Nanoscale Thermal Transport Research Articles

Molecular Simulations of Thermal Transport across Iron Oxide-Hydrocarbon Interfaces.

The rational design of dielectric fluids for immersion cooling of batteries requires a molecular-level understanding of the heat flow across the battery casing/dielectric fluid interface. Here, we use nonequilibrium molecular dynamics (NEMD) simulations to quantify the interfacial thermal resistance (ITR) between hematite and poly-α-olefin (PAO), which are representative of the outer surface of the steel battery casing and a synthetic hydrocarbon dielectric fluid, respectively. After identifying the most suitable force fields to model the thermal properties of the individual components, we then compared different solid-liquid interaction potentials for the calculation of the ITR. These potentials resulted in a wide range of ITR values (4-21 K m2 GW-1), with stronger solid-liquid interactions leading to lower ITR. The increase in ITR is correlated with an increase in density of the fluid layer closest to the surface. Since the ITR has not been experimentally measured for the hematite/PAO interface, we validate the solid-liquid interaction potential using the work of adhesion calculated using the dry-surface method. The work of adhesion calculations from the simulations were compared to those derived from experimental contact angle measurements for PAO on steel. We find that all of the solid-liquid potentials overestimate the experimental work of adhesion. The experiments and simulations can only be reconciled by further reducing the strength of the interfacial interactions. This suggests some screening of the solid-liquid interactions, which may be due to the presence of an interfacial water layer between PAO and steel in the contact angle experiments. Using the solid-liquid interaction potential that reproduces the experimental work of adhesion, we obtain a higher ITR (33 K m2 GW-1), suggesting inefficient thermal transport. The results of this study demonstrate the potential for NEMD simulations to improve understanding of the nanoscale thermal transport across industrially important interfaces. This study represents an important step toward the rational design of more effective fluids for immersion cooling systems for electric vehicles and other applications where thermal management is of high importance.

Nanoscale Heat Transport of Vertically Aligned Carbon Nanotube Bundles for Thermal Management Applications.

Electronic devices continue to shrink in size while increasing in performance, making excess heat dissipation challenging. Traditional thermal interface materials (TIMs) such as thermal grease and pads face limitations in thermal conductivity and stability, particularly as devices scale down. Carbon nanotubes (CNTs) have emerged as promising candidates for TIMs because of their exceptional thermal conductivity and mechanical properties. However, the thermal conductivity of CNT films decreases when integrated into devices due to defects and bundling effects. This study employs a novel cross-sectional approach combining high-vacuum scanning thermal microscopy (SThM) with beam-exit cross-sectional polishing (BEXP) to investigate the nanoscale morphology and thermal properties of vertically aligned CNT bundles at low and room temperatures. Using appropriate thermal transport models, we extracted effective thermal conductivities of the vertically aligned nanotubes and obtained 4 W m-1 K-1 at 200 K and 37 W m-1 K-1 at 300 K. Additionally, non-negligible lateral thermal conductance between CNT bundles suggests more complex heat transfer mechanisms in these structures. These findings provide unique insights into nanoscale thermal transport in CNT bundles, which is crucial for optimizing novel thermal management strategies.

Electronic interfacial thermal conductance between metal nano-films in sub-picosecond non-equilibrium transport process

Interfaces play a critical role in nanoscale thermal transport, and understanding thermal transport mechanisms across metal/metal interfaces at the non-equilibrium states is urgently needed for highly integrated electronic structures or devices. In this work, the electronic interfacial thermal conductance hee of two metal interfaces, Au/Pt and Au/Al, was measured by time domain thermoreflectance (TDTR) at the non-equilibrium states and an extended two-temperature model was applied to well describe the interactions of electrons between the metal films. For the Au/Pt structure, the measured hee is 4.4 ± 1.8 GWm−2K−1, which is consistent with the predicted value by the electronic diffuse mismatch model (DMM). While for the Au/Al structure, the measured hee (0.13±0.05 GWm−2K−1) is an order of magnitude smaller than that of Au/Pt and the predicted value of the electronic DMM. The results indicate that even the extremely thin oxide layer at the Au/Al interface can significantly hinder the electron thermal transport across the metal interface. Overall, our findings contribute to revealing the non-equilibrium interfacial thermal transport mechanisms and pave the way for designing the highly integrated electronic devices.

