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This study explored the relationship between the design of calf compression sleeves and the comfort of young women in long sitting and standing work environments. By studying the relationship between material elongation and comfort pressure, a prediction model was obtained. The characteristics of the calf models of 94 women were classified, and the influence of different calf characteristics on the pressure distribution and tensile value design was objectively analyzed through simulation tests. The samples were then produced based on the simulation results, and subjective and objective try-on tests and evaluations were carried out. The results show that the difference in the shape of the calf has a certain impact on the pressure distribution and comfort. The predicted value of the theoretical model is in good agreement with the actual test value. The sample can bring a suitable gradient pressure and meet the comfort requirements and safety standards.

Heat dissipation plays a crucial role in the performance and reliability of high-power GaN-based electronics. While AlN transition layers are commonly employed in the heteroepitaxial growth of GaN-on-SiC substrates, concerns have been raised about their impact on thermal transport across GaN/SiC interfaces. In this study, we present experimental measurements of the thermal boundary conductance (TBC) across GaN/SiC interfaces with varying thicknesses of the AlN transition layer (ranging from 0 to 73 nm) at different temperatures. Our findings reveal that the addition of an AlN transition layer leads to a notable increase in the TBC of the GaN/SiC interface, particularly at elevated temperatures. Structural characterization techniques are employed to understand the influence of the AlN transition layer on the crystalline quality of the GaN layer and its potential effects on interfacial thermal transport. To gain further insights into the trend of TBC, we conduct molecular dynamics simulations using high-fidelity deep learning-based interatomic potentials, which reproduce the experimentally observed enhancement in TBC even for atomically perfect interfaces. These results suggest that the enhanced TBC facilitated by the AlN intermediate layer could result from a combination of improved crystalline quality at the interface and the “phonon bridge” effect provided by AlN that enhances the overlap between the vibrational spectra of GaN and SiC.

BackgroundHigh myopia (HM) refers to an eye refractive error exceeding −5.00 D, significantly elevating blindness risk. The underlying mechanism of HM remains elusive. Given the extensive genetic heterogeneity and vast genetic base opacity, it is imperative to identify more causative genes and explore their pathogenic roles in HM.MethodsWe employed exome sequencing to pinpoint the causal gene in an HM family. Sanger sequencing was used to confirm and analyse the gene mutations in this family and 200 sporadic HM cases. Single-cell RNA sequencing was conducted to evaluate the gene’s expression patterns in developing human and mouse retinas. The CRISPR/Cas9 system facilitated the gene knockout cells, aiding in the exploration of the gene’s function and its mutations. Immunofluorescent staining and immunoblot techniques were applied to monitor the functional shifts of the gene mutations at the cellular level.ResultsA suspected nonsense mutation (c.C172T, p.Q58X) in CCDC66was found to be co-segregated with the HM phenotype in the family. Additionally, six other rare variants were identified among the 200 sporadic patients. CCDC66was consistently expressed in the embryonic retinas of both humans and mice. Notably, in CCDC66-deficient HEK293 cells, there was a decline in cell proliferation, microtube polymerisation rate and ace-tubulin level. Furthermore, the mutated CCDC66 failed to synchronise with the tubulin system during Hela cell mitosis, unlike its wild type counterpart.ConclusionsOur research indicates that the CCDC66variant c.C172T is associated with HM. A deficiency in CCDC66 might disrupt cell proliferation by influencing the mitotic process during retinal growth, leading to HM.

This paper presents a gel-based three-dimensional (3D) substrate for surface-enhanced Raman spectroscopy (SERS) mediated by photonic nanojets (PNJs) to enhance the sensitivity of SERS detection. The porous structure of the gel-based substrate allowed small molecules to diffuse into the substrate, while the placement of silica beads on the substrate surface resulted in the generation of photonic nanojets during SERS measurements. Because the gel-based SERS substrate had electromagnetic (EM) hot spots along the Z-direction for several tens of microns, the focuses of the PNJs, which were located a few microns away from the substrate surface, could excite the EM hot spots located within the substrate. Our objective was to maximize SERS signal intensity by coating the substrate with a close-packed array of silica beads to enable the generation of multiple PNJs. The bead array was formed using an optical fiber decorated with gold nanorods (AuNRs) to create a temperature gradient in a mixture containing silica beads, thereby enabling their arrangement and deposition in arbitrary locations across the substrate. In experiments, the Raman enhancement provided by multiple PNJs significantly exceeded that provided by single PNJs. The proposed PNJ-mediated SERS method reduced the limit of detection for malachite green by 100 times, compared to SERS results obtained using the same substrate without beads. The proposed enhancement scheme using a gel-based 3D SERS substrate with a close-packed array of silica beads could be utilized to achieve high-sensitivity SERS detection for a variety of molecules in a diverse range of applications.

