Excessive Energy Consumption Research Articles

Towards carbon neutrality: asymmetric impact of financial development and digitalization on carbon dioxide emissions in Mediterranean countries

AbstractThe current research investigates the impact of financial development, digitalization, green trade, manufacturing, and national income on carbon dioxide (CO2) emissions of six Mediterranean countries (MEDIT-6). The study uses a nonlinear panel quantile regression model with panel data of MEDIT-6 countries from 1994 to 2022. The study asserts that higher financial development will reduce CO2 emissions for MEDIT-6 countries, as it provides more financing options to invest in green energy and potentially curb excessive energy consumption which in turn reduces CO2 emissions. The study also provides evidence that digitalization in MEDIT-6 countries has led to dematerialization, thereby reducing CO2 emissions. Digitalization makes trade and commerce platforms more efficient by facilitating the smooth flow of information and enhancing the efficiency of production processes. The positive relationship between manufacturing and national income and CO2 emissions exhibits a U-shaped pattern, which supports the existence of Environmental Kuznets Curve (EKC) hypothesis. The study shows how the MEDIT-6 countries have been successful in promoting financial development and digitalization, which helps reduce their CO2 emissions. However, it also raises concerns for policymakers as promoting developmental activities such as manufacturing is inevitable, but it comes with environmental challenges such as higher CO2 emissions. The current study contributes to the reservoir of existing literature by providing fresh evidence from the Mediterranean region on the impact of financial development and digitalization on CO2 emissions. Graphical Abstract

Electrocatalytic conversion of nitrate to ammonia on the oxygen vacancy engineering of zinc oxide for nitrogen recovery from nitrate-polluted surface water.

Nitrate pollution in surface water poses a significant threat to drinking water safety. The integration of electrocatalytic reduction reaction of nitrate (NO3RR) to ammonia with ammonia collection processes offers a sustainable approach to nitrogen recovery from nitrate-polluted surface water. However, the low catalytic activity of existing catalysts has resulted in excessive energy consumption for NO3RR. Herein, we developed a facile approach of electrochemical reduction to generate oxygen vacancy (Ov) on zinc oxide nanoparticles (ZnO1-x NPs) to enhance catalytic activity. The ZnO1-x NPs achieved a high NH3-N selectivity of 92.4% and NH3-N production rate of 1007.9 h-1 m-2 at -0.65 V vs. RHE in 22.5 mg L-1, surpassing both pristine ZnO and the majority of catalysts reported in the literature. DFT calculations with in-situ Raman spectroscopy and ESR analysis revealed that the presence of Ov significantly increased the affinity for the (nitrate) and key intermediate of (nitrite). The strong adsorption of on Ov decreased the energy barrier of potential determining step ( →*NO3) from 0.49 to 0.1 eV, boosting the reaction rate. Furthermore, the strong adsorption of on Ov prevented its escape from the active sites, thereby minimizing by-product formation and enhancing ammonia selectivity. Moreover, the NO3RR, when coupled with a membrane separation process, achieved a 100% nitrogen recycling efficiency with low energy consumption of 0.55 kWh at a flow rate below 112 mL min-1 for the treatment of nitrate-polluted lake water. These results demonstrate that ZnO1-x NPs are a reliable catalytic material for NO₃RR, enabling the development of a sustainable technology for nitrogen recovery from nitrate-polluted surface water.

