Search Results (58)

Continuous growth in energy demand is observed throughout the world, with simultaneous rapid consumption of fossil fuels. New effective technologies and systems are needed that allow for a significant increase in the use of renewable energy sources, such as the sun, wind, biomass, and sea tides. Currently, one of the main research challenges refers to thermal energy management, taking into account the discontinuity and intermittency of both energy supply and demand. Phase change materials (PCMs) are a useful solution in the design and manufacturing of multifunctional materials for energy storage technologies such as solar cells and photovoltaic systems. In order to design efficient PCM-based systems for energy applications, ideas and behaviors from nature should be taken account as it has created over millions of years a plethora of unique structures and morphologies in complex hierarchical materials. Inspirations for nature have been applied to improve and adjust the properties of materials for energy conversion and storage as well as in the design of advanced energy systems. Therefore, this review presents recent developments in biomimetic and bio-inspired multifunctional phase change materials for the energy storage and conversion of different types of renewable energy to thermal or electrical energy. Future outlooks are also provided to initiate integrated interdisciplinary bio-inspired efforts in the field of modern sustainable PCM technologies. Full article

The advantages of green roofs and solar panels are numerous, but in dry periods, green roofs can place urban water resources under pressure, and the efficiency of solar panels can be affected negatively by high temperatures. In this context, our analysis investigated the advantages of bio-solar green roofs and evaluated the impact of green roofs on solar panel electricity production and solar panels on green roof water consumption. The assessment was conducted through simulation in a selected case study located in Cosenza, a city with a Mediterranean climate, with solar panels covering 10% to 60% of the green roof. Analyses were performed on the power outputs of four kinds of photovoltaic panels: polycrystalline, monocrystalline, bifacial, and Passivated Emitter and Rear Contact (PERC). The energy production and shade frequencies were simulated using PVGIS 5.3 and PVSOL 2024 R3. The impact of photovoltaic (PV) shade on the water consumption of green roofs was evaluated by image processing of a developed code in MATLAB R2024b. Moreover, water–energy interconnections in bio-solar green roof systems were assessed using the developed dynamic model in Vensim PLE 10.2.1. The results revealed that the water consumption by the green roof was reduced by 30.8% with a bio-solar coverage area of 60%. However, the electricity production by the PV panel was enhanced by about 4% with bio-solar green roofs and was at its maximum at a coverage rate of 50%. This investigation demonstrates the benefits of bio-solar green roofs, which can generate more electricity and require less irrigation. Full article

For a solar-powered unmanned aerial system (UAS), the performance and integration of the solar panel are of paramount importance. This paper examines the safety aspects of solar panels in electrical power systems, with a particular focus on the installation of solar cells onto an aircraft’s carbon fiber wing. Three distinct installation techniques are evaluated, and their respective advantages and disadvantages are discussed. A preliminary test is conducted to assess the viability of adhering commercial solar panels intended for boats using a bio-adhesive layer placed underneath the series of encapsulated solar panels. To ensure adhesion, the piece is placed under a vacuum. The subsequent test evaluates the lamination of the solar cells onto the carbon fiber skin with a resin as a component of the laminate. Finally, as a definitive solution, the adhesion of the solar panels onto the entire polymer layer used to seal the solar cells themselves was evaluated. This solution offers objective advantages in terms of adhesion, lightness and whiteness. Adhesion is guaranteed by the bond of the thermoplastic polymer used to seal the photovoltaic cells and the epoxy resin of the laminate. The bond is created through the autoclave process, which involves placing the laminate and solar cells in an oven at a specific temperature and pressure for a defined period of time. This solution results in a weight reduction of approximately three times compared to a solution not specifically designed for these materials and a reduction in thickness of approximately two times. Full article

Coherent spatial data are crucial for informed land use and regional planning decisions, particularly in the context of securing a crisis-proof food supply and adapting to climate change. This dataset provides spatial information on climate-robust and high-yield agricultural arable land in Brandenburg, Germany, based on the results of a classification using bio-economic climate simulations. The dataset is intended to support regional planning and policy makers in zoning decisions (e.g., photovoltaic power plants) by identifying climate-robust arable land with high current and stable future production potential that should be reserved for agricultural use. The classification method used to generate the dataset includes a wide range of indicators, including established approaches, such as a soil quality index, drought, water, and wind erosion risk, as well as a dynamic approach, using bio-economic simulations, which determine the production potential under future climate scenarios. The dataset is a valuable resource for spatial planning and climate change adaptation, contributing to long-term food security especially in dry areas such as the state of Brandenburg facing increased production risk under future climatic conditions, thereby serving globally as an example for land use planning challenges related to climate change. Full article

