Advantages Of Energy Efficiency Research Articles

Comparative analysis of energy efficiency for three heating and cooling supply schemes in a region with hot summers and cold winters in a chemical industrial park

Building energy consumption in China accounts for 45% of the total national energy consumption, with air conditioning energy consumption representing approximately two-thirds of that. Therefore, energy efficiency in buildings is of utmost importance. This study focuses on a chemical industrial park located along the Fujiang River and compares three heating and cooling supply schemes: the river water source heat pump system, which utilizes river water as the heat source and heat sink; the water cooling unit and boiler system, which uses water-cooled electric compression chillers for cooling and an oil-fired boiler system for heating; and the split air conditioning and gas water heater scheme, which relies on refrigerants such as fluorine-containing compounds for cooling and a gas water heater for heating. By calculating the energy consumption of the above three schemes and conducting a comparative analysis, it is found that the river water source heat pump system exhibits significantly higher energy efficiency throughout the year compared to the water cooling unit and boiler system and the split air conditioning and gas water heater scheme. This highlights the notable energy efficiency advantage of the river water source heat pump system.

Leaching kinetics of ash impurities from aphanitic graphite by combining dual-ultrasound and hydrochloric acid–potassium hydrogen fluoride

The hydrochloric acid-fluoride salt is useful for purifying graphite. Ultrasonic-assisted technique can significantly reduce the leaching time and improve the leaching efficiency. Compared with single-frequency, dual-frequency ultrasound has the advantages of high energy efficiency and wide cavitation area. In this study, the combination of a dual-frequency ultrasound-assisted technique and hydrochloric acid–potassium hydrogen fluoride leaching agent was proposed for the leaching of aphanitic graphite to remove impurity minerals. First, the effects of probe-type ultrasonic power, tank-type ultrasonic power, temperature, HCl concentration, ultrasonication time, and KHF2 concentration on the purification efficiency of impurities from aphanitic graphite with the assistance of dual-frequency ultrasound were investigated. It was found that the combination of dual-frequency ultrasound and hydrochloric acid–potassium hydrogen fluoride can reduce the ash content of aphanitic graphite from 13.02 % to 1.02 % with an ash removal rate of 94.17 %. Second, volumetric reaction models and unreacted shrinkage nucleation models were used to fit the kinetics of impurities from aphanitic graphite with dual-frequency ultrasound-assisted HCl-KHF2 leaching. Kinetic analysis shows that the volumetric reaction model with chemical control was better to fit the leaching process. This is consistent with the calculation results of the activation energy of the reaction (Ea = 58.13 kJ/mol). Finally, laser particle size analyzer, X-ray diffraction (XRD), scanning electron microscopy-energy dispersive X-ray spectroscopy (SEM-EDS), X-ray fluorescence spectroscopy (XRF), transmission electron microscopy-energy dispersive X-ray spectroscopy (TEM-EDS) were used to analyze the fugacity of impurity minerals during the process of dual-frequency ultrasound-assisted HCl-KHF2 leaching. It was revealed that combining ultrasonic cavitation fragmentation with chloric acid–potassium fluoride generated SiF4 with high solubility, thereby removing silica-bearing impurities more efficiently. The challenges in further reducing ash content from 1.02 % in the leached concentrate of aphanitic graphite could be attributed to the existence of titanium-bearing mineral impurities on the surface of graphite particles and the presence of silica-bearing minerals between graphite carbon layers.

