Transfer Theory Research Articles

Elucidating the significance of molecular interaction between sulphur doped zinc oxide nanoparticles and serum albumin using multispectroscopic approach.

Ingenious nanomaterials with improved biocompatibility and multifunctional properties are gaining vital significance in biomedical applications, including advanced drug delivery and nanotheranostics. In a biological system, these nanoparticles interact with serum proteins forming a dynamic corona that affects their biological or toxicological properties producing undesirable effects. Thus, the current study focuses on the synthesis of sulphur-doped zinc oxide nanoparticles (ZnO/S NPs) and characterizing their mechanism of interaction with serum proteins using multispectroscopic approach. ZnO/S NPs were synthesized by employing a co-precipitation approach and characterized using various analytical techniques. The results of interaction studies demonstrated that ZnO/S NPs interact with serum albumins via the static quenching process. Analysis of thermodynamic parameters (ΔG, ΔH and ΔS) revealed that the binding process is spontaneous, exothermic and van der Waals force or hydrogen bonding plays a major role. The interaction of ZnO/S NPs with tyrosine residue in bovine serum albumin was established by synchronous fluorescence spectroscopy. In addition, the results of UV-visible, circular dichroism, Fourier transform infrared, Forster's resonance energy transfer theory and dynamic light scattering spectroscopic studies revealed that the ZnO/S NPs interact with albumin by inducing the conformational changes in secondary structure and reducing the α-helix content.

Assessment of the Influence of Instrument Parameters on the Detection Accuracy of Greenhouse-Gases Absorption Spectrometer-2 (GAS-2)

Satellite-based monitoring of atmospheric greenhouse gas (GHG) concentrations has emerged as a prominent and globally recognized field of research. With the imminent launch of the Greenhouse-Gases Absorption Spectrometer-2 (GAS-2) on the FengYun3-H (FY3-H) satellite in 2024, there is a promising prospect for substantial advancements in GHG detection capabilities. Crucially, the accurate acquisition of spectral information by GAS-2 is heavily reliant on its instrument parameters. However, the existing body of research predominantly emphasizes the examination of atmospheric parameters and their impact on GHG detection accuracy, thereby leaving a discernible gap in the comprehensive evaluation of instrument parameters specifically concerning the acquisition of atmospheric greenhouse gas concentration data by GAS-2. To address this knowledge gap, our study employs a radiation transfer model grounded in radiation transfer theory. This comprehensive investigation aims to quantitatively analyze the effects of various instrument parameters, encompassing crucial aspects such as spectral resolution, spectral sampling rate, signal-to-noise ratio, radiometric resolution, and spectral calibration accuracy (including instrument line shape function, central wavelength shift, and spectral resolution broadening). Based on our preliminary findings, it is evident that GAS-2 has the necessary spectral resolution, spectral sampling rate, and signal-to-noise ratio, slightly surpassing existing international instruments and enabling a significant detection accuracy level of 1 part per million (ppm). Moreover, it is essential to recognize the critical impact of instrument spectral calibration accuracy on overall detection precision. Among the five commonly used instrument line shape functions, the sinc function has the least impact on detection accuracy. Additionally, GAS-2’s radiance quantization depth is 14 bits, which is comparable to similar international payloads and maintains a root mean squared error below 0.1 ppm, thus ensuring a high level of precision. This study provides a comprehensive evaluation of the influence of GAS-2’s instrument parameters on detection accuracy, offering valuable insights for the future development of spectral calibration, the optimization of similar payload instrument parameters, and the overall improvement of instrument quantification capabilities.

Matching target color in polyolefins by estimating pigment concentrations using a four-flux model.

