Efficient Strategy Research Articles

Synergistic Passivation Strategies for Enhancing Efficiency and Stability of Perovskite Solar Cells

Perovskite solar cells (PSCs) are celebrated for their potential in clean and renewable energy applications. However, their performance and longevity are often compromised by surface and grain boundary defects. Herein, a posttreatment strategy using 4‐hydroxy‐4′‐biphenylcarboxylic acid ethyl ester (EHBC) is introduced to passivate these defects in perovskite films, thereby enhancing the performance of PSCs. As a Lewis base, the carbonyl group of EHBC interacts with uncoordinated lead ions to passivate lead vacancy defects, while the hydroxyl group forms hydrogen bonds with iodide ions, reducing their migration. Additionally, the hydrophobic biphenyl groups of EHBC enhance the resistance to moisture. The study demonstrates that PSCs treated with EHBC retain 69% of their initial performance after 700 h under 30% relative humidity, achieving a maximum power conversion efficiency (PCE) of 24.48%, a significant improvement over the untreated control PSCs (PCE = 23.04%). This synergistic passivation strategy offers an effective approach for fabricating high‐efficiency and stable PSCs.

Gas-Kinetic Unified Algorithm for Aerodynamics Covering Various Flow Regimes by Computable Modeling of Boltzmann Equation

The gas-kinetic unified algorithm (GKUA), to solve the modeling of the Boltzmann equation, has been developed to study the aerothermodynamics problems with the effects of wall activation energy covering various flow regimes. The unified velocity distribution function equation could be accordingly presented on the basis of the Boltzmann-Shakhov model. To remove the dependence of the distribution function on velocity space, the conservational discrete velocity ordinate method has been developed for hypervelocity flows. The gas-kinetic finite difference scheme is constructed to directly solve the discrete velocity distribution functions by the operator splitting technique. The discrete velocity numerical integration method with the Gauss-type weight function has been developed to evaluate the macroscopic flow variables. Specially, to model the real physical process between gas molecules and the surface, the Maxwell-type gas-surface interaction model has been presented by the MD (molecular dynamic) simulation to obtain the energy adaptability coefficient. The multi-processing domain decomposition strategy and parallel implementation of high parallel efficiency and expansibility designed for the gas-kinetic numerical method is presented with good load balance and data communication efficiency. To validate the accuracy and feasibility of the present algorithm, the supersonic flows past two-dimensional circular cylinder are simulated covering various flow regimes. The results are in good agreement with the related theoretical, DSMC (Direct Simulation Monte Carlo), N-S (Navier-Stokes), and experimental data. The hypersonic reentry flows with the effects of wall activation energy around the Tianzhou-5 cargo spacecraft are simulated by the present GKUA and the massive parallel strategy. It has been confirmed that the present algorithm from the gas-kinetic point of view probably provides a promising approach to resolve the hypersonic aerothermodynamic problems with the complete spectrum of flow regimes during the re-entry and disintegration of the large-scale spacecraft.

Analysis of ventilation and infiltration rates using physics-informed neural networks: Impact of space operation and meteorological factors

This study presents the development and application of a Physics-Informed Neural Network (PINN) model to estimate ventilation and infiltration rates using long-term observation data, addressing the challenge of dynamically varying space operations and meteorological conditions. A central research equestion is: How can we accurately estimate ventilation rates while accounting for these time-varying factors? Traditional tracer gas methods require numerous measurements to accurately characterize air change rates (ACR) under dynamic space operations and varying meteorological conditions. Our PINN model integrates these fluctuating factors, providing a more precise analysis of their transient effects on ACR. We employed Shapley Additive Explanations (SHAP) to interpret the sensitivity and contributions of each influencing factor. Our findings indicate that the state of windows and doors significantly affects spatial operations, while wind speed and direction are the most impactful meteorological factors. The interaction between open windows and doors results in higher ventilation rates compared to their individual effects. Wind-related factors cause ACR variations exceeding 200 %, with the wind direction relative to the office window playing a crucial role. Additionally, external temperature and indoor-outdoor temperature differences show a strong correlation with ACR. However, limitations include the lack of outdoor CO2 measurements and the assumption of uniform indoor CO2 levels, which may affect accuracy. Generalizability is also limited due to the specificity of the space studied. Future work should incorporate outdoor CO2 data and multiple spaces to enhance model applicability. This study contributes to optimizing ventilation strategies for better indoor air quality and energy efficiency.

