Minimum Energy Requirements Research Articles

A new optimization framework for piezoelectric actuators location identification

The study addresses piezoelectric actuator placement for active vibration control using an open-access framework that couples ANSYS and Python. It outlines a three-stage procedure: creating a finite element model in ANSYS APDL, using Python to determine the objective function, and applying a genetic algorithm optimization to find optimal actuator locations. Numerical simulations on plates and thin-walled conical structures demonstrate the effectiveness of the approach, showing it efficiently finds optimal placements with minimal search time and energy requirements. The study provides open-access codes for the framework, enhancing its accessibility and reproducibility.

Interfacial stability and electronic properties of YBCO/ABO3 heterostructures: A comparative DFT study

In this study, we utilized density functional theory (DFT) to analyze the interfacial properties of YBa2Cu3O7 (YBCO) with perovskite metal oxides LaAlO3 (LAO), KTaO3 (KTO), and SrTiO3 (STO). We focused on surface energies, lattice mismatches, strain energies, and adhesion energies to gauge the stability and compatibility of these interfaces. Our findings indicate that KTO exhibits the highest surface preference due to its lowest surface energy (0.054 eV/Å 2), suggesting superior surface stability. Moreover, LAO and STO show minor lattice mismatches with YBCO, implying effective interface integration, while YBCO/KTO interfaces experience significant strain due to extensive lattice mismatches. STO is distinguished by the lowest strain energy (0.07 eV), indicating minimal energy requirement for lattice mismatch accommodation, unlike KTO, which demonstrates high strain energy (0.42 eV) and potential structural distortions. The strongest interfacial bond, as indicated by an adhesion energy of −2.16 eV, was observed at YBCO/LAO, while the weakest was found at the YBCO/KTO interface, with an adhesion energy of −0.56 eV. Additionally, charge density difference (CDD) analysis highlighted electron density redistribution at the interfaces, predominantly around interfacial oxygen atoms, indicating a mix of ionic and covalent bonding. This study provides comparative insights into the interfacial characteristics of YBCO/ABO3 heterostructures, suggesting pathways for optimizing their design and performance.

Fe‐Based Materials for Electrocatalytic Water Splitting: A Mini Review

AbstractIn the last few years, the development of effective electrocatalysts hold fascinating importance towards scalable green hydrogen (H2) and oxygen (O2) production has become an appealing area of research. A good number of iron‐based catalysts have been designed and synthesized which can mediate water splitting under mild conditions with minimum energy requirements. In this review, recent progress on iron‐based electrocatalysts focusing on Oxygen Evolution Reaction (OER), Hydrogen Evolution Reaction (HER), and Overall Water Splitting (OWS) are summarized. Tactical designing, targeted synthesis with electronic tuning, efficiency as well as durability are discussed here. The review is comprehensive and our target is to promote the development of highly efficient economical catalysts, to make their way from the laboratory to market by replacing noble metal‐based electrocatalysts.

Exploring Bacillus species xylanases for industrial applications: screening via thermostability and reaction modelling.

Xylanases derived from Bacillus species hold significant importance in various large-scale production sectors, with increasing demand driven by biofuel production. However, despite their potential, the extreme environmental conditions often encountered in production settings have led to their underutilisation. To address this issue and enhance their efficacy under adverse conditions, we conducted a theoretical investigation on a group of five Bacillus species xylanases belonging to the glycoside hydrolase GH11 family. Bacillus sp. NCL 87-6-10 (sp_NCL 87-6-10) emerged as a potent candidate among the selected biocatalysts; this Bacillus strain exhibited high thermal stability and achieved a transition state with minimal energy requirements, thereby accelerating the biocatalytic reaction process. Our approach aims to provide support for experimentalists in the industrial sector, encouraging them to employ structural-based reaction modelling scrutinisation to predict the ability of targeted xylanases. Utilising crystal structure data available in the Carbohydrate-Active enzymes database, we aimed to analyse their structural capabilities in terms of thermal-stability and activity. Our investigation into identifying the most prominent Bacillus species xylanases unfolds with the help of the semi-empirical quantum mechanics MOPAC method integrated with the DRIVER program is used in calculations of reaction pathways to understand the activation energy. Additionally, we scrutinised the selected xylanases using various analyses, including constrained network analyses, intermolecular interactions of the enzyme-substrate complex and molecular orbital assessments calculated using the AM1 method with the MO-G model (MO-G AM1) to validate their reactivity.

