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Energy saving in higher education institutions holds significant importance in the establishment of environmentally friendly and low-carbon societies, with the energy-saving behaviors of university students playing a pivotal role in the development of sustainable campuses. However, there is a clear need for customized strategies to encourage energy-saving habits among university students in areas of China with extreme weather conditions, such as hot summers and cold winters. This study offers a thorough examination of the literature regarding energy-saving behaviors among college students and presents a new theoretical framework based on the Theory of Planned Behavior (TPB). A survey questionnaire is conducted at universities in regions with hot summers and cold winters across China, with the goal of identifying the main factors that influence students' intentions and actions regarding campus energy conservation. From July to August 2022, we collected 512 survey responses from different university campuses in China's hot summer-cold winter weather zone. The survey asked about subjective norms, understanding of energy conservation, and the importance of saving energy. Utilizing the Structural Equation Model (SEM), we examined how influencing factors are associated with energy conservation behaviors. Our findings indicate that (1) both the significance of energy conservation and subjective norms significantly drive energy-saving actions; (2) distinct factors impact different forms of energy-saving practices; and (3) the inclination to save energy partially mediates the relationship between comfort choices and the significance of energy conservation. This study presents a validated behavioral model tailored for regions experiencing hot summers and cold winters, offering valuable insights for college administrators in managing energy usage while also serving as a theoretical reference for establishing environmentally sustainable campuses.

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Cryogenics is the science and technology of very low temperatures, typically below 120 K. The most common applications are liquified natural gas carriers, ground-based tanks, and propellant tanks for space launchers. A crucial aspect of cryogenic technology is effective insulation to minimise boil-off from storage tanks and prevent frost build-up. Rigid closed-cell foams are prominent in various applications, including cryogenic insulation, due to their balance between thermal and mechanical properties. Polyurethane (PU) foam is widely used for internal insulation in cryogenic tanks, providing durability under thermal shocks and operational loads. External insulation, used in liquified natural gas carriers and ground-based tanks, generally demands less compressive strength and can utilise lower-density foams. The evolution of cryogenic insulation materials has seen the incorporation of environmentally friendly blowing agents and bio-based polyols to enhance sustainability. Fourth-generation physical blowing agents, such as HFO-1233zd(E) and HFO-1336mzz(Z), offer low global warming potential and improved thermal conductivity. Additionally, bio-based polyols from renewable resources like different natural oils and recycled polyethylene terephthalate (PET) are being integrated into rigid PU foams, showing promising properties for cryogenic applications. Research continues to optimise these materials for better mechanical performance and environmental impact.

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The cyclical variations in environmental temperature generated by natural rhythms constantly impact the wastewater treatment process through the aeration system. Engineering data show that fluctuations in environmental temperature cause the reactor temperature to drop at night, resulting in increased dissolved oxygen concentration and improved effluent wastewater quality. However, the impact of natural temperature variation on wastewater treatment systems and the energy-saving potential has yet to be fully recognized. Here, we conducted a comprehensive study, using a full-scale oxic-hydrolytic and denitrification-oxic (OHO) coking wastewater treatment process as a case and developed a dynamic aeration model integrating thermodynamics and kinetics to elucidate the energy-saving mechanisms of wastewater treatment systems in response to diurnal temperature variations. Our case study results indicate that natural diurnal temperature variations can cut the energy consumption of 660,980 kWh annually (up to 30%) for the aeration unit in the OHO system. Wastewater treatment facilities located in regions with significant environmental temperature variation stand to benefit more from this energy-saving mechanism. Methods such as flow dynamic control, load shifting, and process unit editing can be fitted into the new or retrofitted wastewater treatment engineering.

