Review
Energy & Fuels
Esmail Dabirian, Alireza Hajipour, Abbasali Abouei Mehrizi, Ceren Karaman, Fatemeh Karimi, Pau Loke-Show, Onur Karaman
Summary: Global warming is a critical environmental problem caused by burning fossil fuels and releasing CO2. The use of biofuels, especially those produced with nanotechnology, such as biohydrogen and bioethanol, can improve production efficiency and contribute to a greener future.
Article
Biotechnology & Applied Microbiology
Lisandra Rocha-Meneses, Anjana Hari, Abrar Inayat, Abdallah Shanableh, Mohamed Abdallah, Chaouki Ghenai, Sabarathinam Shanmugam, Timo Kikas
Summary: This paper provides a state-of-the-art review on utilizing nano-catalysts in the biomass anaerobic digestion process. Nanoparticles, as catalysts, have been used to enhance the performance of anaerobic digestion technologies and increase biogas production. However, further research is needed to address the energetic, technological, and economical utilization of nanoparticles in anaerobic digestion processes.
BIOCHEMICAL ENGINEERING JOURNAL
(2022)
Review
Biotechnology & Applied Microbiology
Xiaoli Xiong, Wenxing Zhang, Xia Ha, Ning Li, Shengming Chen, Hongwei Xing, Jing Yang
Summary: Kitchen waste is both harmful and rich in resources, with approximately 1.3 billion tons being produced worldwide every year. Conventional treatments such as landfilling and incineration cause environmental, economic, and social problems. Therefore, there is an urgent need for harmless and resource-based treatment technology.
FERMENTATION-BASEL
(2023)
Review
Agricultural Engineering
Jung Yoon Seo, Diyar Tokmurzin, Doyeon Lee, See Hoon Lee, Myung Won Seo, Young-Kwon Park
Summary: A sustainable carbon-neutral society requires the use of biochars and biofuels, with crop residues being a promising feedstock. This article presents the distribution and resource potential of major crop residues and discusses their application in biofuel production. It also proposes the challenges and opportunities for future research in terms of crop residue supply, biochar production, and biochar utilization for biofuel production.
BIORESOURCE TECHNOLOGY
(2022)
Review
Green & Sustainable Science & Technology
Nongmaithem Debeni Devi, Angana Chaudhuri, Vaibhav V. Goud
Summary: This review discusses an innovative biofilm cultivation system for microalgae that aims to reduce the cost of biomass recovery and processing. It outlines two main cultivation strategies and highlights the influence of physicochemical parameters on microalgae growth.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2022)
Article
Agricultural Engineering
Mateus Eugenio Boscaro, Danieli Fernanda Canaver Marin, Daiana Camila da Silva, Sandra Imaculada Maintinguer
Summary: This study investigated the effects of citrate-coated Fe3O4 nanoparticles on the anaerobic digestion of crude glycerol. The results showed that the addition of Fe3O4 nanoparticles significantly increased CH4 production and the maximum rate of CH4 production, as well as the relative abundance of bacteria and archaea.
BIOMASS & BIOENERGY
(2022)
Article
Energy & Fuels
Silvia Zabala, Ines Reyero, Idoia Campo, Gurutze Arzamendi, Luis M. Gandia
Summary: This study focused on the biphasic nature of the methanolysis reaction of vegetable oils, investigated the behavior of the liquid phases in the reaction medium, and developed two kinetic models of different complexity levels. The results indicate that a heterogeneous model considering the biphasic nature of the reaction medium is crucial for describing the methanolysis reaction effectively.
Review
Agricultural Engineering
Juli Wang, Stacy D. Singer, Bernardo A. Souto, Justice Asomaning, Aman Ullah, David C. Bressler, Guanqun Chen
Summary: This article reviews the interactions between lipid feedstocks and lipid-based biofuels, as well as the advancements in lipid-associated biofuel technology and the applicability of various lipid sources. It also provides an overview of the latest research on plant lipids, microbial lipids, and animal fats in the context of lipid-based biofuel technology.
BIORESOURCE TECHNOLOGY
(2022)
Article
Materials Science, Multidisciplinary
Mrituanjay D. Pandey
Summary: This article discusses the role of nanomaterials in enhancing the efficiency of bioenergy storage and conversion, particularly in biomass, biofuel, bioethanol, and biodiesel systems. It also addresses the potential and challenges associated with using nanomaterials in these applications.
