arXiv subjects

Junichiro Shiomi

Publications and source records attributed to Junichiro Shiomi.

At least 37 records · Page 2Linked to original sources

arXiv2022

RadonPy: Automated Physical Property Calculation using All-atom Classical Molecular Dynamics Simulations for Polymer Informatics

The rapid growth of data-driven materials research has made it necessary to develop systematically designed, open databases of material properties. However, there are few open databases for polymeric materials compared to other material systems such as inorganic crystals. To this end, we developed RadonPy, the world-first open-source Python library for fully automated all-atom classical molecular dynamics (MD) simulations. For a given polymer repeating unit, the entire process of molecular modeling, equilibrium and nonequilibrium MD calculations, and property calculations can be conducted fully automatically. In this study, 15 different properties, including the thermal conductivity, density, specific heat capacity, thermal expansion coefficients, and refractive index, were calculated for more than 1,000 unique amorphous polymers. The calculated properties were compared and validated systematically with experimental values from PoLyInfo. During the high-throughput data production, eight amorphous polymers with extremely high thermal conductivities, exceeding 0.4 W/mK, were identified, including six polymers with unreported thermal conductivities. These polymers were found to have a high density of hydrogen bonding units or rigid backbones. A decomposition analysis of the heat conduction, which is implemented in RadonPy, revealed the underlying mechanisms that yield a high thermal conductivity of the amorphous polymers: heat transfer via hydrogen bonds and dipole-dipole interactions between the polymer chains with their hydrogen bonding units or via the covalent bonds of the polymer backbone with high rigidity. The creation of massive amounts of computational property data using RadonPy will facilitate the development of polymer informatics, similar to how the emergence of the first-principles computational database for inorganic crystals had significantly advanced materials informatics.

cond-mat.mtrl-sci↗

arXiv2022

Phase-transition-induced giant Thomson effect for thermoelectric cooling

The Seebeck and Peltier effects have been widely studied and used in various thermoelectric technologies, including thermal energy harvesting and solid-state heat pumps. However, basic and applied studies on the Thomson effect, another fundamental thermoelectric effect in conductors, are limited despite the fact that the Thomson effect allows electronic cooling through the application of a temperature gradient bias rather than the construction of junction structures. In this article, we report the observation of a giant Thomson effect that appears owing to magnetic phase transitions. The Thomson coefficient of FeRh-based alloys reaches large values approaching $-$1,000 $μ$VK$^{-1}$ around room temperature because of the steep temperature dependence of the Seebeck coefficient associated with the antiferromagnetic-ferromagnetic phase transition. The Thomson coefficient is several orders of magnitude larger than the Seebeck coefficient of the alloys. Using the active thermography technique, we demonstrate that the Thomson cooling can be much larger than Joule heating in the same material even in a nearly steady state. The operation temperature of the giant Thomson effect in the FeRh-based alloys can be tuned over a wide range by applying an external magnetic field or by slightly changing the composition. Our findings provide a new direction in the materials science of thermoelectrics and pave the way for thermal management applications using the Thomson effect.

cond-mat.mtrl-sci↗

arXiv2021

Descriptors of intrinsic hydrodynamic thermal transport: screening a phonon database in a machine learning approach

Machine learning techniques are used to explore the intrinsic origins of the hydrodynamic thermal transport and to find new materials interesting for science and engineering. The hydrodynamic thermal transport is governed intrinsically by the hydrodynamic scale and the thermal conductivity. The correlations between these intrinsic properties and harmonic and anharmonic properties, and a large number of compositional (290) and structural (1224) descriptors of 131 crystal compound materials are obtained, revealing some of the key descriptors that determines the magnitude of the intrinsic hydrodynamic effects, most of them related with the phonon relaxation times. Then, a trained black-box model is applied to screen more than 5000 materials. The results identify materials with potential technological applications. Understanding the properties correlated to hydrodynamic thermal transport can help to find new thermoelectric materials and on the design of new materials to ease the heat dissipation in electronic devices.

cond-mat.mtrl-sci↗

arXiv2021

Machine Learning-Assisted Exploration of Thermally Conductive Polymers Based on High-Throughput Molecular Dynamics Simulations