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During long-distance migrations, some bird species make use of in-wake flying, which should allow them to profit from the upwash produced by another bird. While indirect evidence supports energy saving as the primary benefit of in-wake flying, measurements are still missing. We equipped migrating northern bald ibises (Geronticus eremita) with high-precision global navigation satellite system data loggers to track their position in the flock. We estimated birds' energy expenditure through different proxies, namely dynamic body acceleration (DBA), heart rate and effective wingbeat frequency. During active flapping flight, DBA estimates dropped off when in-wake compared with when not-in-wake. In addition, effective wingbeat frequency decreased, suggesting an increased use of intermittent gliding flight during in-wake periods. Heart rate varied greatly among individuals, with a clear decrease during gliding-corroborating its energy-saving function. Furthermore, we found consistent proof for decreased heart rate during in-wake flying, by up to 4.2%. Hence, we have shown that flying in the wake of another individual reduces birds' DBA, heart rate and effective wingbeat frequency, which could reflect reduced energy requirement.

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The mismatch between solar radiation resources and building heating demand on a seasonal scale makes cross-seasonal heat storage a crucial technology, especially for plateau areas. Utilizing phase change materials with high energy density and stable heat output effectively improves energy storage efficiency. This study integrates cascaded phase change with a cross-seasonal heat storage system aimed at achieving low-carbon heating. The simulation analyzes heat distribution and temperature changes from the heat storage system to the heating terminal. The results indicate that although the solar collectors operate for 26.3% of the total heat storage and heating period, the cumulative heat stored is 45.4% higher than the total heating load. Heat transferred by the cross-seasonal heat storage system accounts for up to 61.2% of the total heating load. Therefore, the system reduces fuel consumption by 77.6% compared to conventional fossil fuel heating systems. Moreover, radiant floor heating terminals, with a wide range of operating temperatures, match well with cascaded phase change heat storage and can reduce operation time by 19.5% and heat demand by 5.2% compared to conventional radiators. In addition to demonstrating the feasibility of applying cascaded phase change technology in cross-seasonal heat storage heating, this study reveals the lifecycle sustainability due to the shortened heat storage period. The configuration, parameters, and simulation results provide a reference basis for system application and design.

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Torpor is an adaptive strategy allowing heterothermic animals to cope with energy limitations. In birds and mammals, intrinsic and extrinsic factors, such as body mass and ambient temperature, are the main variables influencing torpor use. A theoretical model of the relationship between metabolic rate during torpor and ambient temperature has been proposed. Nevertheless, no empirical attempts have been made to assess the model predictions under different climates. Using open-flow respirometry, we evaluated the ambient temperature at which bats entered torpor and when torpid metabolic rate reached its minimum, the reduction in metabolic rate below basal values, and minimum torpid metabolic rate in 11 bat species of the family Vespertilionidae with different body mass from warm and cold climates. We included data on the minimum torpid metabolic rate of five species we retrieved from the literature. We tested the effects using mixed-effect phylogenetic models. All models showed a significant interaction between body mass and climate. Smaller bats went into torpor and reached minimum torpid metabolic rates at warmer temperatures, showed a higher reduction in the metabolic rate below basal values, and presented lower torpid metabolic rates than larger ones. The slopes of the models were different for bats from different climates. These results are likely explained by differences in body mass and the metabolic rate of bats, which may favor larger bats expressing torpor in colder sites and smaller bats in the warmer ones. Further studies to assess torpor use in bats from different climates are proposed.

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Exacerbated by human activities and natural events, air pollution poses severe health risks, requiring effective control measures to ensure healthy living environments. Traditional filtration systems that employ high-efficiency particulate air (HEPA) filters are capable of effectively removing particulate matter (PM) in indoor environments. However, these systems often work without considering the fluctuations in air pollution levels, leading to high energy consumption. This study proposed a novel PM2.5 pollution-level adaptive air filtration system that combined elastic thermoplastic polyurethane (TPU) filters and an Internet of Things (IoT) system. The developed system can effectively adjust its filtration performance (i.e., pressure drop and PM2.5 filtration efficiency) in response to real-time air quality conditions by mechanically altering the structures of TPU filters. Furthermore, while operating in varied pollution conditions, the proposed system demonstrated remarkable reductions in pressure drop without notably compromising the pollution control capability. Finally, the energy consumption of the pollution-level adaptive air filtration system was estimated when applied in mechanical ventilation systems in different cities (Hong Kong, Beijing, and Xi'an) with various pollution conditions. The results revealed that, compared to a traditional fixed system, the annual energy consumption could be reduced by up to ∼26.4 % in Hong Kong.