Reactor and Plant Designs for the Solar Photosynthesis of Fuels

Solar-boosted photo-technology stands out as a powerful strategy for photosynthesis and photocatalytic processes due to its minimal energy requirements, cost-effectiveness and operation under milder, environmentally friendly conditions compared to conventional thermocatalytic options. The design and development of photocatalysts have received a great deal of attention, whereas photoreactor development must be studied deeper to enable the design of efficient devices for practical exploitation. Furthermore, scale-up issues are important for this application, since light distribution through the photoreactor is a concurrent factor. This review represents a comprehensive study on the development of photoreactors to be used mainly for the photoreduction of CO2 to fuels, but with concepts easily transferable to other photosynthetic applications such as ammonia synthesis and water splitting, or wastewater treatment, photovoltaics combined to photoreactors, etc. The primary categories of photoreactors are thoroughly examined. It is also explained which parameters influence the design of a photoreactor and next-generation high-pressure photoreactors are also discussed. Last but not least, current technologies for solar concentrators are recalled, considering their possible integration within the photoreactor. While many reviews deal with photocatalytic materials, in the authors’ view, photoreactors with significant scale and their merged devices with solar concentrators are still unexploited solutions. These are the key to boost the efficiency of these processes towards commercial viability; thus, the aim of this review is to summarise the main findings on solar photoreactors for the photoreduction of CO2 and for related applications.

ROSMOSE: A web-based decision support tool for the design and optimization of industrial and urban energy systems

Energy efficiency is crucial for the sustainable operation of industrial and urban sectors. However, practicing engineers seldom have access to open-source tools that can readily evaluate and compare scenarios. In this work, a novel web-based tool called ROSMOSE is developed and proposed for analyzing the energy efficiency of industrial and urban systems and comparing potential process integration options. This optimization framework computes and graphically represents the minimum energy requirements, the pinch temperatures, and the Grand and integrated Carnot composite curves of process systems. Results are used to design utility systems that meet energy demands, while minimizing a specified objective function, such as total cost or environmental impacts. The Quarto environment, in which ROSMOSE is built upon, allows the integration of various open-source software and tools, such as database handling software, process modeling suites, and optimization solvers, along with interactive data visualization and reporting tools. This paper discusses the application of ROSMOSE for the energy integration and total site optimization of a dairy process consisting of milk treatment, and cream and cheese production to demonstrate the tool features. Other integration options, such as the use of heat pumps or solar panels, and the production of soft drinks or biogas as value-added byproducts, are also proposed and evaluated. As a result, from 75 % to 90 % in fuel savings and up to 80 % CO2 emissions reduction in the dairy plant are identified by optimizing the utility systems integration. Moreover, complete electrification via heat pumps eliminates any fossil fuel needs and it results in 85 % energy savings and up to 96 % CO2 emissions reduction. The activation of renewable electricity sources, such as solar power, made plausible this fully electrified scenario. Finally, optimized waste management strategies led to in-house fuel production and net export of biogas to the grid, but they also reduce cheese yield by prioritizing the biogas production from whey upgrading process. In this way, decision-makers have access to a clear performance comparison for a list of system configurations to draw informed trade-offs. A similar approach could be adopted to aid decision-making for the design and operation of other industrial and urban energy systems using ROSMOSE.

Recent advances in engineering fast-growing cyanobacterial species for enhanced CO2 fixation

Atmospheric CO2 removal (CDR) is a fundamentally endergonic process. Performing CDR or Bioenergy with Carbon Capture and Storage (BECCS) at the gigatonne scale will produce a significant additional burden on the planet’s limited renewable energy resources irrespective of the technology employed. Harnessing photosynthesis to drive industrial-scale CO2 fixation has been of significant interest because of its minimal energy requirements and potential low costs. In this review, we evaluated the thermodynamic considerations of performing atmospheric carbon removal using microalgae and cyanobacteria versus physicochemical processes and explore the implications of these energetic costs on the scalability of each respective solution. We review the biomass productivities of recently discovered fast-growing cyanobacterial strains and discuss the prospects of genetically engineering certain metabolic pathways for channeling the fixed carbon into metabolic ‘carbon sinks’ to further enhance their CO2 capture while concurrently extracting value. We share our perspectives on how new highly productive chassis strains combined with advanced flux balance models, essentially coupling synthetic biology with industrial biotechnology, may unlock more favorable methods for CDR, both from an economic and thermodynamic perspective.

