Applied Chemical Engineering

AI-Driven Optimization of Bio-Energy Systems: Models for Resource Assessment and Emission Reduction

Sajal Suhane

Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, Texas, USA-75080.

Rushali Rajaram Katkar

Department of Computer Engineering, Army Institute of Technology, Dighi Hills, Pune-411015, Maharashtra, India.

Smita Suhane

Department of First Year Engineering (Engineering Chemistry), Dr. D. Y. Patil Institute of Technology, Sant Tukaram Nagar, Pimpri, Pune - 411018, Maharashtra, India;Dnyaan Prasad Global University (DPGU), School of Technology and Research - Dr. D. Y. Patil Unitech Society, Sant Tukaram Nagar, Pimpri - 411018, Pune, Maharashtra, India.

S. Sugumaran

Department of Electronics and Communication Engineering, Vishnu Institute of Technology, Bhimavaram - 534202, Andhra Pradesh, India.

Santosh Bhauso Takale

MCA Department (Commerce and Management), Vishwakarma University, Laxminagar, Kondhwa (Bk.), Pune – 411048, Maharashtra, India.

Surekha Dehu Khetree

Department of Mechanical Engineering, Bharati Vidyapeeth College of Engineering, Navi Mumbai – 400614, Maharashtra, India.

Shyamsing Thakur

Department of Mechanical Engineering, D. Y. Patil College of Engineering, Akurdi – 411044, Pune, Maharashtra, India, Affiliated to Savitribai Phule Pune University, Maharashtra, India.

Shital Yashwant Waware

Department of Mechanical Engineering, Dr. D. Y. Patil Institute of Technology, Sant Tukaram Nagar, Pimpri - 411018, Pune, Maharashtra, India. ; Dnyaan Prasad Global University (DPGU), School of Technology and Research - Dr. D. Y. Patil Unitech Society, Sant Tukaram Nagar, Pimpri - 411018, Pune, Maharashtra, India.

Anant Sidhappa Kurhade

Department of Mechanical Engineering, Dr. D. Y. Patil Institute of Technology, Sant Tukaram Nagar, Pimpri - 411018, Pune, Maharashtra, India. ; Dnyaan Prasad Global University (DPGU), School of Technology and Research - Dr. D. Y. Patil Unitech Society, Sant Tukaram Nagar, Pimpri - 411018, Pune, Maharashtra, India.

DOI: https://doi.org/10.59429/ace.v9i1.5837

Keywords: Artificial intelligence in bio-energy; biomass resource assessment; machine-learning optimization; bio-energy supply chains; emission prediction and mitigation; sustainable energy systems.

---

Abstract

The increasing complexity of bio-energy systems is a reason for the need of advanced analytical methods to enhance resource utilization, process stability and environmental performance. AI methods are popular in this domain, but many papers neglect concerns around data quality, interpretability, scalability and the low generalization potential of models toward plants and feedstocks different from those they were trained on. This paper intends to offer a systematic review on AI techniques available for biomass resource assessment, conversion-process optimization, and supply-chain planning and emission management. The review is structured adopting a rigorous review approach focusing on model, data set, optimization framework and hybrid method developed in the scope of bio-energy value chain. Highlights – The key findings are that AI improves the prediction of biomass availability and biogas/syngas yields, of feedstock properties and emission behavior; surrogate and hybrid models result in expedited simulation time and facilitate real-time decision making. The review also highlights an emerging trend with digital twins, remote sensing with application of machine learning, and federated learning in multi-plant optimization. These findings also have important implications for researchers, engineers and policy-makers who aim to develop robust low emissions bio-energy systems that are economically feasible.

---

References

[1]. Wang Z, Peng X, Xia A, Shah AA, Huang Y, Zhu X, Zhu X, Liao Q. The role of machine learning to boost the bioenergy and biofuels conversion. Bioresource Technology. Elsevier BV; 2021 Oct 8;343:126099. https://doi.org/10.1016/j.biortech.2021.126099

[2]. Anbarasu K, Sundaram T, Sathishkumar K, Alam MM, Al-Sehemi AG, Devarajan Y. Harnessing artificial intelligence for sustainable bioenergy: optimization, waste reduction, and environmental sustainability. Bioresource Technology. Elsevier BV; 2024 Nov 1;131893. https://doi.org/10.1016/j.biortech.2024.131893

[3]. Liao M, Yao Y. Applications of artificial intelligence-based modeling for bioenergy systems: A review. GCB Bioenergy. Wiley; 2021 Feb 18;13(5):774. https://doi.org/10.1111/gcbb.12816

[4]. Meena MK, Shubham S, Paritosh K, Pareek N, Vivekanand V. Production of biofuels from biomass: predicting the energy employing artificial intelligence modelling. Bioresource Technology. Elsevier BV; 2021 Jul 23;340:125642. https://doi.org/10.1016/j.biortech.2021.125642

[5]. Deshpande SV, Pawar RS, Keche AJ, Kurhade A. Real-time surface finish measurement of stepped holding shaft by automatic system. J Adv Manuf Syst. 2025 Feb 25:1-26.

