Table of contents

The surface charge accumulation is very likely to trigger the surface flashover, which limits the large-scale application of DC GIL/GIS. This article comprehensively reviews the effect of six factors, including insulator-electrode shape, surface roughness of the insulator and conductor, metal particles, temperature, humidity, and gas type, on the insulator surface charging property. Furthermore, three models i.e. 'analogous ineffective region' expansion model, charge cluster triggered surface flashover model, and synergistic model of adsorbed gas, revealing the mechanism of charge triggered surface flashover phenomenon are reviewed and discussed. Future work from the perspective of theoretical analysis and engineering application are suggested in this field.

Single hole transport and spin detection is achievable in standard p-type silicon transistors owing to the strong orbital quantization of disorder based quantum dots. Through the use of the well acting as a pseudo-gate, we discover the formation of a double-quantum dot system exhibiting Pauli spin-blockade and investigate the magnetic field dependence of the leakage current. This enables attributes that are key to hole spin state control to be determined, where we calculate a tunnel coupling t_c of 57 μeV and a short spin−orbit length l_SO of 250 nm. The demonstrated strong spin−orbit interaction at the interface when using disorder based quantum dots supports electric-field mediated control. These results provide further motivation that a readily scalable platform such as industry standard silicon technology can be used to investigate interactions which are useful for quantum information processing.

The aim of this study is to evaluate the effect of rare earth upconversion nanoparticles (UCNs) on hepatic ischemia reperfusion injury (IRI) and explore its possible mechanism. Hepatic IRI seriously affects the prognosis of patients undergoing liver surgery. Liver-resident Kupffer cells have been reported to promote IRI. Nanomedicines are known to be effective in the treatment of liver diseases, however, Kupffer cell-targeting nanomedicines for the treatment of IRI are yet to be developed. As potential bioimaging nanomaterials, UCNs have been found to specifically deplete Kupffer cells, but the underlying mechanism is unknown. In this study, we found that UCNs specifically depleted Kupffer cells by pyroptosis, while the co-administration of the caspase-1 inhibitor VX-765 rescued the UCN-induced Kupffer cell pyroptosis in mice. Furthermore, the pre-depletion of Kupffer cells by the UCNs significantly suppressed the release of inflammatory cytokines and effectively improved hepatic IRI. The rescue of the pyroptosis of the Kupffer cells by VX-765 abrogated the protective effect of UCNs on the liver. These results suggest that UCNs are highly promising for the development of Kupffer cell-targeting nanomedicines for intraoperative liver protection.

Neural probes are in vivo brain-invasive devices that record and manipulate neural circuits using electricity, light, or drugs. The capability to shine distinct wavelengths and control their respective output locations for activation or deactivation of specific groups of neurons is desirable but remains unachieved. Here, we discuss our probe's capability to deliver two independently controllable wavelengths (450 and 655 nm) in the location(s) of interest using nanophotonic directional couplers and ring resonators. These nanophotonics are scalable to dozens of outputs without significantly increasing the device's lateral dimensions. Furthermore, they are entirely passive and thus do not require electrical input that results in heat generation. Besides, we integrate a high number of electrodes for a simultaneous neural activity readout. Thus, we overcome the challenges associated with multicolor illumination for neural devices by exploiting the capability of miniaturizable, passive probes to deliver two different frequencies in several areas of interest. These devices open the path towards investigating the in vivo electrical signal propagation under the individual or simultaneous activation or inhibition of distinct brain regions.

Layered two-dimensional (2D) materials such as MoS₂ have attracted much attention for nano- and opto-electronics. Recently, intercalation (e.g. of ions, atoms, or molecules) has emerged as an effective technique to modulate material properties of such layered 2D films reversibly. We probe both the electrical and thermal properties of Li-intercalated bilayer MoS₂ nanosheets by combining electrical measurements and Raman spectroscopy. We demonstrate reversible modulation of carrier density over more than two orders of magnitude (from 0.8 × 10¹² to 1.5 × 10¹⁴ cm⁻²), and we simultaneously obtain the thermal boundary conductance between the bilayer and its supporting SiO₂ substrate for an intercalated system for the first time. This thermal coupling can be reversibly modulated by nearly a factor of eight, from 14 ± 4.0 MW m⁻² K⁻¹ before intercalation to 1.8 ± 0.9 MW m⁻² K⁻¹ when the MoS₂ is fully lithiated. These results reveal electrochemical intercalation as a reversible tool to modulate and control both electrical and thermal properties of 2D layers.