A three-probe method for accurate nanoscale thermal transport measurements

Measurements of transport phenomena are constantly plagued by contact resistance, prohibiting the sample's intrinsic electrical or thermal conductivity from being accurately determined. This predicament is particularly severe in thermal transport measurements due to the inability to meet similar impedance requirements for a four-probe method used in electrical resistance measurements. Here, we invent a three-probe measurement method that makes an accurate determination of thermal conductivity possible for nanomaterials. Incorporating electron beam heating provided by a scanning electron microscope (SEM) on a diffusive thermal conductor not only quantifies the thermal contact resistance, which may introduce an error of more than 270% to a sample's thermal conductivity, but also eliminates several device uncertainties that may contribute an additional 17% error in a measurement. The method also enables local temperature measurements, revealing nanoscale structural variations unfound by SEM. The high accuracy of the technique would make standardization of nanoscale thermal transport measurement possible.

Neural network architecture to optimize the nanoscale thermal transport of ternary magnetized Carreau nanofluid over 3D wedge

SignificanceIncorporation of nanoparticles in base fluid water is significant for analysis of thermal behavior of nanofluid mixtures, which has various applications in materials science and thermal engineering, and supervised neural scheme predicts the thermal behavior by solving Carreau nanofluid model. MotiveThis article brings the investigation related to prediction of thermal transport of a ternary magnetized hybrid nanofluid [(Al2O3, CuO, TiO2)/H2O] with a three-dimensional Carreau nanofluid model over a wedge. Three nanoparticles dispersed in water (H2O). Inclined magnetic field is considered for judgement of velocity profile and thermal radiation is utilized to scrutinize the temperature distribution of nanofluid. The Carreau mathematical model is chosen to depict the rheological characteristics of non-Newtonian fluids at very high and very low shear rate. MethodologyPhysical assumptions creates the system of Partial differential equations (PDEs) and these are converted into ordinary differential equations (ODEs) by similarity tool. Further ODEs are dealt with bvp4c scheme and further prediction of solution is made by Levenberg-Marquardt neural network (LM-NN) supervised neural scheme. FindingsIncreased volume friction coefficients of nanoparticles increases the transport of heat. High inclined magnetic effect, thermal radiation, pressure gradient and shear strain parameter predict higher thermal transport.

Impact of swift heavy ion-induced point defects on nanoscale thermal transport in ZnO

Near-surface nanoscale thermal conductivity (k) variation of ion-irradiated single-crystalline ZnO was studied by time-domain thermoreflectance. ZnO was irradiated by 710 MeV Bi swift heavy ions (SHI) in the 1010–1013 ion/cm2 fluence range to investigate the progression of radiation damage both from single ion impacts and ion path overlapping regimes. Structural characterization using X-ray diffraction, Raman spectroscopy, and transmission electron microscopy indicated the absence of amorphization. The degradation in kwas attributed primarily due to phonon scattering on point defects. The results of measured k were used to validate several models including the semi-analytical Klemens-Callaway model, and a novel hybrid modeling approach based on the Monte-Carlo code TREKIS coupled with molecular dynamics simulations which captures the effects of single ion and ion path overlapping regimes, respectively. The findings promote a novel approach to developing radiation-controlled thermally functional materials.

Nanoscale Thermal Transport in Vertical Gate-All-Around Junctionless Nanowire Transistors—Part I: Experimental Methods

Nanoscale Thermal Transport in Vertical Gate-All-Around Junctionless Nanowire Transistors—Part I: Experimental Methods

Nanoscale Thermal Transport in Vertical Gate- All-Around Junctionless Nanowire Transistors— Part II: Multiphysics Simulation

Nanoscale Thermal Transport in Vertical Gate- All-Around Junctionless Nanowire Transistors— Part II: Multiphysics Simulation

Physics-informed neural networks for solving time-dependent mode-resolved phonon Boltzmann transport equation