The emergence of wide and ultrawide bandgap semiconductors has revolutionized the advancement of next-generation power, radio frequency, and opto- electronics, paving the way for chargers, renewable energy inverters, 5G base stations, satellite communications, radars, and light-emitting diodes. However, the thermal boundary resistance at semiconductor interfaces accounts for a large portion of the near-junction thermal resistance, impeding heat dissipation and becoming a bottleneck in the devices’ development. Over the past two decades, many new ultrahigh thermal conductivity materials have emerged as potential substrates, and numerous novel growth, integration, and characterization techniques have emerged to improve the TBC, holding great promise for efficient cooling. At the same time, numerous simulation methods have been developed to advance the understanding and prediction of TBC. Despite these advancements, the existing literature reports are widely dispersed, presenting varying TBC results even on the same heterostructure, and there is a large gap between experiments and simulations. Herein, we comprehensively review the various experimental and simulation works that reported TBCs of wide and ultrawide bandgap semiconductor heterostructures, aiming to build a structure–property relationship between TBCs and interfacial nanostructures and to further boost the TBCs. The advantages and disadvantages of various experimental and theoretical methods are summarized. Future directions for experimental and theoretical research are proposed.

Coordination cages with a well-defined nanocavity are a class of promising supramolecular materials for molecular recognition and sensing. However, their applications in sequential sensing of multiple types of pollutants are highly desirable yet extremely limiting and challenging. Herein, we demonstrate a convenient strategy to develop a supramolecular fluorescence sensor for sequentially detecting environmental pollutants of aluminum ions and nitrofurantoin. A coordination cage (Ni-NTB), adopting an octahedral structure with triphenylamine chromophores occupying on the faces, is weakly emissive in solution due to the intramolecular rotations of the phenyl rings. Ni-NTBexhibits sensitive and selective fluorescence “off–on–off” processes during consecutive sensing of Al3+and nitrofurantoin, an antibacterial drug. These sequential detection processes are highly interference-tolerant and visually observable with the naked eye. Mechanism studies reveal that the fluorescence switch is controllable by tuning the degree of intramolecular rotations of the phenyl rings and the pathway of intermolecular charge transfer, which is associated with the host–guest interaction. Moreover, the fabrication of Ni-NTBon test strips enabled a quick naked-eye sequential sensing of Al3+and nitrofurantoin in seconds. Hence, this novel supramolecular fluorescence “off–on–off” sensing platform provides a new approach to developing supramolecular functional materials for monitoring environmental pollution.

In real industrial applications, intelligent methods are recently emerging for remaining useful life (RUL) prediction. However, their development is hindered by two obstacles. First, it is hard for an ordinary edge client to achieve RUL prediction owing to its weak computing capacity and limited data volume. Second, as for all edge clients, it is unrealistic to share data with each other due to the potential conflict of interests. Therefore, a federated learning-based RUL prediction method namely FedRUL is proposed to solve these problems. In this method, multiple edge clients and a cloud server are applied to train a global encoder and an RUL predictor without data sharing. Each client includes a convolutional autoencoder (CAE) comprised of an encoder and a decoder while the server includes a same encoder and an RUL predictor. During each epoch, CAEs are trained in all clients through their corresponding local training datasets first. Then, all local encoders are uploaded to the server and aggregated to a global encoder through assigning weights for all clients according to their performance on a validation dataset in the server. At last, this global encoder is sent back to all clients for extracting low-level features from their datasets and uploading these features to train the RUL predictor for each client one by one. Two experiments suggest FedRUL offers a promising solution on confidential decentralized learning for RUL prediction.