Characterizing electrical breakdown limits of materials is a crucial step in device development. However, methods for repeatable measurements are scarce in two-dimensional materials, where breakdown studies have been limited to destructive methods. This restricts our ability to fully account for variability in local electronic properties induced by surface contaminants and the fabrication process. To tackle this, we implement a two-step deep-learning model to predict the breakdown mechanism and breakdown voltage of monolayer MoS₂ devices with varying channel lengths and resistances using current measured in the low-voltage regime as inputs. A deep neural network (DNN) first classifies between Joule and avalanche breakdown mechanisms using partial current traces from 0 to 20 V. Following this, a convolutional long short-term memory network (CLSTM) predicts breakdown voltages of these classified devices based on partial current traces. We test our model with electrical measurements collected using feedback-control of the applied voltage to prevent device destruction, and show that the DNN classifier achieves an accuracy of 79% while the CLSTM model has a 12% error when requiring only 80% of the current trace as inputs. Our results indicate that information encoded in the current behavior far from the breakdown point can be used for breakdown predictions, which will enable non-destructive and rapid material characterization for 2D material device development.

GaAs nanowire (NW) arrays were grown by molecular beam epitaxy using the self-assisted vapor−liquid−solid method with Ga droplets as seed particles. A Ga pre-deposition step is examined to control NW yield and diameter. The NW yield can be increased with suitable duration of a Ga pre-deposition step but is highly dependent on oxide hole diameter and surface conditions. The NW diameter was determined by vapor-solid growth on the NW sidewalls, rather than Ga pre-deposition. The maximum NW yield with a Ga pre-deposition step was very close to 100%, established at shorter Ga deposition durations and for larger holes. This trend was explained within a model where maximum yield is obtained when the Ga droplet volume approximately equals the hole volume.

In recent years the most studied carbon allotrope has been graphene, due to the outstanding properties that this two-dimensional material exhibits; however, it turns out to be a difficult material to produce, pattern, and transfer to a device substrate without contamination. Carbon microelectromechanical systems are a versatile technology used to create nano/micro carbon devices by pyrolyzing a patterned photoresist, making them highly attractive for industrial applications. Furthermore, recent works have reported that pyrolytic carbon material can be graphitized by the diffusion of carbon atoms through a transition metal layer. In this work we take advantage of the latter two methods in order to produce multilayer graphene by improving the molecular ordering of photolithographically-defined pyrolytic carbon microstructures, through the diffusion (annealing) of carbon atoms through nickel, and also to eliminate any further transfer process to a device substrate. The allotropic nature of the final carbon microstructures was inspected by Raman spectroscopy (Average I_D/I_G of 0.2348 ± 0.0314) and TEM clearly shows well-aligned lattice planes of 3.34 Å fringe separation. These results were compared to measurements made on pyrolytic carbon (Average I_D/I_G of 0.9848 ± 0.0235) to confirm that our method is capable of producing a patterned multilayer graphene material directly on a silicon substrate.

Electrospinning is a simple, cost-effective, and versatile technique for fabrication of nanofibers. However, nanofibers obtained from the conventional electrospinning are typically disordered, which seriously limits their application. In this work, we present a novel and facile technique to obtain aligned nanofibers with high efficiency by using parallel inductive-plates assisted electrospinning (PIES). In this new electrospinning setup, the electrostatic spinneret is contained in a pair of parallel inductive-plates, which can change the shape and direction of the electric field line during the electrospinning so as to control the flight trajectory and spatial alignment of the spinning nanofibers. This electrospinning setup can divide the electric field line into two parts which are respectively directed to the edge of the upper and lower inductive-plates. Then the nanofibers move along the electric field line, suspend and align between the parallel inductive-plates. Finally, the well aligned nanofibers could be easily transferred onto other substrates for further characterizations and applications. The aligned nanofibers with an average diameter of 469 ± 115 nm and a length as long as 140 mm were successfully achieved by using PIES technique. Moreover, nanofiber arrays with different cross angles and three-dimensional films formed by the aligned nanofibers were also facilely obtained. The novel PIES developed in this work has been proved to be a facile, cost-effective and promising approach to prepare aligned nanofibers for a wide range of applications.

