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Steven Chu, Qi Wang. Climate change and innovative paths to a more sustainable future. Climate change is a worldwide urgent and serious crisis requiring innovative paths to accelerate the green and sustainable transition, as outlined in the article by the Nobel Laureate in Physics, Steven Chu. The article emphasizes the need for a fourth industrial and agricultural revolution to eliminate greenhouse gas emissions across all sectors. It highlights the progress in renewable en [Detail] ...
Download coverThe 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.
Co-processing of biomass feedstock with petroleum feedstock in existing refineries is a promising technology that enables the production of low-carbon fuels, reduces dependence on petroleum feedstock, and utilizes the existing infrastructure in refinery. Much effort has been dedicated to advancing co-processing technologies. Though significant progress has been made, the development of co-processing is still hindered by numerous challenges. Therefore, it is important to systematically summarize up-to-date research activities on co-processing process for the further development of co-processing technologies. This paper provides a review of the latest research activities on co-processing biomass feedstock with petroleum feedstock utilizing fluid catalytic cracking (FCC) or hydrotreating (HDT) processes. In addition, it extensively discusses the influence of different types and diverse physicochemical properties of biomass feedstock on the processing of petroleum feedstock, catalysts employed in co-processing studies, and relevant projects. Moreover, it summarizes and discusses co-processing projects in pilot or larger scale. Furthermore, it briefly prospects the research trend of co-processing in the end.
As the next-generation oxy-fuel combustion technology for controlling CO2 emissions, pressurized oxy-fuel combustion (POC) technology can further reduce system energy consumption and improve system efficiency compared with atmospheric oxy-fuel combustion. The oxy-fuel combustion causes high CO2 concentration, which has a series of effects on the combustion reaction process, making the radiation and reaction characteristics different from air-fuel conditions. Under the pressurized oxy-fuel condition, the combustion reaction characteristics are affected by the coupling effect of pressure and atmosphere. The radiation and heat transfer characteristics of the combustion medium are also affected by pressure. In recent years, there have been many studies on POC. This review pays attention to the thermal-science fundamental research. It summarizes several typical POC systems in the world from the perspective of system thermodynamic construction. Moreover, it reviews, in detail, the current research results of POC in terms of heat transfer characteristics (radiant heat transfer and convective heat transfer), combustion characteristics, and pollutant emissions, among which the radiation heat transfer and thermal radiation model are the focus of this paper. Furthermore, it discusses the development and research direction of POC technology. It aims to provide references for scientific research and industrial application of POC technology.
To achieve effective intraday dispatch of photovoltaic (PV) power generation systems, a reliable ultra-short-term power generation forecasting model is required. Based on a gradient boosting strategy and a dendritic network, this paper proposes a novel ensemble prediction model, named gradient boosting dendritic network (GBDD) model which can reduce the forecast error by learning the relationship between forecast residuals and meteorological factors during the training of sub-models by means of a greedy function approximation. Unlike other machine learning models, the GBDD proposed is able to make fuller use of all meteorological factor data and has a good model interpretation. In addition, based on the structure of GBDD, this paper proposes a strategy that can improve the prediction performance of other types of prediction models. The GBDD is trained by analyzing the relationship between prediction errors and meteorological factors for compensating the prediction results of other prediction models. The experimental results show that the GBDD proposed has the benefit of achieving a higher PV power prediction accuracy for PV power generation and can be used to improve the prediction performance of other prediction models.
Spectral beam split is attracting more attention thanks to the efficient use of whole spectrum solar energy and the cogenerative supply for electricity and heat. Nanofluids can selectively absorb and deliver specific solar spectra, making various nanofluids ideal for potential use in hybrid photovoltaic/thermal (PV/T) systems for solar spectrum separation. Clarifying the effects of design parameters is extremely beneficial for optimal frequency divider design and system performance enhancement. The water-based SiO2 nanofluid with excellent thermal and absorption properties was proposed as the spectral beam splitter in the present study, to improve the efficiency of a hybrid PV/T system. Moreover, a dual optical path method was applied to get its spectral transimissivity and analyze the impact of its concentration and optical path on its optical properties. Furthermore, a PV and photothermal model of the presented system was built to investigate the system performance. The result indicates that the transimissivity of the nanofluids to solar radiation gradually decreases with increasing SiO2 nanofluid concentration and optical path. The higher nanofluid concentration leads to a lower electrical conversion efficiency, a higher thermal conversion efficiency, and an overall system efficiency. Considering the overall efficiency and economic cost, the optimal SiO2 nanofluid concentration is 0.10 wt.% (wt.%, mass fraction). Increasing the optical path (from 0 to 30 mm) results in a 60.43% reduction in electrical conversion efficiency and a 50.84% increase in overall system efficiency. However, the overall system efficiency rises sharply as the optical path increases in the 0–10 mm range, and then slowly at the optical path of 10–30 mm. Additionally, the overall system efficiency increases first and then drops upon increasing the focusing ratio. The maximum efficiency is 51.93% at the focusing ratio of 3.