The phonon Boltzmann transport equation (BTE) is a powerful tool for modeling and understanding micro-/nanoscale thermal transport in solids, where Fourier’s law can fail due to non-diffusive effect when the characteristic length/time is comparable to the phonon mean free path/relaxation time. However, numerically solving phonon BTE can be computationally costly due to its high dimensionality, especially when considering mode-resolved phonon properties and time dependency. In this work, we demonstrate the effectiveness of physics-informed neural networks (PINNs) in solving time-dependent mode-resolved phonon BTE. The PINNs are trained by minimizing the residual of the governing equations, and boundary/initial conditions to predict phonon energy distributions, without the need for any labeled training data. The results obtained using the PINN framework demonstrate excellent agreement with analytical and numerical solutions. Moreover, after offline training, the PINNs can be utilized for online evaluation of transient heat conduction, providing instantaneous results, such as temperature distribution. It is worth noting that the training can be carried out in a parametric setting, allowing the trained model to predict phonon transport in arbitrary values in the parameter space, such as the characteristic length. This efficient and accurate method makes it a promising tool for practical applications such as the thermal management design of microelectronics.

Accelerating Quantum Materials Development with Advances in Transmission Electron Microscopy.

Quantum materials are driving a technology revolution in sensing, communication, and computing, while simultaneously testing many core theories of the past century. Materials such as topological insulators, complex oxides, superconductors, quantum dots, color center-hosting semiconductors, and other types of strongly correlated materials can exhibit exotic properties such as edge conductivity, multiferroicity, magnetoresistance, superconductivity, single photon emission, and optical-spin locking. These emergent properties arise and depend strongly on the material's detailed atomic-scale structure, including atomic defects, dopants, and lattice stacking. In this review, we describe how progress in the field of electron microscopy (EM), including in situ and in operando EM, can accelerate advances in quantum materials and quantum excitations. We begin by describing fundamental EM principles and operation modes. We then discuss various EM methods such as (i) EM spectroscopies, including electron energy loss spectroscopy (EELS), cathodoluminescence (CL), and electron energy gain spectroscopy (EEGS); (ii) four-dimensional scanning transmission electron microscopy (4D-STEM); (iii) dynamic and ultrafast EM (UEM); (iv) complementary ultrafast spectroscopies (UED, XFEL); and (v) atomic electron tomography (AET). We describe how these methods could inform structure-function relations in quantum materials down to the picometer scale and femtosecond time resolution, and how they enable precision positioning of atomic defects and high-resolution manipulation of quantum materials. For each method, we also describe existing limitations to solve open quantum mechanical questions, and how they might be addressed to accelerate progress. Among numerous notable results, our review highlights how EM is enabling identification of the 3D structure of quantum defects; measuring reversible and metastable dynamics of quantum excitations; mapping exciton states and single photon emission; measuring nanoscale thermal transport and coupled excitation dynamics; and measuring the internal electric field and charge density distribution of quantum heterointerfaces- all at the quantum materials' intrinsic atomic and near atomic-length scale. We conclude by describing open challenges for the future, including achieving stable sample holders for ultralow temperature (below 10K) atomic-scale spatial resolution, stable spectrometers that enable meV energy resolution, and high-resolution, dynamic mapping of magnetic and spin fields. With atomic manipulation and ultrafast characterization enabled by EM, quantum materials will be poised to integrate into many of the sustainable and energy-efficient technologies needed for the 21st century.

Insights into Thermal Transport through Molecular π-Stacking.

π-Stacking, which is a ubiquitous structural motif in assemblies of aromatic compounds, is well-known to provide a transport pathway for charge carriers and excitons, while its contribution to thermal transport is still unclear. Herein, based on detailed experimental observations of the thermal diffusivity, thermal conductivity, and specific heat of a single-crystalline triphenylene featuring a one-dimensionally π-stacked structure, we describe the nature of thermal transport through the π-stacked columns. We reveal that acoustic phonons are responsible for thermal transport through the π-stacked columns, which exhibit crystal-like behavior. Importantly, the thermal energy stored as intramolecular vibrations can also be transported by coupling to the acoustic phonons. In contrast, in the direction perpendicular to the π-stacked columns, an amorphous-like thermal transport behavior dominates. The present finding offers deep insight into nanoscale thermal transport in organic materials, where the constituent molecules exist as discrete entities linked together by weak intermolecular interactions.

