Module-Level Polaritonic Thermophotovoltaic Emitters via Hierarchical Sequential Learning.

Thermophotovoltaic (TPV) generators provide continuous and high-efficiency power output by utilizing local thermal emitters to convert energy from various sources to thermal radiation matching the bandgaps of photovoltaic cells. Lack of effective guidelines for thermal emission control at high temperatures, poor thermal stability, and limited fabrication scalability are the three key challenges for the practical deployment of TPV devices. Here we develop a hierarchical sequential-learning optimization framework and experimentally realize a 6″ module-scale polaritonic thermal emitter with bandwidth-controlled thermal emission as well as excellent thermal stability at 1473 K. The 300 nm bandwidth thermal emission is realized by a complex photon polariton based on the superposition of Tamm plasmon polariton and surface plasmon polariton. We experimentally achieve a spectral efficiency of 65.6% (wavelength range of 0.4-8 µm) with statistical deviation less than 4% over the 6″ emitter, demonstrating industrial-level reliability for module-scale TPV applications.

Quantitative Description of Bubble Formation in Response to Electrolyte Engineering.

The green hydrogen economy is expected to play a crucial role in carbon neutrality, but industrial-scale water electrolysis requires improvements in efficiency, operation costs, and capital costs before broad deployment. Electrolysis operates at a high current density and involves the substantial formation of gaseous products from the electrode surfaces to the electrolyte, which may lead to additional resistance and a resulting loss of efficiency. A detailed clarification of the bubble departure phenomena against the electrode surface and the surrounding electrolytes is needed to further control bubbles in a water electrolyzer. This study clarifies how electrolyte properties affect the measured bubble detachment sizes from the comparisons with analytical expressions and dynamic simulations. Bubble behavior in various electrolyte solutions and operating conditions was described using various physical parameters. A quantitative relationship was then established to connect electrolyte properties and bubble departure diameters, which can help regulate the bubble management through electrolyte engineering.

Enhanced High Thermal Conductivity Cellulose Filaments via Hydrodynamic Focusing.

Nanocellulose is regarded as a green and renewable nanomaterial that has attracted increased attention. In this study, we demonstrate that nanocellulose materials can exhibit high thermal conductivity when their nanofibrils are highly aligned and bonded in the form of filaments. The thermal conductivity of individual filaments, consisting of highly aligned cellulose nanofibrils, fabricated by the flow-focusing method is measured in dried condition using a T-type measurement technique. The maximum thermal conductivity of the nanocellulose filaments obtained is 14.5 W/m-K, which is approximately five times higher than those of cellulose nanopaper and cellulose nanocrystals. Structural investigations suggest that the crystallinity of the filament remarkably influence their thermal conductivity. Smaller diameter filaments with higher crystallinity, that is, more internanofibril hydrogen bonds and less intrananofibril disorder, tend to have higher thermal conductivity. Temperature-dependence measurements also reveal that the filaments exhibit phonon transport at effective dimension between 2D and 3D.

Tuning phonon transport spectrum for better thermoelectric materials.

The figure of merit of thermoelectric materials can be increased by suppressing the lattice thermal conductivity without degrading electrical properties. Phonons are the carriers for lattice thermal conduction, and their transport can be impeded by nanostructuring, owing to the recent progress in nanotechnology. The key question for further improvement of thermoelectric materials is how to realize ultimate structure with minimum lattice thermal conductivity. From spectral viewpoint, this means to impede transport of phonons in the entire spectral domain with noticeable contribution to lattice thermal conductivity that ranges in general from subterahertz to tens of terahertz in frequency. To this end, it is essential to know how the phonon transport varies with the length scale, morphology, and composition of nanostructures, and how effects of different nanostructures can be mutually adopted in view of the spectral domain. Here we review recent advances in analyzing such spectral impedance of phonon transport on the basis of various effects including alloy scattering, boundary scattering, and particle resonance.

Thermal Boundary Conductance Across Heteroepitaxial ZnO/GaN Interfaces: Assessment of the Phonon Gas Model.