Finding amorphous polymers with higher thermal conductivity is important, as they are ubiquitous in heat transfer applications. With recent progress in material informatics, machine learning approaches have been increasingly adopted for finding or designing materials with desired properties. However, relatively limited effort has been put into finding thermally conductive polymers using machine learning, mainly due to the lack of polymer thermal conductivity databases with reasonable data volume. In this work, we combine high-throughput molecular dynamics (MD) simulations and machine learning to explore polymers with relatively high thermal conductivity (> 0.300 W/m-K). We first randomly select 365 polymers from the existing PolyInfo database and calculate their thermal conductivity using MD simulations. The data are then employed to train a machine learning regression model to quantify the structure-thermal conductivity relation, which is further leveraged to screen polymer candidates in the PolyInfo database with thermal conductivity > 0.300 W/m-K. 133 polymers with MD-calculated thermal conductivity above this threshold are eventually identified. Polymers with a wide range of thermal conductivity values are selected for re-calculation under different simulation conditions, and those polymers found with thermal conductivity above 0.300 W/m-K are mostly calculated to maintain values above this threshold despite fluctuation in the exact values. A classification model is also constructed, and similar results were obtained compared to the regression model in predicting polymers with thermal conductivity above or below 0.300 W/m-K. The strategy and results from this work may contribute to automating the design of polymers with high thermal conductivity.

cond-mat.mtrl-sci↗

arXiv2021

A Novel Strategy for GaN-on-Diamond Device with a High Thermal Boundary Conductance

To achieve high device performance and high reliability for the gallium nitride (GaN)-based high electron mobility transistors (HEMTs), efficient heat dissipation is important but remains challenging. Enormous efforts have been made to transfer a GaN device layer onto a diamond substrate with a high thermal conductivity by bonding. In this work, two GaN-diamond bonded composites are prepared via modified surface activated bonding (SAB) at room temperature with silicon interlayers of different thicknesses (15 nm and 22 nm). Before and after post-annealing process at 800 oC, thermal boundary conductance (TBC) across the bonded interface including the interlayer and the stress of GaN layer are investigated by time-domain thermoreflectance and Raman spectroscopy, respectively. After bonding, the 15 nm Si interlayer achieved a higher TBC. The post-annealing significantly increased the TBC of both interfaces, while the TBC of 22 nm silicon interlayer increased greater and became higher than that of 15 nm. Detailed investigation of the microstructure and composition of the interfaces were carried out to understand the difference in interfacial thermal conduction. The obtained stress was no more than 230 MPa for both before and after the annealing, and this high thermal stability of the bonded composites indicates that the room temperature bonding can realize a GaN-on-diamond template suitable for further epitaxial growth or device process. This work brings a novel strategy of SAB followed by high-temperature annealing to fabricate a GaN-on-diamond device with a high TBC.

physics.app-ph↗

arXiv2021

Modulation of interfacial thermal transport between fumed silica nanoparticles by surface chemical functionalization for advanced thermal insulation

Since solid-state heat transport in a highly porous nanocomposite strongly depends on the thermal boundary conductance (TBC) between constituent nanomaterials, further suppression of the TBC is important for improving performance of thermal insulators. Here, targeting a nanocomposite fabricated by stamping fumed silica nanoparticles, we perform a wide variety of surface functionalization on fumed silica nanoparticles by silane coupling method and investigate the impact on the thermal conductivity (Km). The Km of the silica nanocomposite is approximately 20 and 9 mW/m/K under atmospheric and vacuum condition at the material density of 0.2 g/cm3 without surface functionalization, respectively, and the experimental results indicate that the Km can be modulated depending on the chemical structure of molecules. The surface modification with a linear alkyl chain of optimal length significantly suppresses Km by approximately 30%, and the suppression can be further enhanced to approximately 50% with the infrared opacifier. The magnitude of suppression was found to sensitively depend on the length of terminal chain. The magnitude is also related to the number of reactive silanol groups in the chemical structure, where the surface modification with fluorocarbon gives the largest suppression. The surface hydrophobization merits thermal insulation through significant suppression of the TBC, presumably by reducing the water molecules that otherwise would serve as heat conduction channels at the interface. On the other hand, when the chain length is long, the suppression is counteracted by the enhanced phonon transmission through the silane coupling molecules that grows with the chain length. This is supported by the analytical model and present simulation results, leading to predict the optimal chemical structure for better thermal insulation.

physics.app-ph↗

arXiv2021

Anisotropic Thermal Conductivity Measurement of Organic Thin Film with Bidirectional 3omega Method