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Plant essential oils have a wide range of applications including cosmetics, food, leather, and textiles. Traditional methods employed for essential oils extraction suffer from several drawbacks, which have escalated into a major bottleneck for industrial applications. To circumvent the limitations, various innovative and eco-friendly technologies have emerged for the extraction of essential oils, such as ultrasound-assisted extraction, pulsed electrical-assisted extraction, ohmic-assisted technology, supercritical fluid extraction, and solvent-free microwave extraction. These cutting-edge technologies provide notable advantages over traditional methods in terms of extraction efficiency, environmental safety, and product quality enhancement. This review highlights the advantage of these innovative techniques, with a particular focus on their ability to enhance the yield and antioxidant activity of essential oils while simultaneously reducing energy consumption. Additionally, the mechanisms of these new and eco-friendly extraction methods are thoroughly discussed. This review provides valuable insights into the advancements in essential oils extraction.

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It is common practice in laboratories to store biological samples in ultra-low temperature (ULT) freezers. There is growing interest in raising the temperature of ULT freezers in order to save energy and reduce expenses, as energy conservation becomes increasingly important and sustainable laboratory practices gain popularity. In our laboratory, plasma samples are stored for three months for diagnostic purposes. We therefore took the opportunity to investigate the effect of two different storage temperatures (-70 °C vs -80 °C), on activated partial thromboplastin time (APTT), factor VIII (FVIII), international normalized ratio (INR) and factor VII (FVII) measurements on paired plasma samples collected from 26 individuals after three months of storage. Automated coagulation analysers CS-5100 and ACL TOP were used to perform the tests. We found no consistent difference between the two storage temperatures for any of the four coagulation parameters (all p-values > 0.05). We conclude that the temperature of ULT freezers used to store plasma samples for APTT, FVIII, INR, and FVII measurements can be safely increased from -80 to -70 °C without affecting the stability of the samples.

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Combining the urea oxidation reaction (UOR) with the hydrogen evolution reaction (HER) is an effective technology for energy-saving hydrogen production. Herein, a bifunctional electrocatalyst with CoNiP nanosheet coating on P-doped MoO2 nanorods (P-MoO2@CoNiP) is obtained via a two-step hydrothermal followed a phosphorization process. The catalyst demonstrates exceptional alkaline HER performance due to the formation of MoO2 and the dissolution/absorption of Mo. Meanwhile, the inclusion of Co and P in the P-MoO2@CoNiP catalyst facilitated the formation of NiOOH, enhancing UOR performance. Density functional theory calculations reveal that the hydrogen adsorption Gibbs free energy (ΔGH*) of P-MoO2@CoNiP is closer to 0 eV than CoNiP, favoring the HER. The catalyst only needs -0.08 and 1.38 V to reach 100 mA cm-2 for catalyzing the HER and UOR, respectively. The full urea electrolysis system driven by P-MoO2@CoNiP requires 1.51 V to achieve 100 mA cm-2, 120 mV lower than the traditional water electrolysis.

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Birds commonly exploit environmental features such as columns of rising air and vertical windspeed gradients to lower the cost of flight. These environmental subsidies may be especially important for birds that forage via continuous flight, as seen in black skimmers. These birds forage through a unique behavior, called skimming, where they fly above the water surface with their mandible lowered into the water, catching fish on contact. Thus, their foraging flight incurs costs of moving through both air and water. Prior studies of black skimmer flight behavior have focused on reductions in flight cost due to ground effect, but ignored potential beneficial interactions with the surrounding air. We hypothesized a halfpipe skimming strategy for skimmers to reduce the foraging cost by taking advantage of the wind gradient, where the skimmers perform a wind gradient energy extraction maneuver at the end of a skimming bout through a foraging patch. Using video recordings, wind speed and wind direction measurements, we recorded 70 bird tracks over 4 days at two field sites on the North Carolina coast. We found that while ascending, the skimmers flew more upwind and then flew more downwind when descending, a pattern consistent with harvesting energy from the wind gradient. The strength of the wind gradient and flight behavior of the skimmers indicate that the halfpipe skimming strategy could reduce foraging cost by up to 2.5%.

