Article
Nanoscience & Nanotechnology
C. Ulises Gonzalez-Valle, Bladimir Ramos-Alvarado
Summary: Engineering nano- and microscale systems for water filtration, drug delivery, and biosensing is enabled by the intrinsic interactions of ionic compounds in aqueous environments and limited by our understanding of these polar solid-liquid interfaces. Particularly, the fundamental understanding of the electrostatic properties of the inner pore surface of alumina nanoporous membranes could lead to performance enhancement for evaporation and filtration applications. This investigation reports on the modeling and characterization of the wettability and thermal transport properties of water-alumina interfaces. Abnormal droplet spreading was observed while using documented modeling parameters for water-alumina interfaces. This issue was attributed to the overestimation of Coulombic interactions and was corrected using reactive molecular dynamics simulations. The interfacial entropy change (from bulk to interface) of liquid molecules was calculated for different alumina surfaces. It was found that surfaces with high interfacial entropy change correlate with a high interfacial concentration of water molecules and a dominant contribution from in-plane modes to thermal transport. Conversely, highly mobile water molecules in low entropy interfaces concurred with the out-of-plane modes contributing the most to the energy transport. The hydroxyls on the passivated solid interface led to the formation of hydrogen bonds, and the density number of hydrogen bonds pe...
ACS APPLIED NANO MATERIALS
(2021)
Review
Nanoscience & Nanotechnology
Tianli Feng, Hao Zhou, Zhe Cheng, Leighann Sarah Larkin, Mahesh R. R. Neupane
Summary: The emergence of wide and ultrawide bandgap semiconductors has revolutionized the advancement of next-generation power, RF, and optoelectronics, but the thermal boundary resistance at semiconductor interfaces hinders heat dissipation. Many new high thermal conductivity materials and techniques have been developed to improve thermal boundary resistance, and simulation methods have been developed to advance understanding. However, there is a large gap between experiments and simulations. This review comprehensively summarizes the experimental and simulation works, aiming to build a structure-property relationship between thermal boundary resistance and interfacial nanostructures and to improve thermal boundary resistance.
ACS APPLIED MATERIALS & INTERFACES
(2023)
Article
Physics, Applied
Yijun Ge, Yanguang Zhou, Timothy S. Fisher
Summary: This study combines first-principles calculations, spin-lattice dynamics, and NEGF method to compute thermal boundary conductance at a three-dimensional Co-Cu interface, considering spin-lattice interactions. It is found that spin-wave transmission is low and interfacial thermal conductance is reduced. The results are compared to the NEGF method, showing a similar trend with spins included.
JOURNAL OF APPLIED PHYSICS
(2021)
Article
Nanoscience & Nanotechnology
Ashutosh Giri, Ramez Cheaito, John T. Gaskins, Takanori Mimura, Harlan J. Brown-Shaklee, Douglas L. Medlin, Jon F. Ihlefeld, Patrick E. Hopkins
Summary: Experimental results show that thermal resistance may not increase with the addition of confined solid-solution films of varying thicknesses between parent materials. This contradicts the conventional understanding that adding more material leads to larger thermal resistances. The results potentially support the concept of vibrational matching across interfaces, suggesting that adding a thin vibrational bridge layer between two solids could enhance thermal boundary conductance.
ACS APPLIED MATERIALS & INTERFACES
(2021)
Article
Thermodynamics
Roisul H. Galib, Prabhakar R. Bandaru
Summary: Vertically stacked devices are a promising direction in electronics, but thermal resistance is a major issue. This study estimated the thermal boundary conductance and converse thermal resistance using a graphene-based platform, and found that weak van der Waals interactions and phonon frequency mismatch are the reasons for the reduced thermal boundary conductance.
INTERNATIONAL JOURNAL OF THERMAL SCIENCES
(2022)
Review
Physics, Condensed Matter
Christopher M. Stanley
Summary: The miniaturization of microelectronics has resulted in increased energy and interface density, creating new thermal resistors that prevent heat escape. Kapitza resistance has become the dominant cause of thermal resistance in microelectronics, yet remains poorly understood. This review critically examines existing literature, focusing on molecular dynamic simulations of the Si/Ge interface, and presents a research strategy to control Kapitza resistance. It proposes benchmark systems for verification and characterization of size effects, and suggests that first-principles calculations with anharmonic contributions are key to future progress.