ILP-based resource optimization realized by quantum annealing for optical wide-area communication networks—A framework for solving combinatorial problems of a real-world application by quantum annealing

Resource allocation of wide-area internet networks is inherently a combinatorial optimization problem that if solved quickly, could provide near real-time adaptive control of internet-protocol traffic ensuring increased network efficacy and robustness, while minimizing energy requirements coming from power-hungry transceivers. In recent works we demonstrated how such a problem could be cast as a quadratic unconstrained binary optimization (QUBO) problem that can be embedded onto the D-Wave Advantage™ quantum annealer system, demonstrating proof of principle. Our initial studies left open the possibility for improvement of D-Wave solutions via judicious choices of system run parameters. Here we report on our investigations for optimizing these system parameters, and how we incorporate machine learning (ML) techniques to further improve on the quality of solutions. In particular, we use the Hamming distance to investigate correlations between various system-run parameters and solution vectors. We then apply a decision tree neural network (NN) to learn these correlations, with the goal of using the neural network to provide further guesses to solution vectors. We successfully implement this NN in a simple integer linear programming (ILP) example, demonstrating how the NN can fully map out the solution space that was not captured by D-Wave. We find, however, for the 3-node network problem the NN is not able to enhance the quality of space of solutions.

Amino-modified upcycled biochar achieves selective chromium removal in complex aqueous matrices

Chromium pollution of groundwater sources is a growing global issue, which correlates with various anthropogenic activities. Remediation of both the Cr(VI) and Cr(III), via adsorption technologies, has been championed in recent years due to ease of use, minimal energy requirements, and the potential to serve as a highly sustainable remediation technology. In the present study, a biochar sorbent sourced from pineapple skins, allowed for the upcycling of agricultural waste into water purification technology. The biochar material was chemically modified, through a green amination method, to produce an efficient and selective adsorbent for the removal of both Cr(VI) and Cr(III) from complex aqueous matrices. From FTIR analysis it was evident that the chemical modification introduced new C–N and N–H bonds observed in the modified biochar along with a depletion of N–O and C–H bonds found in the pristine biochar. The amino modified biochar was found to spontaneously adsorb both forms of chromium at room temperature, with binding capacities of 46.5 mg/g of Cr(VI) and 27.1 mg/g of Cr(III). Interference studies, conducted in complex matrices, showed no change in adsorption capacity for Cr(VI) in matrices containing up to 3,000× the concentration of interfering ions. Finally, Cr(III) removal was synergized to 100% adsorption at interfering ions concentrations up to 330× of the analyte, which were suppressed at higher interference concentrations. Considering such performance, the amino modified biochar achieved selective removal for both forms of chromium, showing great potential for utilization in complex chromium pollution sources.

Modeling and optimization of an integrated membrane – P/VSA separation process for CO2 removal from coal plant flue gas

This work presents a mathematical framework for the simulation and optimization of an integrated membrane – Pressure/Vacuum Swing Adsorption (P/VSA) process for CO2 removal from coal plant flue gas. The integrated process includes a membrane module in the first stage and a P/VSA unit in the second stage and it is optimized to minimize energy requirement for 95% and 90% total CO2 purity and recovery, respectively. Three membrane specifications, with CO2/N2 selectivity of 75, 50 and 25, and two adsorbents, zeolite 13X and MOF UTSA-16, are examined. The configuration which includes a membrane module with a CO2/N2 selectivity of 75 followed by a P/VSA unit with a UTSA-16 adsorbent leads to a minimum energy demand of 163 kWh/tn CO2, which is lower than the energy requirements of competitive CO2 separation processes, such as a two-stage P/VSA and multi-stage membrane processes. In addition, lowering the CO2/N2 selectivity from 75 to 50, leads to a minimum energy requirement of 177 kWh/tn CO2, which is still competitive to the other CO2 capture technologies. Furthermore, a comparison between different operating temperatures demonstrates that although a higher temperature increases the total energy demand, it has no impact on the optimal operating conditions and separation efficiency.