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In recent years, smart windows have attracted widespread attention due to their ability to respond to external stimuli such as light, heat, and electricity, thereby intelligently adjusting the ultraviolet, visible, and near-infrared light in solar radiation. VO2(M) undergoes a reversible phase transition from an insulating phase (monoclinic, M) to a metallic phase (rutile, R) at a critical temperature of 68 °C, resulting in a significant difference in near-infrared transmittance, which is particularly suitable for use in energy-saving smart windows. However, due to the multiple valence states of vanadium ions and the multiphase characteristics of VO2, there are still challenges in preparing pure-phase VO2(M). Machine learning (ML) can learn and generate models capable of predicting unknown data from vast datasets, thereby avoiding the wastage of experimental resources and reducing time costs associated with material preparation optimization. Hence, in this paper, four ML algorithms, namely multi-layer perceptron (MLP), random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGB), were employed to explore the parameters for the successful preparation of VO2(M) films via magnetron sputtering. A comprehensive performance evaluation was conducted on these four models. The results indicated that XGB was the top-performing model, achieving a prediction accuracy of up to 88.52%. A feature importance analysis using the SHAP method revealed that substrate temperature had an essential impact on the preparation of VO2(M). Furthermore, characteristic parameters such as sputtering power, substrate temperature, and substrate type were optimized to obtain pure-phase VO2(M) films. Finally, it was experimentally verified that VO2(M) films can be successfully prepared using optimized parameters. These findings suggest that ML-assisted material preparation is highly feasible, substantially reducing resource wastage resulting from experimental trial and error, thereby promoting research on material preparation optimization.

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Urban blue-green infrastructure (BGI) offers a multitude of ecological advantages to residents, thereby playing a pivotal role in fortifying urban resilience and fostering the development of climate-resilient cities. Nonetheless, current research falls short of a comprehensive analysis of BGI's overall potential for carbon reduction and its indirect carbon reduction impact. To fill this research gap, we utilized the integrated valuation of ecosystem services and trade-offs model and remote sensing estimation algorithm to quantify the direct carbon sequestration and resultant indirect carbon reduction facilitated by the BGI within the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) (China). To identify the regions that made noteworthy contributions to carbon offsets and outliers, spatial autocorrelation analysis was also employed. The findings of this study reveal that in 2019, the BGI within the study area contributed an overall carbon offset of 1.5 × 108 t·C/yr, of which 3.5 × 107 and 11.0 × 107 t·C/yr were the result of direct carbon sequestration and indirect carbon reduction, respectively. The GBA's total CO2 emissions were 1.1 × 108 t in 2019. While the direct carbon sequestration offset 32.0% of carbon emissions, the indirect carbon reduction mitigated 49.9% of potential carbon emissions. These results highlight the critical importance of evaluating BGI's indirect contribution to carbon reduction. The findings of this study provide a valuable reference for shaping management policies that prioritize the protection and restoration of specific areas, thereby facilitating the harmonized development of carbon offset capabilities within urban agglomerations.

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Fibrillated cellulose-based nanocomposites can improve energy efficiency of building envelopes, especially windows, but efficiently engineering them with a flexible ability of lighting and thermal management remains highly challenging. Herein, a scalable interfacial engineering strategy is developed to fabricate haze-tunable thermal barrier films tailored with phosphorylated cellulose nanofibrils (PCNFs). Clear films with an extremely low haze of 1.6% (glass-scale) are obtained by heat-assisted surface void packing without hydrophobization of nanocellulose. PCNF gel cakes serve here as templates for surface roughening, thereby resulting in a high haze (73.8%), and the roughened films can block heat transfer by increasing solar reflection in addition to a reduced thermal conduction. Additionally, obtained films can tune distribution of light from visible to near-infrared spectral range, enabling uniform colored lighting and inhibiting localized heating. Furthermore, an integrated simulation of lighting and cooling energy consumption in the case of office buildings shows that the film can reduce the total energy use by 19.2-38.1% under reduced lighting levels. Such a scalable and versatile engineering strategy provides an opportunity to endow nanocellulose-reinforced materials with tunable optical and thermal functionalities, moving their practical applications in green buildings forward.