Factors Affecting Project Owners' Commitment to Implement Green Building Principles in the South Kalimantan Province of Indonesia

The construction of green buildings faces various challenges, including high costs, extended implementation timelines, and numerous requirements that must be satisfied. This study aims to analyze the factors influencing the implementation of green buildings. The research focuses on the PUPR Office in South Kalimantan Province, as well as planning consultants, construction management personnel, and contractors involved in the construction projects of the South Kalimantan Sports Hall and the Sheikh Muhammad Arsyad Al-Banjari Mosque in South Kalimantan Province. Key factors affecting the implementation of green buildings include financial commitment, energy savings, and the utilization of environmentally friendly materials. These factors encompass several variables: additional fund allocation for green buildings, the skills and experience of designers, the integration of natural and artificial lighting, energy-saving planning, the application of prefabrication technology and flatpack design, the use of sustainable materials, the incorporation of local wisdom, and strategies for light efficiency and outsourcing that involve gain sharing. Keywords: Building Construction, Building Energy Performance, Energy, Green Building, Green Construction

Effective Archival of Salesforce Stale Data: A Strategy for System Optimization and Cost Efficiency

This paper explores the importance of archiving stale data in Salesforce and how implementing an ongoing archival process helps maintain accurate, up-to-date information while optimizing system performance and reducing storage costs. As businesses generate vast amounts of data daily, the accumulation of outdated information can slow system operations, increase storage costs, and lead to data inaccuracies. The paper will outline best practices for Salesforce data archival, including soft archival strategies, hard deletion, data backup procedures, and integration precautions. Examples of account data archival, key performance indicators (KPIs), and cost-saving opportunities will be discussed, along with recommended tools and methods for successful data management. Keywords Salesforce, Data Archival, Stale Data, Data Backup, Soft Archival, Data Management, System Optimization, Cost Savings, AWS Backup, OwnBackup, Salesforce Queries

New Strategies for High Efficiency and Precision Bioprinting by DOE Technology and Machine Learning

New Strategies for High Efficiency and Precision Bioprinting by DOE Technology and Machine Learning

Morphophysiological Adaptations of Aquatic Macrophytes in Wetland-Based Sewage Treatment Systems: Strategies for Resilience and Efficiency under Environmental Stress

There is a common misconception that aquatic macrophytes face significant challenges in wetland-based sewage treatment systems. This study aims to correct this perception by focusing on the crucial morphophysiological adaptations of aquatic macrophytes that enable them to thrive in wetland-based sewage treatment systems, particularly under environmental stress. These adaptations are vital for improving the efficiency and resilience of wastewater treatment processes, offering sustainable solutions in the face of variable environmental conditions and complex contaminant mixtures. The review emphasizes the role of macrophytes as natural engineers, capable of enhancing pollutant removal and system stability through their unique structural and functional traits. By understanding these adaptations, the review aims to guide the optimization of wetland design and management, ultimately contributing to more sustainable and effective wastewater treatment practices. The findings underscore the importance of species selection and the integration of nature-based solutions in environmental management, advocating for policies that support the use of macrophytes in modern wastewater management.

Automated Discovery of Efficient Behavior Strategies for Distributed Shape Formation of Swarm Robots by Genetic Programming

Automated Discovery of Efficient Behavior Strategies for Distributed Shape Formation of Swarm Robots by Genetic Programming

Double-Structured Sparsity Guided Flexible Embedding Learning for Unsupervised Feature Selection.

In this article, we propose a novel unsupervised feature selection model combined with clustering, named double-structured sparsity guided flexible embedding learning (DSFEL) for unsupervised feature selection. DSFEL includes a module for learning a block-diagonal structural sparse graph that represents the clustering structure and another module for learning a completely row-sparse projection matrix using the l2,0 -norm constraint to select distinctive features. Compared with the commonly used l2,1 -norm regularization term, the l2,0 -norm constraint can avoid the drawbacks of sparsity limitation and parameter tuning. The optimization of the l2,0 -norm constraint problem, which is a nonconvex and nonsmooth problem, is a formidable challenge, and previous optimization algorithms have only been able to provide approximate solutions. In order to address this issue, this article proposes an efficient optimization strategy that yields a closed-form solution. Eventually, through comprehensive experimentation on nine real-world datasets, it is demonstrated that the proposed method outperforms existing state-of-the-art unsupervised feature selection methods.