[6]. Ramani P, Reji V, Sathish Kumar V, Murali G, Kurhade AS. Deep learning-based detection and classification of moss and crack damage in rock structures for geo-mechanical preservation. J Mines Met Fuels. 2025 Mar 1;73(3). https://doi.org/10.18311/jmmf/2025/47760

[7]. Kurhade AS, Siraskar GD, Deshmukh MT, Patil PA, Chaudhari SS, Kadam AA, Dolas AS, Mahajan RG, Waware SY, Yadav RS. Impact of PCM on heat dissipation from IC chips. J Mines Met Fuels. 2025 Mar 1;73(3). https://doi.org/10.18311/jmmf/2025/47522

[8]. Kurhade AS, Kharat PV, Chougule SM, Darade MM, Karad MM, Murali G, Charwad GA, Waware SY, Yadav RS. Harnessing the power of plastic waste: a sustainable approach to fuel production. J Mines Met Fuels. 2025 Feb 1;73(2). https://doi.org/10.18311/jmmf/2025/47354

[9]. Sarode GC, Gholap P, Pathak KR, Vali PSNM, Saharkar U, Murali G, Kurhade AS. Edge AI and explainable models for real-time decision-making in ocean renewable energy systems. Sustain Mar Struct. 2025 Jun 24;7(3):17-42. https://doi.org/10.36956/sms.v7i3.2239

[10]. Chougule SM, Murali G, Kurhade AS. Dynamic simulation and performance evaluation of vibratory bowl feeders integrated with paddle shaft mechanisms. Adv Sci Technol Res J. 2025;19(7). https://doi.org/10.12913/22998624/203873

[11]. Chougule SM, Murali G, Kurhade AS. Design and analysis of industrial material handling systems using FEA and dynamic simulation techniques. J Sci Ind Res. 2025 Jun 18;84(6):645-53. https://doi.org/10.56042/jsir.v84i6.17512

[12]. Kurhade AS, Siraskar GD, Raut PN, Dolas AS, Murali G, Dalvi SA, Waware SY, Yadav RS. Investigating the impact of oxygenated additives on exhaust emissions from unleaded gasoline vehicles. J Mines Met Fuels. 2025 Feb 1;73(2). https://doi.org/10.18311/jmmf/2025/47410

[13]. Siraskar GD, Kurhade AS, Murali G, Prakash MA, Bharathiraja N, Dharmadhikari DD, Waware SY. Turbulence model comparison and optimal geometry identification in trapped vortex combustors: a RANS-based study. Int J Mod Phys C. 2025 Sep 24:2650020. https://doi.org/10.1142/S0129183126500208

[14]. Keloth Kaithari D, Kaulage A, Ayyappadas MT, Gholap P, Puri A, Bhandari MA, et al. A review of smart AI systems for real-time monitoring and optimization of ocean-based carbon capture, utilization, and storage networks. Appl Chem Eng. 2025 Sep 17;8(3):ACE-5747. https://doi.org/10.59429/ace.v8i3.5747

[15]. Dhamdhere P, Dixit SM, Tatiya M, Shinde BA, Deone J, Kaulage A, et al. AI-based monitoring and management in smart aquaculture for ocean fish farming systems. Appl Chem Eng. 2025 Sep 17;8(3):ACE-5746. https://doi.org/10.59429/ace.v8i3.5746

[16]. Keloth Kaithari D, Ayyappadas MT, Goel S, Shahin A, Patil SK, Chaudhari SS, et al. A review on GA-NN based control strategies for floating solar-ocean hybrid energy platforms. Appl Chem Eng. 2025 Sep 15;8(3):ACE-5745. https://doi.org/10.59429/ace.v8i3.5745

[17]. Khan M, Chuenchart W, Surendra KC, Khanal SK. Applications of artificial intelligence in anaerobic co-digestion: recent advances and prospects. Bioresource Technology. Elsevier BV; 2022 Dec 17;370:128501. https://doi.org/10.1016/j.biortech.2022.128501

[18]. Kabir M, Ekici S. Energy-agriculture nexus: exploring the future of artificial intelligence applications. Energy Nexus. 2023 Dec 24;13:100263. https://doi.org/10.1016/j.nexus.2023.100263

[19]. Olatunji KO, Oladipo S, Madyira DM, Sun Y. Performance evaluation of clustering techniques and parameters of hybrid PSO- and GA-ANFIS for biomethane yield of alkali-pretreated groundnut shells. Waste and Biomass Valorization. 2024 Aug 5. https://doi.org/10.1007/s12649-024-02674-2

[20]. Zheng Y, Larsen OC, Muhayodin F, Hu J, Xue B, Rotter VS. Review of anaerobic digestion models for organic solid waste treatment with focus on C, N, and P cycles. Energy Ecology and Environment. 2024 Nov 28. https://doi.org/10.1007/s40974-024-00343-7

[21]. Chen L, He P, Zhang H, Peng W, Qiu J, Lü F. Applications of machine learning tools for biological treatment of organic wastes: perspectives and challenges. Circular Economy. 2024 May 31;3(2):100088. https://doi.org/10.1016/j.cec.2024.100088

[22]. Gupta R, Zhang L, Hou J, Zhang Z, Liu H, You S, Ok YS, Li W. Review of explainable machine learning for anaerobic digestion. Bioresource Technology. Elsevier BV; 2022 Dec 9;369:128468. https://doi.org/10.1016/j.biortech.2022.128468

