Transfer Capability Research Articles

Potent Covalent Organic Framework Nanophotosensitizers with Staggered Type I/II Motifs for Photodynamic Immunotherapy of Hypoxic Tumors.

Photodynamic therapy (PDT) using oxygen-dependent type II photosensitizers is frequently limited by the hypoxic microenvironment of solid tumors. Type I photosensitizers show oxygen-independent reactive oxygen species (ROS) generation upon light irradiation but still face the challenges of aggregation-caused quenching (ACQ) and low efficiency to produce ROS. Herein, we first prepare an efficient type I photosensitizer from a perylene derivative via intramolecular donor-acceptor binding and sulfur substitution, which significantly enhance intersystem crossing between singlet and triplet states and electron transfer capability. After reaction with a type II photosensitizer, the covalent organic framework (COF) nanophotosensitizer is formed with alternated type I and II photosensitizer motifs in the same layer and staggered AB stacking between layers to avoid ACQ. The nanophotosensitizer exhibits high-efficiency generation of singlet oxygen (1O2) and superoxide anion radicals (O2•-) via type I and II mechanism under normoxia upon exposure to light irradiation. Under hypoxia, massive O2•- can be produced continuously. The potent ROS generation capability results in efficient cellular apoptosis and immunogenic cell death (ICD) efficiently. After combination with immune checkpoint inhibitors, tumor immunosuppressive microenvironment is reversed, which effectively ablates bulky hypoxic primary tumors and suppresses metastases via photodynamic immunotherapy. The COF nanophotosensitizers with staggered type I and II photosensitizer motifs represent a promising strategy to boost photodynamic immunotherapy of hypoxic tumors.

Thermal-Fluid study of curved tubes in cross-flow

Three-dimensional simulations have been performed to investigate thermal performance by the external surface of curved circular tubes provided with concave and convex curvatures. The simulations were performed in Ansys-fluent software and results has been validated against the available results. The tubes were placed in a uni-directional free stream of air at a Reynolds number of 35000 which is within subcritical range for circular tube. The heat transfer capabilities of curved tubes have been compared with that of a straight tube of same diameter and height. A constant-heat-flux condition over the external surface has been used. The curved tubes have been designed such that it has vertical extensions at the end and curvatures at the middle section with curvature ratios of 0.075, 0.15, 0.225 and 0.3. Plots of coefficients of pressure, drag and lift, Nusselt number, heat transfer ratio and contours of pathlines were utilized to investigate the thermal behaviour around the tube surface. Results show the highest augmenting thermal performance exhibited by convex curved tube with curvature ratio 0.15 followed by curvature ratio of 0.225. Other reasonably better augmented heat transfer exhibited by concave curved tube with curvature ratio of 0.3. The present study also identifies augmenting, mitigating and insignificant zones around the tubes based on heat transfer rates. The results show an improvement in heat transfer when curved tube is used instead of straight tube which can be utilised in waste heat recovery recuperators.

Assessment of Photovoltaic Thermal Efficiency using Phase Change Material and Water-Channel Collector with T-Fin Design

Photovoltaic thermal systems, also known as hybrid solar panels, combine photovoltaic and solar thermal components to generate both electrical and heat energy from the sun. Despite solar energy has significant potential, conventional photovoltaic systems suffer from low efficiencies due to the wasted heat energy and high working temperature. This research aims to develop and examine the efficiency of a photovoltaic thermal system integrated with commercial phase change material (PCM) using copper T-fin absorber to increase solar energy conversion efficiency. The research involved fabricating aluminium packets for commercial PCM, filling fabricated packets into a developed photovoltaic thermal system with T-fin absorber, and conducting final experiments under three different water flow rates for each of three different irradiance levels under solar simulator with 30 minutes run for each test. The final experiment assessed temperature difference, electrical efficiency, thermal efficiency, and overall efficiency. At 800 W/m² and 90 l/h, the highest temperature drop was 11.20°C. The highest electrical efficiency of 8.0% was achieved at 800 W/m2 and 90 l/h. The highest thermal efficiency was 72.5% at 400 W/m² and 90 l/h. The highest overall efficiency of 79.8% at 400 W/m² and 90 l/h for the T-fin absorber. These results concluded the enhanced heat transfer capability and contribution to higher overall system efficiency after integrated commercial PCM and T-fin absorber.

