Gasification of Solid Fuels (Coal, Biomass and MSW): Overview, Challenges and Mitigation Strategies

Bipolar Membrane Seawater Splitting for Hydrogen Production: A Review

The growing demand for clean energy has spurred the quest for sustainable alternatives to fossil fuels. Hydrogen has emerged as a promising candidate with its exceptional heating value and zero emissions upon combustion. However, conventional hydrogen production methods contribute to CO2 emissions, necessitating environmentally friendly alternatives. With its vast potential, seawater has garnered attention as a valuable resource for hydrogen production, especially in arid coastal regions with surplus renewable energy. Direct seawater electrolysis presents a viable option, although it faces challenges such as corrosion, competing reactions, and the presence of various impurities. To enhance the seawater electrolysis efficiency and overcome these challenges, researchers have turned to bipolar membranes (BPMs). These membranes create two distinct pH environments and selectively facilitate water dissociation by allowing the passage of protons and hydroxide ions, while acting as a barrier to cations and anions. Moreover, the presence of catalysts at the BPM junction or interface can further accelerate water dissociation. Alongside the thermodynamic potential, the efficiency of the system is significantly influenced by the water dissociation potential of BPMs. By exploiting these unique properties, BPMs offer a promising solution to improve the overall efficiency of seawater electrolysis processes. This paper reviews BPM electrolysis, including the water dissociation mechanism, recent advancements in BPM synthesis, and the challenges encountered in seawater electrolysis. Furthermore, it explores promising strategies to optimize the water dissociation reaction in BPMs, paving the way for sustainable hydrogen production from seawater.

Artificial intelligence methods for modeling gasification of waste biomass: a review

Gasification is a highly promising thermochemical process that shows considerable potential for the efficient conversion of waste biomass into syngas. The assessment of the feasibility and comparative advantages of different biomass and waste gasification schemes is contingent upon a multifaceted combination of interrelated criteria. Conventional analytical approaches employed to facilitate decision-making rely on a multitude of inadequately defined parameters. Consequently, substantial efforts have been directed toward enhancing the efficiency and productivity of thermochemical conversion processes. In recent times, artificial intelligence (AI)-based models and algorithms have gained prominence, serving as indispensable tools for expediting these processes and formulating strategies to address the growing demand for energy. Notably, machine learning (ML) and deep learning (DL) have emerged as cutting-edge AI models, demonstrating exceptional effectiveness and profound relevance in the realm of thermochemical conversion systems. This study provides an overview of the machine learning (ML) and deep learning (DL) approaches utilized during gasification and evaluates their benefits and drawbacks. Many industries and applications related to energy conversion systems use AI algorithms. Predicting the output of conversion systems and subjects linked to optimization are two of this science's critical applications. This review sheds light on the burgeoning utility of AI, particularly ML and DL, which have garnered significant attention due to their applications in productivity prediction, process optimization, real-time process monitoring, and control. Furthermore, the integration of hybrid models has become commonplace, primarily owing to their demonstrated success in modeling and optimization tasks. Importantly, the adoption of these algorithms significantly enhances the model's capability to tackle intricate challenges, as DL methodologies have evolved to offer heightened accuracy and reduced susceptibility to errors. Within the scope of this study, an exhaustive exploration of ML and DL techniques and their applications has been conducted, uncovering existing research knowledge gaps. Based on a comprehensive critical analysis, this review offers recommendations for future research directions, accentuating the pivotal findings and conclusions derived from the study.

Municipal solid waste treatment for bioenergy and resource production: Potential technologies, techno-economic-environmental aspects and implications of membrane-based recovery

World estimated municipal solid waste generating at an alarming rate and its disposal is a severe concern of today's world. It is equivalent to 0.79 kg/d per person footprint and causing climate change; health hazards and other environmental issues which need attention on an urgent basis. Waste to energy (WTE) considers as an alternative renewable energy potential to recover energy from waste and reduce the global waste problems. WTE reduced the burden on fossil fuels for energy generation, waste volumes, environmental, and greenhouse gases emissions. This critical review aims to evaluate the source of solid waste generation and the possible routes of waste management such as biological landfill and thermal treatment (Incineration, pyrolysis, and gasification). Moreover, a comparative evaluation of different technologies was reviewed in terms of economic and environmental aspects along with their limitations and advantages. Critical literature revealed that gasification seemed to be the efficient route and environmentally sustainable. In addition, a framework for the gasification process, gasifier types, and selection of gasifiers for MSW was presented. The country-wise solutions recommendation was proposed for solid waste management with the least impact on the environment. Furthermore, key issues and potential perspectives that require urgent attention to facilitate global penetration are highlighted. Finally, practical implications of membrane and comparison membrane-based separation technology with other conventional technologies to recover bioenergy and resources were discussed. It is expected that this study will lead towards practical solution for future advancement in terms of economic and environmental concerns, and also provide economic feasibility and practical implications for global penetration.