In applications of computer color formulation where color stimuli are optically thick (e.g.,textiles, coatings, etc.), a simple single-constant or two-constant theory (e.g.,Kubelka-Munk model) would suffice. To accurately predict reflectance and transmittance of materials with optical thickness ranging from optically thin to optically thick (e.g.,plastics), mathematically complex radiative transfer theories (e.g.,many-flux models) have been recommended. A many-flux model can even predict color formulation involving special-effect pigments (e.g.,metallic, pearlescent, etc.), but implementation of such models is manyfold complicated. In the current study, applicability of a relatively simple Maheu-Letoulouzan-Gouesbet (MLG) four-flux radiative transfer model to optically varying pigmented polyolefins is thoroughly investigated. First, the MLG model was implemented to determine absorption and scattering coefficients of over 120 pigments where a new mean relative absolute spectral error (MRASE) between measured and calculated spectral reflectance and transmittance of the calibration samples was minimized as an objective function. Second, currently determined absorption and scattering coefficients were further validated by color recipe prediction of 350 historical product colors. Measured and predicted reflectance curves were compared in units of MRASE, CIEDE2000 color difference, metamerism index, root mean square error, and goodness-of-fit coefficient. Moreover, transmission matching was evaluated in units of percent difference between the required and predicted average transmittance. Results showed that with the current implementation of the MLG four-flux model, color recipes of at least 95% of the target colors can be predicted within the acceptability thresholds in units of different error metrics used in the study.

Improving IEC thermal model for oil natural air natural transformers using optimised parameters based on dynamic simulation

AbstractAccurate assessment of hot‐spot temperature is essential for the safe operation of power transformers. Existing dynamic thermal models cannot estimate hot‐spot temperature accurately since some input parameters are roughly determined by transformer capacity and cooling mode while ignoring the effect of winding structure, tank dimensions, and material physical properties. To improve the accuracy of temperature assessment, empirical parameters of the IEC thermal model including thermal constants, winding and oil exponents are optimised with the help of numerical simulation in this article. Based on energy conservation and heat transfer theory, a computational fluid dynamic (CFD) model of a transformer in oil natural air natural (ONAN) cooling mode is established. This CFD model simulates the entity's structure, sizes, and multi‐stage heat dissipation processes realistically, so it can more precisely calculate the dynamic hot‐spot temperature. According to the simulated temperature curves at different operating conditions, the thermal constants and oil exponent are estimated using non‐linear regression, and the winding exponent is optimised using linear regression. A case study is conducted on an ONAN transformer. It shows the improved IEC model with optimised parameters can more accurately evaluate hot‐spot temperature, and the absolute error is decreased by 2.4 K (38.7%) compared with traditional thermal models.

Thermal characteristics and distribution rule of lubrication film of full ceramic ball bearing under different service condition

PurposeThe study aims to the distribution rule of lubricating oil film of full ceramic ball bearing and improve its performance and life.Design/methodology/approachThe paper established an analysis model based on the fluid–solid conjugate heat transfer theory for full ceramic ball bearings. The distribution of flow, temperature and pressure field of bearings under variable working conditions is analyzed. Meanwhile, the mathematical model of elastohydrodynamic lubrication (EHL) of full ceramic ball bearings is established. The numerical analysis is used to study the influence of variable working conditions on the lubricant film thickness and pressure distribution of bearings. The temperature rise test of full ceramic ball bearing under oil lubrication was carried out to verify the correctness of simulation results.FindingsAs the speed increased, the oil volume fraction in full ceramic ball bearing decreased and the surface pressure of rolling element increased. The temperature rise of full ceramic ball bearings increases with increasing speed and load. The lubricant film thickness of full ceramic ball bearing is positively correlated with speed and negatively correlated with load. The pressure of lubricating film is positively correlated with speed and load. The test shows that the higher inner ring speed and radial load, the higher the steady-state temperature rise of full ceramic ball bearing. The test results are in high agreement with simulation results.Originality/valueBased on the fluid–solid conjugate heat transfer theory and combined with Reynolds equation, lubricating oil film thickness formula, viscosity temperature and viscosity pressure formula. The thermal analysis model and EHL mathematical model of ceramic ball bearings are established. The flow field, temperature field and pressure field distribution of the full ceramic ball bearing are determined. And the thickness and pressure distribution of lubricating oil film in the contact area of full ceramic ball bearing were determined.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2023-0126/