Preparation of high acidity coefficient slag wool fiber with molten slag and modifying agents is considered to be a positive approach for value-added utilization of blast furnace slag. In order to achieve the multi-purposes of fiber-forming, energy saving, and waste heat recovery, the modifying agents that can improve the acidity coefficient of slag effectively, economically, and environmentally were investigated. Three agents with different acidity coefficients were adopted to modify slag and manufacture wool fibers. The effect of agent and slag proportion on the melting temperature and viscosity of molten slag was studied at a fixed acidity coefficient of 1.8 and 2.0. The results indicate that the sample modified with high acidity coefficient agent and high slag proportion has lower melting temperature and viscosity. The effect of agent and slag temperature on the fiber diameter was also investigated when the acidity coefficient of slag is 2.0. At a fixed slag proportion of 50 wt.%, the mean diameter decreases with increasing temperature and decreasing viscosity coefficient. Besides, the temperature drops caused by the addition of agents and energy consumption of samples for heating the slag were also analyzed.

Magnetometry sensors have wide applications across science and technology. A magnetometer at room temperature can be made by coupling a magnetostrictive material to a high-Q optical cavity, which is crucial for achieving the high sensitivity in detecting the magnetic field. In this work, we have designed a hybrid structure based on the high-Q optical capillary microresonator filled with a yttrium iron garnet (YIG) microsphere to realize highly sensitive magnetic field sensing in the range of kHz. The device shows a peak magnetic field sensitivity of 146 pT Hz $^{-1/2}$ at frequency of 16.85 kHz. This sensor structure provides high sensitivity in the range of 9 kHz to 100 kHz, thus allowing applications in magnetic anomaly detection and other fields.

The high-temperature operation of the AlGaN/GaN high electron mobility transistors (HEMTs) and direct-coupled FET logic (DCFL) inverters, NOR gates, and NAND gates are demonstrated. The ${p}$ -GaN-gate HEMTs which are used as drivers in DCFL circuits exhibit proper E-mode operation with a relatively stable threshold voltage ${V}_{\text {TH}}$ (drift −0.31 V) and high electron mobility $\mu $ of 587 cm2/ $\text{V}\cdot \text{S}$ at 300 °C. The fabricated logic gates have a small switching time at room temperature (RT). As the temperature increases to 300 °C, these logic gates exhibit a slight increase in switching time, wherein the fall time and rise time of the inverter from room temperature to 300 °C increases from 16 ns to 129 ns and 128 ns to $0.864~\mu \text{s}$ , respectively. The logic gates herein exhibit accurate and stable operation at 300 °C. Furthermore, the reason for the switching time increase at high temperature is revealed from the perspective of devices.

In order to assess the health condition of machines, it is necessary to construct a suitable health indicator (HI) for detecting the initial degeneration point (IDP). However, there are two limitations aimed at existing HIs: 1) manually extracted feature-based construction methods strongly rely on the expert knowledge and experience and 2) most HIs are insensitive to the early faults of machines the fault component is unobvious and even overwhelmed by noises whether in the time domain or the frequency domain. For addressing these problems, a deep metric learning-based HI construction method is proposed for detecting IDPs of machines. The proposed method is mainly comprised of three steps. First, a multiscale deep metric learning model with self-attention modules is built to extract features according to an improved contrastive loss (ICL). Then, the relative similarity of extracted features between the baseline sample data and the currently acquired sample data is calculated as the current HI to represent the health condition of machines. Finally, an optimization algorithm, namely particle swarm optimization (PSO)-genetic algorithm (GA), is designed to search for the optimal model parameters. The performance of the proposed method is verified in two different experiments and compared with other methods. Results show that this method is able to identify IDPs more precisely for machines.

In this brief, a scaled In $_{{0}.{17}}$ Al $_{{0}.{83}}\text{N}$ /GaN high-electron-mobility transistor (HEMT) was fabricated on sapphire substrate with 47-nm ${T}$ -gate length, 300-nm source–drain distance, and selective area regrown $\text{n}^{+}$ -GaN. The device exhibits cutoff frequencies ${f}_{\text {T}}/{f}_{\text {max}}$ of 190/301 GHz, which gives a record sqrt ( ${f}_{\text {T}} \times {f}_{\text {max}}{)}$ = 239 GHz among reported Ga-polar GaN-on-sapphire HEMTs. The device shows a maximum current density, a peak external direct current transconductance, and an ${I}_{\text {on}}/{I}_{\text {off}}$ ratio of 1.45 A/mm, 610 mS/mm, and $2.9\times 10^{6}$ , respectively. Drain-induced barrier lowering of 75 mV/V is measured at ${I}_{\text {ds}}$ = 1 mA/mm between ${V}_{\text {ds}}$ = 1 V and 5 V. The three-terminal OFF-state breakdown voltage is 14.7 V. The effective electron velocity of the 2-D electron gas (2DEG) under the gate foot is estimated to be $1.4\times 10^{7}$ cm/s. These characteristics of this Ga-polar millimeter wave (mm-wave) GaN-on-sapphire HEMT are comparable with those state-of-the-art counterparts on SiC substrates.