Rectifiable Conductive Thermal Diodes Enabling Thermal Circuits with Selectable Operations for Thermal Logic Applications

AbstractThermal logic paves the way to replace electric logic in scenarios where electronic signals are susceptible to interference or traditional electronics cannot be used, however, is still considered a theoretical and numerical stage. Emerging thermal metalmaterials (TMMs) have the potential to enhance thermal information processes. Compared to TMMs with single‐and‐fixed heat transfer capabilities, rectifiable‐TMMs enable thermal circuits to perform selectable operations, but they are also limited by low operating temperatures and narrow temperature biases. Here, macro‐ and experimental thermal diodes with tree‐like eutectic gallium‐indium/printed polylactic‐acid (EGaIn/PPLA) interface, are demonstrated to be capable of extending asymmetric heat transfer difference to 5.81 times in ambient operation, compared with basic EGaIn/PPLA interface with an input temperature bias of 63.7 °C. Given this, basic thermal gates can be constructed through the incorporation of resistors and a pair of diodes working in the same or opposite directions, with the propagation delay time td within 18 min. Compound logic gates can be cascaded by basic gates in the same way as composed Boolean functions, with td within 4 min. Such thermal circuits prove to perform reliably under dynamic ambient conditions, advancing the engineering of devices designed to manipulate thermal energy and process abundant thermal information.

Graphene nanoplatelets inclusion effects on mechanical properties of the hybrid kevlar/basalt fiber reinforced epoxy composites

Abstract This study experimentally examined the effects of hybridizing Basalt and Kevlar fibers on the tensile, and flexural performance of composite materials with the inclusion of Graphene nanoplatelets (GnPs). Various hybrid composites were fabricated, incorporating Basalt and Kevlar fiber composites with 1, 3, and 5 wt% of GnPs as well as without GnPs, as well as hybrid composites featuring different weight content of GnPs reinforcing with with Basalt and Kevlar fibers. The findings of this study indicated that the mechanical properties of epoxy resin were significantly enhanced through the synergistic effects of hybridization with basalt and Kevlar fibers, as well as the incorporation of graphene nanoplatelets (GnPs). The significant increasing in mechanical properties was attributed to the strong interfacial interactions between the epoxy matrix and GnPs nanoparticles, which facilitate improved stress transfer from the fibers and nanoparticles to the matrix. This enhanced stress transfer capability accounts for the superior resistance to fiber pullout observed in composites reinforced with GnPs compared to those without nanoparticles.

A proposed methodology for mollification of subsynchronous oscillation in DFIG-based wind farm

High levels of series compensation in transmission lines, particularly those integrated with wind farms, exacerbate the risk of sub-synchronous oscillation (SSO), a phenomenon detrimental to system stability. Gate-controlled series capacitor (GCSC) is one of the used means to mitigate the SSO and enhance power transfer capability. In the previous studies, the combined proportional-integral controller with supplementary damping controller was an effective approach for controlling the GCSC and mitigating the SSO. In this paper, the ability to cascade a proportional-resonant controller with a PI controller for damping the SSO is investigated. The proposed method’s performance is evaluated through extensive time-domain simulations using the modified IEEE First benchmark model. The simulations incorporate a diverse range of wind speeds, compensation levels, as well as sub-synchronous control interactions. Furthermore, a comparative analysis with recent SSO damping techniques is conducted to assess the strategy’s performance under varying operating conditions. The comparative results overwhelmingly demonstrate the superiority and effectiveness of the proposed strategy in alleviating SSO, especially at low wind speeds and high compensation levels.

