The environmental impacts of hydrogen production can vary widely depending on the production energy source and process. This implies that the collection and management of sustainability data for hydrogen production globally is desired to ensure accountable development of the sector. Life cycle assessment (LCA) is an internationally recognized tool for environmental impact assessment. Integrating LCA in the holistic evaluation of the hydrogen value chain is desirable to ensure the cleanness and sustainability of the various available hydrogen production pathways. The objective of this review is to evaluate the methodology used in assessing the life cycle impact of hydrogen production including proposed documentation such as the guarantee of origin (GO) and certification schemes, and review case studies from Australia. An analysis of the sustainability strategies and schemes designed by the Australian government, aimed at mitigating climate change and promoting the hydrogen economy, was conducted. The case studies that were discussed identified the preferred available scaled routes of clean hydrogen production to be water electrolysis, which is based on technologies using renewable energy. Other dominant technologies which incorporate carbon capture and storage (CCS) were envisaged to continue playing a role in the transition to a low carbon economy. Additionally, it is critical to assess the greenhouse gas (GHG) emissions using appropriate system boundaries, in order to classify clean hydrogen production pathways. Harmonizing regulatory stringency with appropriate tracking of renewable electricity can promote clean hydrogen production through certification and GO schemes. This approach is deemed critical for the sustainable development of the hydrogen economy at the international level.

Phase change energy storage technology has great potential for enhancing the efficient conversion and storage of energy. While triply periodic minimal surface (TPMS) structures have shown promise in improving heat transfer, research on their application in phase change heat transfer remains limited. This paper presents numerical simulations of composite phase change materials (PCMs) featuring TPMS skeletons, specifically gyroid, diamond, primitive, and I-graph and wrapped package-graph (I-WP) utilizing the lattice Boltzmann method (LBM). A comparative analysis of the effects of four TPMS skeletons on enhancing the phase change process reveals that the PCM containing the gyroid skeleton melts the fastest, with a complete melting time of 24.1% shorter than that of the PCM containing the I-WP skeleton. The PCM containing the gyroid skeleton is further simulated to explore the effects of the Rayleigh (Ra) number, Prandtl (Pr) number, and Stefan (Ste) number on the melting characteristics. Notably, the complete melting time is reduced by 60.44% when Ra is increased to 10⁶ compared to the case with Ra at 10⁴. Increasing the Pr number accelerates the migration of the mushy zone, resulting in fast melting. Conversely, the convective heat transfer effect from the heating surface decreases as the Ste number increases. The temperature differences caused by the local thermal non-equilibrium (LTNE) effect over time are significant and complex, with peaks becoming more pronounced nearer the heating surface. This study intends to provide theoretical support for the further development of TPMS skeletons in enhancing the phase change process.

Compressed air energy storage (CAES) is an effective technology for mitigating the fluctuations associated with renewable energy sources. In this work, a hybrid cogeneration energy system that integrates CAES with high-temperature thermal energy storage and a supercritical CO₂ Brayton cycle is proposed for enhancing the overall system performance. This proposal emphasizes system cost-effectiveness, eco-friendliness, and adaptability. Comprehensive analyses, including thermodynamic, exergoeconomic, economic, and sensitivity evaluations, are conducted to assess the viability of the system. The findings indicate that, under design conditions, the system achieves an energy storage density, a round-trip efficiency, an exergy efficiency, a unit product cost, and a dynamic payback period of 5.49 kWh/m³, 58.39%, 61.85%, 0.1421 $/kWh, and 4.81 years, respectively. The high-temperature thermal energy storage unit, intercoolers, and aftercooler show potential for optimization due to their suboptimal exergoeconomic performance. Sensitivity evaluation indicates that the operational effectiveness of the system is highly sensitive to the maximum and minimum air storage pressures, the outlet temperature of the high-temperature thermal energy storage unit, and the isentropic efficiencies of both compressors and turbines. Ultimately, the system is optimized for maximum exergy efficiency and minimum dynamic payback period. These findings demonstrate the significant potential of this system and provide valuable insights for its design and optimization.