Understanding the Energetics of Ion Intercalation in Lithium-Ion Batteries

Researchers around the world are working to increase the energy efficiency and the energy density of lithium-ion batteries. However, the mechanism and the factors influencing the charge transfer (CT) kinetics at the electrode-electrolyte interface remain poorly understood. Recently, Fraggedakis et al. [1] proposed the theory of coupled ion-electron transfer (CIET) to explain the process of charge transfer at the electrode-electrolyte interfaces. In this work, we provide deep atomistic understanding of the interfacial CT mechanism, the underlying microscopic steps, and the factors influencing the CT rates in a Li-ion battery. In addition, we connect our computational results with the experimental measurements and Marcus-like theories of charge transfer (viz. CIET [1]).Using state-of-the-art computational techniques, such as metadynamics and molecular dynamics simulations, we model the electrode-electrolyte interface and compute the free energy profiles of Li-ion adsorption at the interface, subsequent ion-desolvation, and intercalation into the cathode. Specifically, we study the adsorption of Li+ ion on LixCoO2 surface for different (i) electrolytes, (ii) Li+ concentrations in electrolyte, (iii) salt compositions, and (iv) temperatures to uncover the trends governing charge transfer kinetics. Using the obtained free energy profiles of Li+ desolvation and intercalation at the solid-liquid interface, we provide estimation of the adsorption and desolvation energy at the interface and identify the key energy barrier which acts as the roadblock for ion transfer in Li-ion batteries. Based on this identified key kinetic barrier, we then propose strategies to tune the energy barrier for ion transport. In addition, we identify important thermo-physical observations that can explain the existing experimental trends. For instance, we find that increasing the salt concentration in the electrolyte increases the accessible solvation states to Li+ ion, thereby changing the energy barrier for the Li+ ion to intercalate into the electrode, and thus leading to higher currents. Moreover, we find that changing the salt from LiPF6 to LiClO4 further modifies the energy landscape of Li+ ion, leading to increased measured experimental kinetics as well. This work builds an understanding of the influence of various effects, such as salt concentration and electrolyte composition, on the Li+ transport properties at interfacial regions. Our computational framework can also provide descriptors to enhance the performance and stability of lithium-ion batteries.

Mechanistic Insights into Tyrosine Oxidation Revealed by Fast-Scan Cyclic Voltammetry

A precise understanding of opioid dynamics in the brain is lacking, largely because few analytical tools are available that are sufficiently sensitive and selective for directly monitoring these important neurochemicals in situ. Tyrosine is a key part of the opioid neuropeptides, and its redox activity can be exploited in their detection. However, a solid understanding of tyrosine electrochemistry on carbon electrodes is first required. It is known that, upon oxidation, tyrosine quickly undergoes chemical transformation to products that foul the electrode, compromising the electrochemical information. This issue can be avoided by using fast-scan cyclic voltammetry (FSCV) which enables collection of well-defined voltammograms on a millisecond timescale before appreciable accumulation of byproducts. In this work, the tyrosine oxidation reaction is characterized and electrode fouling is assessed when tyrosine is incorporated into short synthetic peptides containing other amino acids that are part of the opioid neuropeptides: Gly, Phe, Met, Leu, and Arg. Voltammetric data were obtained in phosphate buffered solution on carbon microelectrodes at scan rates up to 1 kV/s. The results demonstrate the dependence of the peak oxidation potential on solution pH, and identify possible reaction pathways and byproducts that foul the electrode. Peak oxidation potential, peak shape, and ultimately, sensitivity to tyrosine are dependent on the peptide sequence. NMR spectroscopy is used to relate the proximity of proton acceptor/donor functional groups to the electrochemical results in the context of proton-coupled electron transfer (PCET) theory. These fundamental studies are important for the electrochemical detection of important neuropeptides in the complex in vivo environment. Furthermore, a better understanding of the tunability of PCET reaction rates in electrochemical systems has broad implications for technology in a range of areas including artificial photosynthesis, solar energy conversion, and energy storage.

Photon Energy-Dependent Ultrafast Exciton Transfer in Chlorosomes of Chlorobium tepidum and the Role of Supramolecular Dynamics.