Effect of infrared technology on the behavior of <i>Listeria monocytogens</i>, <i>Salmonella</i> spp. and Enterobacteriaceae in homogenized raw vaccine milk: preliminary results

Traditional heat treatments in the dairy industry are known for their high water and energy consumption, and more economically and environmentally friendly solutions are being sought. Infrared (IR) technology offers advantages in energy efficiency and environmental sustainability; however, its effectiveness in milk processing, particularly in pathogen inactivation, remains relatively unexplored. In this study, homogenized raw milk was subjected to IR treatment, and its impact on Listeria monocytogenes, Salmonella spp., and Enterobacteriaceae was assessed. Results indicate that the IR treatment effectively reduces the microbial load, achieving levels of inactivation comparable to conventional pasteurization methods (around 6 Log10 CFU/mL). Moreover, the treatment maintains milk pH levels, suggesting minimal alteration to its composition. Further research is needed to explore the full extent of IR treatment on milk sanitation efficacy, deeply exploring IR technology to fully assess its applicability and integration into dairy processing practices. Despite regulatory challenges, the Wir System Milk shows promise as a cost-effective and eco-friendly alternative for raw milk treatment.

Green buildings and their impact on health outcomes and dietary intake: What do we know?

Background: While numerous research has been conducted on the energy efficiency advantages of green buildings, there remains a limited exploration of their effects on individuals’ health conditions and dietary intake. Green building’s structure and design aim to reduce the impact on the surrounding environments while also helping to improve the quality of health of individuals who live within them.Aim: The objective of this study was to examine the impact of green buildings on health outcomes and dietary intake.Method: Using four databases (Agricola, EBSCO, PubMed, and Web of Science), search of literature was directed with the following keywords: green buildings, green homes, built environment, housing design, health outcomes, dietary patterns, dietary intake, eating behavior, food choices, and others. We reviewed 33 articles, and 19 met our inclusion criteria.Results: The synthesis of literature revealed four overarching themes: the association between green buildings and respiratory diseases, mental health, dietary intake, and physical activity level. Our findings suggest an association between green buildings and the improvement of certain health conditions, including asthma, depression, and obesity.Conclusion: The results emphasize the necessity for additional research to investigate the sustained impact of green buildings on residents’ health and dietary habits over an extended period. The implications of the findings are significant for policymakers, urban planners, and researchers, underscoring the potential of green building initiatives in promoting healthy living environments.

Impact of white noise in artificial neural networks trained for classification: Performance and noise mitigation strategies.

In recent years, the hardware implementation of neural networks, leveraging physical coupling and analog neurons has substantially increased in relevance. Such nonlinear and complex physical networks provide significant advantages in speed and energy efficiency, but are potentially susceptible to internal noise when compared to digital emulations of such networks. In this work, we consider how additive and multiplicative Gaussian white noise on the neuronal level can affect the accuracy of the network when applied for specific tasks and including a softmax function in the readout layer. We adapt several noise reduction techniques to the essential setting of classification tasks, which represent a large fraction of neural network computing. We find that these adjusted concepts are highly effective in mitigating the detrimental impact of noise.

Enhanced resistance of PdNiAu membranes under CO and H2S-containing streams

Pd-based membranes offer energy efficiency and economic advantages, providing a promising route for hydrogen separation and recovery from several streams. Alloying Pd with other elements increases its resistance to corrosive gases while improving H2 permeability. This study investigated the permselective properties of PdNiAu membranes with different Ni contents (17, 23, and 27 at.% Ni) in pure H2 and under CO/He/H2 and H2S/H2 mixtures. The permselective properties were evaluated at different temperatures (573-723 K) and pressure differences across the membrane (ΔP: 10-100 kPa). The membranes studied exhibited promising H2 permeation properties; the highest permeability at 673 K and 100 kPa was obtained with the membrane containing 23 at.% Ni (2.1 x10-8 mol m-1 s-1 Pa-0.5). All membranes exhibited high H2/N2 selectivity (>10,000). Regarding chemical stability, the membranes with 23 and 27 at.% Ni, showed high tolerance to inhibition by CO and H2S. These results suggest that increasing Ni improves membrane performance in streams containing CO or S; however, the high chemical resistance of the membranes could be attributed to both Ni and Au.