Article
Energy & Fuels
Srijoni Banerjee, Dipankar Ghosh, Chetan Pandit, Sagnik Saha, Anwesha Mohapatra, Soumya Pandit, Minaxi Sharma, Kandi Sridhar, Baskaran Stephen Inbaraj, Ram Prasad
Summary: Microalgae have shown great potential as a prominent source for biomass production in the production of biofuels and bioenergy. They are capable of producing high yields of biomass and fuel while occupying smaller land footprints. Additionally, microalgae can be utilized in wastewater treatment and the generation of bioelectricity.
Article
Energy & Fuels
Sana Gohar Khan, Muhammad Hassan, Mustafa Anwar, Zeshan, Uneeb Masood Khan, Chao Zhao
Summary: This research presents the synthesis and application of Pr-CaO catalysts for biodiesel production from castor oil, which showed stable, active, and low-cost characteristics. The obtained catalyst exhibited a high FAME yield of 87.42% under optimal reaction conditions using 7% Pr-CaO mixed oxide catalyst.
Article
Biotechnology & Applied Microbiology
Senthil Nagappan, Gopalakrishnan Kumar
Summary: The study explores the use of nitrogen-deficient synthetic wastewater to increase lipid and carbohydrate content in selected microalgae, while maintaining carotenoids. This approach shows promise as a low-cost and economical option for biorefinery.
ENVIRONMENTAL TECHNOLOGY & INNOVATION
(2021)
Review
Energy & Fuels
Sivasubramanian Manikandan, Ramasamy Subbaiya, Muniyandi Biruntha, Radhakrishnan Yedhu Krishnan, Govarthanan Muthusamy, Natchimuthu Karmegam
Summary: Biofuels, derived from biomass, are viewed as important technologies for energy supply, climate, foreign exchange savings, and rural socioeconomic issues. Modern biomass technologies can effectively utilize biomass resources for various purposes.
Article
Energy & Fuels
Haoran Ye, Jiangjing Shi, Ying Wu, Yan Yuan, Lu Gan, Yingji Wu, Huan Xie, Arivalagan Pugazhendhi, Changlei Xia
Summary: This article emphasizes the importance of developing sustainable and environmentally friendly fuels in the face of serious environmental pollution and the eventual depletion of fossil fuels. Nano-catalysts, with their unique nanostructures and properties, play a crucial role in the conversion of biomass into biofuels. By using renewable resources, multifunctional and efficient nano-catalysts can be developed to improve resource utilization and reduce catalyst usage.
Article
Energy & Fuels
Minyoung Kim, Dong-Jun Lee, Sungyup Jung, Scott X. Chang, Kun-Yi Andrew Lin, Amit Bhatnagar, Eilhann E. Kwon, Yiu Fai Tsang
Summary: The study focused on converting peanut waste into biofuels through a thermochemical process, using biochar derived from pyrolysis of the waste as a catalyst to enhance reaction kinetics and lower reaction temperature. Biochars produced at different temperatures were effective in transesterification of soybean oil, showing higher yields compared to conventional methods.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Tzu-Chia Chen, Abdullah M. Iliyasu, Seyed Mehdi Alizadeh, Ahmed S. Salama, Ehsan Eftekhari-Zadeh, Kaoru Hirota
Summary: When scale builds up in a transmission pipeline, it narrows the pipe's interior and causes losses in power and efficiency. A noninvasive instrument based on gamma-ray attenuation is suggested for determining volumetric percentages in various circumstances. Using a system with a NaI detector and dual-energy gamma generator simulations, volumetric percentages can be forecasted with an RMSE of less than 0.90, independent of scale thickness.