In this article, the synthesis of phase pure iron pyrite nanocubes (FeS₂ NCs) and their various effects on the charge carrier dynamics and photovoltaic performances of P3HT:PC₇₁BM based hybrid bulk-heterojunction solar cells have been studied. The optimum doping concentration of FeS₂ NCs was found to be 0.3 wt%. For the optimally doped devices, the short-circuit current density was found to have improved from 5.47 to 7.99 mA cm⁻² leading to an overall cell efficiency improvement from 2.10% to 3.22% as compared to the undoped reference devices. The enhancement in photovoltaic performance is mainly attributed to the formation of localized energy states near the band edges leading to higher carrier generation rate by 72% whereas carrier dissociation probability is also increased by 13%. Urbach energy estimation reveals that the optimally doped devices have achieved a relatively balanced amount of localized states resulting in reduced non-radiative recombination. Such localized defect states formation with FeS₂ NCs doping was also found to have significant influence over the charge carrier dynamics of the active layer. Transient photocurrent and photovoltage studies revealed that FeS₂ NCs assist in faster carrier extraction by reducing the transport time from 1.4 to 0.6 μs and by enhancing carrier recombination time from 51.7 to 78.9 μs for the reference and optimum devices respectively. Such an unorthodox approach of defect state assisted efficiency improvement demonstrates the importance of simultaneously understanding the charge carrier dynamics and photovoltaic performance for rational device optimization, and opens new prospects for developing high-efficiency solution processable hybrid devices.

In the past decades, defect engineering has become an effective strategy to significantly improve the hydrogen evolution reaction (HER) efficiency of electrocatalysts. In this work, a facile chemical vapor deposition (CVD) method is firstly adopted to demonstrate defect engineering in high-efficiency HER electrocatalysts of vanadium diselenide nanostructures. For practical applications, the conductive substrate of carbon cloth (CC) is selected as the growth substrate. By using a four-time CVD method, uniform three-dimensional microflowers with defect-rich small nanosheets on the surface are prepared directly on the CC substrate, displaying a stable HER performance with a low Tafel slope value of 125 mV dec⁻¹ and low overpotential voltage of 295 mV at a current density of 10 mA cm⁻² in alkaline electrolyte. Based on the results of x-ray photoelectron spectra and density functional theory calculations, the impressive HER performance originates from the Se vacancy-related active sites of small nanosheets, while the microflower/nanosheet homoepitaxy structure facilitates the carrier flow between the active sites and conductive substrate. All the results present a new route to achieve defect engineering using the facile CVD technique, and pave a novel way to prepare high-activity layered electrocatalysts directly on a conductive substrate.

Herein, Ti₃C₂T_x MXene/N-doped reduced graphene oxide (MXene/N-rGO) composite was employed as the electrocatalyst to construct a new electrochemical sensing platform for the determination of adrenaline (AD). The MXene/N-rGO was synthesized via a facile one-step hydrothermal method, where ethylenediamine acted as a reducing agent and N source. The doped N in rGO served as a bridge between MXene and rGO through tight hydrogen bonds. Scanning electron microscopy showed that large numbers of MXenes with accordion-like morphology were distributed on the surface of the N-rGO. The MXene/N-rGO composite displayed a synergetic catalytic effect for oxidizing AD, originating from the unique catalytic activity of N-rGO and the large surface area and satisfactory conductivity of MXene. These characteristics of composite material led to a remarkable effect on signal amplification for the detection of AD, with a wide linear range from 10.0 nM to 90.0 μM and a low detection limit of 3.0 nM based on a signal to noise ratio of 3. Moreover, the MXene/N-rGO electrode displayed good stability, repeatability, and reproducibility. Additionally, the proposed sensor was successfully applied for voltammetric sensing of AD in urine with recoveries from 97.75% to 103.0%.