[23]. Metwally A, Abo-bakr RM, Ahmed DS. Sustainable methane energy from bagasse treated via bokashi technology: neural network vs mathematical modeling. Clean Technologies and Environmental Policy. 2023 Oct 10;26(3):661. https://doi.org/10.1007/s10098-023-02601-4

[24]. Rutland H, You J, Liu H, Bowman K. Machine learning for FOS/TAC soft sensing in bio-electrochemical anaerobic digestion. Molecules. 2025 Feb 27;30(5):1092. https://doi.org/10.3390/molecules30051092

[25]. Zhang P, Zhang T, Zhang J, Liu H, Chicaiza-Ortiz C, Lee JTE, He Y, Dai Y, Tong YW. Machine-learning-assisted prediction of potential biochar for anaerobic digestion. Carbon Neutrality. 2024 Jan 8;3(1). https://doi.org/10.1007/s43979-023-00078-0

[26]. Osman AI, Nasr M, Farghali M, Rashwan AK, Abdelkader A, Al-Muhtaseb AH, Ihara I, Rooney DW. Optimizing biodiesel production from waste using computational chemistry and machine learning. Environmental Chemistry Letters. 2024 Feb 13;22(3):1005. https://doi.org/10.1007/s10311-024-01700-y

[27]. Achinas S, Quintero M de JD, Euverink GJW. Machine learning in the biogas power industry. Frontiers in Energy Research. 2025 Oct 1;13. https://doi.org/10.3389/fenrg.2025.1589782

[28]. Andiappan V, How BS, Ngan SL. Post-pandemic biomass supply chains: opportunities and challenges. Process Integration and Optimization for Sustainability. 2021 Jul 15;5(4):1003. https://doi.org/10.1007/s41660-021-00176-5

[29]. Nair LG, Verma P. Carbon potential of lignocellulosic biomass and the role of machine learning in biorefineries. Bioresources and Bioprocessing. 2025 Sep 13;12(1). https://doi.org/10.1186/s40643-025-00935-z

[30]. Blay-Roger R, Saif M, Bobadilla LF, Reina TR, Nawaz MA, Odriozola JA. Bioenergy innovations for a sustainable energy future. Frontiers in Chemistry. 2024 Jul 30;12. https://doi.org/10.3389/fchem.2024.1416102

[31]. Ghani WAWAK et al. Sustainable bio-economy achievements in Malaysia. Food and Bioproducts Processing. 2019 Sep 17;118:167. https://doi.org/10.1016/j.fbp.2019.09.002

[32]. Pirotti F, González-Olabarria JR, Kutchartt E. Updating aboveground biomass using satellite data and AI. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences. 2023 Dec 14;1763. https://doi.org/10.5194/isprs-archives-xlviii-1-w2-2023-1763-2023

[33]. Aal MAMA. Matheuristic approach and a mixed-integer linear programming model for biomass supply chain optimization with demand selection. International Journal of Industrial Engineering Computations. 2023 Dec 22;15(1):235. https://doi.org/10.5267/j.ijiec.2023.10.001

[34]. Li F, Li Y, Novoselov KS, Liang F, Meng J, Ho S, Zhao T, Zhou H, Ahmad A, Zhu Y, Hu L, Ji D, Jia L, Liu R, Ramakrishna S, Zhang X. Bioresource upgrade for sustainable energy, environment, and biomedicine. Nano-Micro Letters. Springer; 2023 Jan 11;15(1). https://doi.org/10.1007/s40820-022-00993-4

[35]. Ahmad I, Sana A, Kano M, Cheema II, Menezes BC, Shahzad J, Ullah Z, Khan M, Habib A. Machine learning applications in biofuels’ life cycle: soil, feedstock, production, consumption, and emissions. Energies. 2021 Aug 18;14(16):5072. https://doi.org/10.3390/en14165072

[36]. Ascher S, Watson I, You S. Machine learning methods for modelling gasification and pyrolysis of biomass and waste. Renewable and Sustainable Energy Reviews. 2021 Nov 20;155:111902. https://doi.org/10.1016/j.rser.2021.111902

[37]. Jeon PR, Moon JH, Ogunsola NO, Lee SH, Ling JLJ, You S, Park YK. Recent advances and future prospects of thermochemical biofuel conversion processes with machine learning. Chemical Engineering Journal. 2023 Jul 1;471:144503. https://doi.org/10.1016/j.cej.2023.144503

[38]. Li J, Li L, Tong YW, Wang X. Understanding and optimizing gasification of biomass waste with machine learning. Green Chemical Engineering. 2022 May 27;4(1):123. https://doi.org/10.1016/j.gce.2022.05.006

[39]. Wang C. A novel biomass fluidized bed gasification model coupled with machine learning and CFD simulation. arXiv. 2025 Sep 7. http://arxiv.org/abs/2509.06056

[40]. Kurhade AS, Gadekar T, Siraskar GD, Jawalkar SS, Biradar R, Kadam AA, Yadav RS, Dalvi SA, Waware SY, Mali CN. Thermal performance analysis of electronic components on different substrate materials. J Mines Met Fuels. 2024 Oct 1;72(10). https://doi.org/10.18311/jmmf/2024/45569