Diminishing benefits of thermal mass in Iranian climate: Present and future scenarios

Thermal mass, a pivotal element in a building’s performance, functions as an indoor thermal buffer. While literature underscores its advantages, the enduring impact of thermal mass amid climate change remains uncertain. This study methodically assesses thermal mass effects in 21 Iranian cities across contemporary and future climates, juxtaposing heavyweight and lightweight constructions. The EPSAP algorithm, a generative building design method, created a dataset of two-story single-family houses. Cooling and heating demands were evaluated in EnergyPlus, accounting for current and future system design efficiencies. Future climates were simulated using EC-Earth3 model estimations for the SPP5-8.5 scenario in 2050 and 2080 timeframes. The findings reveal that the energy efficiency advantage of heavyweight over lightweight buildings will diminish by up to 0.60 kW·h·m-2 in 2050 (40 % less than the present-day climate difference between constructions) and 0.93 kW·h·m-2 in 2080 (63 %) for cities in central and southern regions. The performance differences between constructions will sometimes be null, making thermal mass negligible. Conversely, only three cities in Northern Iran exhibit an opposing trend for mid to very-high thermal transmittances. Regarding building geometry, heavyweight construction correlates strongly with indexes related to building compactness, while lightweight construction aligns more with glazing-related indexes. However, as climates warm or we move towards warmer regions, discernible differences between lightweight and heavyweight constructions vanish for both shape- and glazing-related indexes. In conclusion, although the use of thermal mass will be less effective, building design professionals will have greater latitude for innovative construction and design solutions.

CNT thin films based on epoxy mixtures: fabrication, electrical characteristics

The simple scaling of silicon transistors no longer ensures the advantages of high energy efficiency, driving research into nanotechnologies beyond silicon. Specifically, digital circuits based on carbon nanotube (CNT) field-effect transistors promise significant advantages in energy efficiency. However, the inability to perfectly control internal nanoscale defects and the variability of carbon nanotubes hinder the realization of very large-scale integrated systems. In this study, we investigated a novel method for fabricating transistors based on carbon nanotubes (CNTs) using epoxy mixtures, obtained the electrical properties of the transistors, and compared their microstructure and composition via the scanning electron microscopy. The carrier mobility on epoxy-based transistors was 28.87 cm²/V∙s, and the transistor switching frequency was 2.2 MHz. The samples exhibited electrical and physical stability over an extended period of time. The use of carbon nanotubes in epoxy resin as a conducting layer for transistors opens significant prospects in the field of electronics. The CNT-epoxy mixture technology allows for more flexible and rapid fabrication of thin-film transistors compared to classical methods. However, it is not appropriate to speak of a complete replacement; in this study, we present an alternative method for producing thin-film transistors, which may be of interest for specific purposes.

Optimization design of heliostat field based on high-dimensional particle swarm and multiple population genetic algorithms

INTRODUCTION: Tower-type heliostat field is a new type of energy conversion, which has the advantages of high energy efficiency, flexibility and sustainability and environmental friendliness.
 OBJECTIVES: Through the research and improvement of the tower heliostat field to promote the development of solar energy utilization technology.
 METHODS: In this paper, we calculate and optimize the tower heliostat field by using single objective optimization, high-dimensional particle swarm algorithm and multiple group genetic algorithm.
 RESULTS: In this case of question setting, average annual optical efficiency is 0.6696; average annual cosine efficiency is 0.7564; annual average shadow occlusion efficiency is 0.9766; average annual truncation efficiency is 0.9975; average annual output thermal power is 35539.1747W; mean annual output thermal power per unit area is 0.5657W.The optimal solution after the initial optimization of the algorithm is that the total number of mirror fields is 6,384 pieces, and the average annual output power per unit area is 530.6W.
 CONCLUSION: The model of this paper can reasonably solve the problem and has strong practicability and high efficiency, but high dimensional particle swarm algorithm due to easily get local optimal solution, so can introduce the chaotic mapping to increase the randomness of the search space, improve the global search ability of the algorithm.