PHYSICA STATUS SOLIDI B-BASIC SOLID STATE PHYSICS
(2023)
Article
Physics, Applied
Cecilia Herrero, Laurent Joly, Samy Merabia
Summary: This paper investigates the interfacial heat transfer between water and gold and proposes a method to increase the interfacial resistance by nanostructuring the gold surface and coating it with graphene. The results show a significant increase in the resistance compared to the planar gold situation. The predicted high thermal resistance makes this system a robust alternative to superhydrophobic materials.
APPLIED PHYSICS LETTERS
(2022)
Article
Nanoscience & Nanotechnology
Weidong Zheng, Connor J. McClellan, Eric Pop, Yee Kan Koh
Summary: In this study, accurate measurements of thermal boundary resistance (R) of 2D material interfaces were conducted. It was found that, in addition to phonon transport, thermal resistance between nonequilibrium phonons in the 2D materials could also play a critical role. These findings provide important insights into heat dissipation in 2D material devices and highlight the significance of considering the influence of nonequilibrium phonons in device design.
ACS APPLIED MATERIALS & INTERFACES
(2022)
Article
Physics, Applied
David A. Brantley, Ryan S. Crum, Minta C. Akin
Summary: This study demonstrates the presence of thermal conduction effects in temperature measurements of tin and iron coatings during dynamic compression experiments. Tin coatings, unlike iron coatings, may fail to converge to a bulk temperature source over the time scale of the experiment, requiring modifications by the experimenter. This work helps to set boundaries on thermal transport under shocked conditions.
JOURNAL OF APPLIED PHYSICS
(2021)
Article
Thermodynamics
Shanchen Li, Chenchen Lu, Chao Zhang, Zhihui Li, Junhua Zhao, Jige Chen, Ning Wei
Summary: In this work, a model is proposed to investigate the effect of fluid flow on the thermal boundary conductance between solid and fluid using molecular dynamics simulations. The results show that controlling temperature by excluding velocity components along the flow direction is the best way to eliminate viscous temperature rise. Thermal conduction is insensitive to fluid flow in atomic-smooth channel, but highly dependent on flow velocity in rough channel, where the thermal boundary conductance decreases by 11.7% when flow velocity reaches 18 m/s. These findings reveal the influence of fluid flow on interfacial thermal exchange and provide insights for improving cooling systems based on microfluidics.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2023)
Article
Nanoscience & Nanotechnology
Cameron Foss, Zlatan Aksamija
Summary: This study investigates the temperature-dependent thermal boundary conductance (TBC) of various beyond-graphene 2D materials on different substrates, showing the effect of temperature and encapsulation on TBC. The results reveal that some 2D materials can achieve or exceed the thermal conductivity of graphene, with the potential to tune the properties through encapsulation. Additionally, promising III-V materials are identified as potential 2D materials for thermal isolation and energy scavenging applications.
Article
Engineering, Electrical & Electronic
Joon Sang Kang, Man Li, Huan Wu, Huuduy Nguyen, Toshihiro Aoki, Yongjie Hu
Summary: Thermal management is crucial in electronic systems, and the integration of novel semiconductor materials like boron arsenide and boron phosphide with other materials such as gallium nitride can significantly improve cooling performance and reduce hot-spot temperatures in high-electron-mobility transistors.
NATURE ELECTRONICS
(2021)
Article
Nanoscience & Nanotechnology
Samreen Khan, Frank Angeles, John Wright, Saurabh Vishwakarma, Victor H. Ortiz, Erick Guzman, Fariborz Kargar, Alexander A. Balandin, David J. Smith, Debdeep Jena, H. Grace Xing, Richard Wilson
Summary: The study aims to investigate the impact of bulk vibrational properties and interfacial structure on thermal transport at interfaces in wide band gap semiconductor systems. The results suggest that thermal conductance depends on the bulk phonon properties of the softer material and the interfacial structure, rather than just the vibrational similarity between the two materials.
ACS APPLIED MATERIALS & INTERFACES
(2022)
Article
Physics, Multidisciplinary
Haiyang Li, Jun Wang, Guodong Xia
Summary: Thermal rectification, the phenomenon where the heat flux is much larger in one direction than in the opposite direction, is implemented in an asymmetric solid-liquid-solid sandwiched system with a nano-structured interface. Non-equilibrium molecular dynamics simulations reveal that the thermal rectification effect is due to the difference in interfacial thermal resistance between Cassie and Wenzel states when reversing the temperature bias. The effects of liquid density, solid-liquid bonding strength, and nanostructure size on thermal rectification are also examined, providing new insights for the design of thermal devices.