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This research introduces an Artificial Intelligence (AI) based model designed to concurrently optimize energy supply management, biocide dosing, and maintenance scheduling for heat exchangers. This optimization considers energetic, technical, economic, and environmental considerations. The impact of biofilm on heat exchangers is assessed, revealing a 41% reduction in thermal efficiency and a 113% increase in flow frictional resistance of the fluid compared to the initial state. Consequently, the pump's power consumption, required to maintain hydraulic conditions, rises by 9%. The newly developed AI model detects the point at which the heat exchanger's performance begins to decline due to accumulating dirt, marking day 44 of experimentation as the threshold to commence the antifouling biocide dosing. Leveraging this AI model to monitor heat exchanger efficiency represents an innovative approach to optimizing antifouling biocide dosing and reduce the environmental impact stemming from industrial plants.

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Purchasing energy-saving products is key for public participation in energy conservation and sustainable development. However, the sale of fraudulent energy-saving products has boomed through online shopping, with little research on these products and consumer demands. This study explored the underlying factors driving consumer purchases of fraudulent energy-saving products and measured their impact on environmental awareness. Sales data for such products from four major online shopping platforms were collected. Results suggested unique demand characteristics from consumers who unknowingly purchase fraudulent energy-saving products, referred to as "hidden energy savers", including a preference for moderately priced products, a desire for straightforward energy-saving explanations, and a tendency to seek multiple additional features, even if they conflict with the core functionality. Perceived installation and usage difficulty significantly influences purchasing behavior. A practical survey of freight companies and individual transporters' demand for freight energy-saving products was conducted as a case study to validate the practical application of this research. This study presents a novel perspective on public energy-saving behavior, aiding in creating true energy-saving products, boosting public energy conservation interest, and reducing the negative impact of fraudulent products on environmental awareness. It also sheds light on hidden consumer needs, guiding the development of authentic energy-saving products.

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The energy consumption of up to 90 % of the total power input in the anodic oxygen evolution reaction (OER) slows down the implementation of electrochemical CO2 reduction reaction (CO2RR) to generate valuable chemicals. Herein, we present an alternative strategy that utilizes methanol oxidation reaction (MOR) to replace OER. The iron single atom anchored on nitrogen-doped carbon support (Fe-N-C) use as the cathode catalyst (CO2RR), low-loading platinum supported on the composites of tungsten phosphide and multiwalled carbon nanotube (Pt-WP/MWCNT) use as the anode catalyst (MOR). Our results show that the Fe-N-C exhibits a Faradaic selectivity as high as 94.93 % towards CO2RR to CO, and Pt-WP/MWCNT exhibits a peak mass activity of 544.24 mA mg-1Pt, which is 5.58 times greater than that of PtC (97.50 mA mg-1Pt). The well-established MOR||CO2RR reduces the electricity consumption up to 52.4 % compared to conventional OER||CO2RR. Moreover, a CO2 emission analysis shows that this strategy not only saves energy but also achieves carbon neutrality without changing the existing power grid structure. Our findings have crucial implications for advancing CO2 utilization and lay the foundation for developing more efficient and sustainable technologies to address the rising atmospheric CO2 levels.