A comparative study of FPGA and CGRA technologies in hardware acceleration for deep learning

With the rapid growth of deep neural networks, their increasing demand for computing resources poses significant challenges to resource-constrained edge devices. Field Programmable Gate Array (FPGA) and Coarse-Grained Reconfigurable Arrays (CGRA) have emerged as promising solutions due to their parallelism and energy efficiency advantages. This paper conducts a comprehensive comparative analysis of FPGA and CGRA for accelerating deep learning workloads. It begins by introducing convolutional neural network architecture and optimization techniques. Various dataflow strategies are discussed for memory access optimization. The paper then analyzes representative cases to clarify FPGA and CGRA architectural advantages, along with optimization techniques through different dataflow strategies. The comparison reveals that FPGA offers higher throughput with fine-grained programmability for flexible bit-level operations and dataflow control. In contrast, CGRA excels in energy efficiency and area consumption with coarse-grained custom processing units and optimized on-chip interconnection networks. Quantitative comparisons are provided for throughput, energy efficiency, and area occupation. These insights can serve as a reference for selecting the appropriate architecture when designing custom hardware accelerators for deep learning workloads.

A novel dual-functional flexible dimming film for smart window applications: Energy saving and self-cleaning performance

Polymer dispersed liquid crystal (PDLC) is a promising candidate for electrically controlled smart window applications because of its energy efficiency, convenience and other advantages. However, its flexibility and heat management capabilities are not effectively evaluated. Herein, a flexible dual-functional intelligent window based on PDLC composite is designed for this purpose, which integrates Ag nanowires as a transparent conductive electrode (TCE) and Tm3+/Yb3+-CsxWO3 (Tm3+/Yb3+-CWO) as a near-infrared shielding and air purification layer. Specifically, the as-made smart window can control the transmission of both visible and near-infrared light. Furtherly, it also possesses self-cleaning capability. A series of characterization has been carried out. The resistance of the Ag nanowire layer is measured to be 22.47 Ω/sq and the transmittance reaches 78.8 %. Flexibility test shows that when the bending radius is 4 mm, the resistance value of the TCE changes only 6 % after 500 repetitions, indicating good flexibility and stability. The spectrum examination reveals that the near-infrared light shielding efficiency achieves 80 % and the average transmittance of visible light is 76.7 %. The degradation of Rhodamine B (RhB) is used to evaluate the purification performance and result shows that the degradation percentage reaches 70 % in 120 min. Heat-regulation simulation test discloses that the indoor temperature can be decreased by 10 °C. Compared to traditional PDLC windows, the designed flexible window has broader application prospects in areas of architecture, vehicle glass, military stealth materials and so on.

Energetic analysis and economic viability of active atmospheric water generation technologies

Water scarcity is a growing global and systematic problem in regions with low groundwater availability. Atmospheric water generation (AWG) technologies are an innovative solution to the water shortage problem, as atmospheric water vapor is a readily available resource even in arid regions, with the drawback of high energy consumption. In this paper, the viability of AWG technologies on an energy and economic level is investigated by thermodynamic modeling of three main active AWG systems consisting of cooling condensation, adsorption and absorption processes. A location analysis model is developed to evaluate the performance based on representative weather data of temperature, pressure and relative humidity over a period of one year to account for seasonal shifts and daily variations in climatic conditions. The specific energy consumption kWh/kg, water production trend and total specific cost are calculated for each technology. Water production by seawater desalination at the nearest coastline and transportation to the site by tanker truck, as well as bottled water prices, are used as benchmarks to assess economic viability. The results show that active AWG systems can only be an economically viable alternative if the water consumption site is relatively far from the coast or other water-rich regions and low electricity costs are available (distance >600 km, electricity price <0.10 US$/kWh). Compared to bottled water, all AWG technologies are in a competitive price range. Absorption systems have an energy efficiency advantage over conventional cooling condensation and adsorption systems (cooling condensation: average 0.42 kWh/kg; absorption: average 0.38 kWh/kg; adsorption: average 1.16 kWh/kg), but require a higher degree of process and plant design development. However, because of the high fluctuation in water production, atmospheric water generation technologies should be considered as a complementary supply to conventional water sources.