APPLIED ARTIFICIAL INTELLIGENCE
(2023)
Article
Physics, Condensed Matter
Tzu-Chia Chen
Summary: This paper investigates the changes in microstructure and micromechanical properties of solder joints in a semiconductor subjected to thermal-cycling loading. A model was developed using expectation-maximization machine learning and nanoindentation mapping, allowing for prediction and interpretation of the microstructural features of solder joints through micromechanical variations. The ML model successfully classified the Sn-based matrix, intermetallic compounds (IMCs), and grain boundaries based on their elastic modulus ranges. However, overestimations were observed in the regression process when the interfacial regions thickened. The ML outcomes also revealed that thermal-cycling led to stiffening and growth of IMCs, while the portion of Sn-based matrix decreased in the microstructure. The stiffness gradient became intensified in the treated samples, indicating increased mechanical mismatch between the matrix and the IMCs.
JOURNAL OF PHYSICS-CONDENSED MATTER
(2023)
Article
Engineering, Environmental
Tzu-Chia Chen
Summary: Modern artificial intelligence techniques can effectively simulate water quality parameters, and the accuracy of machine learning models can be improved by using wavelet theory. The study conducted in Gao-ping River, Taiwan found that hybrid models with wavelet transform significantly increased the accuracy of ANN and ANFIS models.
WATER SCIENCE AND TECHNOLOGY
(2023)
Article
Environmental Sciences
Tzu-Chia Chen, T. Ch. Anil Kumar, Ngakan Ketut Acwin Dwijendra, Ali Majdi, Abdul Rab Asary, Acim Heri Iswanto, Imran Khan, Dag Oivind Madsen, Reza Alayi
Summary: In this study, the authors investigated the thermodynamic performance of a combined gas turbine system that utilized a tubular solid oxide fuel cell and hydrogen fuel. By separately modeling each component using thermodynamic relations, it was found that as turbine inlet temperature increased, the system's efficiency decreased while power output increased. Additionally, increasing temperature and pressure ratio led to higher entropy production and greater irreversibility in the system. The research results showed that the combustion chamber and fuel cell contributed to 65% of the system's irreversibility, while the heat exchanger contributed to 19%. Furthermore, the combined system achieved an efficiency of 9.81%, highlighting its exceptional performance compared to a system without a fuel cell, which had an efficiency of 33.4%.
Article
Green & Sustainable Science & Technology
Xuesong Zhang, Farag M. A. Altalbawy, Tahani A. S. Gasmalla, Ali Hussein Demin Al-Khafaji, Amin Iraji, Rahmad B. Y. Syah, Moncef L. Nehdi
Summary: This research compared various machine learning models to forecast the uniaxial compressive strength (UCS) of rocks. The support vector machine with radial basis function outperformed all other methods and achieved high accuracy (R-2 = 0.99, PI = 1.92). The models showed excellent accuracy (R-2 > 90%) in estimating UCS, with a small average difference of +0.28% compared to the measured values.
Article
Green & Sustainable Science & Technology
Tzu-Chia Chen, Jose Ricardo Nunez Alvarez, Ngakan Ketut Acwin Dwijendra, Zainab Jawad Kadhim, Reza Alayi, Ravinder Kumar, Seepana PraveenKumar, Vladimir Ivanovich Velkin
Summary: This research focuses on modeling the electrical energy network with renewable energy sources and gas production systems. The model provides a mixed integer linear optimization model that integrates distributed generation sources, energy storage systems, gas power systems, and electric vehicles in an integrated electricity and gas system. The research also considers electric vehicles as a base load, which presents a limitation in optimizing their maximum charging. One of the important findings is that the investment cost in the first scenario was USD 879,340, with purchased electric energy of 37,374 kW and gas of 556,233 m(3) from the respective networks.
Article
Green & Sustainable Science & Technology
Mohammad Hijji, Tzu-Chia Chen, Muhammad Ayaz, Ali S. Abosinnee, Iskandar Muda, Yury Razoumny, Javad Hatamiafkoueieh
Summary: A new fuzzy-based intelligent system integrated with optimization algorithms was developed to predict total dissolved solids, which can support early warning of water pollution in areas exposed to multiple pollutants. Monthly water quality parameters data from two gaging stations in coastal Iran were used for modeling the TDS parameter in a river system. Results show that the proposed integrated model can accurately simulate the dynamics of TDS records compared to other machine learning techniques.