Reduced-order model to predict thermal conductivity of dimensionally confined materials

Predicting nanoscale thermal transport in dielectrics requires models, such as the Boltzmann transport equation (BTE), that account for phonon boundary scattering in structures with complex geometries. Although the BTE has been validated against several key experiments, its computational expense limits its applicability. Here, we demonstrate the use of an analytic reduced-order model for predicting the thermal conductivity in dimensionally confined materials, i.e., monolithic and porous thin films, and rectangular and cylindrical nanowires. The approach uses the recently developed “Ballistic Correction Model,” which accounts for materials' full distribution of phonon mean-free-paths. The model is validated against BTE simulations for a selection of base materials, obtaining excellent agreement. By furnishing a precise yet easy-to-use prediction of thermal transport in nanostructures, our work strives to accelerate the identification of materials for energy-conversion and thermal-management applications.

Picosecond magneto-optic thermometry measurements of nanoscale thermal transport in AlN thin films

The thermal conductivity Λ of wide bandgap semiconductor thin films, such as AlN, affects the performance of high-frequency devices, power devices, and optoelectronics. However, accurate measurements of Λ in thin films with sub-micrometer thicknesses and Λ > 100 W m−1 K−1 is challenging. Widely used pump/probe metrologies, such as time–domain thermoreflectance (TDTR) and frequency–domain thermoreflectance, lack the spatiotemporal resolution necessary to accurately quantify thermal properties of sub-micrometer thin films with high Λ. In this work, we use a combination of magneto-optic thermometry and TiN interfacial layers to significantly enhance the spatiotemporal resolution of pump/probe thermal transport measurements. We use our approach to measure Λ of 100, 400, and 1000 nm AlN thin films. We coat AlN thin films with a ferromagnetic thin-film transducer with the geometry of (1 nm-Pt/0.4 nm-Co)x3/(2 nm-TiN). This PtCo/TiN transducer has a fast thermal response time of <50 ps, which allows us to differentiate between the thermal response of the transducer, AlN thin film, and substrate. For the 100, 400, and 1000 nm thick AlN films, we determine Λ to be 200 ± 80, 165 ± 35, and 300 ± 70 W m−1 K−1, respectively. We conclude with an uncertainty analysis that quantifies the errors associated with pump/probe measurements of thermal conductivity, as a function of transducer type, thin-film thermal conductivity, and thin-film thickness. Time resolved magneto-optic Kerr effect experiments can measure films that are three to five times thinner than is possible with standard pump/probe metrologies, such as TDTR. This advance in metrology will enable better characterization of nanoscale heat transfer in high thermal conductivity material systems like wide bandgap semiconductor heterostructures and devices.

A pre-time-zero spatiotemporal microscopy technique for the ultrasensitive determination of the thermal diffusivity of thin films.

Diffusion is one of the most ubiquitous transport phenomena in nature. Experimentally, it can be tracked by following point spreading in space and time. Here, we introduce a spatiotemporal pump-probe microscopy technique that exploits the residual spatial temperature profile obtained through the transient reflectivity when probe pulses arrive before pump pulses. This corresponds to an effective pump-probe time delay of 13ns, determined by the repetition rate of our laser system (76MHz). This pre-time-zero technique enables probing the diffusion of long-lived excitations created by previous pump pulses with nanometer accuracy and is particularly powerful for following in-plane heat diffusion in thin films. The particular advantage of this technique is that it enables quantifying thermal transport without requiring any material input parameters or strong heating. We demonstrate the direct determination of the thermal diffusivities of films with a thickness of around 15nm, consisting of the layered materials MoSe2 (0.18 cm2/s), WSe2 (0.20 cm2/s), MoS2 (0.35 cm2/s), and WS2 (0.59 cm2/s). This technique paves the way for observing nanoscale thermal transport phenomena and tracking diffusion of a broad range of species.