Field-free control and switching of perpendicular magnetization by voltage induced manipulation of RKKY interaction

Voltage control of magnetization offers substantial advantages in energy efficiency for the development of spintronics technology. However, achieving a complete 180° magnetization switching remains as a challenging task since the electric field cannot provide torques to turn the magnetic moment in the ferromagnetic material. To address this challenge, we explore the utilization of synthetic antiferromagnetic (sAFM) structure coupled by Ruderman–Kittel–Kasuya–Yosida (RKKY) interaction in the two ferromagnetic (FM) Co layers separated by a suitable thickness Ru spacer layer. One of the FM layers was prepared to be in contact with the GdOx layer, where ionic motion of oxygen can be manipulated via an application of electric field. Depending on the oxidation state at the interface with GdOx, the RKKY coupling can be adjusted and achieves reversible transitions between antiferromagnetic (AFM) and FM orders of FM layers at room temperature. The transition is mediated by the migration and redistribution of oxygen ions, transforming the Co/Gd interface into Co/GdOx and vice versa. This method suggests a stable and electrical route for magnetization reversals without an external magnetic field.

Efficient Spiking Neural Networks With Radix Encoding.

Spiking neural networks (SNNs) have advantages in latency and energy efficiency over traditional artificial neural networks (ANNs) due to their event-driven computation mechanism and the replacement of energy-consuming weight multiplication with addition. However, to achieve high accuracy, it usually requires long spike trains to ensure accuracy, usually more than 1000 time steps. This offsets the computation efficiency brought by SNNs because a longer spike train means a larger number of operations and larger latency. In this article, we propose a radix-encoded SNN, which has ultrashort spike trains. Specifically, it is able to use less than six time steps to achieve even higher accuracy than its traditional counterpart. We also develop a method to fit our radix encoding technique into the ANN-to-SNN conversion approach so that we can train radix-encoded SNNs more efficiently on mature platforms and hardware. Experiments show that our radix encoding can achieve 25× improvement in latency and 1.7% improvement in accuracy compared to the state-of-the-art method using the VGG-16 network on the CIFAR-10 dataset.

Estimating Energy Consumption of Cloud, Fog and Edge Computing Infrastructures

Abstract: To address the imperative need for enhanced locality considerations, innovative Cloud-related architectures, such as Edge Computing, have emerged. Despite the burgeoning popularity of these architectures, their energy consumption remains a relatively unexplored domain. To delve into this critical question, we present a comprehensive approach. Initially, we establish a taxonomy delineating diverse Cloud-related architectures. Subsequently, we introduce an intricate energy model designed to assess their consumption patterns. What sets our model apart is its inclusivity, encapsulating not only the energy usage of computing facilities but also factoring in cooling systems and the energy consumption of network devices connecting end users to Cloud resources. In contrast to prior proposals, our model provides a holistic view of energy consumption within the Cloud ecosystem. The instantiation of our model on various Cloud-related architectures, ranging from fully centralized to entirely distributed ones, facilitates a nuanced comparison of their energy consumption. Our findings reveal that a fully distributed architecture, by eschewing intra-data center networks and large-scale cooling systems, exhibits a notable energy efficiency advantage, consuming between 14% and 25% less energy than fully centralized and partially distributed architectures, respectively. Notably, our work represents a pioneering effort in introducing a model that empowers researchers to analyze and compare the energy consumption of diverse Cloud-related architectures.