Article
Physics, Applied
Zexuan Zhang, Jimy Encomendero, Reet Chaudhuri, Yongjin Cho, Vladimir Protasenko, Kazuki Nomoto, Kevin Lee, Masato Toita, Huili Grace Xing, Debdeep Jena
Summary: High-density 2DHGs are observed in undoped pseudomorphic GaN/AlN heterostructures on single-crystal AlN substrates, providing potential for high performance wide-bandgap p-channel transistors. The use of plasma-assisted molecular beam epitaxy allows for the achievement of record-high mobility and density of the 2DHGs, indicating significant improvements in 2D hole mobilities.
APPLIED PHYSICS LETTERS
(2021)
Article
Chemistry, Physical
Ruiyang Li, Jian-Xun Wang, Eungkyu Lee, Tengfei Luo
Summary: This study introduces a data-free deep learning scheme, physics-informed neural network (PINN), for solving the phonon Boltzmann transport equation (BTE) with arbitrary temperature gradients. Numerical experiments suggest that the proposed PINN can accurately predict phonon transport under arbitrary temperature gradients and shows great promise for thermal design.
NPJ COMPUTATIONAL MATERIALS
(2022)
Article
Nanoscience & Nanotechnology
Ruimin Ma, Hanfeng Zhang, Tengfei Luo
Summary: In this study, polymers with desired thermal conductivity were designed using a reinforcement learning scheme. Machine learning models and neural networks were utilized for training and generating polymers with target properties. The synthesized polymers were evaluated for thermal conductivity and their synthetic accessibility. This approach can advance polymer development for specific applications.
ACS APPLIED MATERIALS & INTERFACES
(2022)
Article
Engineering, Chemical
Xiao Zhao, Tengfei Luo, Hui Jin
Summary: In this study, machine learning and transfer learning techniques with deep neural networks were explored to predict diffusion coefficients of multi-component supercritical water mixtures. Diffusion coefficients were initially calculated using molecular dynamics simulations, and a cross-validation method was used to find an accurate predictive model. Transfer learning was then applied to improve the model performance for ternary mixtures, based on the knowledge learned from the pretrained model for binary mixtures.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2022)
Article
Physics, Applied
Dezhao Huang, Shiwen Wu, Guoping Xiong, Tengfei Luo
Summary: In this study, the influence of external electric fields on the free energy of water molecules in graphene nanochannels was investigated using molecular dynamics simulations and the free energy perturbation method. It was found that the application of an electric field can reduce the thermal energy required to evaporate water from the nanochannels, which is related to the alignment of water molecules in the channels.
JOURNAL OF APPLIED PHYSICS
(2022)
Article
Chemistry, Physical
Seongmin Kim, Wenjie Shang, Seunghyun Moon, Trevor Pastega, Eungkyu Lee, Tengfei Luo
Summary: By utilizing a quantum computing-assisted active learning scheme and layered photonic structures, a visually transparent radiative cooler is designed to achieve high visible transparency and radiative cooling performance. It has the potential to significantly save energy in hot climates and can be used to design other complex materials.
ACS ENERGY LETTERS
(2022)
Article
Materials Science, Multidisciplinary
Ruimin Ma, Hanfeng Zhang, Jiaxin Xu, Luning Sun, Yoshihiro Hayashi, Ryo Yoshida, Junichiro Shiomi, Jian-xun Wang, Tengfei Luo
Summary: Finding polymers with high thermal conductivity is important but challenging. In this study, molecular dynamics simulations and machine learning are combined to explore polymers with relatively high thermal conductivity (>0.300 W/m-K). A regression model is trained to quantify the structure-thermal conductivity relation, and eventually, 121 polymers with thermal conductivity above the threshold are identified.
MATERIALS TODAY PHYSICS
(2022)
Article
Materials Science, Multidisciplinary
Z. Liu, M. Jiang, T. Luo
Summary: This study demonstrates the use of transfer learning to improve machine learning models for fast screening of semiconductor candidates with desirable thermal conductivity (TC), utilizing a large low-fidelity dataset as a proxy task to improve models trained on high-fidelity but small data. The transfer learning models show improved accuracy and have potential implications for materials informatics.
MATERIALS TODAY PHYSICS
(2022)
Article
Physics, Applied
Sina Malakpour Estalaki, Tengfei Luo, Khachatur V. Manukyan
Summary: Spontaneous crystallization of metals under extreme conditions is a unique phenomenon that could lead to the development of revolutionary metastable metals. In this study, non-equilibrium molecular dynamics simulations are used to investigate the formation of the hcp-Ni metastable phase, aiming to maximize its fraction in the final crystallized phase. Bayesian optimization with Gaussian processes regression is employed to guide the active learning process and achieve the maximum hcp-Ni fraction.