Analysis of Hydrothermal Flow and Performance of Heat Transfer in 3D Pipes Based on Varying Dimple Structure Configurations

ABSTRACTIn the current work, the study examines the flow patterns and heat transfer capabilities of tubes with various spherical dimple configurations. A numerical analysis, supported by experimental validation on a reference model, was conducted on a circular tube with an alternating flow path. The primary goal was to enhance the thermal performance of circular tubes by inducing mixing and vortex flows. The impact of three design factors on thermal–hydraulic performance was investigated, dimple pipe diameter (DPD), dimple group number (DGN), and number of dimples (NODs). Dimpled tubes consistently outperformed smooth tubes in heat transfer due to increased flow mixing and separation. Both increasing the Reynolds number and decreasing the design factors led to the formation of mixing and vortex patterns. The performance evaluation factor (PEF) varied across different dimple configurations. For DPD, PEF ranged from 1.14 to 1.33; for DGN, it ranged from 1.15 to 1.28; for NOD, it ranged from 0.95 to 1.21, all within a Reynolds number range of 4000–15,000. At a Reynolds number of 6000, all three configurations of DPD, DGN, and NOD outperformed the smooth pipe in terms of the Nusselt number. For DPD, Nusselt number improvements ranged from 25.7% to 30.8%, and friction factors increased by 21% to 67%. DGN configurations exhibited a wider range of Nusselt number enhancement from 25% to 49.6%, and friction factor increase from 37% to 72%. NOD configurations also demonstrated consistent improvements, with Nusselt number increases ranging from 27.35% to 31% and friction factor increases from 42% to 74%. Spherical dimples can significantly enhance the thermal–hydraulic performance of tubes, so the best configuration depends on the specific application, and the highest performance, with a 1.33 increase in PEF, was achieved with a dimple diameter of 2 mm (DPD = 2 mm) and a dimple density of four dimples per unit area (NOD = 4).

Extracting coarse-grained classifiers from large Convolutional Neural Networks

Coarse-grained classification and classification at different hierarchy levels are important in many engineering applications. Conventional approaches include post-inference aggregation of fine-grained predictions or multi-task learning with its disadvantages: necessity to incorporate post-prediction mechanisms, possible mistakes between unrelated categories when generic fine-grained models are used, and the need of training multi-task models with joint procedures. To overcome them, this paper proposes a novel method for extracting coarse-grained classifiers from large Convolutional Neural Networks (CNNs) trained on fine-grained tasks with no additional training. Leveraging the knowledge transfer capabilities of CNNs and acknowledging that a model proficient in a challenging task should inherently address easier, hierarchically related problems, the approach finds and aggregates available representatives of coarse-grained classes within existing fine-grained models. Unlike conventional approaches, the proposed technique aggregates the fine-grained model’s weights and not its predictions. As a result, a new coarse-grained model is obtained with the same feature extractor as the original model. The original and new models can be used to create a multi-output model without the multi-task learning. The method eliminates additional post-prediction mechanisms and limits the mistakes between unrelated categories. It can be used with three strategies to find the sets of fine-grained classes for weight aggregation. They are based on external WordNet knowledge or internal network knowledge. Two of the methods leverage the concepts of semantic and visual similarity. Experimental results with MobileNetV2, InceptionV3, ResNet50V2, EfficientNetV2B0 and ConvNeXt-Small trained on ImageNet demonstrate up to 98% accuracy in the coarse-grained classification, which is superior to the post-prediction aggregation.

ICESat-2 data denoising and forest canopy height estimation using Machine Learning

Supervised classification methods can distinguish between noise and signal in ice, cloud, and land elevation satellite-2 (ICESat-2) data across various feature perspectives and autonomously optimize parameters. Nevertheless, model generalization remains a significant limitation for practical applications. This study focuses on developing a universal denoising model for ICESat-2 using machine learning algorithms and analyzing its spatial transferability under various forest and terrain conditions. A photon-denoising feature parameter system is developed based on the analysis of the three-dimensional distribution of photons in forested regions. This system reduces the parameters dependent on absolute physical quantities and increases those that are less influenced by terrain and forest features to enhance the model’s transferability. Subsequently, automated machine learning algorithms (AutoML) are used for model selection and parameter optimization across six non-parametric regression models. We evaluate the accuracies of the local, global, and transfer models in estimating canopy height across four representative forested areas in China. Results show that the algorithm can effectively distinguish between signal and noise photons. The estimated canopy heights from signal photons are highly consistent with heights obtained using airborne laser scanning (ALS), exhibiting a Pearson correlation coefficient (r) of 0.89, root mean square errors (RMSE) of 3.75 m, relative root mean square error (rRMSE) of 0.27, relative bias (rBias) of −0.11 and mean Bias of −1.45 m. Notably, the accuracy of canopy height estimation by the global model has increased by an average of 21 % compared to ICESat-2 land-vegetation along-track products (ATL08). Furthermore, the model exhibits significant spatial transfer capabilities, with the accuracies of the transfer model exceeding those of ATL08 by margins ranging from 4 % to 41 %. This study marks a significant advancement in photon-denoising methodologies, providing a robust and transferable solution for large-scale environmental data analysis.