The antenna complex of green sulfur bacteria, the chlorosome, is one of the most efficient supramolecular systems for efficient long-range exciton transfer in nature. Femtosecond transient absorption experiments provide new insight into how vibrationally induced quantum overlap between exciton states supports highly efficient long-range exciton transfer in the chlorosome of Chlorobium tepidum. Our work shows that excitation energy is delocalized over the chlorosome in <1 ps at room temperature. The following exciton transfer to the baseplate occurs in ∼3 to 5 ps, in line with earlier work also performed at room temperature, but significantly faster than at the cryogenic temperatures used in previous studies. This difference can be attributed to the increased vibrational motion at room temperature. We observe a so far unknown impact of the excitation photon energy on the efficiency of this process. This dependency can be assigned to distinct optical domains due to structural disorder, combined with an exciton trapping channel competing with exciton transfer toward the baseplate. An oscillatory transient signal damped in <1 ps has the highest intensity in the case of the most efficient exciton transfer to the baseplate. These results agree well with an earlier computational finding of exciton transfer driven by low-frequency rotational motion of molecules in the chlorosome. Such an exciton transfer process belongs to the quantum coherent regime, for which the Förster theory for intermolecular exciton transfer does not apply. Our work hence strongly indicates that structural flexibility is important for efficient long-range exciton transfer in chlorosomes.

Origin of Prebiotic Organics and Oxygen on Earth. A case for the Pre-Photosynthetic and Carbonyl Sulfide Catalyzed Reduction of Carbon Dioxide by Water, Methane, Ammonia and Hydrogen sulfide.

It is estimated that the earth is about 4.5 billion years old and it is now believed that by 4.3 billion years ago, earth may have developed physico-chemical conditions suitable to support life, when its atmosphere consisted largely of water (H2O) vapor, nitrogen (N2), and carbon dioxide (CO2) with much smaller amounts of methane (CH4), carbon monoxide (CO), ammonia (NH3), hydrogen (H2), hydrogen sulfide (H2S) and other sulfur compounds like carbonyl sulfide (COS), and the earth had a reducing atmosphere without any free oxygen. The oldest known fossil records show that life came into being about 3.7 billion years ago. It is also believed that life proliferated and evolved in largest scale only after first aoxygenic photosynthesis by viruses and then oxygenic photosynthesis by plants produced large scale biochemocules and molecular oxygen (O2). But this necessitated a period of the evolution of primitive life forms like reprocing cells, which required enormous carbon-based prebiotic chemicals mediated by dialectical chance and necessity as is the case with later biological evolution. This had to involve the production within about a billion years, of specific prebiotic ingradients in enough quantities, in sufficient concentration in a limited, dynamic and physicochemically suitable localized evironment. But only the few primitive chemical compounds mentioned above, most abundent being H2O and CO2 , laready existing on earth, potentially could be source of enormous amount and variety of prebiotic chemicals necessary for the formation the first reproducing cell. Based on the SET (Selective Energy Transfer Theory) developed by one of us (RL), we have reason to speculate for the first time that the carbonyl sulphide (COS) catalyzed reduction of CO2 by H2O and by other less abundant molecules like CH4, NH3 and H2S was the decisive prerequisite for the formation of prebiotic chemical ingredients and for the chemical evolution of the first reproducing cell on Earth.

Mass Transfer Theory Based Analysis of Influencing Factors on Component Gradient of Near-surface Atmosphere on Venus

The atmosphere of Venus differs completely from that of Earth despite the planets’ similarity in size and mass. At Venus's surface, the atmosphere is hot and dense, with a temperature of approximately 735 K and a pressure of approximately 92 bar. The temperature profile from the Soviet VeGa-2 probe shows high instability of the near-ground potential temperature, which, according to relevant research, can be explained by the vertical gradient of N2 mole fraction. Based on the Maxwell–Stefan mass transfer theory, we propose a theoretical model of binary gas component for a quantitative discussion of influencing factors for the N2 vertical concentration gradient, which consist of temperature, gravity, specific heat ratio, mass relative factor, thermal diffusion factor, and CO2 flux. Our model shows that the 0%–3.5% N2 concentration gradient cannot be generated without CO2 flux in the near-ground atmosphere of Venus. And the result with CO2 source indicates that the 0.000001%–3.5% N2 concentration gradient at 0–7 km atmosphere can be generated by the 2.7 × 10−6 mol m−2 s−6 CO2 flux on Venusian surface, which is in agreement of gradient reckoned by VeGa-2's data. This magnitude of CO2 flux is close to the one produced by volcanic eruptions on Earth, indicating possible existence of volcanic activities on the surface of Venus. This work has provided the community a new vision to understand the influencing factors of Venusian atmospheres composition distribution.