Rising global energy demand, particularly in the building sector, has catalyzed a shift toward sustainable building practices. Buildings are now being redefined from mere energy consumers to potential energy providers, with building façades offering extensive areas for solar installations. This paper reviews recent advances in Wall-Integrated Solar Energy (WISE) systems that produce heat and electricity. A detailed comparison of their structures and performance is provided for various WISE systems, including building-integrated photovoltaic/thermal (BIPV/T) systems, attached sunspaces, Trombe walls, solar thermal collectors (STCs), PV–Trombe, Bio–PV, etc. The goal of this review is to understand the capacity of these technologies to produce energy via walls. The review concludes with key findings and future recommendations, aiming to guide the sustainable evolution of the building industry. Data from the literature suggest that building walls can be a promising energy source with the appropriate integration of solar energy. Full article

Solar photovoltaic technology has consistently been regarded as a crucial direction for the development of clean energy systems in the future. Bio-photovoltaics (BPV), an emerging solar energy utilization technology, is mainly based on the photosynthesis process of photoautotrophic organisms to convert solar energy into electrical energy and output a photocurrent via extracellular electron transfer. As the fundamental unit of the bio-photovoltaic system, the stability of photosynthetic microorganisms under fluctuating and stressful light and heat conditions is likely to have a significant influence on the efficiency of bio-photovoltaic devices. However, this aspect has often been overlooked in previous bio-photovoltaics research. This study took an important cyanobacteria chassis strain, Synechococ elongatus PCC 7942, as the model organism and explored the impact of physiological robustness optimization on its performance as a bio-photovoltaic functional unit. In this work, two types of BPV systems, namely the suspension mode and the biofilm attachment mode, were assembled to evaluate the electricity-generating activity of Synechococcus cells. Overall, the latter demonstrated a remarkable photoelectric output performance. When its light and temperature tolerance was enhanced through FoF1-ATP synthase engineering, the optimized Synechococcus strain exhibited stronger photosynthetic physiology and photoelectric output activity. Under the condition of a light intensity of 2400 μmol photons/m²/s, the maximum photocurrent output of the Synechococcus-based BPV device was increased significantly by 41% over the system based on the wild-type control strain. The results of this study provided a new perspective for the future development and optimization of bio-photovoltaics. Full article

Solar energy is one of the most favorable renewable energy sources and has undergone significant development in the past few years. This paper investigates a novel concept of harvesting the maximum power of a photovoltaic (PV) system using a long-short term memory (LSTM) to forecast the irradiance value and a feedforward neural network (FNN) to predict the maximum power point (MPP) voltage. This study paves a way to mitigate avoidable inefficiencies that hinder the optimal performance of a PV system, due to the intermittent nature of solar energy. MATLAB/Simulink software platform was used to validate the proposed algorithm with real irradiance data from different geographical and weather conditions. Furthermore, the maximum power point tracking (MPPT) algorithm was implemented in a laboratory setup. The simulation results portray the superiority of the proposed method in terms of tracking performance and dynamic response through a comprehensive case study conducted with five other state-of-the-art MPPT methods selected from conventional, AI based, and bio-inspired MPPT categories. In addition to that, faster response time and lesser oscillations around the MPP were observed, even during volatile weather conditions and partial shading. Full article

The performance of photovoltaic (PV) cells is significantly influenced by their operating temperature. While conventional active cooling methods are limited by economic feasibility, passive cooling strategies often face challenges related to insufficient heat dissipation capacity. This study presents a bio-inspired evaporative heat sink, modeled on the transpiration and water transport mechanisms of plant leaves, which leverages porous media flow and heat transfer. The device uses capillary pressure, generated through the evaporation of the cooling medium under sunlight, to maintain continuous coolant flow, thereby achieving effective cooling. An experimental setup was developed to validate the device’s performance under a heat flux density of 1200 W/m², resulting in a maximum temperature reduction of 5 °C. This study also investigated the effects of porous medium thickness and porosity on thermal performance. The results showed that increasing the thickness of the porous medium reduces cooling efficiency due to reduced fluid flow. In contrast, the effect of porosity was temperature-dependent: at evaporation temperatures below 67 °C, a porosity of 0.4 provided better cooling, while at higher temperatures, a porosity of 0.6 was more effective. These findings confirm the feasibility of the proposed device and provide valuable insights into optimizing porous media properties to enhance the passive cooling of photovoltaic cells. Full article