To increase the power generated by solid oxide fuel cells (SOFCs), multiple cells have to be connected into a stack. Nonuniformity of cell performance is a worldwide concern in the practical application of stack, which is known to be unavoidable and caused by manufacturing and operating conditions. However, the effect of such nonuniformity on SOFCs that are connected in parallel has not been discussed in detail so far. This paper provides detailed experimental data on the current distribution within a stack with nonuniform cells in parallel connection, based on the basics of electricity and electrochemistry. Particular phenomena found in such a parallel system are the “self-discharge effect” in standby mode and the “capacity-proportional-load sharing effect” under normal operating conditions. It is believed that the experimental method and results proposed in this paper can be applied to other types of fuel cell or even other energy systems.
Knowing the correct phase connectivity information plays a significant role in maintaining high-quality power and reliable electricity supply to end-consumers. However, managing the consumer-phase connectivity of a low-voltage distribution network is often costly, prone to human errors, and time-intensive, as it involves either installing expensive high-precision devices or employing field-based methods. Besides, the ever-increasing electricity demand and the proliferation of behind-the-meter resources have also increased the complexity of leveraging the phase connectivity problem. To overcome the above challenges, this paper develops a data-driven model to identify the phase connectivity of end-consumers using advanced metering infrastructure voltage and current measurements. Initially, a preprocessing method that employs linear interpolation and singular value decomposition is adopted to improve the quality of the smart meter data. Then, using Kirchoff’s current law and correlation analysis, a discrete convolution optimization model is built to uniquely identify the phase to which each end-consumer is connected. The data sets utilized are obtained by performing power flow simulations on a modified IEEE-906 test system using OpenDSS software. The robustness of the model is tested against data set size, missing smart meter data, measurement errors, and the influence of prosumers. The results show that the method proposed correctly identifies the phase connections of end-consumers with an accuracy of about 98%.
Fe-N-C catalysts are potential substitutes to displace electrocatalysts containing noble chemical elements in the oxygen reduction reaction (ORR). However, their application is hampered by unsatisfactory activity and stability issues. The structures and morphologies of Fe-N-C catalysts have been found to be crucial for the number of active sites and local bonding structures. In this work, dicyandiamide (DCDA) and polyaniline (PANI) are shown to act as dual nitrogen sources to tune the morphology and structure of the catalyst and facilitate the ORR process. The dual nitrogen sources not only increase the amount of nitrogen doping atoms in the electrocatalytic Fe-C-N material, but also maintain a high nitrogen-pyrrole/nitrogen-graphitic: (N-P)/(N-G) value, improving the distribution density of catalytic active sites in the material. With a high surface area and amount of N-doping, the Fe-N-C catalyst developed can achieve an improved half-wave potential of 0.886 V (vs. RHE) in alkaline medium, and a better stability and methanol resistance than commercial Pt/C catalyst.
NiFe (oxy)hydroxide (NiFeOOH) is recognized as a highly active non-precious metal catalyst in alkaline water electrolysis due to its exceptional catalytic properties. In this work, high valence molybdenum (Mo) is introduced to improve the electronic structure and enhance the electrical conductivity of NiFeOOH for oxygen evolution reaction (OER). The introduction of Mo results in a Mo-doped NiFeOOH catalyst with a significantly reduced overpotential of 205 mV at 10 mA/cm2 and a Tafel slope of 31.7 mV/dec, enabling stable operation for up to 170 h. Both empirical experiment and theory simulations are employed to gain insight into the 3d-electron interactions between molybdenum and nickel (Ni), iron (Fe) in Mo-doped NiFeOOH. The results indicate that Mo-doping enhances the valence states of Ni and Fe, leading to a shift in the d-band center of the bimetallic active sites. This modification affects the transformation of Mo-doped NiFeOOH into the γ-NiFeOOH active phase. This potent combination lends credence to its potential suitability and utility in OER applications.
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.
Ammonia is an exceptional fuel for solid oxide fuel cells (SOFCs), because of the high content of hydrogen and the advantages of carbon neutrality. However, the challenge lies in its unsatisfactory performance at intermediate temperatures (500‒600 °C), impeding its advancement. An electrolyte-supported proton-ceramic fuel cell (PCFC) was fabricated employing BaZr0.1Ce0.7Y0.2O3–δ (BZCY) as the electrolyte and Ba0.5Sr0.5Co0.8Fe0.2O3–δ (BSCF) as the cathode. In this study, the performance of PCFC using NH3 as fuel within an operating temperature range of 500‒700 °C was improved by adding an M(Ni,Ru)/CeO2 catalyst layer to reconstruct the anode surface. The electrochemical performance of direct ammonia PCFC (DA-PCFC) were improved to different extents. Compared to H2 as fuel, the degradation ratio of peak power densities (PPDs) of Ni/CeO2-loaded PCFC fueled with NH3 decreased at 700‒500 °C, with a decrease to 13.3% at 700 °C and 30.7% at 500 °C. The findings indicate that Ru-based catalysts have a greater promise for direct ammonia SOFCs (DA-SOFCs) at operating temperatures below 600 °C. However, the enhancement effect becomes less significant above 600 °C when compared to Ni-based catalysts.