Fostering trust and overcoming psychological resistance towards cryptocurrencies and cryptoassets

AbstractThis research investigates the extent to which sponsorships can be utilised to foster trust and reduce barriers to adopting new technologies. Using Crypto.com's sponsorship of the 2022 FIFA World Cup as the context, this mixed‐methods study utilises innovation resistance theory (IRT) and trust transfer theory (TTT) to investigate the extent to which such a sponsorship can increase trust and reduce barriers in innovative technologies such as cryptoassets, while also filling a research gap concerning consumer resistance to innovations in digital financial products and services. The findings of study 1, using a survey (n = 1081), and study 2 using interviews (n = 24) reveal that a positive image of sponsorship significantly influences favourability and interest, and trust of the product of the sponsor which subsequently reduces psychological barriers to adoption. Integrating the theoretical viewpoints of IRT and TTT, this study enhances our conceptual understanding regarding the psychological dimension of sponsorship and the extent to which a sponsorship generates interest, giving assurance and trust in the sponsor's product, and removing uncertainty; thus, reducing barriers to adoption.

Heat Transfer Model and Thermal Insulation Characteristics of Surrounding Rock of Thermal Insulation Roadway in a High-Temperature Mine

The thermal insulation method is one of the effective methods for controlling the thermal environment of a high-temperature mine. In order to explore the thermal insulation mechanism and characteristics of thermal insulation roadways in high-temperature mines, a heat transfer model for the surrounding rock of the thermal insulation roadway was established based on the steady heat transfer theory. The temperature field of the surrounding rock of the thermal insulation roadway was studied, and the effects and sensitivities of thermal insulation layer thickness and thermal conductivity, convective heat transfer coefficient between roadway wall and airflow, and roadway radius on the thermal insulation performance of thermal insulation roadway were discussed. The results suggest the following: (1) The temperature gradient inside the thermal insulation layer is greater than that inside the surrounding rock. The thermal insulation roadway reduces the temperature difference between the original rock and the outside surface of the thermal insulation layer, thereby reducing the heat dissipation of the surrounding rock. (2) As the thermal insulation layer thickness increases, the thermal insulation capacity gradually increases, but its enhancement rate gradually weakens; as the thermal conductivity of the thermal insulation layer or the roadway radius increases, the thermal insulation capacity gradually decreases and its decline rate gradually weakens; and the convective heat transfer coefficient between the roadway wall and airflow has almost no effect on the thermal insulation capacity. (3) The thermal insulation performance of the thermal insulation roadway is highly sensitive or above the thickness and thermal conductivity of the thermal insulation layer, as well as the roadway radius. The sensitivity of thickness and thermal conductivity of the thermal insulation layer is greater than that of roadway radius. Therefore, the research results have guiding significance for the application of thermal insulation methods in the prevention and control of thermal hazards in mines.

Wireless Charger for Electrical Vehicles with Large Air Gap

In this paper the work has been done to analyze the idea of transmitting power wirelessly to Electric Vehicles. The research depicts a mechanism which has the ability to transfer power wirelessly which will reduce the dependence on foreign oil. Wireless Power Transfer using magnetic resonance is the technology which would set the human free from the hassle of wires. It adopts the basic theory of Inductive Power Transfer. The transferring distance increases from several millimeters to hundred millimeter. This adaptive technique will prove to be a revolutionary change in the field of Electronics.

S-CO2 flow in vertical tubes of large-diameter: Experimental evaluation and numerical exploration for heat transfer deterioration and prevention