Boron and nitrogen co-doped carbon dots (B, N-CDs) were fabricated through a simple, one-step hydrothermal reaction of citric acid, boric acid, and tris base. The obtained B, N-CDs exhibit excitation-dependent fluorescence, high quantum yield (QY), biocompatibility, photostability, and aqueous solubility. The QY was substantially increased to 57% by doping boron atoms. Furthermore, the fluorescence intensity of B, N-CDs was temperature-dependent and decreased linearly from 283 to 333 K. The prepared B, N-CDs were used as a fluorescence probe for the detection of para-nitrophenol (p-NP) and Fe (III) ions with low detection limits of 0.17 μM and 0.30 μM, respectively. Moreover, the presence of p-NP could be further confirmed by a colorimetric assay. The fluorescent probe has been applied to determine p-NP and Fe (III) in a spiked serum sample and spiked water samples (lake and tap water). Moreover, the as-prepared B, N-CDs were of low toxicity and capable of bioimaging.

Conventional sensors are rigid, involve complex processes and structures, and one sensor can detect only one type of stimulus. The manufacturing costs of such devices are high owing to the use of vacuum processes for the formation of thin films and electrodes and the complicated fabrication processes required to construct multiple layers. In addition, the multiple-layer design increases the risk of peeling due to mechanical movement. In this study, to solve the aforementioned problems, a simple two-layer multi-sensor has been fabricated using a non-vacuum solution process. The sensor consists of a light absorption layer comprising polyvinyl butyral and semiconductor particles and a top layer comprising two spiral-shaped Ag nanowire electrodes. The sensor experiences minimal damage by external adhesives and has a light-sensitive optical response at 420 nm and at 1.2 mW cm⁻². Herein, the capacitance of the sensor applied to the two-electrode structure was determined, along with the light sensitivity and change in noise with frequency. We believe that the proposed multi-sensor can be applied in a wide range of fields because it can act as a touch sensor and light sensor.

Mass production of defect-free and large-lateral-size 2D materials via cost-effective methods is very important. Recently, shear exfoliation has shown great promise for large-scale production due to its simple operation, environmental-benignity and wide adaptability. However, a long-standing challenge is that with the production of more nanosheets, a ceiling yield and shattered products are encountered, which significantly limits their wider application. The method and efficiency of energy transfer in fluid is undoubtedly the key point in determining exfoliation efficiency, yet its in-depth mechanism has not yet been described. Thus, a thorough investigation of turbulence energy transfer is critically necessary. Herein, we identify two main factors that critically determine the exfoliation yield and provide a statistical analysis of the relationship between these factors and the exfoliation yield. In the initial shearing process, the coexistence of the 2D nanosheets and raw particles is the dominant factor; as time passes, the dimensional change of raw materials gradually has a greater influence on the energy transfer. These factors together lead to attenuated efficiency and a power function relationship between yield and exfoliation time. This investigation gives a statistical explanation of shear exfoliation technology for 2D material preparation and provides valuable insights for mechanical exfoliating high-quality 2D materials.

Ultrathin silicon nanowires (SiNWs) are ideal 1D channels to construct high performance nanoelectronics and sensors. We here report on a high-density catalytic growth of orderly ultrathin SiNWs, with diameter down to ${{\rm{D}}}_{{\rm{nw}}}=27\pm 2\,{\rm{nm}}$ and narrow NW-to-NW spacing of only ${{\rm{S}}}_{{\rm{nw}}}$ ∼80 nm, without the use of high-resolution lithography. This has been accomplished via a terrace-confined strategy, where tiny indium (In) droplets move on sidewall terraces to absorb precoated amorphous Si layer as precursor and produce self-aligned SiNW array. It is found that, under proper parameter control, a tighter terrace-step confinement can help to scale the dimensions of the SiNW array down to the extremes that have not been reported before, while maintaining still a stable guiding growth over complex contours. Prototype SiNW field effect transistors demonstrate a high I_on/I_off current ratio ∼10⁷, low leakage current of ∼0.3 pA and steep subthreshold swing of 220 mV dec⁻¹. These results highlight the unexplored potential of catalytic growth in advanced nanostructure fabrication that is highly relevant for scalable SiNW logic and sensor applications.

Core–shell nanocomposites with a catalytic metal-organic framework (MOF) shell are more effective and stable than bare MOF. We have successfully designed an effective heterogeneous catalyst for the synthesis of benzimidazole by integrating acidic catalytic activity, and promoted the aerobic oxidation and magnetic recyclability of core–shell nanocomposite Fe₃O₄@SiO₂@UiO-66. The Fe₃O₄@SiO₂ core is encapsulated by the in situ-grown UiO-66 shell, and the UiO-66 shell retains the porous structure and crystallinity of UiO-66 with abundant exposed Lewis acid sites. It shows high catalytic ability for the synthesis of various benzimidazoles through the acid-catalyzed condensation and aerobic oxidation with in situ oxygen. The Fe₃O₄@SiO₂ core provides magnetic recyclability of Fe₃O₄@SiO₂@UiO-66, and maintains high catalytic ability and stability over six cycles.