This study compares bio-inspired optimization algorithms for enhancing an ANN-based Maximum Power Point Tracking (MPPT) forecast system under partial shading conditions in photovoltaic systems. Four algorithms—grey wolf optimizer (GWO), particle swarm optimization (PSO), squirrel search algorithm (SSA), and cuckoo search (CS)—were evaluated, with the dataset augmented by perturbations to simulate shading. The standard ANN performed poorly, with 64 neurons in Layer 1 and 32 in Layer 2 (MSE of 159.9437, MAE of 8.0781). Among the optimized approaches, GWO, with 66 neurons in Layer 1 and 100 in Layer 2, achieved the best prediction accuracy (MSE of 11.9487, MAE of 2.4552) and was computationally efficient (execution time of 1198.99 s). PSO, using 98 neurons in Layer 1 and 100 in Layer 2, minimized MAE (2.1679) but had a slightly longer execution time (1417.80 s). SSA, with the same neuron count as GWO, also performed well (MSE 12.1500, MAE 2.7003) and was the fastest (987.45 s). CS, with 84 neurons in Layer 1 and 74 in Layer 2, was less reliable (MSE 33.7767, MAE 3.8547) and slower (1904.01 s). GWO proved to be the best overall, balancing accuracy and speed. Future real-world applications of this methodology include improving energy efficiency in solar farms under variable weather conditions and optimizing the performance of residential solar panels to reduce energy costs. Further optimization developments could address more complex and larger-scale datasets in real-time, such as integrating renewable energy sources into smart grid systems for better energy distribution. Full article

Predicting the system efficiency of green energy and developing forward-looking power technologies are key points to accelerating the global energy transition. This research focuses on optimizing the parameters of proton exchange membrane fuel cells (PEMFCs) and photovoltaic (PV) cells using the honey badger algorithm (HBA), a swarm intelligence algorithm, to accurately present the performance characteristics and efficiency of the systems. Although the HBA has a fast search speed, it was found that the algorithm’s search stability is relatively low. Therefore, this study also enhances the HBA’s global search capability through the rapid iterative characteristics of spiral search. This method will effectively expand the algorithm’s functional search range in a multidimensional and complex solution space. Additionally, the introduction of a sigmoid function will smoothen the algorithm’s exploration and exploitation mechanisms. To test the robustness of the proposed methodology, an extensive test was conducted using the CEC’17 benchmark functions set and real-life applications of PEMFC and PV cells. The results of the aforementioned test proved that with regard to the optimization of PEMFC and PV cell parameters, the improved HBA is significantly advantageous to the original in terms of both solving capability and speed. The results of this research study not only make definite progress in the field of bio-inspired computing but, more importantly, provide a rapid and accurate method for predicting the maximum power point for fuel cells and photovoltaic cells, offering a more efficient and intelligent solution for green energy. Full article

Identification of a natural-based sensitizer with optimal stability and efficiency for dye-sensitized solar cell (DSSC) application remains a challenging task. Previously, we proposed a new class of sensitizers based on bio-nano hybrids. These systems composed of natural cyanidin dyes interacting with silver nanoclusters (NCs) have demonstrated enhanced opto-electronic and photovoltaic properties. In this study, we explore the doping of silver nanocluster within a cyanidin-Ag₃ hybrid employing Density Functional Theory (DFT) and its time-dependent counterpart (TDDFT). Specifically, we investigate the influence of coinage metal atoms (Au and Cu) on the properties of the cyanidin-Ag₃ system. Our findings suggest that cyanidin-Ag₂Au and cyanidin-AgAuCu emerge as the most promising candidates for improved light harvesting efficiency, increased two-photon absorption, and strong coupling to the TiO₂ surface. These theoretical predictions suggest the viability of replacing larger silver NCs with heterometallic trimers such as Ag₂Au or AgAuCu, presenting new avenues for utilizing bio-nano hybrids at the surface for DSSC application. Full article

A micro-photosynthetic power cell (µPSC) generates electricity through the exploitation of living photosynthetic organisms through the principles of photosynthesis and respiration. Modeling such systems will enhance insights into the µPSC that can be employed to design real-time applications from µPSC. In this study, the bio-inspired electrical equivalent modeling of the array of µPSC is elucidated. The model is validated for array configurations of the micro-photosynthetic power cells. The developed arrayed model foresees the steady-state response at various electrical loadings. The polarization characteristics of the current-voltage (I-V) and current-power (I-P) characteristics of the array of µPSC in series and parallel, and their combinations in series and parallel connected µPSCs were validated with the experimental results. From this analysis, it is predicted that the arraying of the µPSC in the combination of series and parallel is the optimal array strategy to obtain the desired voltage and current from the µPSC such that it can be used to power real-time low and ultra-low power devices. Full article