Enhanced Ant Colony Based VM Selection and Consolidation for Energy Conservation

Cloud Computing (CC) involves extensive data centers with numerous computing nodes that consume significant electrical energy. Researchers have identified high service-level agreement (SLA) violations and excessive energy consumption (EC) as major challenges in CC. Traditional approaches often focus on reducing EC but tend to overlook SLA violations, particularly when selecting Virtual Machines (VMs) from overloaded hosts. To address these issues, this paper introduces the Enhanced Ant Colony Optimization (EACO) algorithm, aims to reduce high EC and SLA violations by utilizing a unique approach where the best-performing ant explores movement patterns and identifies distances between movements. The algorithm comprises three key steps: tracking pheromone trails, updating pheromones and selecting the cities (VMs). The effectiveness of EACO was validated through simulations using CloudSim. Compared to existing techniques, EACO demonstrated a significant reduction in EC, achieving approximately 41-44% lower energy consumption than the traditional Ant Colony Optimization (ACO) algorithm when applied to Planet Lab data. This suggests that EACO offers a more efficient and stable solution for managing EC and SLA violations in cloud environments.

Photoinhibition Sensitivity of Abies sachalinensis Saplings Under Different Leaf Mass per Area Conditions: Insights into Acclimation to Current and Future Light Environments

Photoinhibition, a common physiological obstacle in forest regeneration, results from rapid light elevations after removing upper-layer trees, thereby impeding sapling growth and survival. The leaf mass per area (LMA), which reflects the current light environment, may predict saplings’ responses to future elevations in light intensity. However, the relationship between the LMA and photoinhibition sensitivity in boreal forest evergreen conifers remains unclear. In this study, we explored whether the LMA was related to photoinhibition sensitivity in A. sachalinensis saplings. Saplings with a high LMA exhibited higher excitation pressure (1−qP) under the current light environment, leading to increased stress even at low relative light intensities of 3%–17%. A model illustrating the dependence of photosynthetic physiological parameters on the photosynthetic photon flux density (PPFD) revealed that 1−qP significantly decreased with an increasing LMA, while the electron transfer rate (ETR) and non-photochemical quenching (NPQ) significantly increased. Additionally, regardless of the LMA, 1−qP reached near saturation (≈1.0) at a PPFD of 1000 μmol m−2 s−1, likely owing to the inefficient consumption of excess energy by electron transfer, as indicated by the low maximum ETR (approximately 25 μmol m−2 s−1). These findings suggest that although A. sachalinensis exhibits high sensitivity to photoinhibition, a high LMA may reflect physiological acclimation to forthcoming elevations in light exposure, thereby reducing the susceptibility to photoinhibition at present and in the future.

New Solution to 3D Projection in Human-like Binocular Vision

A human eye has about 120 million rod cells and 6 million cone cells. This huge number of light-sensing cells inside a human eye will continuously produce a huge quantity of visual signals that flow into the human brain for daily processing. However, the real-time processing of these visual signals does not cause excessive energy consumption by the human brain. This fact tells us the truth which is to say that human-like vision processes do not rely on complicated and expensive formulas to compute depth, displacement, and colors. On the other hand, the human eye is like a camera with pan-tilt (PT) motions. We all know that in computer vision, each set of PT parameters (i.e., coefficients of pan motion as well as tilt motion) requires a dedicated calibration to determine a camera’s projection matrix. Since there is an infinite number of PT parameters that could be produced by a human eye, it is unlikely that a human brain stores an infinite number of calibration matrices for each human eye. These observations inspire us to look for a simpler and computationally non-expensive solution which is to undertake three-dimensional (3D) projection in human-like binocular vision. In other words, it is an interesting question for us to answer, which is to say whether simpler and learning-friendly formulas for computing depth and displacement exist or not. If the answer is yes, these formulas must also be calibration-friendly (i.e., easy process on the fly or on the go). In this paper, we present an important discovery of a new solution to 3D projection in a human-like binocular vision system. This solution is computationally simpler and could be easily learned or calibrated on the fly. We know that the purpose of doing 3D projection in binocular vision is to undertake forward and inverse transformations (or mappings) between coordinates in 2D digital images and coordinates in a 3D analogue scene. The formulas underlying the new solution are accurate, easily computable, easily tunable (i.e., to be calibrated on the fly or on the go) and could be easily implemented by a neural system (i.e., a network of neurons or a network of computational flows). Experimental results have validated the newly derived formulas which are better than textbook solutions.

