Goettems Kuntzler, Sarita Kushwaha, Juan P. Martínez-Pastor, Golshan Mazloom, Anastasia Memetova, Jyoti Mittal, Michele Greque de Morais, Juliana Botelho Moreira, Arunima Nayak, Hadi Omidinasab, Hitesh Panchal, Anjali Pandit, Diksha Praveen Pathak, Tahereh Pirhoushyaran, Nidhi Rai, Shubham Raina, Saravanan Rajendran, Varun Rawat, Sandra Ricart, Pedro J. Rodríguez-Cantó, Luis D. Rosales-Vázquez, Prerona Roy, Ala Sadooghi, Víctor Sánchez-Mendieta, Bhavana Sethi, Daksha Sharma, Ved Bhushan Sharma, Vishnu Sharma, Gulnara Shigabaeva, Har Mohan Singh, Pooja Singh, Pratibha Singh, Ali Sohani, Sanju Soni, Ananthakumar Soosaimanickam, null Suhas, R. Suresh, Ana Luiza Machado Terra, R.C. Tiwari, Inderjeet Tyagi, Kaomud Tyagi, V.V. Tyagi, Dipti Vaya, Monu Verma, Shalu Yadav, Hüseyin Yagli
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cf7cad46f04ba2f1ae0eabe5459b1711
https://doi.org/10.1016/b978-0-323-99425-5.09990-4
https://doi.org/10.1016/b978-0-323-99425-5.09990-4
Autor:
Golshan Mazloom
Publikováno v:
Chemical Engineering Research Bulletin. 21:1-19
The prediction capability of response surface methodology (RSM) and artificial neural network (ANN) models for propane selective oxidation to acrylic acid (AA) over Mo1V0.3Te0.23Nb0.12Ox catalyst was investigated in this work. 15 experimental runs ba
Publikováno v:
Fuel. 236:1254-1262
Ni and Ni-Co catalysts supported on CeO2-ZnAl2O4 have been prepared, characterized and evaluated in the methane dry reforming. The characterization tests showed that the presence of cobalt improved the physical/chemical properties of the catalyst by