Optimizing mass transfer performance in triply periodic minimal surface porous scaffolds through isosurface offset

Efficient bone tissue regeneration remains a critical challenge in orthopedic medicine, with scaffold mass transfer capabilities playing a pivotal role. Triply periodic minimal surface (TPMS) scaffolds have emerged as promising candidates due to their unique structure characterized by smooth, continuous surfaces with zero mean curvature and high specific surface area. However, optimizing their mass transfer performance to meet the diverse needs of bone tissues at different anatomical sites has been a persistent challenge. This study addresses this gap by investigating the effects of isosurface offset on mass transfer performance in three TPMS scaffolds (Fisher-Koch S, Gyroid, and Split-P) using computational fluid dynamics (CFD). The results showed that isosurface offset significantly increased the effective scaffold permeability range (by 116.8%, 5.3%, and 64.3% for F, G, and S scaffolds, respectively) and improved the wall shear stress (WSS) distribution, enhancing the area that effectively stimulates cell proliferation (by 25.2%, 8.7%, and 14.3% increase, respectively). Additionally, it was found that porosity, specific surface area, the ratio of maximum pore size to tortuosity, and curvature significantly influenced the permeability and WSS distribution of the scaffolds. Finally, permeation experiments using porous scaffolds fabricated by laser powder bed fusion (LPBF) technology were performed to validate the simulation results. This study provides new insights into the design of TPMS porous scaffolds and customized bone implants, enhancing their application prospects in bone tissue engineering.

Enhancement of iron cycling in Fenton-like catalysis by MoO2-C: Carbon-mediated efficient electron transport

In this study, the charge transfer capability of MoO2 materials was significantly improved by introducing carbon materials in situ. The resulting MoO2-C material could accelerate the Fe(III)/Fe(II) redox cycle and promote the continuous generation of reactive oxygen species in Fenton-like system. The results suggested that MoO2-C exhibited significant co-catalytic activity against a variety of pollutants. Meanwhile, the mechanisms behind the Fe(III)/Fe(II) cycle and reactive oxygen species generation were clarified. Analysis indicated that the incorporation of carbon material provided a reduction active site for the reduction of Fe(III) to Fe(II) on the surface of molybdenum oxide, and also reduced the thermodynamic energy barrier associated with Fe(III) reduction. Furthermore, quenching experiments and electron paramagnetic resonance (EPR) technology demonstrated that hydroxyl radicals (∙OH) and singlet oxygen (1O2) rapidly degrade the target pollutants. Fe(II) was verified as the primary component responsible for peroxymonosulfate (PMS) and peroxydisulfate (PDS) activation. Additionally, the main generation pathway for 1O2 differed between the MoO2-C/Fe(III)/PDS and MoO2-C/Fe(III)/PMS systems. This study provides a new strategy to improve the iron reduction properties of metal oxide materials.

Electronic structure modulation and peroxymonosulfate activation mechanism of N-doped MnCo2O4: A study on the efficient catalytic degradation of sulfamethoxazole