We present experimental measurements of the thermal boundary conductance (TBC) from 78-500 K across isolated heteroepitaxially grown ZnO films on GaN substrates. This data provides an assessment of the underlying assumptions driving phonon gas-based models, such as the diffuse mismatch model (DMM), and atomistic Green's function (AGF) formalisms used to predict TBC. Our measurements, when compared to previous experimental data, suggest that TBC can be influenced by long wavelength, zone center modes in a material on one side of the interface as opposed to the '"vibrational mismatch"' concept assumed in the DMM; this disagreement is pronounced at high temperatures. At room temperature, we measure the ZnO/GaN TBC as 490[+150,-110] MW m-2 K-1. The disagreement among the DMM and AGF, and the experimental data at elevated temperatures, suggests a non-negligible contribution from other types of modes that are not accounted for in the fundamental assumptions of these harmonic based formalisms, which may rely on anharmonicity. Given the high quality of these ZnO/GaN interfaces, these results provide an invaluable, critical, and quantitative assessment of the accuracy of assumptions in the current state of the art computational approaches used to predict phonon TBC across interfaces.

Modulation of thermal and thermoelectric transport in individual carbon nanotubes by fullerene encapsulation.

The potential impact of encapsulated molecules on the thermal properties of individual carbon nanotubes (CNTs) has been an important open question since the first reports of the strong modulation of electrical properties in 2002. However, thermal property modulation has not been demonstrated experimentally because of the difficulty of realizing CNT-encapsulated molecules as part of thermal transport microstructures. Here we develop a nanofabrication strategy that enables measurement of the impact of encapsulation on the thermal conductivity (κ) and thermopower (S) of single CNT bundles that encapsulate C 60, Gd@C 82 and Er 2@C 82. Encapsulation causes 35-55% suppression in κ and approximately 40% enhancement in S compared with the properties of hollow CNTs at room temperature. Measurements of temperature dependence from 40 to 320 K demonstrate a shift of the peak in the κ to lower temperature. The data are consistent with simulations accounting for the interaction between CNTs and encapsulated fullerenes.

Ultimate Confinement of Phonon Propagation in Silicon Nanocrystalline Structure.

Temperature-dependent thermal conductivity of epitaxial silicon nanocrystalline (SiNC) structures composed of nanometer-sized grains separated by ultrathin silicon-oxide (SiO_{2}) films (∼0.3 nm) is measured by the time domain thermoreflectance technique in the range from 50 to 300 K. The thermal conductivity of SiNC structures with a grain size of 3 and 5 nm is anomalously low at the entire temperature range, significantly below the values of bulk amorphous Si and SiO_{2}. The phonon gas kinetic model, with intrinsic transport properties obtained by first-principles-based anharmonic lattice dynamics and phonon transmittance across ultrathin SiO_{2} films obtained by atomistic Green's function, reproduces the measured thermal conductivity without any fitting parameters. The analysis reveals that mean free paths of acoustic phonons in the SiNC structures are equivalent or even below half the phonon wavelength, i.e., the minimum thermal conductivity scenario. The result demonstrates that the nanostructures with extremely small length scales and a controlled interface can give rise to ultimate classical confinement of thermal phonon propagation.

MDTS: automatic complex materials design using Monte Carlo tree search.

Complex materials design is often represented as a black-box combinatorial optimization problem. In this paper, we present a novel python library called MDTS (Materials Design using Tree Search). Our algorithm employs a Monte Carlo tree search approach, which has shown exceptional performance in computer Go game. Unlike evolutionary algorithms that require user intervention to set parameters appropriately, MDTS has no tuning parameters and works autonomously in various problems. In comparison to a Bayesian optimization package, our algorithm showed competitive search efficiency and superior scalability. We succeeded in designing large Silicon-Germanium (Si-Ge) alloy structures that Bayesian optimization could not deal with due to excessive computational cost. MDTS is available at https://github.com/tsudalab/MDTS.

Thermoelectric Power of a Single van der Waals Interface between Carbon Nanotubes.

Control of van der Waals interfaces is crucial for fabrication of nanomaterial-based high-performance thermoelectric devices because such interfaces significantly affect the overall thermoelectric performances of the device due to their relatively high thermal resistance. Such interfaces could induce different thermoelectric power from the bulk, i.e., interfacial thermoelectric power. However, from a macroscopic point of view, a correct evaluation of the interfacial thermoelectric power is difficult owing to various interface configurations. Therefore, the study of the thermoelectric properties at a single interface is crucial to address this problem. Herein, we used in situ transmission electron microscopy and nanomanipulation to investigate the thermoelectric properties of carbon nanotubes and their interfaces. The thermoelectric power of the bridged carbon nanotubes was individually measured. The existence of the interfacial thermoelectric power was determined by systematically changing the contact size between the two parallel nanotubes. The effect of interfacial thermoelectric power was qualitatively supported by Green's function calculations. When the contact length between two parallel nanotubes was less than approximately 100 nm, the experimental results and theoretical calculations indicated that the interface significantly contributed to the total thermoelectric power. However, when the contact length was longer than approximately 200 nm, the total thermoelectric power converged to the value of a single nanotube. The findings herein provide a basis for investigating thermoelectric devices with controlled van der Waals interfaces and contribute to thermal management in nanoscale devices and electronics.