A Formulated Method for Streams Splitting in Heat Exchanger Network Design Using Pinch Analysis

Abstract Thermal processes constitute a significant portion of energy consumption in the industrial sector. In this context, pinch analysis has emerged as a powerful method for achieving substantial energy savings. By systematically analyzing process streams and their heat transfer characteristics, pinch analysis enables the identification of heat recovery opportunities, leading to the design of an optimized heat exchanger network that minimizes energy requirements. In this study, a formulated stream splitting method is proposed to design a feasible minimum energy requirement heat exchanger network. This method aims to achieve two main goals. First, it gives a practical formulated method to help the designer when splitting streams and focuses on splitting the streams in such a way that creates sub-streams with the exact enthalpy required to satisfy heat exchanges with a specific number of streams, in order to minimize the need for process-utility heat exchangers whenever possible. Subsequently, the method aims to eliminate exergy destruction caused by temperature differences in the mixer used to recombine the split streams, by ensuring an isothermal mixture of streams, preventing unnecessary energy losses. The design of the heat exchanger network is conducted using the hint software, allowing for a comprehensive and detailed analysis of each step. The results obtained show that the heat exchanger network attained not only achieves the minimum energy consumption but also mitigates exergy destruction and avoids unnecessary process-utility heat exchangers, resulting in enhanced overall system performance.

Optimizing photosynthetic photon flux density and light quality for maximizing space use efficacy in edamame at the vegetative growth stage

Compared with conventional crop cultivation in greenhouses or fields, plant factories with artificial light (PFAL) have advantages in the highly efficient use of space, energy, and resources available for cultivation. However, few studies on environmental controls for improving the space use efficacy (SUE) of PFAL in the production of edamame, a vegetable soybean, have been reported. Therefore, developing an environmental control method for high productivity with minimal space and energy requirements is of high priority. The aims of this study were to (1) identify the optimal photosynthetic photon flux density (PPFD) and light quality to enhance the SUE of edamame at the vegetative growth stage, and (2) examine the effects of PPFD, light quality, and their interaction on edamame plant growth at the vegetative stage. SUE is defined as the crop biomass produced per unit cubic volume of cultivation during the growth period. We examined three PPFD treatments (300, 500, and 700 μmol m−2 s−1) with three color temperature LED lamps (3,000, 5,000, and 6,500 K), for a total of nine treatments. The results demonstrated that, under the same light quality treatment, higher PPFDs resulted in larger fresh and dry weights of all organs, higher stem length, and lower specific leaf area. Under the same PPFD treatment, a high ratio of blue (400–499 nm) to red (600–699 nm) photon flux density increased the plant height but decreased the projected leaf area. The values of SUE at 700 μmol m−2 s−1 increased by 213, 163, and 92% with 3,000, 5,000, and 6,500 K, respectively compared with those at 300 μmol m−2 s−1. The values of SUE at 700 μmol m−2 s−1 increased by 34 and 23% in 5,000 and 6,500 K treatments, respectively compared with that in the 3,000 K treatment. In conclusion, a combination of 700 μmol m−2 s−1 PPFD and 5,000 K color temperature is the suitable condition to increase the SUE of edamame at the vegetative growth stage in a PFAL.

Optimizing the Building Refurbishment Process Using Improved Evolutionary Algorithms

An optimization model that may be applied to analyze building retrofit strategies is presented in this research. The aim of this research paper is to identify the optimal thermal envelope configuration that will assure the minimum energy requirement for heating in the case of a residential building, while also considering price restrictions obtained through a specific market survey. To achieve this, several values for the following parameters are considered: thermal insulation materials’ conductivities and thicknesses, windows’ overall heat transfer coefficients and total solar energy transmittance and doors’ thermal proprieties. Additionally, this paper presents a method used to find the best option from among the available heat pumps that could cover most of the energy requirements for heating and domestic hot water systems, also considering the products’ prices. The proposed method is based on a Non-dominated Sorting Genetic Algorithm II (NSGA-II) model developed in the Pymoo (Multi-Objective Optimization in Python) library. The result shows that the energy requirement for heating can be reduced by up to approximately 75% compared to that obtained in the case of a non-insulated building by using suitable insulation materials and doors and windows with superior thermal proprieties chosen by the NSGA-II.