Three-layered films enable efficient passive radiation cooling of buildings

Abstract To address the excessive energy consumption of building cooling, the coverage of passive radiation cooling materials on the surface of buildings can effectively save the global refrigeration power resources and reduce the greenhouse gas emissions generated by refrigeration equipment. In this work, passive radiation hydrophobic fabric cooling materials with three functional layers (i.e., top polydimethylsiloxane [PDMS] film layer for solar emissivity, middle polymethylmethacrylate [PMMA] film layer for solar reflectivity, and bottom cotton fabric layer for support) were prepared. This passive radiation cooling material with optimized thickness of PDMS (1.5 mm) and PMMA (3.5 mm) have a rich uneven filament structure and ideal internal bonding structure, which enabled 94% of solar reflectivity and 93.4% of atmospheric window emissivity (8–14 μm). Top layer of the composite film was hydrophobic (a contact angle of 117°) and allowed the rolling of water droplets to remove most of the surface dust. Moreover, these composites presented an excellent cooling of 7.7–15.0°C in the outdoor real cooling test. For medium-sized houses, the roof covered with composite was expected to reduce the emission CO2 by 17% every year. The findings of this work indicated that the prepared three-layered radiation cooling materials have great potentials in thermal energy storage buildings.

ENERGY AUTOMATION SUPPORTS ENERGY CONSUMPTION INTENSITY IN CLASSROOMS

Automation of energy use to control energy consumption intensity (IKE) in classrooms is carried out using an Arduino Nano-based system. This system utilizes an IR transmitter to send signals to the air conditioning unit, a servo motor to position the IR transmitter to the appropriate air conditioning unit, a relay to control the lights, and a Real-Time Clock (RTC) module for scheduling based on a specified schedule. The main goal is to prevent energy waste and ensure comfort by turning on and off the air conditioning unit and lights according to a preset schedule. This automatic scheduling includes time setting, transmitter IR control, servo motor, relay control, and LCD. Programmed scheduling ensures that the air conditioner and lights only turn on when needed, while the LCD provides real-time information about the status of the air conditioner and lights. With this automation, the system helps reduce excessive energy consumption, drives significant energy savings, and creates a comfortable and energy-efficient learning environment. The automatic monitoring and regulation system also allows users to focus more on teaching and learning activities without having to worry about manual settings for air conditioning and lights.

A Review on Bioflocculant-Synthesized Copper Nanoparticles: Characterization and Application in Wastewater Treatment.

Copper nanoparticles (CuNPs) are tiny materials with special features such as high electric conductivity, catalytic activity, antimicrobial activity, and optical activity. Published reports demonstrate their utilization in various fields, including biomedical, agricultural, environmental, wastewater treatment, and sensor fields. CuNPs can be produced utilizing traditional procedures; nevertheless, such procedures have restrictions like excessive consumption of energy, low production yields, and the utilization of detrimental substances. Thus, the adoption of environmentally approachable "green" approaches for copper nanoparticle synthesis is gaining popularity. These approaches involve employing plants, bacteria, and fungi. Nonetheless, there is a scarcity of data regarding the application of microbial bioflocculants in the synthesis of copper NPs. Therefore, this review emphasizes copper NP production using microbial flocculants, which offer economic benefits and are sustainable and harmless. The review also provides a characterization of the synthesized copper nanoparticles, employing numerous analytical tools to determine their compositional, morphological, and topographical features. It focuses on scientific advances from January 2015 to December 2023 and emphasizes the use of synthesized copper NPs in wastewater treatment.