Renewable energy consumption and its impacts on agriculturalization under climate neutrality targets

Improvements in energy efficiency, cost savings, and environmental advantages are possible effects of adopting and using renewable energy in agriculture. However, whether renewable energy consumption (REC) has any impact on agricultural productivity is a research question that this analysis tries to answer. Previous research neglected to consider the influence of REC on agriculture. The primary objective of the analysis is to analyze the role of REC in sustainable agriculture in Asia, America, Africa, and Europe with the help latest econometric technique of the CS-ARDL model. The findings show that REC and technological capital (TC) improve long-run agriculturalization in the full sample, Asia, Africa, America, and Europe. The results infer that a 1% increase in REC causes agriculturalization to boost by 1.512% in the full sample, 1.254% in Asia, 1.654% in Africa, 0.897% in America, and 1.325% in Europe. In addition, financial development favorably influences long-run agricultural productivity in the full sample, Africa, America, and Europe, and population growth only impacts agricultural productivity in the long run. In contrast, the long-run agricultural productivity is negatively impacted by environmental pollution globally and in Asia. On the other hand, in the short run, TC positively impacts agricultural productivity in all samples, while other short-run estimates are insignificant in most samples. These findings suggest that renewable energy utilization may lead to more effective and resilient agricultural systems by supplying clean and dependable electricity, lowering greenhouse gas emissions, and supporting sustainable resource management.

The Relationship Between Green Finance, Sustainable Technological Innovation and Energy Efficiency

Sustainable technological innovation can promote this progress in finance. This optimization and upgrading of energy efficiency can provide a good energy environment for green development. The collaborative innovation of financial enterprises has brought such development to the tertiary industry, driving the upgrading of consumer demand, and thus promoting the development of green finance. At this same time, sustainable technological innovation will increase investment in environmental protection, reduce energy consumption, promote the reduction of carbon emissions in the financial industry, and accelerate the development of green finance. This paper uses the data envelopment analysis method to calculate the Marquis production efficiency index, examines the dynamic generation efficiency of intertemporal energy input and output, and calculates the energy efficiency of green finance. This article measures and deconstructs energy efficiency at the provincial level, and pays attention to its changes. The study depicted the efficiency distribution of 28 provinces in two stages of the survey period. By using random kernel estimation for two periods during the survey period, dynamic distribution three-dimensional maps and density contour maps of total factor energy productivity, energy utilization efficiency, and energy allocation efficiency growth rates were drawn for the two periods. The results show that the transfer probability group of energy efficiency and its decomposition terms mainly falls near the diagonal, indicating that TFP and its decomposition term growth rate have certain transferability. From 2005 to 2015, the energy utilization efficiency of the seven economic regions has been significantly improved, and the energy efficiency differences in different regions have gradually converged. The energy efficiency of the Yangtze River Delta and the Pearl River Delta is the highest and has been continuously improved, followed by the Beijing Delta, the central region, the northeast region and the southwest region are again in terms of energy efficiency. Compared with provinces with relatively poor industrial structures, provinces with better industrial structures do not have significant advantages in energy efficiency, while provinces with higher levels of technological innovation typically have relatively higher energy efficiency.

Thermohydraulic performance analysis and parameters optimization of the combined heat sinks with microchannels and micro pin-fins