Geothermal energy is clean and renewable, derived from the heat stored within accessible depths of the Earth’s crust. The adoption of a single-well system for medium-deep and deep geothermal energy extraction has attracted significant interest from the scientific and industrial communities because it effectively circumvents issues such as downhole inter-well connections and induced seismicity. However, the low heat transfer capacity in geothermal formations limits the heat extraction performance of single-well systems and hinders their commercial deployment. This review covers various enhancement concepts for optimizing the heat transfer within single-well systems, emphasizing critical parameters such as heat transfer area, heat transfer coefficient, and temperature difference. Additionally, it presents the thermo-economic evaluation of different configurations of single-well borehole heat exchangers and super-long gravity heat pipes (SLGHPs). The SLHGP, utilizing phase-change heat transfer, is recognized as a highly effective and continuously productive technology, capable of extracting over 1 MW of heat. Its pumpless operation and ease of installation in abandoned wells make it cost-effective, offering a promising economic advantage over traditional geothermal systems. It also highlights the challenges and potential research opportunities that can help identify gaps in research to enhance the performance of single-well geothermal systems.

Carbon dioxide, as a greenhouse gas, is expected to be converted into other useful substances by the electrocatalytic CO₂ reduction reaction (CO₂RR) technology. The electrocatalytic cell, or electrochemical cell, used to provide the experimental environment for CO₂RR plays an irreplaceable role in the study of this process and determines the success or failure of the measurements. In recent years, electrolytic cells that can be applied to in-situ/operational synchrotron radiation (SR) characterization techniques have gradually gained widespread attention. However, the design and understanding of electrolyte systems that can be applied to in-situ/operational SR technologies are still not sufficiently advanced. In this paper, the electrocatalytic cells used to study the CO₂RR processes with in-situ/operando SR techniques are briefly introduced, and the types and characteristics of the electrolytic cells are analyzed. The recent advancements of in situ/operando electrolytic cells are discussed using X-ray scattering, X-ray absorption spectroscopy (XAS), light vibration spectroscopy, and X-ray combined techniques. An outlook is provided on the future prospects of this research field. This review facilitates the understanding of the reduction process and electrocatalytic mechanism of CO₂RR at the atomic and molecular scales, providing insights for the design of electrolysis cells applicable to SR technologies and accelerating the development of more efficient and sustainable carbon negative technologies.

This study explores the structural, electronic, and optical properties of tin-based halide perovskites, MSnX₃ (M = Li, Na; X = Cl, Br, I), under varying pressure conditions. Using volume optimization and the Perdew-Burke-Ernzerhof generalized gradient approximation (PBE-GGA) method, it analyzes these perovskites in their cubic Pm\stackrel{-}{3}m phase. The findings reveal that the lattice constants of these compounds decrease as pressure increases, with more pronounced changes observed when anions are substituted from Cl to I. The electronic analysis shows that these materials maintain their direct band gap nature under pressures, although the band gaps narrow with increasing pressure and larger anion sizes. Notably, Li/NaSnCl₃, Li/NaSnBr₃, and Li/NaSnI₃ may exhibit metallic behavior at pressures exceeding 5 GPa. Optical studies reveal significant pressure-induced enhancements in static dielectric constant and optical absorption, especially in the visible spectrum, highlighting the potential of these perovskites for solar cell applications. The refractive index increases with pressure, indicating a higher material density and enhanced optical performance. Additionally, the extinction coefficient and electron energy loss function provide insights into the energy absorption and scattering characteristics, which are crucial for improving the efficiency of optoelectronic devices. This comprehensive analysis underscores the potential of these tin-based halide perovskites for advanced optoelectronic and photovoltaic technologies.