Smart self-assembled polymeric-MMT/Moringa Oleifera L. particles by solvent replacement method

Obesity, stemming from metabolic syndrome and energy imbalance, is a common health concern characterized by excess energy consumption and fat buildup. Moringa Oleifera L. (MO), known for its anti-obesity properties, is extracted via Soxhlet extraction. MO is extracted using the Soxhlet extraction method. To evaluate the antioxidant properties of MO powder, several analyses were conducted, including the assessment of total phenolic content (TPC), total flavonoid content (TFC), 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulphonic acid) (ABTS) activity, and 2,2-diphenyl-1-picrylhydrazyl (DPPH) activity. The TPC and TFC, DPPH activity, and ABTS activity values were determined to be 386.7 mg GAE/g and 82.33 mg QE/g, 32.86 %, and 49.4 % respectively. To improve drug delivery, the freeze-dried MO powder was encapsulated within a polymeric carrier, poly(e-caprolactone) (PCL). Moreover, the incorporation of montmorillonite (MMT) into the MO-loaded PCL nanoparticles enhanced the encapsulation efficiency and drug loading of MO. Nanoprecipitation was employed as a method to produce the nanoparticles, and the effects of four key parameters were studied: the ratio of aqueous phase volume to organic volume (1.5 – 10), stirring speed (400 rpm – 1200 rpm), mass weightage of MO (1 % -5 %), and mass weightage of MMT (2 % - 5 %). Design Expert was utilized for full factorial analysis to assess the impact of these parameters on encapsulation efficiency and drug loading. The optimal formulation was achieved at the ratio of aqueous phase volume to the organic volume of 1.5, stirring speed of 400 rpm, mass weightage of MO at 1 %, and mass weightage of MMT at 5% The expected encapsulation efficiency is 91.33 % and drug loading is 6.49 %.

Evaluation of Direct Sunlight Availability Using a 360° Camera

One important aspect to consider when buying a house or apartment is adequate solar exposure. The same applies to the evaluation of the shadowing effects of existing buildings on prospective construction sites and vice versa. In different climates and seasons, it is not always easy to assess if there will be an excess or lack of sunlight, and both can lead to discomfort and excessive energy consumption. The aim of our project is to design a method to quantify the availability of direct sunlight to answer these questions. We developed a tool in Octave to calculate representative parameters, such as sunlight hours per day over a year and the times of day for which sunlight is present, considering the surrounding objects. The apparent sun position over time is obtained from an existing algorithm and the surrounding objects are surveyed using a picture taken with a 360° camera from a window or other sunlight entry area. The sky regions in the picture are detected and all other regions correspond to obstructions to direct sunlight. The sky detection is not fully automatic, but the sky swap tool in the camera software could be adapted by the manufacturer for this purpose. We present the results for six representative test cases.

OPTIMIZATION OF HEAT CONSUMPTION IN CENTRAL HEATING SYSTEMS AT COMMERCIAL FACILITIES

Rising energy prices and stricter environmental regulations are exacerbating the problem of inefficient heat consumption in the commercial sector. Central heating systems of office buildings, shopping malls, and industrial complexes are often characterized by excessive thermal energy consumption, which leads to significant economic losses and a negative impact on the natural environment. The purpose of the study is to study the directions and trends of optimization in the field under consideration (taking into account modern technological capabilities, and economic factors). There are disagreements in the professional community about the priority of measures to improve energy efficiency: some experts prefer improving the thermal insulation of buildings, others — the introduction of intelligent control systems, and others — the integration of renewable energy sources. The present study demonstrates that the greatest effect is achieved with a systematic approach combining various initiatives. The conclusion is formulated that in the current conditions and the future, a comprehensive application of modern thermal insulation materials, highly efficient heating equipment, intelligent management mechanisms, and alternative energy sources is required. The article is of interest to engineers-designers of heating systems, energy managers of commercial facilities, specialists in energy efficiency of buildings, and heads of companies interested in optimizing operating costs and improving the environmental friendliness of their real estate.

