Applied machine learning for predicting the properties and carbon and phosphorus fate of pristine and engineered hydrochar

Biochar, Journal Year: 2025, Volume and Issue: 7(1)

Published: Jan. 20, 2025

Language: Английский

---

Machine learning modeling using XGBoost and LightGBM for predicting the minimum ignition temperature of rice husk dust based on the synergistic effect of dispersion pressure and crushed brown rice

Powder Technology, Journal Year: 2025, Volume and Issue: unknown, P. 120682 - 120682

Published: Jan. 1, 2025

Language: Английский

---

Machine learning-driven optimization of pretreatment and enzymatic hydrolysis of sugarcane bagasse: Analytical insights for industrial scale-up

Fuel, Journal Year: 2025, Volume and Issue: 390, P. 134682 - 134682

Published: Feb. 19, 2025

Language: Английский

---

Non-catalytic proteins as promising detoxifiers in lignocellulosic biomass pretreatment: unveiling the mechanism for enhanced enzymatic hydrolysis

Green Chemistry, Journal Year: 2023, Volume and Issue: 25(18), P. 7141 - 7156

Published: Jan. 1, 2023

Dilute acid (DA) pretreatment of biomass generates multiple inhibitory compounds within the pretreated hydrolysates.

Language: Английский

---

A recent advancement on hydrothermal carbonization of biomass to produce hydrochar for pollution control

Carbon letters, Journal Year: 2023, Volume and Issue: 33(7), P. 1909 - 1933

Published: July 24, 2023

Language: Английский

---

Holistic lignocellulosic biorefinery approach for dual production of bioethanol and xylonic acid coupled with efficient dye removal

Renewable and Sustainable Energy Reviews, Journal Year: 2023, Volume and Issue: 185, P. 113605 - 113605

Published: Aug. 4, 2023

Language: Английский

---

Harnessing a Better Future: Exploring AI and ML Applications in Renewable Energy

JOIV International Journal on Informatics Visualization, Journal Year: 2024, Volume and Issue: 8(1), P. 55 - 55

Published: March 16, 2024

Integrating machine learning (ML) and artificial intelligence (AI) with renewable energy sources, including biomass, biofuels, engines, solar power, can revolutionize the industry. Biomass biofuels have benefited significantly from implementing AI ML algorithms that optimize feedstock, enhance resource management, facilitate biofuel production. By applying insight derived data analysis, stakeholders improve entire supply chain - biomass conversion, fuel synthesis, agricultural growth, harvesting to mitigate environmental impacts accelerate transition a low-carbon economy. Furthermore, in combustion systems engines has yielded substantial improvements efficiency, emissions reduction, overall performance. Enhancing engine design control techniques produces cleaner, more efficient minimal impact. This contributes sustainability of power generation transportation. are employed analyze vast quantities photovoltaic systems' design, operation, maintenance. The ultimate goal is increase output system efficiency. Collaboration among academia, industry, policymakers imperative expedite sustainable future harness potential energy. these technologies, it possible establish ecosystem, which would benefit generations.

Language: Английский

---

Review: Biotic and abiotic approaches to artificial humic acids production

Renewable and Sustainable Energy Reviews, Journal Year: 2023, Volume and Issue: 187, P. 113771 - 113771

Published: Sept. 23, 2023

Language: Английский

---

Machine-learning-aided hydrochar production through hydrothermal carbonization of biomass by engineering operating parameters and/or biomass mixture recipes

Energy, Journal Year: 2023, Volume and Issue: 288, P. 129854 - 129854

Published: Dec. 3, 2023

Language: Английский

---

Optimizing pyrolysis and Co-Pyrolysis of plastic and biomass using Artificial Intelligence

Energy Conversion and Management X, Journal Year: 2024, Volume and Issue: 24, P. 100783 - 100783

Published: Oct. 1, 2024

Language: Английский

---