[41]. Kurhade AS, Siraskar GD, Jawalkar SS, Gadekar T, Bhambare PS, Biradar R, Yadav RS, Waware SY, Mali CN. The impact of circular holes in twisted tape inserts on forced convection heat transfer. J Mines Met Fuels. 2024 Oct 16;72(9):1005-12. https://doi.org/10.18311/jmmf/2024/45505

[42]. Kurhade AS, Bhambare PS, Desai VP, Murali G, Yadav RS, Patil P, Gadekar T, Biradar R, Kirpekar S, Charwad GA, Waware SY. Investigating the effect of heat transfer influenced by wavy corrugated twisted tape inserts in double pipe heat exchangers. J Adv Res Fluid Mech Therm Sci. 2024;122:146-55. https://doi.org/10.37934/arfmts.122.2.146155

[43]. Kurhade AS, Murali G, Jadhav PA, Bhambare PS, Waware SY, Gadekar T, Yadav RS, Biradar R, Patil P. Performance analysis of corrugated twisted tape inserts for heat transfer augmentation. J Adv Res Fluid Mech Therm Sci. 2024;121(2):192-200. https://doi.org/10.37934/arfmts.121.2.192200

[44]. Yadav RS, Nimbalkar A, Gadekar T, Patil P, Patil VN, Gholap AB, Kurhade AS, Dhumal JR, Waware SY. Comparison of experimental and numerical investigation of mono-composite and metal leaf spring. J Mines Met Fuels. 2024 Aug 1;72(8). https://doi.org/10.18311/jmmf/2024/45325

[45]. Kurhade AS, Warke P, Maniyar K, Bhambare PS, Waware SY, Deshpande S, Harsur S, Ingle M, Kolhe P, Patil PA, Jadhav P. Wind rose analysis of temperature variation with sensor implantation technique for wind turbine. J Adv Res Fluid Mech Therm Sci. 2024;122(1):1-8. https://doi.org/10.37934/arfmts.122.1.118

[46]. Kurhade AS, Siraskar GD, Bhambare PS, Kaithari DK, Dixit SM, Waware SY. Enhancing smartphone circuit cooling: a computational study of PCM integration. J Adv Res Numer Heat Trans. 2024 Nov 30;27(1):132-45. https://doi.org/10.37934/arnht.27.1.132145

[47]. Kurhade AS, Darade MM, Siraskar GD, Biradar R, Mahajan RG, Kardile CS, Waware SY, Yadav RS. State-of-the-art cooling solutions for electronic devices operating in harsh conditions. J Mines Met Fuels. 2024 Aug 1;72(8). https://doi.org/10.18311/jmmf/2024/45374

[48]. Yadav RS, Gadekar T, Gundage V, Patil P, Patil A, Patil P, Patil A, Sutar R, Kurhade AS. Numerical and experimental investigation of the effect of overlapping angle on strength and deformation of curved plate joined using arc welding process. J Mines Met Fuels. 2024 Oct 1;72(10). https://doi.org/10.18311/jmmf/2024/45697

[49]. Kurhade AS, Bhambare PS, Siraskar GD, Dixit SM, Purandare PS, Waware SY. Computational study on thermal management of IC chips with phase change materials. J Adv Res Numer Heat Trans. 2024;26(1):34-43. https://doi.org/10.37934/arnht.26.1.3443

[50]. Yadav RS, Gandhi P, Veeranjaneyulu K, Gaji R, Kirpekar S, Pawar D, Khairnar YS, Patil S, Kurhade AS, Patil SP. Influence of plate thickness on the mechanical behaviour of mild steel curved plates: an experimental study. J Mines Met Fuels. 2024 Dec 1;72(12). https://doi.org/10.18311/jmmf/2024/46253

[51]. Chippalkatti S, Chekuri RB, Ohol SS, Shinde NM, Barmavatu P, Shelkande VD, Murali G, Kurhade AS. Enhancing heat transfer in micro-channel heat sinks through geometrical optimization. J Mines Met Fuels. 2025 Mar 1;73(3). https://doi.org/10.18311/jmmf/2025/47773

[52]. Raut PN, Dolas AS, Chougule SM, Darade MM, Murali G, Waware SY, Kurhade AS. Green adsorbents for heavy metal removal: a study on zinc ion uptake by Tinospora cordifolia biocarbon. J Mines Met Fuels. 2025 Jan 1;73(1). https://doi.org/10.18311/jmmf/2025/47121

[53]. Kurhade AS, Siraskar GD, Bhambare PS, Murali G, Deshpande SV, Warke PS, Waware SY. Simulation and analysis of heat transfer in counter-flow helical double-pipe heat exchangers using CFD. Int J Mod Phys C. 2025 Mar 15. https://doi.org/10.1142/S0129183125500433

[54]. Patil Y, Tatiya M, Dharmadhikari DD, Shahakar M, Patil SK, Mahajan RG, Kurhade AS. The role of AI in reducing environmental impact in the mining sector. J Mines Met Fuels. 2025 May 1;73(5).