In this study, a nitrogen-doped MnCo2O4 composite material (nN-MCO) was successfully synthesized via a urea-assisted thermal treatment method and applied for the activation of peroxymonosulfate (PMS) to degrade sulfamethoxazole (SMX). By introducing metal-N (M−N) bonds, the concentration of oxygen vacancies on the catalyst surface and its electron transfer capability with PMS were significantly enhanced. Experimental characterizations demonstrated that nitrogen doping not only strengthened the covalency of the metal-O (M−O) bonds but also facilitated the formation of electron-rich metal sites through electronic rearrangement, further improving the adsorption and activation of PMS. The 2 N-MCO catalyst successfully degraded 98.0 % of SMX within 5 min and maintained a removal efficiency of 85.0 % after four consecutive cycles. The study revealed that 1O2, SO4−, OH and O2− were all involved in the degradation of SMX, with 1O2 identified as the dominant reactive oxygen species. This work presents a simple and effective nitrogen-doping strategy for surface modification of spinel-based catalysts, enhancing the MnCo2O4 composite’s electronic structure, strengthening metal–oxygen bonds, and creating electron-rich sites. These modifications promote oxygen vacancies, improve electron transfer, and enable efficient reactive oxygen species (ROS) generation, offering valuable insights and theoretical support for PMS-based oxidation processes in pollutant treatment.

Antibody-Modified 2D MXene Nanosheet Probes for Selective, picolevel Detection of Cancer Biomarkers

Cancer biomarkers are crucial indicators found in clinical samples, playing a key role in early detection, diagnosis, and treatment of cancer. Detecting these biomarkers with high sensitivity is essential for early diagnosis, especially in aggressive cancers like lung cancer, which is the leading cause of cancer-related deaths. Carcinoembryonic antigen (CEA) is a critical biomarker for lung cancer, and its detection aids in identifying the disease at an early stage. Electrochemical sensing, known for its high sensitivity and rapid response, has shown great promise in cancer biomarker detection. MXenes, two-dimensional materials composed of carbides and nitrides, offer excellent electrochemical performance due to their high surface area and conductivity. In this study, MXenes were modified via hydrothermal treatment to produce MXene nanosheets (MNS) with increased interlayer spacing, enhancing their electron transfer capabilities. Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) revealed the superior electrochemical properties of MNS compared to pristine MXene. These MNS were functionalized with CEA-specific antibodies using EDC-NHS chemistry, creating a highly specific electrochemical biosensor for CEA detection. The sensor exhibited a remarkable limit of detection at the picogram level and was validated through real-time blood analysis, achieving a 95% recovery rate. This MNS-based biosensor demonstrates significant potential for clinical diagnostics, particularly for the early detection of cancer biomarkers, paving the way for improved cancer treatment outcomes.

Enhancing thermal performance of jet-regeneration composite cooling systems: An analysis of flow mode and distribution utilizing supercritical n-decane and ambient air

To enhance the heat transfer performance of the scramjet, this paper conducts research and analysis on the impact of flow mode and flow distribution of supercritical n-decane and ambient air on flow and heat transfer characteristics, based on regeneration cooling channels. Given the disparities in fluid flow characteristics within the channel, the three flow configurations exhibit varying degrees of heat transfer deterioration. In the jet single outlet flow mode, the fluid mobility within the channel is relatively poor, leading to the most pronounced deterioration of heat transfer. The combined heat transfer performance between the jet fluid and the crossflow fluid is predominantly influenced by the number of jets and the distribution ratio of flow rates. Notably, the jet-crossflow single outlet arrangement exhibits exceptional heat transfer capabilities when the jet flow rate constitutes a relatively low proportion (12.5 %) while the crossflow flow rate is substantial (87.5 %). Ambient air, with its lower density, arrives at the heated surface with significantly higher velocities and greater turbulence intensity compared to supercritical n-decane. As the number of jet holes increases, the inhomogeneity (R) in the Nusselt number gradually diminishes. For most configurations, R is more pronounced in ambient air than in supercritical n-decane.

Preparation of Bi2WO6/MXene(Ti3C2Tx) Composite Material and Its Photothermal Catalytic Reduction of CO2 in Air

In response to growing concerns about the greenhouse effect, the direct conversion of atmospheric CO2 has become a pivotal research focus. This research utilizes hydrothermal synthesis to develop Bi2WO6/MXene(Ti3C2Tx), which efficiently reduces CO2 directly at the gas–solid interface through photothermal synergy, without requiring additional sacrificial agents or alkaline absorption solutions. The results indicate that the CO formation rate is about 216.9 μmol·g−1h−1. Notably, this system demonstrates exceptional selectivity for reducing CO2 to CO. The outstanding photothermal catalytic efficiency is attributed to the introduction of MXene, which serves as an efficient and economical co-catalyst. The integration of MXene improves the composite material’s specific surface area and pore structure, enhances its CO2 adsorption capacity, and results in the Bi2WO6/MXene hybrid having a shorter charge transfer distance and a larger interface contact area. This ensures superior charge transfer capabilities, ultimately leading to a significant enhancement in the catalytic efficiency of the composite. This study presents a straightforward and highly selective method for capturing and converting atmospheric CO2, offering fresh insights for developing efficient photothermal catalytic materials.