Perception of Implementing a Green Building Rating System for Energy Savings in Nigeria’s Construction Projects Industry

A green building rating system is an evaluation tool that assesses a building's environmental performance throughout its life cycle. It includes criteria addressing various aspects of design, construction, and operation. This study reviews existing research on green building rating systems, aiming to establish their applicability for energy saving in Nigeria, identify obstacles to implementation, and determine the necessary factors for successful adoption. The study is analytical, relying on secondary data sources such as published articles, books, and websites. Additionally, the paper highlights the potential benefits for Nigeria in developing its own green building rating system. By doing so, Nigeria can align with global efforts to create sustainable built environments and develop effective strategies for energy efficiency and environmental stewardship. The study recommends awareness programs, educational talks, and government policies to promote the implementation of green building rating systems in Nigeria based on the analysis conducted.

Fundamental Principles Of Health Management: Integrated Strategies For Efficiency, Quality, And Sustainability In Healthcare

This academic essay addresses healthcare management as an essential and dynamic field encompassing administrative and clinical practices to ensure efficiency, quality, and sustainability in healthcare services. Beyond mere administration, healthcare management faces contemporary challenges such as an aging population and increasing chronic diseases, necessitating agile adaptations and technological innovations. Key principles of effective healthcare management include operational efficiency, ensuring optimization of human and financial resources, and quality of care, promoting safe and personalized healthcare delivery. Financial sustainability is crucial for ensuring service continuity, while innovation and technology play pivotal roles in continuous care improvement and response to public health emergencies. Risk management is also discussed as fundamental to safeguarding patient safety and healthcare institution reputation, involving regulatory compliance and cybersecurity measures. In conclusion, the strategic integration of these principles enhances not only institutions' crisis responsiveness but also fosters a patient-centered and sustainable care environment in the long term.

Mechanistic Investigation of Rapid Catalytic Degradation of Acetaminophen Using Electrochemical-Induced CoFe2O4 by Activation of Peroxymonosulfate

Advanced oxidation technology based on PeroxyMonoSulfate (PMS) has become a research hotspot in the field of water treatment. To improve the activation efficiency of PMS, electrochemically assisted spinel type catalyst CoFe2O4 was used to activate PMS and achieve effective degradation of acetaminophen. The influence of single factor on degradation was explored to determine the best degradation process parameters of E/CoFe2O4/PMS system. Results show that under the optimum reaction conditions (DC voltage is 6[Formula: see text]V, the initial mass concentration of acetaminophen is 10[Formula: see text]mg[Formula: see text]L[Formula: see text], the dosage of CoFe2O4 is 0.3[Formula: see text]g[Formula: see text]L[Formula: see text], and the mass concentration of PMS is 1.5[Formula: see text]g[Formula: see text]L[Formula: see text]), the degradation rate of acetaminophen reaches up to 95% within 20[Formula: see text]min. CoFe2O4 catalyst showed a good stability, with only a 12% decrease in acetaminophen degradation after three cycles. Radical quenching tests show that [Formula: see text] and [Formula: see text] played predominant roles in the advanced oxidation process. This work provides a new strategy for more efficiency in PMS activation.

Optimizing Supply Chain Management: Strategies for Enhancing Efficiency and Reducing Costs in Manufacturing Industries

The optimization of supply chain management (SCM) is crucial for enhancing efficiency and reducing costs in manufacturing industries. This study employs a qualitative research approach to explore various strategies for SCM optimization. Data were collected through semi-structured interviews with SCM experts, focus groups with key stakeholders, and an extensive review of secondary sources. The analysis reveals that the integration of information technology (IT), including ERP systems, supply chain management software, cloud computing, and the Internet of Things (IoT), significantly enhances supply chain visibility and coordination, leading to improved decision-making and reduced lead times. Additionally, lean manufacturing and Just-In-Time (JIT) practices are found to be effective in minimizing waste, optimizing inventory levels, and aligning production schedules with market demand, thereby reducing costs and increasing operational efficiency. Strategic supplier partnerships and collaborations play a vital role in achieving synchronization across the supply chain, improving quality, and managing risks. The adoption of sustainability and green supply chain management (GSCM) practices is also highlighted as a key driver for cost reduction and efficiency improvement. These practices not only enhance environmental performance but also drive innovation and provide a competitive advantage. However, the study acknowledges the challenges associated with implementing these strategies, including high initial costs, the need for skilled personnel, and the complexity of managing multiple supplier relationships. Despite these challenges, the findings suggest that a holistic approach to SCM optimization, integrating traditional methods with cutting-edge technologies, can significantly enhance supply chain performance. This research provides valuable insights for both academia and industry practitioners, offering practical guidelines for implementing effective SCM strategies. By adopting these strategies, manufacturers can build resilient and adaptive supply chains capable of meeting the evolving demands of the global market, ensuring sustainable growth and competitiveness.