[55]. Waware SY, Ahire PP, Napate K, Biradar R, Patil SP, Kore SS, Kurhade AS. Advancements in heat transfer enhancement using perforated twisted tapes: a comprehensive review. J Mines Met Fuels. 2025 May 1;73(5). https://doi.org/10.18311/jmmf/2025/48438

[56]. Chougule SM, Murali G, Kurhade AS. Finite element analysis and design optimization of a paddle mixer shaft. J Mines Met Fuels. 2025 May 1;73(5). https://doi.org/10.18311/jmmf/2025/48664

[57]. Chougule SM, Murali G, Kurhade AS. Failure investigation of the driving shaft in an industrial paddle mixer. J Mines Met Fuels. 2025 May 1;73(5). https://doi.org/10.18311/jmmf/2025/48627

[58]. Kurhade AS, Sugumaran S, Kolhalkar NR, Karad MM, Mahajan RG, Shinde NM, Dalvi SA, Waware SY. Thermal management of mobile devices via PCM. J Mines Met Fuels. 2025 May 1;73(5):1313-20. https://doi.org/10.18311/jmmf/2025/48437

[59]. Kurhade AS, Bhavani P, Patil SA, Kolhalkar NR, Chalapathi KS, Patil PA, Waware SY. Mitigating environmental impact: a study on the performance and emissions of a diesel engine fueled with biodiesel blend. J Mines Met Fuels. 2025 Apr 1;73(4):981-9. https://doi.org/10.18311/jmmf/2025/47669

[60]. Kurhade AS, Siraskar GD, Chekuri RB, Murali G, Pawar P, Patil AR, Waware SY, Yadav RS. Biodiesel blends: a sustainable solution for diesel engine performance improvement. J Mines Met Fuels. 2025 Mar 1;73(3). https://doi.org/10.18311/jmmf/2025/47628

[61]. Kurhade AS, Siraskar GD, Darade MM, Murali G, Katkar TR, Patil SP, Charwad GA, Waware SY, Yadav RS. Enhancement in heat transfer with nanofluids in double-pipe heat exchangers. J Mines Met Fuels. 2025 Jan 7;73(1):165-72. https://doi.org/10.18311/jmmf/2025/47225

[62]. Napte K, Kondhalkar GE, Patil SV, Kharat PV, Banarase SM, Kurhade AS, Waware SY. Recent advances in sustainable concrete and steel alternatives for marine infrastructure. Sustain Mar Struct. 2025 Jun 4:107-31. https://doi.org/10.36956/sms.v7i2.2072

[63]. Kurhade AS, Chougule SM, Kharat PV, Kondhalkar GE, Murali G, Raut PN, Charwad GA, Waware SY, Yadav RS. Integrated approach to enhance vehicle safety: a novel bumper design with energy-absorbing mechanisms. J Mines Met Fuels. 2025 Jan 1;73(1). https://doi.org/10.18311/jmmf/2025/47168

[64]. Yadav R, Nimbalkar A, Kirpekar S, Patil PJ, Dalvi SA, Jadhav PA, Kurhade AS, Wakchaure GN. Effect of transformed-induced plasticity steel plate thickness on ultimate tensile strength of butt welded joint using Nd:YAG laser. Int J Veh Struct Syst. 2024;16(6):857-62. https://doi.org/10.4273/ijvss.16.6.08

[65]. Jalalifar S, Masoudi M, Abbassi R, Garaniya V, Ghiji M, Salehi F. A hybrid SVR-PSO model to predict a CFD-based optimised bubbling fluidised bed pyrolysis reactor. Energy. 2019 Nov 7;191:116414. https://doi.org/10.1016/j.energy.2019.116414

[66]. Wang Z, Mu L, Miao H, Shang Y, Yin H, Dong M. Machine learning prediction of syngas properties in biomass chemical looping gasification using extra trees regression. Energy. 2023 Apr 5;275:127438. https://doi.org/10.1016/j.energy.2023.127438

[67]. Khandelwal K, Dalai AK. Machine-learning-based prediction of gas yields in supercritical water gasification of lignocellulosic biomass. Molecules. 2024 May 16;29(10):2337. https://doi.org/10.3390/molecules29102337

[68]. Kargbo HO, Zhang J, Phan AN. Optimisation of two-stage biomass gasification for hydrogen production via artificial neural network. Applied Energy. 2021 Aug 20;302:117567. https://doi.org/10.1016/j.apenergy.2021.117567

[69]. Marzban N, Psarianos M, Herrmann C, Schulz-Nielsen L, Olszewska-Widdrat A, Arefi A, Pecenka R, Grundmann P, Schlüter O, Hoffmann T, Rotter VS, Nikoloski Z, Sturm B. Smart integrated biorefineries for zero-waste and self-sufficient energy systems. Biofuel Research Journal. 2025 Mar 1;12(1):2319. https://doi.org/10.18331/brj2025.12.1.4

[70]. Parveen F, Slater AG. Digitalisation of catalytic processes for sustainable biobased chemical production. Catalysis Science & Technology. 2025 Jan 1. https://doi.org/10.1039/d4cy01525h

[71]. Cao L, Su J, Saddler J, Cao Y, Wang Y, Lee G, Siang LC, Pinchuk R, Li J, Gopaluni RB. Real-time tracking of renewable carbon content with AI-aided methods for biofeedstock co-processing. Applied Energy. 2024 Feb 10;360:122815. https://doi.org/10.1016/j.apenergy.2024.122815