Economical iron-based catalyst electrode for highly stable catalytic industrial-scale overall seawater splitting

The development of economical and stable catalyst electrodes for industrial-scale seawater splitting is one of the current challenges in hydrogen production. The economical transition metals possess high electrical conductivity and offer the potential for designing electrodes with high intrinsic activity through appropriate modifications, thus holding promising applications in industrial contexts. Herein, a durable and economical self-supported bifunctional electrode (Fe@Ni) with high efficiency and large area is successfully constructed by one step in-situ deposition of iron on the porous structure of nickel foam (NF) via mild (298 K) electroplating method. Transition metals like iron and nickel offer high electrical conductivity and can be properly modified to achieve electrodes with high intrinsic activity. Due to the in-situ growth of cost-effective iron on the NF surface, the electrode surface morphology and electronic structure are reconstructed, which significantly improves the electrochemical activity surface area and electron transfer capability of the electrode. The hydrogen/oxygen evolution reaction (HER/OER) in simulated seawater (1 M KOH + 0.5 M NaCl) require only 129 mV and 323 mV overpotentials to achieve a current density of 100 mA cm−2. Overall seawater splitting (OWS) achieves 10 mA cm−2 at a low voltage of 1.49 V and with a faradaic efficiency of nearly 100%. More importantly, the bifunctional electrodes remain stable at industrial-level current density (1.0 A cm−2) for more than 50 days. More attractively, this work realizes the universal construction of large-area electrode for multiple metals (e.g., Fe, Cu, Al, etc.) with mild and simple process, which provides a new strategy for the current research of energy and materials.

Numerical study of unsteady thin film flow of power-law tetra hybrid nanofluid with velocity slip effect over a stretching sheet using sodium alginate as base fluid

This study examines the influence of power-law nanofluid flow and velocity slip on the heat transfer performance of tetrahybrid nanofluids over a stretching sheet, with the objective of enhancing thermal efficiency in industrial applications. The tetrahybrid nanofluids, consisting of Al2O3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$Al_2O_3$$\\end{document}, TiO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$TiO_2$$\\end{document}, Cu, and Fe3O4\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$Fe_3O_4$$\\end{document} nanoparticles suspended in a sodium alginate base fluid, represent a novel combination of materials whose collective thermal properties have not been extensively studied. The performance of these tetrahybrid nanofluids is compared to that of hybrid and tri-hybrid nanofluids to evaluate their relative heat transfer capabilities. The boundary layer equations are solved using MATLAB’s bvp4c solver, applying similarity transformations to investigate temperature and velocity profiles under varying parameter conditions. The results indicate that tetrahybrid nanofluids significantly enhance heat transfer rates compared to standard nanofluids, with improvements of 7.43%, 6.27%, and 5.35% over hybrid and tri-hybrid nanofluids, respectively. Furthermore, the analysis reveals that velocity profiles intersect at a specific point, and as the velocity slip parameter increases, the profiles move further away from the stretching sheet. Key factors, such as the Prandtl number, power-law index, slip parameter, magnetic field, and Reynolds number, are also examined for their effects on flow and thermal behavior. The key innovation of this research lies in the introduction of tetrahybrid nanofluids as an advanced medium for heat transfer, providing superior thermal efficiency compared to previously studied nanofluids. This study not only builds upon existing research but also provides new computational insights into the potential applications of tetrahybrid nanofluids in areas like food processing and other industries requiring effective thermal management.