Friction, wear, and the consequent energy dissipation pose significant challenges in systems with moving components, spanning various domains, including nanoelectromechanical systems (NEMS/MEMS) and bio-MEMS (microrobots), hip prostheses (biomaterials), offshore wind and hydro turbines, space vehicles, solar mirrors for photovoltaics, triboelectric generators, etc. Nature-inspired bionic surfaces offer valuable examples of effective texturing strategies, encompassing various geometric and topological approaches tailored to mitigate frictional effects and related functionalities in various scenarios. By employing biomimetic surface modifications, for example, roughness tailoring, multifunctionality of the system can be generated to efficiently reduce friction and wear, enhance load-bearing capacity, improve self-adaptiveness in different environments, improve chemical interactions, facilitate biological interactions, etc. However, the full potential of bioinspired texturing remains untapped due to the limited mechanistic understanding of functional aspects in tribological/biotribological settings. The current review extends to surface engineering and provides a comprehensive and critical assessment of bioinspired texturing that exhibits sustainable synergy between tribology and biology. The successful evolving examples from nature for surface/tribological solutions that can efficiently solve complex tribological problems in both dry and lubricated contact situations are comprehensively discussed. The review encompasses four major wear conditions: sliding, solid-particle erosion, machining or cutting, and impact (energy absorbing). Furthermore, it explores how topographies and their design parameters can provide tailored responses (multifunctionality) under specified tribological conditions. Additionally, an interdisciplinary perspective on the future potential of bioinspired materials and structures with enhanced wear resistance is presented. Full article

This work is part of a research project aimed at developing a bio-based binder, composed mainly of polylactic acid (PLA), to produce Ti6Al4V feedstock suitable for use in MAM (Metal Additive Manufacturing) via mFFF (metal Fused Filament Fabrication), in order to manufacture a titanium alloy specimen. While in Bragaglia et al. the mechanical characteristics of this sample were analyzed, the aim used of this study is to compare the mentioned mFFF process with one of the most used MAM processes in aerospace applications, known as Selective Laser Sintering (SLS), based on the Life Cycle Assessment (LCA) method. Despite the excellent properties of the products manufactured via SLS, this 3D printing technology involves high upfront capital costs while mFFF is a cheaper process. Moreover, the mFFF process has the advantage of potentially being exported for production in microgravity or weightless environments for in-space use. Nevertheless, most scientific literature shows comparisons of the Fused Filament Fabrication (FFF) printing stage with other AM technologies, and there are no comparative LCA “Candle to Gate” studies with mFFF processes to manufacture the same metal sample. Therefore, both MAM processes are analyzed with the LCA “Candle to Gate” method, from the extraction of raw materials to the production of the finished titanium alloy sample. The main results demonstrate a higher impact (+50%) process for mFFF and higher electrical energy consumption (7.31 kWh) compared to SLS (0.32 kWh). After power consumption, the use of titanium becomes the main contributor of Global Warming Potential (GWP) and Abiotic Depletion Potential (ADP) for both processes. Finally, an alternative scenario is evaluated in which the electrical energy is exclusively generated through photovoltaics. In this case, the results show how the mFFF process develops a more sustainable outcome than SLS. Full article

Containing global warming to 1.5 °C implies staying on a given carbon budget and therefore being able to design net zero carbon buildings by 2050. A case study corresponding to a French residential building is used to assess the feasibility of achieving this target. Starting from an actual construction built in 2016, various improvement measures are studied: lowering heating energy needs, implementing bio-sourced materials and renewable energy systems (geothermal heat pump, solar domestic hot water production, and photovoltaic electricity production). Dynamic thermal simulation is used to evaluate energy consumption and overheating risk in hot periods. Greenhouse gas emissions are quantified using a consequential life cycle assessment approach, considering that during a transition period, exporting electricity avoids impacts corresponding to marginal production on the grid. Avoided impacts decrease and become zero when the grid is ultimately “decarbonized”. From this point, the building should be net zero emissions, but there remain unavoidable emissions. Residual GhG (greenhouse gas) emissions account for 5.6 kgCO₂ eq/m² annually. The possibility of offsetting these emissions is investigated, considering sequestration in forests or vegetation systems. A net zero emission level can be achieved, but on a national level, it would require that the whole sequestration potential of forest growth be devoted to offset emissions of new construction. A circular economy for construction products and equipment and considering water use will be needed to further decrease environmental impacts. Full article