High-current decoupled hydrogen and oxygen evolution via nickel–cobalt based redox mediators and bifunctional catalyst of 3D printing substrates

The conversion of renewable energy sources with relatively large energy fluctuations into hydrogen represents a crucial aspect of energy storage. Nevertheless, the direct water electrolysis process is known to require excessive instantaneous energy consumption and high cost. Two-step alkaline water electrolysis is regarded as a secure and effective method of generating hydrogen from renewable energy sources when compared to direct water electrolysis. Here we propose a two-step alkaline water electrolysis using nickel–cobalt based hydroxide (Ni0.9Co0.1(OH)2) as a redox mediator, and a high-performance bifunctional catalyst as gas evolution electrodes (GEE). The substrates for the GEE were prepared using 3D printing and then loaded with in-situ grown Ru-doped MoS2/NiFe-LDH hierarchical heterostructure catalysts (MS-NiFe-Ru-3D). The oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) of the MS-NiFe-Ru-3D catalyst can reach up to 500 mA cm−2 at 300 and 250 mV overpotentials, respectively. It can meet the requirement of high catalyst performance for two-step alkaline water electrolysis. The direct water electrolysis using the bifunctional MS-NiFe-Ru-3D catalyst only requires a voltage of 1.85 V at 500 mA cm−2 with minimal attenuation over 300 h. For the two-step alkaline water electrolysis using MS-NiFe-Ru-3D as bifunctional catalysts and Ni0.9Co0.1(OH)2 as redox mediator, only 1.70 V and 0.27 V were required for HER and OER at 500 mA cm−2, respectively. This work offers a promising avenue for the efficient conversion of renewable secondary energy sources into hydrogen.

A multi-scale method for the study of deep drying of ethylene with 3A zeolite

Coal-based ethanol to ethylene (ETE) is an emerging production pathway with the advantages of a short construction period, high product purity, and few by-products. N2 is commonly used in industry to regenerate zeolites during the ETE process, with the problems of excessive material consumption, energy consumption and environmental pollution. To solve this problem, this paper proposed a method of using the ethylene product as regeneration gas to regenerate the zeolite and recover the desorbed gas. In this work, we adopted a multi-scale simulation method combining microscale apparent diffusivity and macroscale mass transfer models. Reactive force field and molecular dynamics (ReaxFF-MD) were used to obtain an equation for the diffusion coefficient versus temperature. The start-up of the twin-tower temperature and pressure swing adsorption (TPSA) process was simulated using Computational Fluid Dynamics (CFD). The TPSA process achieved an outlet water content below 5 ppm, fulfilling the process specifications.

Grouping-maintenance of multi-components production system under ecological background

Purpose: The purpose of this paper is to propose an opportunistic group maintenance model for a multi-component series system considering reducing CO2 emission and increasing system efficiency, which establishes a maintenance policy to minimize the cost rate of the system life cycle.Design/methodology/approach: Structural dependence and economic dependence between the components in a multi-component series system are analyzed to make a condition-based maintenance policy. To minimize the cost rate of the system life cycle, clustering theory and two decision variables, which include the preventative maintenance cycle multiplier and basic preventive maintenance interval of each component, is utilized to make an opportunistic policy for system optimal maintenance under the background of increasing energy efficiency and reducing CO2 emissions.Findings: It can be concluded that the government imposes fines on excessive CO2 emissions and energy consumption indicators, which can influence the maintenance decisions of enterprises, promote enterprises to shorten the cycle of preventive maintenance, and avoid excessive CO2 emissions of various components and exceed the indicators as much as possible, so as to enable enterprises to actively save energy, reduce emissions and control carbon emissions. Furthermore, when the single preparation cost of repair maintenance increases, enterprises need to shorten the maintenance period to avoid frequent component failures. As the cost of a single prep for preventive maintenance rises, organizations need to extend maintenance cycles and avoid frequent parts downtime - minimizing their own repair costs.Practical implications: Considering the high maintenance cost and low energy efficiency of multi-component systems, this model assists production managers to have better maintenance of these systems.Originality/value: 1.Model innovation: comprehensive consideration of two variables in the selection of decision variables for preventive maintenance or opportunistic maintenance; The selection and synthesis of ecological factors when making ecologically conscious maintenance decisions for multi-component systems make up for the gaps of single variables and one-sided indicators in previous studies and models. 2. Methodological innovation: In the identification of opportunity maintenance, the idea of clustering is first combined; In the simulation analysis, genetic algorithm is used to obtain the optimal parameters quickly and accurately. A blend of management, statistics, biology and computer science.