A state‐of‐the‐art review on geothermal energy exploration in Morocco: Current status and prospects

AbstractIn the last few decades, addressing the global challenge of implementation of strategies for renewable energy and energy efficiency has become crucial. Morocco, since 2009, has made a steadfast commitment to sustainability, with a particular focus on advancing the development of renewable energy resources. A comprehensive strategy has been formulated, centering on utilizing the country's energy potential to drive progress in this vital sector. Morocco is considered a country with abundant thermal water, indicating deep reservoirs with significant hydrothermal potential. Geothermal zones were selected based on the abundance of hot springs where water temperatures were high and geothermal gradients were significant. The abundance and importance of hot springs, combined with recent volcanism and ongoing non‐tectonic activity linked to alpine orogeny, strongly suggest that these regions are promising reservoirs for geothermal energy. This great potential also extends to neighboring countries. In northeast and south Morocco, the temperature of thermal water ranges from 26 to 54°C. This study serves as an inclusive review of the geothermal potentialities in Morocco.

A self-growing “Polysulfide-Phobic” interface constructed by in-situ gelation of organic bentonite interlayer to suppress shuttle effect in lithium-sulfur batteries

The shuttle effect of polysulfides hinders the long-term operation of lithium-sulfur batteries (LSBs). As the secondary current collector, the conductive interlayer can achieve induced fixation of polysulfide within a certain range, but the mechanism of action is limited by bearing saturation of the interlayer on polysulfide. In this work, the limited gelation of organic bentonite (OB) in the electrolyte is utilized to construct an in-situ gel-type physical barrier. During the initial discharge activation stage, the gel layer gradually evolves into a "Polysulfide-Phobic" repulsive layer by trapping free Lithium-polysulfides (LiPSs). Due to the strong repulsion between the "Polysulfide-Phobic" layer and free polysulfide anions, the spatial distribution of LiPSs in the positive electrode region is changed. In addition, the physical barrier effect of the gel interlayer and the chemisorbed action on LiPSs ensure the stability of the "Polysulfide-Phobic" layer during the discharge stage, while the low electronic conductivity avoids the risk of oxidation decomposition of the interface during the charging stage, which is verified by in-situ Raman. The Cells with OB interlayers show excellent cycle stability (515.5 mAh g−1 after 300 cycles) under high loading conditions (5 mg cm−2, E/S ≈ 7.5 μL mg−1). This strategy of sacrificing initial efficiency to build an electrostatic repulsion layer in exchange for long-term stability is profitable, providing a new approach to addressing the shuttle effect.

Simulation of Vacuum Distillation Unit in Oil Refinery: Operational Strategies for Optimal Yield Efficiency

Simulation of Vacuum Distillation Unit in Oil Refinery: Operational Strategies for Optimal Yield Efficiency

Upward migration of the shallow gas enhances the production behavior from the vertical heterogeneous hydrate-bearing marine sediments

Low gas production rates and insufficient gas yield hinder the large-scale production from natural gas hydrates; a joint production of gas hydrate and its underlying shallow gas is expected to address this limitation. This study focuses on the interaction between heterogeneous hydrate reservoirs and the upward migration of the shallow gas. The results indicated a 38.4 % increase in production efficiency with the assistance of the shallow gas. Specially, the melt water generated from extensive hydrate decomposition could potentially induce a lateral migration of the shallow gas at the interfacial zones of the heterogeneous reservoirs. Further investigation revealed that a lower production pressure would help the release of the shallow gas as well as the hydrate decomposition, thereby contributing to a 64.55 % shorter t90. A faster depressurization rate could facilitate the temperature recovery by intensifying the lateral movement of the shallow gas in the junction layer. Consequently, a proper control of the upward channeling of the shallow gas was suggested in the field test for a successive and secure gas production. Our results could be of help in elucidating the interlayer interference mechanisms and the selection of the depressurization strategy for a better recovery efficiency from the multi-gas source reservoirs.

