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All Journal ASEAN Journal for Science and Engineering in Materials
Hussain, Tariq
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Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

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Machine Learning-Based CO2 Hydrogenation to High-Value Green Fuels: A Comprehensive Review for Computational Assessment Ahmed, Muhammad; Latif, Rukhsar; Seher, Shabaz; Sajjad, Rida; Hussain, Tariq; Islam, Muhammad Raza; Waleed, Abdul
ASEAN Journal for Science and Engineering in Materials Vol 3, No 2 (2024): AJSEM: Volume 3, Issue 2, September 2024
Publisher : Bumi Publikasi Nusantara

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The biggest candidate for climate change is the emission of CO2 during the burning of fossil fuels and researchers are trying to capture this CO2 efficiently and utilization effectively. This review highlights the parametric effects on conversion, utilization, and selectivity in CO2 hydrogenation via the Fischer-Tropsch method using various catalysts. Collecting the data from reported studies as datasets for quantum mechanical-based simulation software such as DFT and Monte Carlo were employed to probe the characteristics of catalysts, the discovery of novel catalysts, theoretical models for utilization of catalysts and parameters for CO2 hydrogenation such as operational, catalyst information, and mass transfer. Two syntheses such as methanol and methane were studied extensively via machine learning techniques. How artificial intelligence can help experimentalists for finding new catalysts has been discussed and how one can understand the catalytic features in a better way. Furthermore, the key challenges in CO2 hydrogenation technology and future directions based on artificial intelligence have been discussed thoroughly.
Graphene-Based Electrochemical Sensors for Heavy Metal Ions Detection: A Comprehensive Review Dilshad, Muhammad; Hussain, Tariq; Ali, Shahbaz; Shahzad, Muhammad Shakeel; Javed, Muhammad; Ahmad, Farhan Nazir; Zaki, Asaad Ahmad
ASEAN Journal for Science and Engineering in Materials Vol 4, No 1 (2025): AJSEM: Volume 4, Issue 1, March 2025
Publisher : Bumi Publikasi Nusantara

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The accumulation of heavy metallic ions in the human body causes serious damage. The tracking and removal of these ions is very necessary and that is done via electrochemical sensors because of quick response, high sensitivity, and low but large detection range. In this regard, the surface of the electrode plays a critical role in electrochemical performance. Here, we present a detailed review of work that has been done in the past to modify the surface of electrodes by testing the carbon nanoparticles i.e. graphene or graphene derivatives, and their combination with other nanoparticles. Mixing graphene or graphene oxide with other organic or inorganic materials forms nanocomposites which help to detect various kinds of heavy metal ions such as cadmium, mercury, copper, lead, zinc, etc. in tap water or food items. This review article includes the synthesis methodologies, working mechanisms, advantages, disadvantages, and future prospectus of this field.
Co-Authors Ahmad, Farhan Nazir Ahmed, Muhammad Ali, Shahbaz Dilshad, Muhammad Islam, Muhammad Raza Javed, Muhammad Latif, Rukhsar Sajjad, Rida Seher, Shabaz Shahzad, Muhammad Shakeel Waleed, Abdul Zaki, Asaad Ahmad