Article
Green & Sustainable Science & Technology
Habib Satria, Rahmad B. Y. Syah, Moncef L. Nehdi, Monjee K. Almustafa, Abdelrahman Omer Idris Adam
Summary: This article proposes an effective evolutionary hybrid optimization method, CNGPS, based on the northern goshawk optimization algorithm (NGO) and pattern search (PS), for identifying unknown parameters in photovoltaic (PV) models. The effectiveness of the CNGPS algorithm is verified through mathematical test functions and compared with conventional NGO and other optimization methods. The CNGPS algorithm demonstrates better performance and lower error in parameter extraction for PV models.
Article
Engineering, Chemical
Tzu-Chia Chen, Seyed Mehdi Alizadeh, Abdullah K. Alanazi, John William Grimaldo Guerrero, Hala M. Abo-Dief, Ehsan Eftekhari-Zadeh, Farhad Fouladinia
Summary: Measuring the void fraction in different multiphase flows is crucial for industries such as gas, oil, chemical, and petrochemical. Capacitive sensors have been widely used for this purpose, but fluid properties can affect their performance and lead to significant errors in void fraction measurement. In this study, an artificial neural network model was developed to measure the gas percentage in a two-phase flow without the need for recalibration, using a new combined capacitance-based sensor design.
Article
Computer Science, Information Systems
Sutrisno Sutrisno, Nurul Khairina, Rahmad B. Y. Syah, Ehsan Eftekhari-Zadeh, Saba Amiri
Summary: Despite the impact of the Coronavirus pandemic on people's physical and psychological well-being, it has also affected the psychological conditions of many employees, particularly in organizations and privately owned businesses facing pandemic-related restrictions. This study aimed to analyze the relationship between demographic variables, resilience, Coronavirus, and burnout in start-ups using an RBF neural network. The study employed a quantitative research method with a sample population of start-up managers and employees. Standard surveys and specially designed questionnaires were used to collect data, and their validity and reliability were confirmed. The designed network structure had ten neurons in the input layer, forty neurons in the hidden layer, and one neuron in the output layer. The training and test data were divided into 70% and 30% respectively. The results showed that the designed network was able to accurately classify all the data, and the method presented in this research can greatly contribute to the sustainability of companies.
Article
Computer Science, Theory & Methods
Marischa Elveny, Mahyuddin K. M. Nasution, Rahmad B. Y. Syah
Summary: Accurate and efficient business analytical predictions are crucial for decision making in today's competitive landscape. By using data analysis, statistical methods, and predictive modeling, businesses can extract insights and make informed decisions. Optimizing business analytics predictions can lead to improved operations, reduced costs, and increased profits.
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Rahmad B. Y. Syah, Aryan Veisi, Zainal Arifin Hasibuan, Mustafa A. Al-Fayoumi, Mohammad Sh. Daoud, Ehsan Eftekhari-Zadeh
Summary: Accurately determining phase fractions in two-phase flows is crucial in industries related to petroleum and petrochemical production and processing. Among various sensor types, the capacitance-based sensor is recognized as one of the most precise and widely used. This study utilized COMSOL Multiphysics software to simulate and compare different electrode configurations for measuring oil-air two-phase flow in an annular pattern. Results demonstrated that the proposed arrow-shaped capacitance-based sensor had 21% higher sensitivity compared to existing sensor designs, indicating its superior performance and potential for high-sensitivity applications.
Proceedings Paper
Computer Science, Artificial Intelligence
Mahyuddin K. M. Nasution, Raditya Macy Widyatamaka Nasution, Rahmad Syah, Marischa Elveny
Summary: This paper describes the human effort to address the challenges in scientific development. The limitations of biology have led to collaboration with other fields, particularly technology, resulting in the emergence of biotechnology. Another technology, computer science, is also relevant, especially in the field of data science. These fields have the potential to drive scientific and efficient studies in biotechnology, although the business sector is still in its early stages.
DATA SCIENCE AND ALGORITHMS IN SYSTEMS, 2022, VOL 2
(2023)
Article
Computer Science, Theory & Methods
Rizki Muliono, Mayang Septania Iranita, Rahmad B. Y. Syah
Summary: This study categorizes different types of Batak ulos cloth using Convolutional Neural Network (CNN) and Modular Neural Network (MNN) methods for image recognition and classification. 80% of the data was used for training, 20% for testing. The achieved accuracy is 97.83%, loss value is 0.0793, val loss is 2.1885, and val accuracy is 0.7429.
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS
(2023)