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Electrochemical seawater splitting is a sustainable pathway towards hydrogen production independent of scarce freshwater resources. However, the high energy consumption and harmful chlorine-chemistry interference still pose major technological challenges. Herein, thermodynamically more favorable sulfion oxidation reaction (SOR) is explored to replace energy-intensive oxygen evolution reaction (OER), enabling the dramatically reduced energy consumption and the avoidance of corrosive chlorine species in electrocatalytic systems of NiFe layered double hydroxide (LDH)/FeNi2S4 grown on iron foam (IF) substrate. The resulting NiFe-LDH/FeNi2S4/IF with superwettable surfaces and favorable heterointerfaces can effectively catalyze SOR and hydrogen evolution reaction (HER), which greatly reduces the operational voltage by 1.05 V at 50 mA cm-2 compared to pure seawater splitting and achieves impressively low electricity consumption of 2.33 kW h per cubic meter of H2 at 100 mA cm-2. Significantly, benefitting from the repulsive effect of surface sulfate anions to Cl-, the NiFe-LDH/FeNi2S4/IF exhibits outstanding long-term stability for SOR-coupled chlorine-free hydrogen production with sulfion upcycling into elemental sulfur. The present study uncovers the "killing two birds with one stone" effect of SOR for energy-efficient hydrogen generation and value-added elemental sulfur recovery in seawater electrolysis without detrimental chlorine chemistry.

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Smart building equipment monitoring is a well-established field focused on enhancing contemporary building comfort. The proliferation of Internet connectivity, facilitated by the internet of things (IoT), has transformed buildings from static structures into interactive environments. IoT has witnessed substantial growth across various aspects of daily life, from monitoring environmental conditions to managing building systems and storing data in the cloud. One critical application is the intelligent monitoring and control of building equipment, such as air conditioners, to optimize energy efficiency-a matter of increasing concern for building owners, design experts, and system integrators. Achieving comprehensive energy savings demands a meticulous approach to energy-efficient design and control. This paper's primary objective is to explore and analyze IoT-based energy-saving optimization techniques for intelligent building equipment, integrating building information modeling (BIM) technology. It particularly delves into the energy conservation control algorithm for air-conditioning systems. The research presents a challenge rooted in energy-saving optimization, established upon specific objective functions, followed by a detailed explanation of the energy-saving control algorithm. To validate their approach, the paper outlines a comprehensive experimental design. Over three sessions in August, they conducted control experiments in two distinct areas. Area 1 implemented the energy-saving control methodology discussed in the paper, utilizing virtual parameter enhancement mechanisms, while Area 2 adhered to conventional control methods. The results were enlightening. Area 1 demonstrated superior energy efficiency, consuming 735 kWh compared to Area 2's 819 kWh, signifying an impressive 11.43% reduction in energy consumption thanks to the optimized control strategy. This research underscores the practicality and significance of implementing IoT-based energy-saving strategies, with a focus on smart thermostats, HVAC controllers, and daylight sensors, in intelligent building equipment management to achieve substantial energy conservation gains.

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Photovoltaic cells (PVs) are able to convert solar energy to electric energy, while energy storage devices are required to be equipped due to the fluctuations of sunlight. However, the electrical connection of PVs and energy storage devices leads to increased energy consumption, and thus energy storage ability and utilization efficiency are decreased. One of the solutions is to explore an integrated photoelectrochemical energy conversion-storage device. Up to date, the integrated photo-rechargeable Li-ion batteries often suffer from unstable photo-active materials and flammable electrolytes under illumination, with concerns in safety risks and limited lifetime. To address the critical issues, here a novel photo-rechargeable aluminum battery (PRAB) is designed with safe ionic liquid electrolytes and stable polyaniline photo-electrodes. The integrated PRAB presents stable operation with an enhanced reversible specific capacity ≈191% under illumination. Meanwhile, a simplified continuum model is established to provide rational guidance for designing electrode structures along with a charging/discharging strategy to meet the practical operation conditions. The as-designed PRAB presents an energy-saving efficiency ≈61.92% upon charging and an energy output increment ≈31.25% during discharging under illumination. The strategy of designing and fabricating stable and safe photo-rechargeable non-aqueous Al batteries highlights the pathway for substantially promoting the utilization efficiency of solar energy.