Computational study on the order-of-magnitude difference in thermal conductivity between graphene and graphane nanoribbons

The thermal properties of graphane, hydrogenated graphene, are surprisingly underreported, and there are commonly held opposing views on its thermal conductivity. While hydrogenation negatively affects the thermal conductivity, the exact nanoscale thermal transport properties of graphane are still poorly understood and the mechanisms involved remain obscure. The thermal transport properties of graphane nanoribbons were investigated theoretically by performing molecular dynamics simulations. The effect of hydrogenation degree was evaluated, and comparisons of thermal conductivity were carried out between graphene and graphane or between different forms of spatial isomerism. The order-of-magnitude difference in thermal conductivity between graphene and graphane ribbons was determined accordingly. The rule of mixtures was applied to provide the theoretical upper and lower bounds on the thermal conductivity. A theoretical analysis was made to assess the correlation between the thermal conductivity and the peak amplitude of out-of-plane vibration. The results indicated that graphane shows great promise for flexible tuning of thermal properties. The extent of hydrogenation admits a convenient chemical dial for tuning the thermal conductivity. The thermal conductivity of graphane isomers decreases successively in the order of the chair, boat, and stirrup configurations. The thermal conductivity of graphene and graphane differs by one order of magnitude or more, depending upon spatial isomerism and out-of-plane vibration amplitudes. For the stirrup configuration, the thermal conductivity is decreased by a factor of at least 20, and by about a factor of 10 when semi-hydrogenation occurs. The thermal conductivity of partially hydrogenated graphene can be predicted by applying the rule of mixtures. The results have significant implications for understanding of the relations between spatial isomerism and thermal properties.

Unwrapping a full temporal cycle in time domain thermoreflectance for enhanced measurement sensitivity in thermally insulating materials.

Time delayed pump-probe measurement techniques, such as Time Domain Thermoreflectance (TDTR), have opened up a wealth of opportunities for metrology at ultra-fast timescales and nanometer length scales. For nanoscale thermal transport measurements, typical thermal lifetimes used to measure thermal conductivity and thermal boundary conductance span from sub-picosecond to ∼6 nanoseconds. In this work, we demonstrate a simple rearrangement and validation of a configuration that allows access to the entire 12.5ns time delay available in the standard pulse train. By reconfiguring a traditional TDTR system so that the pump and probe arrive concurrently when the delay stage reaches its midpoint, followed by unwrapping the temporal scan, we obtain a dataset that is bounded only by the oscillator repetition rate. Sensitivity analysis along with conducted measurements shows that great increases in measurement sensitivity are available with this approach, particularly for thin films with low thermal conductivities.

Nanoscale Thermal Transport Model of Magnetic Tunnel Junction (MTJ) Device for STT-MRAM

Spin-transfer-torque magnetic random access memory (STT-MRAM) based on magnetic tunnel junction (MTJ) device has attracted significant attention from academics and industries. Nevertheless, the thermal effect under bias operation affects the overall performance and stability of a device. To evaluate the thermal phenomenon in MTJ devices accurately, the non-equilibrium effect between the electron and the phonon near the electrode-barrier interface cannot be ignored. The existence of the interface leads to additional thermal resistance hindering the heat conduction of tunnel junction. Therefore, an effective equivalent model concerning the interface effect is necessary to represent the heat transportation of the device. In this article, a nanoscale thermal transport model of the MTJ device is proposed. The influence of the thermal conductivity of the nano-oxide layer on the temperature distribution is discussed. The interface energy balance transport model is used to clarify the non-equilibrium relationship between the phonon and the electron at the CoFeB/MgO/CoFeB interfaces. A parameterization study is conducted to illustrate the temperature distribution in the nanoscale thermal transport model. Furthermore, the phonon-electron coupling distance ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\delta$ </tex-math></inline-formula> ) based on the thermal conductivity of the phonon ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\kappa _{p}$ </tex-math></inline-formula> ) and the electron ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\kappa _{e}$ </tex-math></inline-formula> ) of the device is implemented to construct the effective equivalent model using finite element modeling (FEM), which could realistically reflect the thermal transport under working conditions. The established equivalent model has a guiding role in exploring the thermal transportation in the nanoscale MTJ device.