An energy efficient leaky integrate and fire neuron using Ge-source TFET for spiking neural network: simulation analysis

The basic building block of neural network is a device, which can mimic the neural behavior. The spiking neural network (SNN) is an efficient methodology in terms of power and area. Due to the excess energy consumption and larger area, various spintronic neural devices are unfit for neuron applications. In this article, we have implemented Ge source based Tunnel FET (TFET) for ultralow energy spike generation using TCAD simulator. It is seen that Ge source TFET has signature spiking frequency in THz range versus input voltage curve of an artificial biological neuron. The simulated device deploy the leaky integrate and fire (LIF) technique for generation of neurons. The simulation result highlights that the energy of device is 1.08 aJ/spike, which is several order less than existing neural based FET devices in literature.

Analysis of operation regulation on delay time in long-distance heating pipe systems for practical engineering

The distribution area of the district heating network (DHN) is extensive, and there are inherent time delays and thermal losses in the process of heat transfer through heating pipes. The delay in heat transfer within long-distance heating pipes may result in inadequate heat supply to end-users or excessive energy consumption at the heat source. Therefore, this paper presents a quasi-dynamic model for calculating the transmission delay time in the long-distance heating pipeline. And the model is validated through the measured values obtained from a heating pipeline. The influencing factors of delay time are further discussed, including operating parameters, pipe structure parameters and thermal insulator thickness. Additionally, the impact of pipe delay time in practical engineering is analyzed. In practical engineering, the transmission delay time varies when the pipe structural or operational parameters differ, even under the same outdoor temperature change. The change in inlet water temperature and mass flow rate can impact the change rate of outlet water temperature, thereby influencing the delay time. Furthermore, the delay time exhibited an increase with pipe length, diameter, and thermal insulator thickness; however, the effect of thermal insulator thickness on it was minimal. When the inlet water temperature rose or dropped by 5℃, the delay time grew by more 70 % per 1 km pipe length, about 40 % per 100 mm diameter and less 2 % per 100 mm thermal insulator thickness, respectively.

Multidisciplinary Optimization of Aircraft Aerodynamics for Distributed Propulsion Configurations

The combination of different aerodynamic configurations and propulsion systems, namely, aero-propulsion, affects flight performance differently. These effects are closely related to multidisciplinary collaborative aspects (aerodynamic configuration, propulsion, energy, control systems, etc.) and determine the overall energy consumption of an aircraft. The potential benefits of distributed propulsion (DP) involve propulsive efficiency, energy-saving, and emissions reduction. In particular, wake filling is maximized when the trailing edge of a blended wing body (BWB) is fully covered by propulsion systems that employ boundary layer ingestion (BLI). Nonetheless, the thrust–drag imbalance that frequently arises at the trailing edge, excessive energy consumption, and flow distortions during propulsion remain unsolved challenges. These after-effects imply the complexity of DP systems in multidisciplinary optimization (MDO). To coordinate the different functions of the aero-propulsive configuration, the application of MDO is essential for intellectualized modulate layout, thrust manipulation, and energy efficiency. This paper presents the research challenges of ultra-high-dimensional optimization objectives and design variables in the current literature in aerodynamic configuration integrated DP. The benefits and defects of various coupled conditions and feasible proposals have been listed. Contemporary advanced energy systems, propulsion control, and influential technologies that are energy-saving are discussed. Based on the proposed technical benchmarks and the algorithm of MDO, the propulsive configuration that might affect energy efficiency is summarized. Moreover, suggestions are drawn for forthcoming exploitation and studies.