Geopolymeric Composites Containing Industrial Waste Reinforced with Arundo donax Fibers

Traditional Portland cement-based composites have a great environmental impact. Alkali-activated binders can offer an alternative, particularly if they can be obtained even partially from waste. Two residuals derived from the finishing steps of the traditional ceramic industry have been used as possible polymerizable sources mixed with metakaolin. Moreover, to contrast the low dimensional stability of alkali-activated materials and their mechanical brittleness, natural fibers derived from the Arundo donax plant have been added to the mortars. The use of renewable natural fibers instead of synthetic ones can contribute a further environmental advantage. The fresh (consistency) and cured (mechanical) properties of composite materials prepared with residuals and metakaolin were analyzed here. For comparison’s sake, a reference set of composite materials not loaded with fibers but with an identical binder/sand and liquid/binder ratio was cast. A room-temperature curing condition was selected that, although inadequate to promote the short-time reactivity of the wastes, has a minimal energy requirement and allows on-site applications. A small-scale decrease in the properties in the compression mode tests was observed in the waste-modified mortars, while the Arundo addition improved their flexural strength and dimensional stability.

Food security and the value of game animals—a study of Sweden

The food security value of wild meat is calculated by combining proxy methods for quantifying game animal abundance with shadow pricing techniques for assessing the unit values of food security. This study calculated the food security values of moose, roe deer, wild boar, and fallow deer for Sweden overall and for individual counties. The results showed that meat from these animal populations accounts for approximately 9% of meat consumption in Sweden and for 1.2% of the minimum energy food consumption during periods of crisis for the whole of Sweden, while in some counties it can be as much as 8%. The calculated unit value, or shadow price, of the minimum energy requirement ranged between € 0.1 and € 4.2/mcal, depending on the magnitude of the crisis scenario. At most, the total food security value of actual animal population sizes amounted to 0.50 billion euros, but this was unevenly distributed, with high values in counties that have an abundance of moose and wild boar.

Bone Marrow Adipose Tissue Is Not Required for Reconstitution of the Immune System Following Irradiation in Male Mice.

Bone marrow adipose tissue (BMAT) is hypothesized to serve as an expandable/contractible fat depot which functions, in part, to minimize energy requirements for sustaining optimal hematopoiesis. We investigated whether BMAT is required for immune reconstitution following injury. Male wild type (WBB6F1, WT) and BMAT-deficient WBB6F1/J-KitW/KitW-v/J (KitW/W-v) mice were lethally irradiated. Irradiation was followed by adoptive transfer of 1000 purified WT hematopoietic stem cells (HSCs). The extent of immune reconstitution in blood, bone marrow, and lymph nodes in the irradiated mice was determined using HSCs from green fluorescent protein (GFP)-expressing mice. We also evaluated skeletal response to treatment. Detection of GFP-positive B and T cells in peripheral blood at 4 and 9 weeks following adoptive transfer and in bone marrow and lymph nodes following necropsy revealed excellent immune reconstitution in both WT and BMAT-deficient mice. Adipocytes were numerous in the distal femur of WT mice but absent or rare in KitW/W-v mice. Bone parameters, including length, mass, density, bone volume, microarchitecture, and turnover balance, exhibited few differences between WT and BMAT-deficient mice. The minimal differences suggest that BMAT is not required for reconstitution of the immune system following lethal radiation and is not a major contributor to the skeletal phenotypes of kit signaling-deficient mice.

PUFchain 3.0: Hardware-Assisted Distributed Ledger for Robust Authentication in Healthcare Cyber-Physical Systems.