Robust and high-sensitivity thermal probing at the nanoscale based on resonance Raman ratio (R3)

Raman spectroscopy-based temperature sensing usually tracks the change of Raman wavenumber, linewidth and intensity, and has found very broad applications in characterizing the energy and charge transport in nanomaterials over the last decade. The temperature coefficients of these Raman properties are highly material-dependent, and are subjected to local optical scattering influence. As a result, Raman-based temperature sensing usually suffers quite large uncertainties and has low sensitivity. Here, a novel method based on dual resonance Raman phenomenon is developed to precisely measure the absolute temperature rise of nanomaterial (nm WS2 film in this work) from 170 to 470 K. A 532 nm laser (2.33 eV photon energy) is used to conduct the Raman experiment. Its photon energy is very close to the excitonic transition energy of WS2 at temperatures close to room temperature. A parameter, termed resonance Raman ratio (R3) is introduced to combine the temperature effects on resonance Raman scattering for the A1g and E2g modes. Ω has a change of more than two orders of magnitude from 177 to 477 K, and such change is independent of film thickness and local optical scattering. It is shown that when Ω is varied by 1%, the temperature probing sensitivity is 0.42 K and 1.16 K at low and high temperatures, respectively. Based on Ω, the in-plane thermal conductivity (k) of a ∼25 nm-thick suspended WS2 film is measured using our energy transport state-resolved Raman (ET-Raman). k is found decreasing from 50.0 to 20.0 Wm−1 K−1 when temperature increases from 170 to 470 K. This agrees with previous experimental and theoretical results and the measurement data using our FET-Raman. The R3 technique provides a very robust and high-sensitivity method for temperature probing of nanomaterials and will have broad applications in nanoscale thermal transport characterization, non-destructive evaluation, and manufacturing monitoring.

Optimized Phonon Band Discretization Scheme for Efficiently Solving the Nongray Boltzmann Transport Equation

Abstract The phonon Boltzmann transport equation (BTE) is an important tool for studying the nanoscale thermal transport. Because phonons have a large spread in their properties, the nongray (i.e., considering different phonon bands) phonon BTE is needed to accurately capture the nanoscale transport phenomena. However, BTE solvers generally require large computational cost. Nongray modeling imposes significant additional complexity on the numerical simulations, which hinders the large-scale modeling of real nanoscale systems. In this work, we address this issue by a systematic investigation on the phonon band discretization scheme using real material properties of four representative materials, including silicon, gallium arsenide, diamond, and lead telluride. We find that the schemes used in previous studies require at least a few tens of bands to ensure the accuracy, which requires large computational costs. We then propose an improved band discretization scheme, in which we divide the mean free path domain into two subdomains, one on either side of the inflection point of the mean free path accumulated thermal conductivity, and adopt the Gauss–Legendre quadrature for each subdomain. With this scheme, the solution of the phonon BTE converges (error &amp;lt; 1%) with less than ten phonon bands for all these materials. The proposed scheme allows significantly reducing the time and memory consumption of the numerical BTE solver, which is an important step toward large-scale phonon BTE simulations for real materials.

Nanoscale limit of the thermal conductivity in crystalline silicon carbide membranes, nanowires, and phononic crystals

Silicon carbide (SiC) aims to be the number one material for power microelectronics due to its remarkable thermal properties. Recent progress in SiC technology finally enabled the fabrication of crystalline SiC nanostructures. Yet, the thermal properties of SiC at the nanoscale remain overlooked. Here, we systematically study heat conduction in SiC nanostructures, including nanomembranes, nanowires, and phononic crystals. Our measurements show that the thermal conductivity of nanostructures is several times lower than that in bulk and that the values scale proportionally to the narrowest dimension of the structures. In the smallest nanostructures, the thermal conductivity reached 10% of that in bulk. To better understand nanoscale thermal transport in SiC, we also probed phonon mean free path and coherent heat conduction in the nanostructures. Our theoretical model links the observed suppression of heat conduction with the surface phonon scattering, which limits the phonon mean free path and thus reduces the thermal conductivity. This work uncovers thermal characteristics of SiC nanostructures and explains their origin, thus enabling realistic thermal engineering in SiC microelectronics.