Bio-inspired wireless sensor networks - a protocol for an enhanced hybrid energy optimization routing

Recently, there has been a focus on the significance of swarm intelligence-inspired routing algorithms for achieving optimum solutions in biologically inspired wireless sensor networks (WSNs). These protocols depict a network of wireless mobile nodes forming an infrastructure that is agile, dynamic, and independent of a central administrative facility. Among the challenges faced by bio-inspired WSNs, mobility awareness and excessive energy consumption (EC) stand out as significant hurdles, particularly in dynamic models with intermittent connections. This project seeks to tackle these obstacles by deploying the hybrid energy efficiency (HEED) approach to distributed clustering for network system cluster formation, along with fusion routing protocol of particle swarm optimization (PSO) and PIO to select cluster-heads and optimize solutions in bio-inspired WSNs. The success of the suggested approach is assessed using a variety of criteria, such as energy usage, rate of packet delivery, EC, and routing overhead and network lifetime. The methods like ad hoc on-demand distance vector's (AODV) and ant colony optimization (ACO) methods are employed in the testing and validation. In comparison to the reactive AODV routing protocol and ACO, the suggested routing protocol (HPSOPIO) reduces energy usage and increases network lifespan.

Implementation and validation of optimal start control strategy for air conditioners and heat pumps

Commercial buildings are responsible for approximately 20 % of the total energy consumption and greenhouse gas emissions in the United States. Over 85 % of these buildings lack building automation systems, and many are small (<50,000 square feet), underserved, and use rooftop units (RTUs) for heating, ventilation, and air-conditioning needs. Because these buildings lack proper energy management systems, several operational deficiencies lead to excess energy consumption. Studies have shown that managing the RTUs’ heating and cooling set points, schedules, setbacks, and optimal start can result in a 20 % to 25 % reduction in electricity consumption in small commercial buildings. These buildings typically use fixed schedules to start the RTUs 60 to 120 min before occupancy begins, which results in excess energy consumption. This paper presents research that demonstrates and evaluates the performance of four optimal start methods, which utilize data-based modeling as a key element in facilitating adaptive control in response to time-varying inputs while requiring minimal sensor inputs. The evaluation found energy savings in two commercial buildings equipped with RTUs by periodically alternating four different optimal start models during the cooling and heating season. The resulting energy savings are positive for all models and range from 2 to 5 kWh/day/unit. The units on the east side of the building showed higher savings, while interior units showed greater variability in savings due to the differences in capacities and room sizes. Savings were considerably greater during the heating season compared to the cooling season. The performance of all four models on Mondays was poor; models suggested a shorter optimal start time, which resulted in relatively larger errors. The future work will look at using a different model for the days after weekends and holidays.

Electroreduction Reactions Mediated by Organic Molecules: Recent Advances and Applications

Electroreduction is an important aspect of organic electrochemistry. Its chemistry does not require the addition of additional reductants, making it an effective alternative to various traditional reduction reactions. Among them, organo‐mediated electroreduction is recognized as a promising approach. Organo‐mediators can be reduced directly at the cathode to form reactive radical anions that subsequently reduce the substrate via electron transfer (ET) to initiate the reaction being investigated. Organo‐mediators typically have a more positive reduction potential, and their role in the whole reaction is similar to that of catalysts. Their addition transforms the ET process from the original heterogeneous process into a homogeneous one. Organo‐mediated electroreduction can effectively avoid the over‐electrolysis of the substrate and the product at the electrode and the intolerance of sensitive substrates or functional groups during electrolysis, thereby preventing the occurrence of side reactions. It can also prevent the excessive consumption of reagents and electrical energy while promoting the reaction to achieve higher or completely different selectivity. Considering the advantages of this type of reaction, this review will provide a detailed description of electroreduction reactions mediated by organic molecules in recent years and elucidate the mechanism of the organo‐mediators in the transformations.