[72]. Habibi F, Chakrabortty RK, Abbasi A. Addressing uncertainties in biofuel supply chains: a systematic review. Environmental Science and Pollution Research. 2023 Sep 2;30(45):100360. https://doi.org/10.1007/s11356-023-29331-w

[73]. Nneoma UC, Chukwudi OF, Nnenna UJ, Ugwu OPC. Hybrid biofactories integrating microalgae and engineered microbiomes for improved biofuel production. Frontiers in Energy Research. 2025 Sep 23;13. https://doi.org/10.3389/fenrg.2025.1654079

[74]. Sahebi IG, Edalatipour A, Dabaghiroodsari M, Hasheminasab SMH, Masoomi B, Kamali SE. AI-driven transformation of renewable energy supply chains: a strategic roadmap. Energy for Sustainable Development. 2025 Feb 8;85:101663. https://doi.org/10.1016/j.esd.2025.101663

[75]. Srivastava S, Shardeo V, Dwivedi A, Paul SK. Enablers of artificial intelligence for decarbonization in circular supply chains. Annals of Operations Research. 2025 Oct 14. https://doi.org/10.1007/s10479-025-06843-x

[76]. Hao X, Demir E. Artificial intelligence in supply chain decision-making: ESG-related drivers and technological barriers. Journal of Modelling in Management. 2023 Jul 13;19(2):605. https://doi.org/10.1108/jm2-01-2023-0009

[77]. Devarakota P, Tsesmetzis N, Alpak FO, Gala A, Hohl D. AI and the net-zero journey: energy demand, emissions, and transition pathways. arXiv. 2025 Jul 14. http://arxiv.org/abs/2507.10750

[78]. Джусупова Р, Bosch J, Olsson HH. Strategic pathways for AI integration in engineering companies. Journal of Systems and Software. 2023 Dec 24;210:111945. https://doi.org/10.1016/j.jss.2023.111945

[79]. Onunka O, Orikpete OF, Daraojimba C, Fawole AA, Egbokhaebho BA, Gidiagba JO. The role of ICT in climate change mitigation and adaptation. Ecofeminism and Climate Change. 2023 Jun 20;4(2):102. https://doi.org/10.26480/efcc.02.2023.102.111

[80]. Rinchi O, Alsharoa A, Shatnawi I, Arora A. Intelligent transportation systems and AI for energy efficiency and emission reduction. arXiv. 2024 Jan 25. http://arxiv.org/abs/2401.14560

[81]. Oliveira P, Marcondes FS, Duarte MS, Durães D, Gonçalves C, Martins G, Nováis P. Incdualpathnet: a hybrid architecture for predicting energy production in wastewater treatment plants. Neural Computing and Applications. 2025 Aug 15. https://doi.org/10.1007/s00521-025-11545-3

[82]. Hua J, Wang R, Hu YC, Chen Z, Chen L, Osman AI, Farghali M, Huang L, Feng J, Wang H, Zhang X, Zhou X, Yap P. Artificial intelligence for calculating and predicting building carbon emissions: a review. Environmental Chemistry Letters. 2025 Mar 21. https://doi.org/10.1007/s10311-024-01799-z

[83]. Chen L, Chen Z, Zhang Y, Liu Y, Osman AI, Farghali M, Hua J, Al-Fatesh AS, Ihara I, Rooney DW, Yap P. Artificial intelligence-based solutions for climate change. Environmental Chemistry Letters. 2023 Jun 13;21(5):2525. https://doi.org/10.1007/s10311-023-01617-y

[84]. Fang B, Yu J, Chen Z, Osman AI, Farghali M, Ihara I, Hamza E, Rooney DW, Yap P. Artificial intelligence for waste management in smart cities: a review. Environmental Chemistry Letters. 2023 May 9;21(4):1959. https://doi.org/10.1007/s10311-023-01604-3

[85]. Mohanty R, Balachandra P, Dasappa S. Circular economy framework for agro-waste to ethanol-based supply chains in Karnataka, India. Frontiers in Sustainability. 2024 Jun 26;5. https://doi.org/10.3389/frsus.2024.1232611

[86]. Wang H. Integrating machine learning into life cycle assessment: review and future outlook. PLOS Climate. 2025 Oct 16;4(10). https://doi.org/10.1371/journal.pclm.0000732

[87]. Pérez-Almada D, Galán-Martín Á, Contreras M del M, Castro E. Techno-economic and environmental assessment of biorefineries: review and future directions. Sustainable Energy & Fuels. 2023 Jan 1;7(17):4031. https://doi.org/10.1039/d3se00405h

[88]. Hasan MR. AI-enhanced decision-making for sustainable supply chains in the USA. arXiv. 2024 Dec 8. http://arxiv.org/abs/2501.10364

[89]. Wang X, Dong X, Zhang Z, Wang Y. Transportation carbon reduction technologies: fundamentals, applications, and performance. Journal of Traffic and Transportation Engineering. Elsevier BV; 2024 Dec 1. https://doi.org/10.1016/j.jtte.2024.11.001

