AI-Driven Circular Economy of Enhancing Sustainability and Efficiency in Industrial Operations DOI Open Access
Bankole I. Oladapo, Mattew A. Olawumi, Francis T. Omigbodun

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(23), P. 10358 - 10358

Published: Nov. 27, 2024

This study investigates integrating circular economy principles—such as closed-loop systems and economic decoupling—into industrial sectors, including refining, clean energy, electric vehicles. The primary objective is to quantify the impact of practices on resource efficiency environmental sustainability. A mixed-methods approach combines qualitative case studies with quantitative modelling using Brazilian Land-Use Model for Energy Scenarios (BLUES) Autoregressive Integrated Moving Average (ARIMA). These models project long-term trends in emissions reduction optimization. Significant findings include a 20–25% waste production an improvement recycling from 50% 83% over decade. Predictive demonstrated high accuracy, less than 5% deviation actual performance metrics, supported by error metrics such Mean Absolute Percentage Error (MAPE) Root Square (RMSE). Statistical validations confirm reliability these forecasts. highlights potential reduce reliance virgin materials lower carbon while emphasizing critical role policy support technological innovation. integrated offers actionable insights industries seeking sustainable growth, providing robust framework future management applications.

Language: Английский

Towards built environment Decarbonisation: A review of the role of Artificial intelligence in improving energy and Materials’ circularity performance DOI Creative Commons
Bankole Awuzie, A.B. Ngowi, Douglas Aghimien

et al.

Energy and Buildings, Journal Year: 2024, Volume and Issue: 319, P. 114491 - 114491

Published: June 28, 2024

Mitigating climate change challenges in the built environment through decarbonisation of energy and construction materials remains a pressing challenge. The circular economy (CE) has been identified as critical pathway to achieving this objective. CE promotes efficient use resources, extending their lifecycle minimising environmental impact using plethora methods. link between becomes evident when intertwined relationship materials, energy, is considered. By reducing waste ensuring continuous significantly lowers carbon emissions. This approach inherently aligned with overarching goals agenda. emergence digital technologies such artificial intelligence (AI) continued transform how activities are conducted improved. However, utility AI models engendering actualisation agenda improved performance within context under-researched. study addresses knowledge-practice gap, scientometric scoping analysis relevant peer-reviewed grey literature. Findings from revealed explored separately decarbonisation. Yet, studies exploring relation circularity for remain scant. narrative review further usefulness driving optimal levels across various economic sectors, including decision making which turn, encourages responsible producer consumer behaviour performance.

Language: Английский

Citations

5
Plasticization Effects of PEG of Low Molar Fraction and Molar Mass on the Molecular Dynamics and Crystallization of PLA-b-PEG-b-PLA Triblock Copolymers Envisaged for Medical Applications DOI Creative Commons
Nikolaos D. Bikiaris, Panagiotis Α. Klonos, Evi Christodoulou

et al.

The Journal of Physical Chemistry B, Journal Year: 2025, Volume and Issue: unknown

Published: March 19, 2025

We prepared and studied a series of triblock copolymers based on poly(ethylene glycol) (PEG) poly(lactic acid) (PLA). PLA blocks were in situ by ring-opening polymerization (ROP) lactide (LA) onto the two sites PEG. While our recent work similar with varying LA/PEG molar ratios fixed PEG [Bikiaris, N. D. Mater. Today Commun. 2024, 38, 107799], herein, we kept this ratio quite low, at 640/1, employed different molecular weights, Mn, initial 1, 4, 6, 8 kg/mol. The triblocks demonstrated high homogeneity, as manifested single thermal transition (glass transition, crystallization) corresponding alternations systematic way Mn With increase latter accelerated segmental mobility lowering Tg up to 15 K recorded, accompanied suppression chain fragility (cooperativity). Compared linear PLAs various Mns [Klonos, P. A. Polymer 305, 127177] other PLA-based ROPs, overall copolymers, here sees play role plasticizer PLA, leading increased free volume. Due these effects, general, low crystalline fraction (∼3%) was significantly enhanced (20–26%), formed spherulites mainly enlarged. Contrary these, nucleation barely affected; thus, exhibited altered semicrystalline morphologies compared that neat PLA. Both aspects dynamics, volume crystallization, connected processability well performance systems, considering envisaged biomedical applications.

Language: Английский

Citations

0
Segmental Mobility, Interfacial Polymer, Crystallization and Conductivity Study in Polylactides Filled with Hybrid Lignin-CNT Particles DOI Creative Commons
Panagiotis Α. Klonos, Rafail O. Ioannidis,

A. Pitsavas

et al.