Talc is a van der Waals and naturally abundant mineral with the chemical formula Mg₃Si₄O₁₀(OH)₂. Two-dimensional (2D) talc could be an alternative to hBN as van der Waals dielectric in 2D heterostructures. Furthermore, due to its good mechanical and frictional properties, 2D talc could be integrated into various hybrid microelectromechanical systems, or used as a functional filler in polymers. However, properties of talcas one of the main representatives of the phyllosilicate (sheet silicates) group are almost completely unexplored when ultrathin crystalline films and monolayers are considered. We investigate 2D talc flakes down to single layer thickness and reveal their efficiency for solid lubrication at the nanoscale. We demonstrate by atomic force microscopy based methods and contact angle measurements that several nanometer thick talc flakes have all properties necessary for efficient lubrication: a low adhesion, hydrophobic nature, and a low friction coefficient of 0.10 ± 0.02. Compared to the silicon-dioxide substrate, 2D talc flakes reduce friction by more than a factor of five, adhesion by around 20%, and energy dissipation by around 7%. Considering our findings, together with the natural abundance of talc, we put forward that 2D talc can be a cost-effective solid lubricant in micro- and nano-mechanical devices.

We investigated the microstructures of carbon nanotube (CNT) films and the effect of CNT length on their mechanical performance. 230 μm-, 300 μm-, and 360 μm- long CNTs were grown and used to fabricate CNT films by a winding process. Opposite from the length effect on CNT fibers, it has been found that the mechanical properties of the CNT films decrease with increasing CNT length. Without fiber twisting, short CNTs tend to bundle together tightly by themselves in the film structure, resulting in an enhanced packing density; meanwhile, they also provide a high degree of CNT alignment, which prominently contributes to high mechanical properties of the CNT films. When CNTs are long, they tend to be bent and entangled, which significantly reduce their packing density, impairing the film mechanical behaviors severely. It has also been unveiled that the determinant effect of the CNT alignment on the film mechanical properties is more significant than that of the film packing density. These findings provide guidance on the optimal CNT length when attempting to fabricate high-performance macroscopic CNT assemblies.

Si–Ni composite nanoparticles have been produced by a single and continuous plasma spray physical vapor deposition (PS-PVD) from Si and Ni powder feedstocks and their electrochemical performances as anode in lithium-ion batteries (LiB) are investigated. Si nanoparticles with 20–40 nm on which Ni is directly attached with Si/NiSi₂ epitaxial interface are formed spontaneously through co-condensation of high temperature elemental gas mixtures during PS-PVD. When only a little amount of Ni is added to Si, the effect of the epitaxial Ni attachment on the Si nanoparticles becomes evident; the cycle capacity is appreciably improved to reach a 1.6 times higher capacity than that of the Si only cell after 50 cycles, due to reduced charge-transfer resistance and nanosized Si particle. In contrast, excessive Ni addition to Si feedstock leads to formation of various silicides as a result of the accelerated silicidation during PS-PVD, which results in a significant decrease in the cycle capacity due to reduction of the active Si phase amount despite reduced charge-transfer resistance.

5, 7, 12, 14-pentacenetetrone (PT), polycyclic quinone derivatives, are rich in carbonyl, which were investigated as a novel organic electrode material for supercapacitors. PT with a π conjugated system, is a flat molecule, generating strong π–π interactions between molecules. PT molecules were uniformly fixed on conductive reduced graphene oxide (rGO) through π–π interaction by one-step solvothermal method, forming a three-dimensional cross-linked PT@rGO hydrogel. This composite structure was conducive to reducing the charge transfer resistance and promoting the Faraday reaction of electrode, which achieved the superposition of electric double-layer capacitance and pseudocapacitance. Appropriate organic molecular loading can effectively improve electrochemical performance. The optimal PT@rGO electrode material displayed the specific capacitance of 433.2 F g⁻¹ at 5 mV s⁻¹ with an excellent rate capability in 1 mol l⁻¹ H₂SO₄ electrolyte. Finally, the fully pseudocapacitive asymmetric supercapacitor has been assembled by using PT@rGO as positive electrode and benz[a]anthracene-7,12-quinone (BAQ) modified rGO(BAQ/rGO)as negative electrode, which exhibited the good energy storage performance in a cell voltage of 1.8 V.