Organic thin film materials with molecular ordering are gaining attention as they exhibit semiconductor characteristics. When using them for electronics, the thermal management becomes important, where heat dissipation is directional owning to the anisotropic thermal conductivity arising from the molecular ordering. However, it is difficult to evaluate the anisotropy by simultaneously measuring in-plane and cross-plane thermal conductivities of the film on a substrate, because the film is typically as thin as tens to hundreds of nanometers and its in-plane thermal conductivity is low. Here, we develop a novel bidirectional 3ω system that measures the anisotropic thermal conductivity of thin films by patterning two metal wires with different widths and preparing the films on top, and extracting the in-plane and cross-plane thermal conductivities using the difference in their sensitivities to the metal-wire width. Using the developed system, the thermal conductivity of spin-coated poly(3,4-ethylenedioxythiophene) olystyrene sulfonate (PEDOT:PSS) with thickness of 70 nm was successfully measured. The measured in-plane thermal conductivity of PEDOT:PSS film was as high as 2.9 W m-1 K-1 presumably due to the high structural ordering, giving anisotropy of 10. The calculations of measurement sensitivity to the film thickness and thermal conductivities suggest that the device can be applied to much thinner films by utilizing metal wires with smaller width.

physics.ins-det↗

arXiv2021

Electronic transport descriptors for the rapid screening of thermoelectric materials

The discovery of novel materials for thermoelectric energy conversion has potential to be accelerated by data-driven screening combined with high-throughput calculations. One way to increase the efficacy of successfully choosing a candidate material is through its evaluation using transport descriptors. Using a data-driven screening, we selected 12 potential candidates in the trigonal ABX2 family, followed by charge transport property simulations from first principles. The results suggest that carrier scattering processes in these materials are dominated by ionised impurities and polar optical phonons, contrary to the oft-assumed acoustic-phonon-dominated scattering. Combined with calculations of thermal conductivity based on three-phonon scattering, we predict p-type AgBiS2 and TlBiTe2 as potential high-performance thermoelectrics in the intermediate temperature range for low grade waste heat harvesting, with a predicted zT above 1 at 500 K. Using these data, we further derive ground-state transport descriptors for the carrier mobility and the thermoelectric power factor. In addition to low carrier mass, high dielectric constant was found to be an important factor towards high carrier mobility. A quadratic correlation between dielectric constant and transport performance was established and further validated with literature. Looking ahead, dielectric constant can potentially be exploited as an independent tuning knob for improving the thermoelectric performance.

cond-mat.mtrl-sci↗

arXiv2021

Scalable monolayer-functionalized nanointerface for thermal conductivity enhancement in copper/diamond composite

Aiming at developing high thermal conductivity copper/diamond composite, an unconventional approach applying self-assembled monolayer (SAM) prior to the high-temperature sintering of copper/diamond composite was utilized to enhance the thermal boundary conductance (TBC) between copper and diamond. The enhancement was first systematically confirmed on a model interface system by detailed SAM morphology characterization and TBC measurements. TBC significantly depends on the SAM coverage and ordering, and the formation of high-quality SAM promoted the TBC to 73 MW/m^2-K from 27 MW/m^2-K, the value without SAM. With the help of molecular dynamics simulations, the TBC enhancement was identified to be determined by the number of SAM bridges and the overlap of vibrational density of states. The diamond particles of 210 {\micro\metre} in size were simultaneously functionalized by SAM with the condition giving the highest TBC in the model system and sintered together with the copper to fabricate isotropic copper/diamond composite of 50% volume fraction. The measured thermal conductivity marked 711 W/m-K at room temperature, the highest value among the ones with similar diamond-particles volume fraction and size. This work demonstrates a novel strategy to enhance the thermal conductivity of composite materials by SAM functionalization.

cond-mat.mtrl-sci↗

arXiv2020

Above-room-temperature giant thermal conductivity switching in spintronic multilayer

Thermal switching provides an effective way for active heat flow control, which has recently attracted increasing attention in terms of nanoscale thermal management technologies. In magnetic and spintronic materials, the thermal conductivity depends on the magnetization configuration: this is the magneto-thermal resistance effect. Here we show that an epitaxial Cu/Co$_{50}$Fe$_{50}$ multilayer film exhibits giant magnetic-field-induced modulation of the cross-plane thermal conductivity. The magneto-thermal resistance ratio for the Cu/Co$_{50}$Fe$_{50}$ multilayer reaches 150% at room temperature, which is much larger than the previous record high. Although the ratio decreases with increasing the temperature, the giant magneto-thermal resistance effect of ~100% still appears up to 400 K. The magnetic field dependence of the thermal conductivity of the Cu/Co$_{50}$Fe$_{50}$ multilayer was observed to be about twice greater than that of the cross-plane electrical conductivity. The observation of the giant magneto-thermal resistance effect clarifies a potential of spintronic multilayers as thermal switching devices.

cond-mat.mtrl-sci↗

arXiv2020

Heat diffusion related damping process in highly precise coarse-grained model for SWCNT's nonlinearity