Anisotropic Thermal Conductivity Enhancement of the Aligned Metal-Organic Framework under Water Vapor Adsorption.

Metal-organic frameworks (MOFs) exhibit high adsorption and catalytic activities for various gas species. Because gas adsorption can cause a temperature increase in the MOF, which decreases the capacity and adsorption rate, a strict evaluation of its effect on the thermal conductivity of MOFs is essential. In this study, the thermal conductivity measurement of the MOF under water vapor adsorption was performed using an oriented film of copper tetrakis(4-carboxyphenyl)porphyrin (Cu-TCPP) MOF. A recently developed bidirectional 3ω method enabled the anisotropic thermal conductivity measurement of layered Cu-TCPP while maintaining its ordered structure. The water adsorption was found to increase the thermal conductivity in both in-plane and cross-plane directions with different trends and magnitudes, owing to the structural anisotropy. Molecular dynamics simulations suggest that additional vibrational modes provided by the adsorbed water molecules were the reason for the thermal conductivity enhancement.

Ultrahigh-efficient material informatics inverse design of thermal metamaterials for visible-infrared-compatible camouflage.

Multispectral camouflage technologies, especially in the most frequently-used visible and infrared (VIS-IR) bands, are in increasing demand for the ever-growing multispectral detection technologies. Nevertheless, the efficient design of proper materials and structures for VIS-IR camouflage is still challenging because of the stringent requirement for selective spectra in a large VIS-IR wavelength range and the increasing demand for flexible color and infrared signal adaptivity. Here, a material-informatics-based inverse design framework is proposed to efficiently design multilayer germanium (Ge) and zinc sulfide (ZnS) metamaterials by evaluating only ~1% of the total candidates. The designed metamaterials exhibit excellent color matching and infrared camouflage performance from different observation angles and temperatures through both simulations and infrared experiments. The present material informatics inverse design framework is highly efficient and can be applied to other multi-objective optimization problems beyond multispectral camouflage.

General deep learning framework for emissivity engineering.

Wavelength-selective thermal emitters (WS-TEs) have been frequently designed to achieve desired target emissivity spectra, as a typical emissivity engineering, for broad applications such as thermal camouflage, radiative cooling, and gas sensing, etc. However, previous designs require prior knowledge of materials or structures for different applications and the designed WS-TEs usually vary from applications to applications in terms of materials and structures, thus lacking of a general design framework for emissivity engineering across different applications. Moreover, previous designs fail to tackle the simultaneous design of both materials and structures, as they either fix materials to design structures or fix structures to select suitable materials. Herein, we employ the deep Q-learning network algorithm, a reinforcement learning method based on deep learning framework, to design multilayer WS-TEs. To demonstrate the general validity, three WS-TEs are designed for various applications, including thermal camouflage, radiative cooling and gas sensing, which are then fabricated and measured. The merits of the deep Q-learning algorithm include that it can (1) offer a general design framework for WS-TEs beyond one-dimensional multilayer structures; (2) autonomously select suitable materials from a self-built material library and (3) autonomously optimize structural parameters for the target emissivity spectra. The present framework is demonstrated to be feasible and efficient in designing WS-TEs across different applications, and the design parameters are highly scalable in materials, structures, dimensions, and the target functions, offering a general framework for emissivity engineering and paving the way for efficient design of nonlinear optimization problems beyond thermal metamaterials.

Diameter controlled chemical vapor deposition synthesis of single-walled carbon nanotubes.

In this study, we systematically investigated the influence of catalyst preparation procedures on the mean diameter of single-walled carbon nanotubes (SWNTs) synthesized by the alcohol catalytic chemical vapor deposition (ACCVD) process. It was found that the SWNT diameter is dependent upon both reduction temperature and time, with lower reduction temperature and/or shorter reduction time resulting in smaller diameter SWNTs. The morphology of the SWNTs also changed from vertically aligned to randomly oriented when the reduction temperature was below 500 degrees C. We also found that introducing a small amount of water during the catalyst reduction stage significantly decreased the mean diameter of the SWNTs. Lastly, we report on the use of a new binary catalyst system in which rhodium was combined with cobalt. This new Co/Rh combination produced SWNTs of smaller diameter than the conventional Co/Mo catalyst.