This article presents a novel hardware-assisted distributed ledger-based solution for simultaneous device and data security in smart healthcare. This article presents a novel architecture that integrates PUF, blockchain, and Tangle for Security-by-Design (SbD) of healthcare cyber-physical systems (H-CPSs). Healthcare systems around the world have undergone massive technological transformation and have seen growing adoption with the advancement of Internet-of-Medical Things (IoMT). The technological transformation of healthcare systems to telemedicine, e-health, connected health, and remote health is being made possible with the sophisticated integration of IoMT with machine learning, big data, artificial intelligence (AI), and other technologies. As healthcare systems are becoming more accessible and advanced, security and privacy have become pivotal for the smooth integration and functioning of various systems in H-CPSs. In this work, we present a novel approach that integrates PUF with IOTA Tangle and blockchain and works by storing the PUF keys of a patient's Body Area Network (BAN) inside blockchain to access, store, and share globally. Each patient has a network of smart wearables and a gateway to obtain the physiological sensor data securely. To facilitate communication among various stakeholders in healthcare systems, IOTA Tangle's Masked Authentication Messaging (MAM) communication protocol has been used, which securely enables patients to communicate, share, and store data on Tangle. The MAM channel works in the restricted mode in the proposed architecture, which can be accessed using the patient's gateway PUF key. Furthermore, the successful verification of PUF enables patients to securely send and share physiological sensor data from various wearable and implantable medical devices embedded with PUF. Finally, healthcare system entities like physicians, hospital admin networks, and remote monitoring systems can securely establish communication with patients using MAM and retrieve the patient's BAN PUF keys from the blockchain securely. Our experimental analysis shows that the proposed approach successfully integrates three security primitives, PUF, blockchain, and Tangle, providing decentralized access control and security in H-CPS with minimal energy requirements, data storage, and response time.

Accounting for the evolution of sedentarism on minimum dietary energy requirements

Estimates of food-insecure populations are biased upwards, lacking adjustment for global increases in sedentary behavior in recent decades. We construct a household model to account for sedentary choices during leisure and work time decisions. The model rationalizes increasing sedentary behavior from the household by accounting for increasing returns to cognitive human capital vs physical capital, alongside increased productivity of more sedentary activities both at work and at home. The household model informs an empirical model applied to our unique international pseudo-panel data on sitting time, proxy-ing for sedentarism. We econometrically estimate a transfer function linking sedentarism to widely available covariates and make out-of-sample predictions. It is applicable to most countries. The estimated sedentary time can be used to adjust the physical activity level reflected in the minimum dietary energy requirement used to determine a cutoff for food insecurity.

A novel semi-active control of an integrated chassis and seat quasi-zero stiffness suspension system for off-road vehicles

This article introduces an innovative semi-active suspension system for off-road vehicles, incorporating a quasi-zero stiffness suspension to enhance driver comfort. The system includes a central pneumatic spring, double-acting pneumatic linear actuators for adjustable stiffness, and magnetorheological dampers for controlled damping. Using Lyapunov stability theory, a static output feedback control law is designed to address uncertainties in road profiles, driver body parameters, and actuator saturation, relying on measured variables as feedback. Performance constraints focus on driver head acceleration, suspension displacement, and dynamic tire load. The control law problem is converted into a convex optimization problem with linear matrix inequalities. The new semi-active QZSS system is theoretically tested via Matlab simulations and validated through hardware-in-the-loop testing. Comparative analysis between passive QZSS and the new semi-active QZSS on different roads, and vehicle speeds closely aligns with simulation results, with minor disparities attributable to network discrepancies and signal interruptions. Impressively, the semi-active QZSS system reduces driver head vertical acceleration between 26.53 and 35.0% compared to passive air QZSS, showing potential for significantly improving ride comfort, reducing vibration transfer, and enhancing driver wellbeing with minimal energy requirement.

Investigation of the Performance of Zero Energy Homes in Hot Climates

Globally, the rate at which buildings use resources and energy has been rising. Due to population growth, rise in living standard, and global warming, strategies for energy conservation have been adopted lately in zero energy buildings. Over the past decade, the energy consumption in constructions has increased at an unprecedented rate. Therefore, it is of great importance to mandate energy rationalization in building construction. This research investigates the impact of applying zero energy concept in homes in Egypt. The study begins by analysing the current situation of the energy sector and existing buildings in Egypt, the NZEB concept is defined and its different aspects are highlighted. Energy simulation by DesignBuilder simulation software is used to evaluate energy performance for a residential single family house model after applying Passive and Active design strategies. A number of energy saving strategies have been examined to optimize the building envelope with minimum energy requirements. The building energy consumption was reduced when various energy efficient strategies were combined. Besides utilizing energy efficient HVAC systems. a solar PV system is installed to meet the reduced energy. The case study was transformed into a zero-energy house. Results show that passive and active techniques can be dependable for steady energy production in buildings in hot dry regions.