Nanomaterials, Journal Year: 2025, Volume and Issue: 15(9), P. 660 - 660

Published: April 26, 2025

A newly developed series of polylactide (PLA)-based composites filled with hybrid lignin–carbon nanotube (CNTs) particles were studied using thermal and dielectric techniques. The low CNT content (up to 3 wt%) aimed create conductive networks while enhancing particle–polymer adhesion. For comparison, PLA based on lignin CNTs also examined. Although infrared spectroscopy showed no significant interactions, calorimetry revealed a rigid interfacial layer exhibiting restricted mobility. polymer amount was found increase monotonically the particle content. hybrid-filled exhibited electrical conductivity, whereas PLA/Lignin PLA/CNTs remained insulators. result indicative synergistic effect between CNTs, leading lowering percolation threshold wt%, being almost ideal for sustainable printing inks. Despite addition at different loadings, glass transition temperature (60 °C) decreased slightly (softer composites) by 1–2 K in composites, melting stable ~175 °C, favoring efficient processing. Regarding crystallization, which is typically slow PLA, lignin/CNT promoted crystal nucleation without increasing total crystallizable fraction. Overall, these findings highlight potential eco-friendly new-generation applications, such as printed electronics.

Language: Английский

Citations

0
Renewable Energy Credits Transforming Market Dynamics DOI Open Access
Bankole I. Oladapo,

Mattew A. Olawumi,

Francis T. Omigbodun

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(19), P. 8602 - 8602

Published: Oct. 3, 2024

This research uses advanced statistical methods to examine climate change mitigation policies’ economic and environmental impacts. The primary objective is assess the effectiveness of carbon pricing, renewable energy subsidies, emission trading schemes, regulatory standards in reducing CO2 emissions, fostering growth, promoting employment. A mixed-methods approach was employed, combining regression analysis, cost–benefit analysis (CBA), computable general equilibrium (CGE) models. Data were collected from national global databases, sensitivity analyses conducted ensure robustness findings. Key findings revealed a statistically significant reduction emissions by 0.45% for each unit increase pricing (p < 0.01). Renewable subsidies positively correlated with 3.5% employment green sector 0.05). Emission schemes projected GDP 1.2% over decade However, chi-square tests indicated that disproportionately affects low-income households 0.05), highlighting need compensatory policies. study concluded balanced policy mix, tailored contexts, can optimise outcomes while addressing social equity concerns. Error margins projections remained below ±0.3%, confirming models’ reliability.

Language: Английский

Citations

3
Data analytics driving net zero tracker for renewable energy DOI Creative Commons
Bankole I. Oladapo, Mattew A. Olawumi, Temitope Olumide Olugbade

et al.

Renewable and Sustainable Energy Reviews, Journal Year: 2024, Volume and Issue: 208, P. 115061 - 115061

Published: Nov. 1, 2024

Language: Английский

Citations

3
Revolutionising waste management with the impact of Long Short-Term Memory networks on recycling rate predictions DOI Creative Commons
Mattew A. Olawumi, Bankole I. Oladapo,

Rukayat Abisola Olawale

et al.

Waste Management Bulletin, Journal Year: 2024, Volume and Issue: 2(3), P. 266 - 274

Published: Aug. 17, 2024

This study explores the efficacy of Long Short-Term Memory (LSTM) networks in predicting recycling rates and enhancing resource allocation waste management systems. It addresses limitations traditional statistical models machine learning algorithms that struggle with sequential data temporal dependencies. The methodology comprised collecting extensive datasets from public repositories, configuring LSTM network architecture, training model historical data, testing various activation functions hyperparameters. model's performance was rigorously compared to alternative using metrics such as Mean Absolute Error (MAE), Root Square (RMSE), R-squared (R2). findings demonstrate significantly outperformed approaches, achieving an MAE 3.5%, RMSE 2.8%, R2 0.92. These results underscore superior capability capture complex patterns offering substantial improvements predictive accuracy reliability. Consequently, highlights potential revolutionize strategies, contributing more effective sustainable practices.

Language: Английский

Citations

2
AI-Driven Circular Economy of Enhancing Sustainability and Efficiency in Industrial Operations DOI Open Access
Bankole I. Oladapo, Mattew A. Olawumi, Francis T. Omigbodun

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(23), P. 10358 - 10358

Published: Nov. 27, 2024

This study investigates integrating circular economy principles—such as closed-loop systems and economic decoupling—into industrial sectors, including refining, clean energy, electric vehicles. The primary objective is to quantify the impact of practices on resource efficiency environmental sustainability. A mixed-methods approach combines qualitative case studies with quantitative modelling using Brazilian Land-Use Model for Energy Scenarios (BLUES) Autoregressive Integrated Moving Average (ARIMA). These models project long-term trends in emissions reduction optimization. Significant findings include a 20–25% waste production an improvement recycling from 50% 83% over decade. Predictive demonstrated high accuracy, less than 5% deviation actual performance metrics, supported by error metrics such Mean Absolute Percentage Error (MAPE) Root Square (RMSE). Statistical validations confirm reliability these forecasts. highlights potential reduce reliance virgin materials lower carbon while emphasizing critical role policy support technological innovation. integrated offers actionable insights industries seeking sustainable growth, providing robust framework future management applications.

Language: Английский

Citations

1