Heat transfer deterioration (HTD) problems can undermine the thermal safety of heating tubes for supercritical carbon dioxide (S-CO2) flows. Relevant experimental evidence is highly desired, but most cases were investigated for small tube diameters (below 10 mm) and under limited operation parameters, far from the industry-scale applications. In the present work, large tubes (24 mm) are investigated experimentally with pressures of 7.5–15 MPa, mass flow rates of 100–1200 kg·m−2·s−1 and heat fluxes of 30–350 kW·m−2. The seriousness of HTD in large tubes was experimentally confirmed, and the mechanism is explored via a carefully-designed comprehensive comparison between present numerical simulations and experimental tests. Detailed analysis of vapor-like film development inspires us to mitigate the problem using structured-inner-surface, from the viewpoint of “supercritical pseudo-boiling”. This inspiration is further evaluated numerically: five types of enhancement structures are proposed to interfere with the development of vapor-like film. It was found that the proposed methods can fully prevent HTD problems, and especially the conical strips can achieve a high heat transfer performance (with performance evaluation criteria PEC of 1.21–1.35) and are thus recommended for HTD prevention in vertical large-diameter tubes under near-critical conditions. Overall, the experimental tests and numerical explorations can deliver more evidence on the theory and applications of supercritical fluid flow and heat transfer.

Establishing a transient model of double-layer porous media interfacial evaporation system to reveal the relationship between porous media parameters and evaporation performance

The solar interfacial evaporation system can generate steam efficiently by localizing solar thermal energy to heat air–water interface, which has great application potential in seawater desalination, sewage treatment, and other fields. At present, the solar absorption layer and substrate of the interfacial evaporation system are mainly made of carbon materials, sponges, foams, and other porous media materials. However, the transient interfacial evaporation heat and mass transfer model and the influence of the physical parameters of porous media on evaporation performance have rarely been investigated. Based on heat and mass transfer theory of porous media, a transient theoretical model of porous media interfacial evaporation system is established in this paper. Moreover, the effects of physical parameters such as the porosity and thermal conductivity of porous media on evaporation performance are analyzed, and the accuracy of the model is verified through outdoor experiments. Based on the model calculation, as the porosity of the substrate increases, the evaporation rate and efficiency of the evaporator first increase and then decrease. The lower the thermal conductivity of the substrate and the higher the porosity and thermal conductivity of the solar absorption layer are, the better the evaporation performance is, but the growth rate gradually decreases. Therefore, the relationship between the improvement of evaporation performance and the increased cost caused by the improvement of material properties needs to be considered. The model and related theoretical analysis results can provide a theoretical basis for system structure optimization, material selection and other aspects of future research on double-layer porous media interfacial evaporation system.

Evaluation and Application of SMRT Model for L-Band Brightness Temperature Simulation in Arctic Sea Ice

Using L-band microwave radiative transfer theory to retrieve ice and snow parameters is one of the focuses of Arctic research. At present, due to limitations of frequency and substrates, few operational microwave radiative transfer models can be used to simulate L-band brightness temperature (TB) in Arctic sea ice. The snow microwave radiative transfer (SMRT) model, developed with the support of the European Space Agency in 2018, has been used to simulate high-frequency TB in polar regions and has obtained good results, but no studies have shown whether it can be used appropriately in the L-band. Therefore, in this study, we systematically evaluate the ability of the SMRT model to simulate L-band TB in the Arctic sea ice and snow environment, and we show that the results are significantly optimized by improving the simulation method. In this paper, we first consider the thermal insulation effect of snow by adding the thermodynamic equation, then use a reasonable salinity profile formula for multi-layer model simulation to solve the problem of excessive L-band penetration in the SMRT single-layer model, and finally add ice lead correction to resolve the large influence it has on the results. The improved SMRT model is evaluated using Operation IceBridge (OIB) data from 2012 to 2015 and compared with the snow-corrected classical L-band radiative transfer model for Arctic sea ice proposed in 2010 (KA2010). The results show that the SMRT model has better simulation results, and the correlation coefficient (R) between SMRT-simulated TB and Soil Moisture and Ocean Salinity (SMOS) satellite TB is 0.65, and the RMSE is 3.11 K. Finally, the SMRT model with the improved simulation method is applied to the whole Arctic from November 2014 to April 2015, and the simulated R is 0.63, and the RMSE is 5.22 K. The results show that the SMRT multi-layer model is feasible for simulating L-band TB in the Arctic sea ice and snow environment, which provides a basis for the retrieval of Arctic parameters.