N-p-n AlGaN/GaN heterojunction bipolar transistors (HBTs) on sapphire substrates with high current gain $\beta $ of 129, low specific ON-resistance ( ${R}_{ \mathrm{\scriptscriptstyle ON},\text {sp}}{)}$ of 0.28 $\text{m}\sf \Omega \cdot $ cm2 and high current density ${J}_{C}$ of ~15 kA/cm2 (if normalized to emitter area, ${R}_{ \mathrm{\scriptscriptstyle ON},\text {sp}} \sim 0.15 \text{m}\sf \Omega \cdot \text{m}^{{2}}$ and ${J}_{C} \sim 28.4$ kA/cm2) have been demonstrated. The analysis of component of ${R}_{ \mathrm{\scriptscriptstyle ON},\text {sp}}$ yields the collector resistance is ~5.2% of the total ${R}_{ \mathrm{\scriptscriptstyle ON},\text {sp}}$ , showing the low ON-resistance advantage of GaN HBTs. The open-base avalanche breakdown voltage (BVCEO) is ~160 V. High-temperature performance of GaN HBT is also evaluated. The ${R}_{ \mathrm{\scriptscriptstyle ON},\text {sp}}$ is reduced as temperature increasing in the range of 25 °C–100 °C due to enhanced hole concentration in the base layer. The cutoff frequency ( ${f}_{T}{)}$ of greater than 4 GHz is determined at ${V}_{\text {CE}} =$ 9 V. These results dominate that GaN HBTs have been anticipated to become a new technology for next-generation power switches and RF power amplifier circuit.

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In the postharvest processing of tea leaves, withering is the first indispensable manufacturing process which produces the mellow, umami and sweet taste of white tea. In this study, we aimed to determine the dynamic changes of the main metabolites and clarify the key differentially expressed genes (DEGs) involved in forming the characteristic taste of white tea during withering. Phytochemical analyses revealed that the contents of total catechins and starch decreased continuously, whereas the contents of theaflavin, γ-aminobutyric acid (GABA), maltose, and soluble sugars increased significantly during withering (from 0–48 h). Meanwhile, the elevation of α-amylase (AMY), β-amylase (BAM), total amylase, and glutamate decarboxylase (GAD) activities may be correlated with the accumulation of GABA and maltose. By transcriptome sequencing, we detected 9 707, 15 921, 17 353, and 17 538 DEGs at 12, 24, 36, and 48 h of the withering process, respectively, compared with 0 h sample (fresh leaves). The transcript levels of most of the DEGs involved in catechin biosynthesis were significantly inhibited, whereas those involved in catechin oxidation were significantly up-regulated, which could be correlated to a decrease in catechin content and an increase in theaflavin content. The DEGs involved in GABA biosynthesis were considerably up-regulated, and the down-regulation of SPMScould reduce the competition for converting spermidine to GABA. The up-regulation of the AMYand BAMgenes could trigger starch degradation, resulting in the increase of soluble sugar content. These results provide new insights into the importance of the withering process to the characteristic taste of white tea.

Nowadays the development of high-field magnets strongly relies on the performance of superconducting materials. Iron-based superconductors (IBSs) exhibit high upper critical fields and low electromagnetic anisotropy, making them particularly attractive for high-field applications, especially in particle accelerator magnets, nuclear magnetic resonance spectrometers, medical magnetic resonance imaging systems and nuclear fusion reactors. Herein, through an industrially scalable manufacturing strategy, a practical-level critical current density up to 1.1×105A cm−2at 4.2 K in an external magnetic field of 10 T was achieved in Cu/ Ag composite-sheathed Ba1−xKxFe2As2(Ba122) superconducting tapes. The preparation strategy combines flat rolling to induce grain texture and subsequent hot-isostatic-pressing densification. By varying the parameters of rolling, the degree of grain texture was engineered. It is found that the transport properties of the Ba122 tapes can be enhanced by applying a large amount of deformation during rolling, which can be attributed to the improved degree of c-axis texture. Microstructure characterizations on the highest-performance tape demonstrate that the Ba122 phase has a uniform element distribution and small grains with good connectivity. Grain boundary pinning is consequently enhanced as proved by large currents circulating through the sample even at 25 K. Our work proves that Cu/Ag composite-sheathed Ba122 superconducting tapes can be a promising competitor for practical high-field applications in terms of the viable, scalable and cost-effective fabrication strategy applied and the high transport properties achieved in this work.