The combined heat sinks of microchannels and micro pin-fins are numerically studied in depth by three-dimensional conjugate heat transfer models for flow rate (Qv) ranging from 18 to 90 ml/min. The influence degrees of multiple parameters, i.e., the lengths and widths of the cavities and pin-fins, on cooling effect, pressure drop and comprehensive performance are analyzed quantitatively by Taguchi method. And the optimal combination structures for temperature of heat sink (OCS-T), pressure drop (OCS-PD) and performance evaluation criterion (OCS-PEC) are obtained accordingly. The original heat sink with fan shaped cavities and diamond pin-fins (FC-DPF) and the smooth rectangular heat sink (SR) are selected for comparison. The coupling effects of four structure parameters on the local and average thermal hydraulic characteristics are elucidated. The interrelation of multiple physical fields and the comprehensive efficiency of the optimal combination structures are discussed thoroughly. Moreover, the thermodynamic properties and irreversibility are illustrated based on the entropy generation. Results demonstrate that the length of fan shaped cavity and the width of diamond pin–fin have a dominant impact on heat dissipation and pressure drop. The width of cavity has a noticeable impact on the overall performance. Large width of cavity is favorable to induce transverse flow, and large width of pin–fin contributes to distinct vortices. The symmetrical vortices in the direction of channel height can improve chaotic mixing and temperature uniformity. At high flow rate, the performance evaluation criterion (PEC) of the OCS-PEC is increased by 29 % compared to the original structure FC-DPF. When total thermal resistances of the above two heat sinks are similar (0.43 K/W of the OCS-PEC and 0.45 K/W of the FC-DPF), the pumping power of the OCS-PEC (0.47 W) is 35 % lower than that of the FC-DPF (0.72 W) proving the excellent overall efficiency. In addition, the OCS-PD and OCS-PEC show better thermodynamic performance and less irreversible loss for high flow rate, which implies the energy efficiency advantage. The synergistic mechanism of flow and heat transfer is revealed and the results are significant for further understanding the rules of performance enhancement. The excellent overall performance of the OCS-PEC at high flow rate makes it more promising in application for electronic chips cooling in aerospace, defense and communication fields, thermal management of battery, hydrogen storage, fusion energy management, etc.

Humidity-Induced Protein-Based Artificial Synaptic Devices for Neuroprosthetic Applications.

Neuroprosthetics and brain-machine interfaces are immensely beneficial for people with neurological disabilities, and the future generation of neural repair systems will utilize neuromorphic devices for the advantages of energy efficiency and real-time performance abilities. Conventional synaptic devices are not compatible to work in such conditions. The cerebrospinal fluid (CSF) in the central part of the nervous system is composed of 99% water. Therefore, artificial synaptic devices, which are the fundamental component of neuromorphic devices, should resemble biological nerves while being biocompatible, and functional in high-humidity environments with higher functional stability for real-time applications in the human body. In this work, artificial synaptic devices are fabricated based on gelatin-PEDOT: PSScomposite as an active material to work more effectively in a highly humid environment (≈90% relative humidity). These devices successfully mimic various synaptic properties by the continuous variation of conductance, like, excitatory/inhibitory post-synaptic current(EPSC/IPSC), paired-pulse facilitation/depression(PPF/PPD), spike-voltage dependent plasticity (SVDP), spike-duration dependent plasticity (SDDP), and spike-rate dependent plasticity (SRDP) in environments at a relative humidity levels of ≈90%.

Chlorella vulgaris Harvesting: Chemical Flocculation with Chitosan, Aluminum Sulfate, and Ferric Sulfate

Chlorella vulgaris, a widely cultivated microalgae with diverse commercial applications, faces challenges in economic viability and scalability during the crucial biomass harvesting step. This study explores chemical flocculation followed by sedimentation as a cost-effective solution. Optimization was performed for three flocculants (chitosan, aluminum sulfate, and ferric sulfate), with experiments determining optimal pH and dosage ranges (10–200 mg·L−1). A 24-full factorial design optimized flocculant dosage, settling time, rapid mixing time, and slow mixing time, analyzing their effects on harvesting efficiency through empirical models. The optimal dosage ranges were 50–200 mg·L−1 for aluminum sulfate and 150–200 mg·L−1 for ferric sulfate at pH 9, and 10–50 mg·L−1 for chitosan at pH 5. Empirical models exhibited high fitting performance (R2 &gt; 95%) and predictive capability (predicted R2 &gt; 96%). All flocculants demonstrated high efficiencies (98.4–99.5%), with inorganic types requiring fast and slow mixing phases, while chitosan achieved optimal results without the need for both mixing phases, suggesting potential industrial advantages in time and energy efficiency for microalgae harvesting.