A Review of Studies on Heat Transfer in Buildings with Radiant Cooling Systems

Due to their benefits in interior thermal comfort, energy saving, and noise reduction, radiant cooling systems have received wide attention. Radiant cooling systems can be viewed as a part of buildings’ maintenance structure and a component of cooling systems, depending on their construction. This article reviews studies on heat exchange in rooms utilizing radiant cooling systems, including research on conduction in radiant system structures, system cooling loads, cooling capacity, heat transfer coefficients of cooling surfaces, buildings’ thermal performance, and radiant system control strategy, with the goal of maximizing the benefits of energy conservation. Few studies have examined how radiant cooling systems interact with the indoor environment; instead, earlier research has focused on the thermal performance of radiant cooling systems themselves. Although several investigations have noted variations between the operating dynamics of radiant systems and conventional air conditioning systems, the cause has not yet been identified and quantified. According to heat transfer theory, the authors suggest that additional research on the performance of radiant systems should consider the thermal properties of inactive surfaces and that buildings’ thermal inertia should be used to coordinate radiant system operation.

Effects of Relational Bonds on Continuance Purchase Behavior in Live Streaming Commerce

Shopping through live streaming commerce (LSC) has become popular in China. From the perspective of trust transfer theory, this study integrated three kinds of relational bonds as antecedents of trust development to examine the trust mechanism in the context of LSC and extend the marketing literature. Our research model was validated using data from 525 consumers with LSC experience. Results of structural equation modeling showed that financial, social, and structural bonds had a significant impact on trust in live streamers. Further, trust in live streamers significantly affected trust in products and continuance purchase intention, and trust in products significantly affected continuance purchase intention. Thus, we can conclude that relational bonds affect continuance purchase behavior through trust in live streamers and products. The findings have theoretical implications for understanding the factors that affect continuance purchase behavior and have practical implications for stimulating consumer behavior in LSC.

Quantum Kinetics of the Electronic Energy Transformation in Molecular Nanostructures

A quantum theory of electronic energy transfer in a layered nanostructure with molecular J-aggregates of polymethine dyes was proposed. An expression for the exciton-plasmon bond energy depending on various parameters of the system was given. The rate of non-radiative Fὄrster resonance energy transfer (FRET) from surface plasmon polaritons (SPPs) of a metal substrate to Frenkel excitons of J-aggregates was determined and dispersion dependences for hybrid states were obtained. It was established that the energy transfer rate can reach values of 1012–1013 s–1, and the value of the Rabi splitting is up to 100 MeV. The kinetics of the process under strong exciton-plasmon interaction was investigated. The time dependence of the energy exchange between the system components had the form of damped oscillations depending on the relaxation parameters, the Rabi frequency, and the response to resonance. In addition, the exciton FRET between two parallel monolayers of J-aggregates of polymethine dyes separated by a nanometer-thick metal film was investigated. It was found that the presence of the metal layer increases the FRET rate. The spin evolution of a pair of two triplet (T) molecules localized in the nano-cell region under the over-barrier jumps regime in a magnetic field was studied. The influence of the parameters of the two-dimensional potential on the frequency of inter-dimensional motions and the population of triplets was considered. The spin dynamics of molecular T-T pairs in the magnetic field of a ferromagnetic globular nanoparticle under free surface diffusion of a spin-carrying molecule was investigated.

Building a nomological network for creative learning transfer focusing on leadership development

PurposeThe study attempts to build a creative learning transfer (CLT) theory represented by a nomological network incorporating relevant theories and empirical support for the relationships among the transfer predictors in the learning transfer system (LTS), leaders' CLT and their job performance.Design/methodology/approachThe authors used 76-item survey data from 471 managers who worked for 16 large companies located in South Korea, had completed leadership training at least three months before the data collection and had received a performance review just before the data collection. A series of exploratory and confirmatory factor analyses (CFA) and reliability tests were conducted, followed by a common method variance test and structural equation modeling.FindingsA nomological network of LTS, CLT and job performance was established. The findings supported the mechanism for motivating managers to transfer acquired leadership skills to challenging organizational situations and eventually, increase their managerial job performance. This study provided a parsimonious CLT scale and verified the influence of CLT on leaders' job performance.Originality/valueThis study is the first attempt to measure the concept of CLT and suggest a parsimonious CLT scale. In addition, this study conceptualized, operationalized and confirmed a nomological network for CLT. Organizations may develop such a system and help managers apply the learned leadership knowledge and skills to novel business situations for creating more competitive work systems, products and services.