Second sound and heat diffusion in single-walled carbon nanotubes (SWCNT) is well-known phenomena which is related to the high thermal conductivity of this material. In this paper, we have shown that the heat diffusion along the tube axis affects the macroscopic motion of SWCNT and adapting this phenomena to coarse-grained model can improve the precision of the coarse-grained molecular dynamics (CGMD) exceptionally. The nonlinear macroscopic motion of SWCNT in the free thermal vibration condition in adiabatic environment is demonstrated in the most simplified version of CG modeling as maintaining finite temperature and total energy with suggested dissipation process derived from internal heat diffusion. The internal heat diffusion related to the cross correlated momentum from different potential energy functions is considered, and it can reproduce the nonlinear dynamic nature of SWCNTs without external thermostatting in CG model. Memory effect and thermostat with random noise distribution are not included, and the effect of heat diffusion on memory effect is reviewed through Mori-Zwanzig formalism. This diffusion shows perfect syncronization of the motion between that of CGMD and MD simulation, which is started with initial conditions from the molecular dynamics (MD) simulation. The heat diffusion related to this process has shown the same dispersive characteristics to second wave in SWCNT. This replication with good precision indicates that the internal heat diffusion process is the essential cause of the nonlinearity of the tube. The nonlinear dynamic characteristics from the various scale of simple beads systems are examined with expanding its time step and node length simultaneously.

cond-mat.soft↗

arXiv2020

Akhiezer Mechanism Dominates Relaxation of Propagons in Amorphous at Room Temperature

Propagons play an important role in tuning the thermal conductivity of nanostructured amorphous materials. Although advances have been made to quantitatively evaluate the relaxation time of propagons with molecular dynamics, the underlying relaxation mechanism remains unexplored. Here, we investigate the relaxation process of propagons in amorphous silicon, amorphous silica, and amorphous silicon nitride at room temperature in terms of Akhiezer model, the parameters of which were evaluated by performing lattice dynamics and molecular dynamics analysis. The results show that the Akhiezer model can well reproduce experimental results obtained by various kinds of measurement methods, indicating that Akhiezer mechanism dominates the relaxation process of propagons at room temperature. Moreover, we show that the appropriate sound speed of propagons is around 80% of the Debye sound speed and comparable to that of the sound speed of the transversal modes. We also reveal that the contribution of diffusons to the total thermal conductivity of these amorphous is similar, which is around 1 W/m K, while the contribution of propagons varies significantly depending on the materials, which is 30% in amorphous silicon and silica but can be as high as 70% in amorphous silicon nitride.

cond-mat.mes-hall↗

arXiv2020

Two-Path Phonon-Interference Resonance Induces a Stop Band in Silicon Crystal Matrix by Embedded Nanoparticles Array

In this work, we report a new stop-band formation mechanism by performing the atomistic Green's function calculation and the wave-packet molecular dynamics simulation for a system with germanium-nanoparticle array embedded in a crystalline silicon matrix. When only a single nanoparticle is embedded, the local resonance, induced through destructive interference between two different phonon wave paths, gives rise to several sharp and significant transmittance dips. On the other hand, when the number of embedded nanoparticles further increases to ten, a stop band with complete phonon reflection is formed due to the two-path resonance Bragg-like phonon interference. The wave packet simulations further uncover that the stop band originates from the collective phonon resonances at the embedded nanoparticles. Compared with the traditional stop-band formation mechanism that is the single-path Bragg reflection, the resonance mechanism has a significant advantage in not requiring the strict periodicity in the embedded nanoparticles array. We also demonstrate that the stop band can significantly suppress thermal conductance in the low-frequency regime. Our work provides a robust, scalable. and easily modulable stop-band formation mechanism. which opens a new degree of freedom for phononics-related heat control.

cond-mat.mtrl-sci↗

arXiv2020

Machine learning analysis of tunnel magnetoresistance of magnetic tunnel junctions with disordered MgAl2O4

Through Bayesian optimization and the least absolute shrinkage and selection operator (LASSO) technique combined with first-principles calculations, we investigated the tunnel magnetoresistance (TMR) effect of Fe/disordered-MgAl2O4(MAO)/Fe(001) magnetic tunnel junctions (MTJs) to determine structures of disordered-MAO that give large TMR ratios. The optimal structure with the largest TMR ratio was obtained by Bayesian optimization with 1728 structural candidates, where the convergence was reached within 300 structure calculations. Characterization of the obtained structures suggested that the in-plane distance between two Al atoms plays an important role in determining the TMR ratio. Since the Al-Al distance of disordered MAO significantly affects the imaginary part of complex band structures, the majority-spin conductance of the Δ1 state in Fe/disordered-MAO/Fe MTJs increases with increasing in-plane Al-Al distance, leading to larger TMR ratios. Furthermore, we found that the TMR ratio tended to be large when the ratio of the number of Al, Mg, and vacancies in the [001] plane was 2:1:1, indicating that the control of Al atomic positions is essential to enhancing the TMR ratio in MTJs with disordered MAO. The present work reveals the effectiveness and advantage of material informatics combined with first-principles transport calculations in designing high-performance spintronic devices based on MTJs.