[90]. Wang Q. Towards zero-emission urban mobility using AI and LCA for targeted interventions. Building Simulation. 2024 Oct 1;17(10):1653. https://doi.org/10.1007/s12273-024-1193-7

[91]. Bencekri M, Kim S, Fan YV, Lee S. Identifying carbon-neutral mobility hubs using artificial intelligence. Scientific Reports. 2024 May 29;14(1). https://doi.org/10.1038/s41598-024-62701-z

[92]. Luo S, Hu W, Huang Q, Chen Z. Prospects of artificial intelligence in low-carbon energy transitions. Science China Technological Sciences. 2023 Jun 26;66(7):2158. https://doi.org/10.1007/s11431-022-2329-3

[93]. Yu S, You L, Zhou S. Optimization modeling and solution methods in renewable energy systems: a review. Frontiers of Engineering Management. 2023 Nov 22;10(4):640. https://doi.org/10.1007/s42524-023-0271-3

[94]. Ayadi R, Forouheshfar Y, Moghadas O. Enhancing system resilience to climate change using artificial intelligence: a systematic review. Frontiers in Climate. 2025 Aug 18;7. https://doi.org/10.3389/fclim.2025.1585331

[95]. Shah M, Wever M, Espig M. Framework for assessing AI potential in the circular bioeconomy. Sustainability. 2025 Apr 15;17(8):3535. https://doi.org/10.3390/su17083535

[96]. Lange L, Skiadas IV, Gavala HN, Jensen AD, Sárossy Z, Thomsen TP, Dam-Johansen K, Meyer AS, Angelidaki İ. Sustainable bioenergy and biofuels innovation challenge. Research Portal Denmark. 2018 Jan 1;63. https://local.forskningsportal.dk/local/dki-cgi/ws/cris-link?src=dtu&id=dtu-b1645ffa-393f-4c34-a8fc-2bdbea3c9970

[97]. Goldenits G, Mallinger K, Raubitzek S, Neubauer T. Reinforcement learning-based digital twins in agriculture: current applications and future directions. Smart Agricultural Technology. 2024 Aug 1;8:100512. https://doi.org/10.1016/j.atech.2024.100512

[98]. Rehan M, Nizami A, Tabatabaei M, Amjad M, Qyyum MA, Javed MH, Al-Muhtaseb AH, Ali AM, Ahmad A, Μουστάκας Κ, Lam SS, Ali I, Farooq M. Integrated waste biorefineries and sustainable development goals: editorial. Frontiers in Energy Research. 2023 Dec 13;11. https://doi.org/10.3389/fenrg.2023.1339666

[99]. Taware RD, Deshmukh A, Singh C, Rathod N. Magnitude of data science & big data in fitness care. InAIP Conference Proceedings 2025 Feb 14 (Vol. 3162, No. 1, p. 020020). AIP Publishing LLC.

[100]. Singh C, Khilari S, Taware R. Active Machine-to-Machine (M2M) and IoT Communication Architecture for Mobile Devices and Sensor Nodes. InInternational Conference on Internet of Things and Connected Technologies 2023 Oct 12 (pp. 25-38). Singapore: Springer Nature Singapore.

[101]. Taware R, Godase M, Singh C. IoT-Enabled Wearable Sensors for Real-Time Stress Monitoring Using Machine Learning Classifiers. InInternational Conference on Internet of Things and Connected Technologies 2024 Sep 27 (pp. 109-122). Singapore: Springer Nature Singapore.

[102]. Bhambare PS, Kaulage A, Darade MM, Murali G, Dixit SM, Vali PSNM, et al. Artificial intelligence for sustainable environmental management in the mining sector: a review. Appl Chem Eng. 2025 Sep 18;8(3):ACE-5756. https://doi.org/10.59429/ace.v8i3.5756

[103]. Dharmadhikari DD, Ray A, Shinde BA, Raut SV, Taware RD, Desai S, et al. Machine learning applications in ore grade estimation and blending optimization for modern mining. Appl Chem Eng. 2025 Nov 6;8(4):ACE-5790. https://doi.org/10.59429/ace.v8i4.5790

[104]. Tatiya M, Darade MM, Shinde BA, Kumbhare MP, Taware RD, Chougule SM, et al. AI applications in tailings and waste management: improving safety, recycling, and water utilization. Appl Chem Eng. 2025 Nov 5;8(4):ACE-5789. https://doi.org/10.59429/ace.v8i4.5789

[105]. Upadhe SN, Mhamane SC, Kurhade AS, Bapat PV, Dhavale DB, Kore LJ. Water saving and hygienic faucet for public places in developing countries. In: Techno-Societal 2018: Proceedings of the 2nd International Conference on Advanced Technologies for Societal Applications. Vol 1. Cham: Springer; 2019. p. 617-24. https://doi.org/10.1007/978-3-030-16848-3_56

[106]. Kurhade AS, Siraskar GD, Darade MM, Dhumal JR, Kardile CS, Biradar R, Patil SP, Waware SY. Predicting heat transfer enhancement with twisted tape inserts using fuzzy logic techniques in heat exchangers. J Mines Met Fuels. 2024;72(7):743-50. https://doi.org/10.18311/jmmf/2024/45348