Vibration sorting of small droplets on hydrophilic surface by asymmetric contact-line friction.

Droplet spreading and transport phenomenon is ubiquitous and has been studied by engineered surfaces with a variety of topographic features. To obtain a directional bias in dynamic wetting, hydrophobic surfaces with a geometrical asymmetry are generally used, attributing the directionality to one-sided pinning. Although the pinning may be useful for directional wetting, it usually limits the droplet mobility, especially for small volumes and over wettable surfaces. Here, we demonstrate a pinning-less approach to rapidly transport millimeter sized droplets on a partially wetting surface. Placing droplets on an asymmetrically structured surfaces with micron-scale roughness and applying symmetric horizontal vibration, they travel rapidly in one direction without pinning. The key, here, is to generate capillary-driven rapid contact-line motion within the time-scale of period of vibration. At the right regime where a friction factor local at the contact line dominates the rapid capillary motion, the asymmetric surface geometry can induce smooth and continuous contact-line movement back and forth at different speed, realizing directional motion of droplets even with small volumes over the wettable surface. We found that the translational speed is selective and strongly dependent on the droplet volume, oscillation frequency, and surface pattern properties, and thus droplets with a specific volume can be efficiently sorted out.

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.

Ultrafast water permeation through nanochannels with a densely fluorous interior surface.

Ultrafast water permeation in aquaporins is promoted by their hydrophobic interior surface. Polytetrafluoroethylene has a dense fluorine surface, leading to its strong water repellence. We report a series of fluorous oligoamide nanorings with interior diameters ranging from 0.9 to 1.9 nanometers. These nanorings undergo supramolecular polymerization in phospholipid bilayer membranes to form fluorous nanochannels, the interior walls of which are densely covered with fluorine atoms. The nanochannel with the smallest diameter exhibits a water permeation flux that is two orders of magnitude greater than those of aquaporins and carbon nanotubes. The proposed nanochannel exhibits negligible chloride ion (Cl-) permeability caused by a powerful electrostatic barrier provided by the electrostatically negative fluorous interior surface. Thus, this nanochannel is expected to show nearly perfect salt reflectance for desalination.

Biomimetic reconstruction of butterfly wing scale nanostructures for radiative cooling and structural coloration.

A great number of butterfly species in the warmer climate have evolved to exhibit fascinating optical properties on their wing scales which can both regulate the wing temperature and exhibit structural coloring in order to increase their chances of survival. In particular, the Archaeoprepona demophon dorsal wing demonstrates notable radiative cooling performance and iridescent colors based on the nanostructure of the wing scale that can be characterized by the nanoporous matrix with the periodic nanograting structure on the top matrix surface. Inspired by the natural species, we demonstrate a multifunctional biomimetic film that reconstructs the nanostructure of the Archaeoprepona demophon wing scales to replicate the radiative cooling and structural coloring functionalities. We resorted to the SiO2 sacrificial template-based solution process to mimic the random porous structure and laser-interference lithography to reproduce the nanograting architecture of the butterfly wing scale. As a result, the biomimetic structure of the nanograted surface on top of the porous film demonstrated desirable heat transfer and optical properties for outstanding radiative cooling performance and iridescent structural coloring. In this regard, the film is capable of inducing the maximum temperature drop of 8.45 °C, and the color gamut of the biomimetic film can cover 91.8% of the standardized color profile (sRGB).

Temperature-dependent phonon conduction and nanotube engagement in metalized single wall carbon nanotube films.

Interfaces dominate the thermal resistances in aligned carbon nanotube arrays. This work uses nanosecond thermoreflectance thermometry to separate interface and volume resistances for 10 microm thick aligned SWNT films coated with Al, Ti, Pd, Pt, and Ni. We interpret the data by defining the nanotube-metal engagement factor, which governs the interface resistance and is extracted using the measured film heat capacity. The metal-SWNT and SWNT-substrate resistances range between 3.8 and 9.2 mm(2)K/W and 33-46 mm(2)K/W, respectively. The temperature dependency of the heat capacity data, measured between 125 and 300 K, is in good agreement with theoretical predictions. The temperature dependence demonstrated by the metal-SWNT interface resistance data suggests inelastic phonon transmission.

Heat diffusion-related damping process in a highly precise coarse-grained model for nonlinear motion of SWCNT.

Second sound and heat diffusion in single-walled carbon nanotubes (SWCNT) are 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 (CG) 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 quantified 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.