The application of a coordination container in biomedicine is hindered by single binding domains and unsatisfactory biostability and biocompatibility. Herein, we designed a sulfonylcalix[4]arene-based decahexanuclear zinc(II) coordination container employing a flexible tetracarboxylate ligand as a linker and utilized it as a novel drug delivery system. The coordination container consisting of one endo and four exo cavities provides multiple binding domains for efficient encapsulation of drug molecules as clearly revealed by systematic host–guest studies using NMR techniques of 1H NMR titration experiments and 2D NOESY and diffusion-ordered NMR spectroscopy studies. Incorporation of a flexible p-phenylene-bis(methanamino) spacer into the container via the carboxylate linker allowed a stepwise drug loading process through sequential binding at endo and exo cavities, as well as enabling pH-responsive stepwise drug release. The drug-loaded coordination container not only exhibits excellent biostability and biocompatibility but also provides encouraging therapeutic efficiency toward inflammatory macrophages as revealed by in vitro studies. The novel strategy for engineering the endo cavity of a coordination container provides a new approach to achieving controlled drug delivery and opens up new opportunities for designing novel functional supramolecular materials.

In this work, we study the thermal transport at β-Ga2O3/metal interfaces, which play important roles in heat dissipation and as electrical contacts in β-Ga2O3devices. A theoretical Landauer approach was used to model and elucidate the factors that impact the thermal transport at these interfaces. Experimental measurements using time-domain thermoreflectance (TDTR) provided data for the thermal boundary conductance (TBC) between β-Ga2O3and a range of metals used to create both Schottky and ohmic electrical contacts. From the modeling and experiments, the relation between the metal cutoff frequency and the corresponding TBC is observed. Moreover, the effect of the metal cutoff frequency on TBC is seen as the most significant factor followed by chemical reactions and defects between the metal and the β-Ga2O3. Among all β-Ga2O3/metal interfaces, for Schottky contacts, Ni/β-Ga2O3interfaces show the highest TBC, while for ohmic contacts, Cr/β-Ga2O3interfaces show the highest TBC. While there is a clear correlation between TBC and the phonon cutoff frequency of metal contacts, it is also important to control the chemical reactions and other defects at interfaces to maximize the TBC in this system.

High thermal conductivity materials show promise for thermal mitigation and heat removal in devices. However, shrinking the length scales of these materials often leads to significant reductions in thermal conductivities, thus invalidating their applicability to functional devices. In this work, we report on high in-plane thermal conductivities of 3.05, 3.75, and 6 μm thick aluminum nitride (AlN) films measured viasteady-state thermoreflectance. At room temperature, the AlN films possess an in-plane thermal conductivity of ∼260 ± 40 W m–1K–1, one of the highest reported to date for any thin film material of equivalent thickness. At low temperatures, the in-plane thermal conductivities of the AlN films surpass even those of diamond thin films. Phonon–phonon scattering drives the in-plane thermal transport of these AlN thin films, leading to an increase in thermal conductivity as temperature decreases. This is opposite of what is observed in traditional high thermal conductivity thin films, where boundaries and defects that arise from film growth cause a thermal conductivity reduction with decreasing temperature. This study provides insight into the interplay among boundary, defect, and phonon–phonon scattering that drives the high in-plane thermal conductivity of the AlN thin films and demonstrates that these AlN films are promising materials for heat spreaders in electronic devices.