[107]. Kurhade AS, Siraskar GD, Kondhalkar GE, Darade MM, Yadav RS, Biradar R, Waware SY, Charwad GA. Optimizing aerofoil design: a comprehensive analysis of aerodynamic efficiency through CFD simulations and wind tunnel experiments. J Mines Met Fuels. 2024;72(7):713-24. https://doi.org/10.18311/jmmf/2024/45361

[108]. Kurhade AS, Kadam AA, Biradar R, Bhambare PS, Gadekar T, Patil P, Yadav RS, Waware SY. Experimental investigation of heat transfer from symmetric and asymmetric IC chips mounted on the SMPS board with and without PCM. J Adv Res Fluid Mech Therm Sci. 2024;121(1):137-47. https://doi.org/10.37934/arfmts.121.1.137147

[109]. Kurhade AS, Siraskar GD, Bhambare PS, Dixit SM, Waware SY. Numerical investigation on the influence of substrate board thermal conductivity on electronic component temperature regulation. J Adv Res Numer Heat Trans. 2024;23(1):28-37. https://doi.org/10.37934/arnht.23.1.2837

[110]. Kurhade AS, Waware SY, Munde KH, Biradar R, Yadav RS, Patil P, Patil VN, Dalvi SA. Performance of solar collector using recycled aluminum cans for drying. J Mines Met Fuels. 2024 May 1;72(5). https://doi.org/10.18311/jmmf/2024/44643

[111]. Kurhade AS, Kardekar NB, Bhambare PS, Waware SY, Yadav RS, Pawar P, Kirpekar S. A comprehensive review of electronic cooling technologies in harsh field environments: obstacles, progress, and prospects. J Mines Met Fuels. 2024;72(6):557-79. https://doi.org/10.18311/jmmf/2024/45212

[112]. Kurhade AS, Waware SY, Bhambare PS, Biradar R, Yadav RS, Patil VN. A comprehensive study on Calophyllum inophyllum biodiesel and dimethyl carbonate blends: performance optimization and emission control in diesel engines. J Mines Met Fuels. 2024;72(5):499-507. https://doi.org/10.18311/jmmf/2024/45188

[113]. Kurhade AS, Biradar R, Yadav RS, Patil P, Kardekar NB, Waware SY, Munde KH, Nimbalkar AG, Murali G. Predictive placement of IC chips using ANN-GA approach for efficient thermal cooling. J Adv Res Fluid Mech Therm Sci. 2024;118(2):137-47. https://doi.org/10.37934/arfmts.118.2.137147

[114]. Waware SY, Chougule SM, Yadav RS, Biradar R, Patil P, Munde KH, Kardekar NB, Nimbalkar AG, Kurhade AS, Murali G, Kore SS. A comprehensive evaluation of recent studies investigating nanofluids utilization in heat exchangers. J Adv Res Fluid Mech Therm Sci. 2024;119(2):160-72. https://doi.org/10.37934/arfmts.119.2.160172

[115]. Kurhade AS, Murali G, Rao TV. CFD approach for thermal management to enhance the reliability of IC chips. Int J Eng Trends Technol. 2022;71(3):65-72. https://doi.org/10.14445/22315381/IJETT-V71I3P208

[116]. Kurhade AS, Rao TV, Mathew VK, Patil NG. Effect of thermal conductivity of substrate board for temperature control of electronic components: a numerical study. Int J Mod Phys C. 2021 Oct 26;32(10):2150132. https://doi.org/10.1142/S0129183121501321

[117]. Waware SY, Kore SS, Kurhade AS, Patil SP. Innovative heat transfer enhancement in tubular heat exchanger: an experimental investigation with minijet impingement. J Adv Res Fluid Mech Therm Sci. 2024;116(2):51-8. https://doi.org/10.37934/arfmts.116.2.5158

[118]. Kurhade AS, Murali G. Thermal control of IC chips using phase change material: a CFD investigation. Int J Mod Phys C. 2022 Dec 28;33(12):2250159. https://doi.org/10.1142/S0129183122501595

[119]. Rami Reddy S, Murali G, Dhana Raju V. Assessment of diethyl ether as a fuel additive on diesel engine characteristics powered with waste mango seed biodiesel blend. Int J Ambient Energy. 2022 Dec 31;43(1):3365-76. https://doi.org/10.1080/01430750.2020.1824944

[120]. Emeema J, Murali G, Reddi BV, Mangesh VL. Investigations on paraffin wax/CQD composite phase change material: improved latent heat and thermal stability. J Energy Storage. 2024 Apr 30;85:111056. https://doi.org/10.1016/j.est.2024.111056

[121]. Rami Reddy S, Murali G, Dhana Raju V. Influence of decanol as fuel additive on characteristics of diesel engine powered with mango seed biodiesel blend. Int J Ambient Energy. 2022 Dec 31;43(1):2875-88. https://doi.org/10.1080/01430750.2020.1783356

[122]. Tamiloli N, Venkatesan J, Murali G, Kodali SP, Sampath Kumar T, Arunkumar MP. Optimization of end milling on Al-SiC-fly ash metal matrix composite using TOPSIS and fuzzy logic. SN Appl Sci. 2019;1(10):1204. https://doi.org/10.1007/s42452-019-1191-z