The impact of digitalization and virtualization on technology transfer in strategic collaborative partnerships

AbstractDigitalization and virtualization are integral parts of today’s competitive and dynamic business environments. Yet very little is known about the impact of digitalization and virtualization on technology transfer in strategic collaborative partnerships. Therefore, examining the impact of digitalization and virtualization on technology transfer in strategic collaborative partnerships holds much potential for contributing to the ongoing discussions in the technology transfer literature. This introductory article to the Special Issue reflects on the contributions of the Special Issue articles to the research on technology transfer and reveals three central themes through which the articles as a whole contribute to research in technology transfer: Theme 1 describes the role of digitalization in technology transfer outcomes, Theme 2 focuses on extending the understanding of knowledge transfer capabilities to include digital and virtual capabilities, and Theme 3 illustrates how technology transfer facilitators and intermediaries continue to play an important role in technology transfer in the digital world. We conclude the introductory article by proposing four promising avenues for future research on technology transfer in the digital age. These include Avenue 1: Understanding context specificity and temporality, Avenue 2: Focusing on capabilities and government policy, Avenue 3: Bridging distance, and Avenue 4: Protecting against threats.

Electrochemically monitored electron transport for wide-bandgap oxides and enhanced antibacterial ROS production

Metal-loaded semiconductor nanomaterials have been extensively studied for years as excellent photocatalytic antibacterial materials, efficiently catalyzing the production of reactive oxygen species (ROS). However, the precise antibacterial mechanism and pathway of ROS generation for metal-loaded wide-bandgap oxides, which exhibit excellent antibacterial efficacy under dark conditions, are still not fully understood. In order to elucidate their antibacterial mechanisms, Ag-loaded MgO is synthesized to verify an increase in the electron density at the interface of the composite and enhanced electron transfer capability, facilitating the formation of ROS, supported by theoretical reasoning and experimental validation. Furthermore, the innovative electrochemical testing system links the electrochemical performance of antibacterial materials with their antibacterial properties, and monitoring the electron transfer pathways between the materials and bacteria. The synergistic antibacterial activity of affinity contact between MgO and the electron transfer effect of Ag-MgO results in a 99.99 % contact-killing effect against Escherichia coli (E. coli) within 5 min. Our work has made significant progress in understanding the ROS generation mechanism of wide-bandgap oxides under dark conditions, and has proposed new insights into electrochemical monitoring of the electron transfer characteristics of antibacterial materials.

Optimal sizing and placement of STATCOM, TCSC and UPFC using a novel hybrid genetic algorithm-improved particle swarm optimization

The increase in global power demand has caused most of today's power networks to become overloaded especially in Sub-Saharan Africa. The increased load demand can be met through expansion of existing generation and transmission system. However, construction of new power infrastructure is limited by financing and technical constraints. Thus, power networks have been left to operate at overload conditions with high power losses and many power quality (PQ) problems. Flexible AC Transmission System (FACTS) devices can improve the power transfer capability of the existing transmission networks without the need of constructing new power infrastructure. In this paper, a multi-objective function comprising of minimization of power loss (PL), voltage deviation (VD) and operational cost (OC) was formulated and solved using a novel algorithm. A novel Genetic Algorithm-Improved Particle Swarm Optimization (GA-IPSO) technique is proposed in this paper for optimization of size and location of FACTS devices. Static Synchronous Compensator (STATCOM), Thyristor Controlled Series Capacitor (TCSC) and Unified Power Flow Controller (UPFC) are the three FACTS devices considered. The proposed technique was validated using IEEE-33 Bus Test System, which is a popular benchmark Radial Distribution System (RDS). The three FACTS devices were optimized separately and also in a combined manner. Under the separate optimization, the size and location of individual FACTS devices were optimized. For combined optimization, the sizes and locations of more than one device were optimized in the same test system. For separate optimization, UPFC produced the best results by reducing the active power losses by 38.44 % and OC from $1.59×105 to $ 1.15×105. Under the combined optimization, combination of TCSC, STATCOM and UPFC gave better results by achieving active power loss reduction of 56.09 % and reducing OC from $1.59×105 to $ 1.03×105. Comparison of GA-IPSO technique with other algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Improved Grey Wolf Optimization (IGWO) and Differential Evolution Algorithm (DEA) showed that the proposed hybrid technique was superior and more efficient in solving the FACTS optimization problem.