Antineutrophil cytoplasmic antibody vasculitis-associated interstitial lung disease (AAV-ILD) is a potentially life-threatening disease. However, very little research has been done on the condition’s mortality risk. Hence, our objective is to find out the factors influencing the prognosis of AAV-ILD and employ these findings to create a nomogram model. Patients with AAV-ILD who received treatment at the First Affiliated Hospital of Zhengzhou University during the period from March 1, 2011, to April 1, 2022 were selected for this research. The development of nomogram entailed a synergistic integration of univariate, Lasso, and multivariate Cox regression analyses. Internal validation ensued through bootstrap techniques involving 1000 re-sampling iterations. Discrimination and calibration were assessed utilizing Harrell’s C-index, receiver operating characteristic (ROC) curve, and calibration curve. Model performance was evaluated through integrated discrimination improvement (IDI), net reclassification improvement (NRI), and likelihood ratio test. The net benefit of the model was evaluated using decision curve analysis (DCA). A cohort comprising 192 patients was enrolled for analysis. Throughout observation period, 32.29% of the population died. Key factors such as cardiac involvement, albumin, smoking history, and age displayed substantial prognostic relevance in AAV-ILD. These factors were incorporated to craft a predictive nomogram. Impressively, the model exhibited robust performance, boasting a Harrell’s C index of 0.826 and an AUC of 0.940 (95% CI 0.904–0.976). The calibration curves depicted a high degree of harmony between predicted outcomes and actual observations. Significantly enhancing discriminative ability compared to the ILD-GAP model, the nomogram was validated through the IDI, NRI, and likelihood ratio test. DCA underscored the superior predictive value of the predictive model over the ILD-GAP model. The internal validation further affirmed this efficacy, with a mean Harrell’s C-index of 0.815 for the predictive model. The nomogram model can be employed to predict the prognosis of patients with AAV-ILD. Moreover, the model performance is satisfactory. In the future, external datasets could be utilized for external validation.

Vascular disrupting agents (VDAs) can destroy tumor vasculature and lead to tumor ischemia and hypoxia, resulting in tumor necrosis. However, VDAs are easy to induce the upregulation of genes that are associated with drug resistance and angiogenesis in tumor cells. Hypoxia-activated chemotherapy will be an ideal supplement to VDAs therapy since it can help to fully utilize the ischemia and hypoxia induced by VDAs to realize a synergistic antitumor therapeutic outcome. Here, we design a liposome whose surface is modified with a tumor-homing peptide Cys-Arg-Glu-Lys-Ala (CREKA, which can specifically target tumor vessels and stroma) and whose inner cavity is loaded by a hypoxia-activated drug banoxantrone dihydrochloride (AQ4N) as well as a VDA combretastatin A4 (CA4). CA4 can selectively target vascular endothelial cells and destroy the tumor blood vessels, which will cause the rapid closure of blood flow in tumor and enhance the hypoxia in the tumor region. As a consequence, AQ4N can exert its boosted cytotoxicity under the enhanced hypoxic environment. The as-prepared liposome with a uniform particle size exhibits good stability and high cancer cell killing efficacy in vitro. In addition, in vivo experiments confirm the excellent tumor-targeting/accumulation, tumor vascular damaging, and tumor inhibition effects of the liposome. This work develops CA-TL which can achieve safe and effective tumor suppression without external stimulus excitation by only single injection, and is expected to benefit the future development of effective antitumor liposomal drugs.

High-power GaN-based electronics are limited by high channel temperatures induced by self-heating, which degrades device performance and reliability. Increasing the thermal boundary conductance (TBC) between GaN and SiC will aid in the heat dissipation of GaN-on-SiC devices by taking advantage of the high thermal conductivity of SiC substrates. For the typical growth method, there are issues concerning the transition layer at the interface and low-quality GaN adjacent to the interface, which impedes heat flow. In this work, a room-temperature bonding method is used to bond high-quality GaN to SiC directly, which allows for the direct integration of high-quality GaN with SiC to create a high TBC interface. Time-domain thermoreflectance is used to measure the GaN thermal conductivity and GaN–SiC TBC. The measured GaN thermal conductivity is larger than that of grown GaN-on-SiC by molecular beam epitaxy. High TBC is observed for the bonded GaN–SiC interfaces, especially for the annealed interface (∼230 MW m–2K–1, close to the highest value ever reported). Thus, this work provides the benefit of both a high TBC and higher GaN thermal conductivity, which will impact the GaN-device integration with substrates in which thermal dissipation always plays an important role. Additionally, simultaneous thermal and structural characterizations of heterogeneous bonded interfaces are performed to understand the structure–thermal property relation across this new type of interface.