Optimizing Power Consumption in Machining Nickel-Based Superalloys: Strategies for Energy Efficiency

<div>In the face of the world’s population growth and ensuing demands, the industrial sector assumes a crucial role in the management of limited energy supplies. Superalloys based on nickel, which are well-known for their remarkable mechanical qualities and resilience to corrosion, are now essential in vital applications like rocket engines, gas turbines, and aviation. However, these metals’ toughness presents a number of difficulties during machining operations, especially with regard to power consumption. This abstract explores the variables that affect power consumption during the machining of superalloys based on nickel in great detail and suggests ways to improve energy efficiency in this area. The effects of important variables on power consumption are extensively investigated, including cutting speed, feed rate, depth of cut, tool geometry, and cooling/lubrication techniques. A careful balance between these factors is necessary to maximize machining efficiency and reduce power usage. Furthermore, this study reviews the effect of different heat source applications on power consumption and the resultant quality of machined nickel-based superalloys. Additionally, the critical role of cooling and lubrication in mitigating the adverse effects of high temperatures generated during machining is thoroughly examined. Innovative cooling strategies, including cryogenic or high-pressure coolant systems, are explored as potential avenues to enhance heat dissipation and minimize power requirements. In essence, this abstract not only sheds light on the challenges inherent in machining nickel-based superalloys but also offers actionable insights into how energy efficiency can be maximized through strategic parameter optimization and the adoption of innovative cooling techniques. By addressing these aspects, manufacturers can effectively navigate the complexities of machining superalloys while minimizing their environmental footprint and operational costs.</div>

Dynamics of odor-source localization: Insights from real-time odor plume recordings and head-motion tracking in freely moving mice.

Animals navigating turbulent odor plumes exhibit a rich variety of behaviors, and employ efficient strategies to locate odor sources. A growing body of literature has started to probe this complex task of localizing airborne odor sources in walking mammals to further our understanding of neural encoding and decoding of naturalistic sensory stimuli. However, correlating the intermittent olfactory information with behavior has remained a long-standing challenge due to the stochastic nature of the odor stimulus. We recently reported a method to record real-time olfactory information available to freely moving mice during odor-guided navigation, hence overcoming that challenge. Here we combine our odor-recording method with head-motion tracking to establish correlations between plume encounters and head movements. We show that mice exhibit robust head-pitch motions in the 5-14Hz range during an odor-guided navigation task, and that these head motions are modulated by plume encounters. Furthermore, mice reduce their angles with respect to the source upon plume contact. Head motions may thus be an important part of the sensorimotor behavioral repertoire during naturalistic odor-source localization.

Forecasting fluid-injection induced seismicity to choose the best injection strategy for safety and efficiency.

Induced seismicity poses a challenge to the development of Enhanced Geothermal Systems (EGS). Improving monitoring and forecasting techniques is essential to mitigate induced seismicity and thereby fostering a positive perception of EGS projects among local authorities and population. Induced seismicity is the result of complex and coupled thermo-hydro-mechanical-chemical mechanisms. Injection flux and pressure are crucial controlling parameters for both hydraulic stimulation and circulation protocols. We develop a methodology combining a hydro-mechanical model with a seismicity rate model to estimate the magnitude and frequency of mainshocks and aftershocks induced by fluid injection. We apply the methodology to the case of the Basel EGS (2006, Switzerland) to compare the effects of progressive, cyclic and constant injections on the mechanical response of discrete faults. Results from the coupled hydro-mechanical models show that the pore pressure diffusion and consequent enhancement of fault permeability are limited to the vicinity of the injection well during cyclic injection. Additionally, constant injection induces seismicity from the start of the injection but enhances the permeability of most of the faults within a shorter duration, inducing less post-injection seismicity. The methodology can be adapted to any numerical model and allows new projects to be developed by anticipating the safest injection protocol.This article is part of the theme issue 'Induced seismicity in coupled subsurface systems'.