C-coated SiC nanocomposites (SiC@C NCs) were one-step synthesized under a mixture atmosphere of Ar and CH₄ using a DC arc-discharge plasma method. The microstructure of the composites could be controlled by varying the volume ratio of Ar and CH₄. A strong response to the terahertz (THz) field was observed due to the existence of a graphite shell. The dielectric properties of SiC@C NCs can be enhanced by altering the thickness of the graphite shell. The thicker graphite shell results in a stronger absorption of THz waves and an enhanced real part of conductivity. Fitting the measured conductivity data using the Drude–Smith model reveals that the carrier transport in the SiC@C NCs and its counterpart, the SiC nanoparticles, is dominated by backscattering. The SiC@C NCs with enhanced conductivity are believed to be fundamental materials for various functionalized optoelectronic devices.

Water pollution is a global environmental problem that has attracted great concern, and functional carbon nanomaterials are widely used in water treatment. Here, to optimize the removal performance of both oil/organic matter and dye molecules, we fabricated porous and hydrophobic core–shell sponges by growing graphene on three-dimensional stacked copper nanowires. The interconnected pores between the one-dimensional nanocore–shells construct the porous channels within the sponge, and the multilayered graphene shells equip the sponge with a water contact angle over 120° even under acidic and alkaline environments, which enables fast and efficient cleanup of oil on or under the water. The core–shell sponge can absorb oil or organic solvents with densities 40–90 times its own, and its oil-sorption capacity is much larger than those of other porous materials like activated carbon and loofah. On the other hand, the adsorption behavior of the core–shell sponge to dyes including methyl orange (MO) and malachite green (MG), also common water pollutants, was also measured. Dynamic adsorption of MG under cyclic compression demonstrated a higher adsorption rate than that in the static state, and an acidic environment was favorable for the adsorption of MO molecules. Finally, the adsorption isotherm for MO molecules was analyzed and fitted with the Langmuir model, and the adsorption kinetics were studied in depth as well.

The use of polymeric additives supporting the growth of hybrid halide perovskites has proven to be a successful approach aiming at high quality active layers targeting optoelectronic exploitation. A detailed description of the complex process involving the self-assembly of the precursors into the perovskite crystallites in presence of the polymer is, however, still missing. Here we take starch:CH₃NH₃PbI₃ (MAPbI₃) as example of highly performing composite, both in solar cells and light emitting diodes, and study the film formation process through differential scanning calorimetry and in situ time-resolved grazing incidence wide-angle x-ray scattering, performed during spin coating. These measurements reveal that starch beneficially influences the nucleation and growth of the perovskite precursor phase, leading to improved structural properties of the resulting film which turns into higher stability towards environmental conditions.

Thermal interface material (TIM) is pivotal for the heat dissipation between layers of high-density electronic packaging. The most widely used TIMs are particle-filled composite materials, in which highly conductive particulate fillers are added into the polymer matrix to promote heat conduction. The numerical simulation of heat transfer in the composites is essential for the design of TIMs; however, the widely used finite element method (FEM) requires large memory and presents limited computational time for the composites with dense particles. In this work, a numerical homogenization algorithm based on fast Fourier transform was adopted to estimate the thermal conductivity of composites with randomly dispersed particles in 3D space. The unit cell problem is solved by means of a polarization-based iterative scheme, which can accelerate the convergence procedure regardless of the contrast between various components. The algorithm shows good precision and requires dramatically reduced computation time and cost compared with FEM. Moreover, the effect of the particle volume fraction, interface thermal resistance between particles (R-PP), interface thermal resistance between particle and matrix (R-PM), and particle size have been estimated. It turns out that the effective conductivity of the particulate composites increases sharply at a critical filler volume fraction, after which it is sensitive to the variation of filler loading. We can observe that the effective thermal conductivity of the composites with low filler volume fraction is sensitive to R-PM, whereas the it is governed by R-PP for the composites with high filler content. The algorithm presents excellent efficiency and accuracy, showing potential for the future design of highly thermally conductive TIMs.