An accurate assessment of the state of health (SOH) is the cornerstone for guaranteeing the long-term stable operation of electrical equipment. However, the noise the data carries during cyclic aging poses a severe challenge to the accuracy of SOH estimation and the generalization ability of the model. To this end, this paper proposed a novel SOH estimation model for lithium-ion batteries that incorporates advanced signal-processing techniques and optimized machine-learning strategies. The model employs a whale optimization algorithm (WOA) to seek the optimal parameter combination (K, α) for the variational modal decomposition (VMD) method to ensure that the signals are accurately decomposed into different modes representing the SOH of batteries. Then, the excellent local feature extraction capability of the convolutional neural network (CNN) was utilized to obtain the critical features of each modal of SOH. Finally, the support vector machine (SVM) was selected as the final SOH estimation regressor based on its generalization ability and efficient performance on small sample datasets. The method proposed was validated on a two-class publicly available aging dataset of lithium-ion batteries containing different temperatures, discharge rates, and discharge depths. The results show that the WOA-VMD-based data processing technique effectively solves the interference problem of cyclic aging data noise on SOH estimation. The CNN-SVM optimized machine learning method significantly improves the accuracy of SOH estimation. Compared with traditional techniques, the fused algorithm achieves significant results in solving the interference of data noise, improving the accuracy of SOH estimation, and enhancing the generalization ability.

The challenges posed by climate change and greenhouse gas net-zero transition are discussed. Several key technology areas which require innovation are briefly reviewed in this article, including renewables, energy storage, distributed energy resources, CO₂ utilization, agriculture, and the synergy between Al and energy transition. The shift in mindset from “re-cycling” to “re-using” and a redefinition of “wealth” for a more sustainable future are also proposed.

Bioluminescent plankton are marine organisms capable of emitting visible light through chemical reactions in their bodies. This unique biochemical trait is attributed to a luciferin-luciferase reaction, which produces a striking blue light. This fascinating phenomenon, often referred to as the “blue tears” effect, has become a major attraction for tourist attractions in many countries. Since their discovery, most investigations related to these marine organisms have primarily focused on the fields of biology, ecology, oceanography, and microbiology. However, there has been limited to almost no study of their potential applications in the area of energy or lighting. This paper provides viewpoints on the opportunities for using these marine organisms and their light-emitting characteristics as an energy-efficient and environmentally friendly lighting solution, rather than just as a tourist attraction. Additionally, it addresses the challenges associated with sustaining the growth of bioluminescent plankton collected from the marine environment, the importance of establishing suitable protocols for in-house cultivation, challenges in stimulating the light-production at desired time, constraint imposed by the circadian rhythm, the toxicity of certain bioluminescent plankton, and the capacity of their luminous intensity.

Mesoporous biochar (MC) derived from biomass is synthesized using a dual-salt template method involving ZnCl₂ and KCl, followed by impregnation with polyethyleneimine (PEI) of varying average molecular weights under vacuum conditions to construct a core-membrane structure for enhancing carbon capture performance. The resulting MC exhibits a highly intricate network of micropores and abundant mesopores, along with defects in graphitic structures, effectively facilitating robust PEI loading. Among the PEI-modified samples, PEI-600@MC demonstrates the highest CO₂ sorption capacity, achieving approximately 3.35 mmol/g at 0.1 MPa and 70 °C, with an amine efficiency of 0.32 mmol CO₂/mmol N. The introduction of amine functional groups in PEI significantly enhances the sorption capacity compared to bare MC. Additionally, PEI with lower average molecular weights exhibits a superior sorption performance at low pressures but shows a reduced thermal stability compared to higher molecular weight counterparts. The area of sorption hysteresis loops gradually decreases with increasing temperature and average molecular weight of PEI. The equilibrium sorption isotherms are accurately modeled by the Langmuir equation, revealing a maximum sorption capacity of approximately 3.53 mmol/g at 70 °C and saturation pressure. This work highlights the potential of dual-salts templated biomass-derived MC, modified with PEI, as an effective, widely available, and cost-efficient material for CO₂ capture.