Optimizing biodiesel production from waste with computational chemistry, machine learning and policy insights: a review

AI Osman, M Nasr, M Farghali, AK Rashwan… - Environmental …, 2024 - Springer
The excessive reliance on fossil fuels has resulted in an energy crisis, environmental
pollution, and health problems, calling for alternative fuels such as biodiesel. Here, we …

Hybrid modeling in bioprocess dynamics: Structural variabilities, implementation strategies, and practical challenges

B Mahanty - Biotechnology and Bioengineering, 2023 - Wiley Online Library
Hybrid modeling, with an appropriate blend of the mechanistic and data‐driven framework,
is increasingly being adopted in bioprocess modeling, model‐based experimental design …

Machine learning-based characterization of hydrochar from biomass: Implications for sustainable energy and material production

A Shafizadeh, H Shahbeik, S Rafiee, A Moradi… - Fuel, 2023 - Elsevier
Hydrothermal carbonization (HTC) is a process that converts biomass into versatile
hydrochar without the need for prior drying. The physicochemical properties of hydrochar …

Artificial intelligence and machine learning for smart bioprocesses

SK Khanal, A Tarafdar, S You - Bioresource Technology, 2023 - Elsevier
In recent years, the digital transformation of bioprocesses, which focuses on
interconnectivity, online monitoring, process automation, artificial intelligence (AI) and …

Challenges and opportunities in bioprocessing of gellan gum: A review

N Sahu, B Mahanty, D Haldar - International Journal of Biological …, 2024 - Elsevier
Gellan gum (GG)—the microbial exopolysaccharide is increasingly being adopted into drug
development, tissue engineering, and food and pharmaceutical products. In spite of the …

Integrated machine learning methods with oversampling technique for regional suitability prediction of waste-to-energy incineration projects

Y Hou, Q Wang, K Zhou, L Zhang, T Tan - Waste Management, 2024 - Elsevier
China's tiered strategy to enhance county-level waste incineration for energy aligns with the
sustainable development goals (SDGs), emphasizing the need for comprehensive …

Harnessing artificial intelligence for enhanced bioethanol productions: a cutting-edge approach towards sustainable energy solution

CS Damian, Y Devarajan… - International Journal of …, 2024 - degruyter.com
The adoption of biofuels as an energy source has experienced a substantial increase,
exceeding the consumption of fossil fuels. The shift can be ascribed to the availability of …

Improved estimation of dark fermentation biohydrogen production utilizing a robust categorical boosting machine-learning algorithm

AF Bandpey, J Abdi, TT Firozjaee - International Journal of Hydrogen …, 2024 - Elsevier
Dark fermentation is attracting great attention due to some capabilities such as wastewater
treatment and biofuel production. In this study, the performance of different machine learning …

Recent advancements in biomass to bioenergy management and carbon capture through artificial intelligence integrated technologies to achieve carbon neutrality

S Chauhan, P Solanki, C Putatunda, A Walia… - Sustainable Energy …, 2025 - Elsevier
Biomass, a renewable resource crucial for carbon neutrality, serves as a sustainable
alternative to fossil fuels by closing the carbon loop. The biotransformation of biomass into …

Enhanced diagnosing patients suspected of sarcoidosis using a hybrid support vector regression model with bald eagle and chimp optimizers

G **e, H Attar, A Alrosan, SMF Abdelaliem… - PeerJ Computer …, 2024 - peerj.com
Searching for a reliable indicator of treatment response in sarcoidosis remains a challenge.
The use of the soluble interleukin 2 receptor (sIL-2R) as a measure of disease activity has …