cond-mat.mtrl-sci↗

arXiv2019

Observation of anomalous Ettingshausen effect and large transverse thermoelectric conductivity in permanent magnets

This study focuses on the potential of permanent magnets as thermoelectric converters. It is found that a SmCo$_5$-type magnet exhibits the large anomalous Ettingshausen effect (AEE) at room temperature and that its charge-to-heat current conversion coefficient is more than one order of magnitude greater than that of typical ferromagnetic metals. The large AEE is an exclusive feature of the SmCo$_5$-type magnet among various permanent magnets in practical use, which is independent of the conventional performance of magnets based on static magnetic properties. The experimental results show that the large AEE originates from the intrinsic transverse thermoelectric conductivity of SmCo$_5$. This finding makes a connection between permanent magnets and thermal energy engineering, providing the basis for creating "thermoelectric permanent magnets."

cond-mat.mtrl-sci↗

arXiv2019

One-directional thermal transport in densely aligned single-wall carbon nanotube films

Individual carbon nanotubes (CNTs) possess extremely high thermal conductivities. However, the thermal conductivities and their anisotropy of macroscopic assemblies of CNTs have so far remained small. Here, we report results of directional thermal transport measurements on a nearly-perfectly aligned CNT film fabricated via controlled vacuum filtration. We found the thermal conductivity to be 43 +- 2.2 W m^-1 K^-1 with a record-high thermal anisotropy of 500. From the temperature dependence of the thermal conductivity and its agreement with the atomistic phonon transport calculation, we conclude that the effect of intertube thermal resistance on heat conduction in the alignment direction is negligible because of the large contact area between CNTs. These observations thus represent ideal unidirectional thermal transport, i.e., the thermal conductivity of the film is determined solely by that of individual CNTs.

physics.app-ph↗

arXiv2019

Exploring diamond-like lattice thermal conductivity crystals via feature-based transfer learning

Ultrahigh lattice thermal conductivity materials hold great importance since they play a critical role in the thermal management of electronic and optical devices. Models using machine learning can search for materials with outstanding higher-order properties like thermal conductivity. However, the lack of sufficient data to train a model is a serious hurdle. Herein we show that big data can complement small data for accurate predictions when lower-order feature properties available in big data are selected properly and applied to transfer learning. The connection between the crystal information and thermal conductivity is directly built with a neural network by transferring descriptors acquired through a pre-trained model for the feature property. Successful transfer learning shows the ability of extrapolative prediction and reveals descriptors for lattice anharmonicity. Transfer learning is employed to screen over 60000 compounds to identify novel crystals that can serve as alternatives to diamond.

cond-mat.mtrl-sci↗

arXiv2019

High Thermal Boundary Conductance across Bonded Heterogeneous GaN-SiC Interfaces

GaN-based HEMTs have the potential to be widely used in high-power and high-frequency electronics while their maximum output powers are limited by high channel temperature induced by near-junction Joule-heating, which degrades device performance and reliability. Increasing the TBC between GaN and SiC will aid in the heat dissipation of GaN-on-SiC power devices, taking advantage of the high thermal conductivity of the SiC substrate. However, a good understanding of the TBC of this technically important interface is still lacking due to the complicated nature of interfacial heat transport. In this work, a lattice-mismatch-insensitive surface activated bonding method is used to bond GaN directly to SiC and thus eliminating the AlN layer altogether. This allows for the direct integration of high quality GaN layers with SiC to create a high thermal boundary conductance interface. TDTR is used to measure the thermal properties of the GaN thermal conductivity and GaN-SiC TBC. The measured GaN thermal conductivity is larger than that of GaN grown by MBE on SiC, showing the impact of reducing the dislocations in the GaN near the interface. High GaN-SiC TBC is observed for the bonded GaN-SiC interfaces, especially for the annealed interface whose TBC (230 MW/m2-K) is close to the highest values ever reported. To understand the structure-thermal property relation, STEM and EELS are used to characterize the interface structure. The results show that, for the as-bonded sample, there exists an amorphous layer near the interface for the as bonded samples. This amorphous layer is crystallized upon annealing, leading to the high TBC found in our work. Our work paves the way for thermal transport across bonded interfaces, which will impact real-world applications of semiconductor integration and packaging.

physics.app-ph↗