JOURNAL OF APPLIED PHYSICS
(2023)
Article
Chemistry, Physical
Zhihao Xu, Shiwen Wu, Siyu Tian, Dezhao Huang, Guoping Xiong, Tengfei Luo
Summary: In this study, we used NEMD simulation to investigate the pressure-driven flow of oil in surface-functionalized graphene channels. By introducing water into the channel, we found that the transport velocity of oil could be improved. Further analysis revealed two possible mechanisms for the increased velocity: the formation of a water film between the oil and graphene substrates, blocking intermolecular interactions, and the reduction of the apparent viscosity of the liquid mixture. Comparative analysis confirmed the universality of this water-induced flow enhancement. These findings have important implications for optimizing oil recovery devices.
JOURNAL OF PHYSICAL CHEMISTRY C
(2023)
Article
Physics, Applied
Ruiyang Li, Eungkyu Lee, Tengfei Luo
Summary: In this work, a physics-informed neural network framework is proposed to solve the coupled electron and phonon Boltzmann transport equations. Instead of relying on labeled data, the framework directly learns the spatiotemporal solutions within a parameterized space by enforcing physical laws. The framework demonstrates its efficacy in accurately resolving temperature profiles in low-dimensional thermal transport problems and visualizing ultrafast electron and phonon dynamics in laser heating experiments.
PHYSICAL REVIEW APPLIED
(2023)
Article
Nanoscience & Nanotechnology
Shiwen Wu, Ruda Jian, Lyu Zhou, Siyu Tian, Tengfei Luo, Shuang Cui, Bo Zhao, Guoping Xiong
Summary: A new method for converting hazardous eggshell biowaste into valuable resources was proposed. Eggshell-based films were fabricated for highly efficient subambient daytime radiative cooling, exhibiting high reflection and emission properties to reduce ambient temperature.
ACS APPLIED MATERIALS & INTERFACES
(2023)
Article
Nanoscience & Nanotechnology
Seongmin Kim, Shiwen Wu, Ruda Jian, Guoping Xiong, Tengfei Luo
Summary: This study designs a high-performance solar absorber based on titanium nitride (TiN) metastructures using quantum computing-assisted optimization. By incorporating machine learning, quantum annealing, and optical simulation in an iterative cycle, an optimal structure with solar absorptance > 95% is achieved within 40 hours, much faster than an exhaustive search. Analysis of electric field distributions reveals that the combined effects of Fabry-Perot interferences and surface plasmonic resonances contribute to the broadband high absorption efficiency of the optimally designed metastructure. The designed absorber shows great potential for solar energy harvesting applications, and the optimization scheme can be applied to the design of other complex functional materials.
ACS APPLIED MATERIALS & INTERFACES
(2023)
Article
Chemistry, Multidisciplinary
Wenjie Shang, Minxiang Zeng, A. N. M. Tanvir, Ke Wang, Mortaza Saeidi-Javash, Alexander Dowling, Tengfei Luo, Yanliang Zhang
Summary: A hybrid data-driven strategy combining Bayesian optimization and Gaussian process regression is proposed to optimize the composition of AgSe-based thermoelectric materials. Through active collection of experimental data, a significant improvement in material performance is achieved within seven iterations.
ADVANCED MATERIALS
(2023)
Article
Chemistry, Physical
Shiwen Wu, Zhihao Xu, Ruda Jian, Siyu Tian, Long Zhou, Tengfei Luo, Guoping Xiong
Summary: The flow behavior of oil in nanochannels has been extensively studied for oil transport applications. In this study, non-equilibrium molecular dynamics simulations are used to investigate the Poiseuille flow of oil in graphene nanochannels. Contrary to prior observations of steady flows, it is found that oil molecules with long hydrocarbon chains exhibit notable stick-slip flow behavior. The stick-slip motion is attributed to changes in molecular alignment near the graphene wall, resulting in significant friction force variations and velocity fluctuations.
JOURNAL OF PHYSICAL CHEMISTRY B
(2023)
Article
Chemistry, Physical
Jiahang Zhou, Ruiyang Li, Tengfei Luo
Summary: In this work, the authors demonstrate the effectiveness of physics-informed neural networks (PINNs) in solving time-dependent mode-resolved phonon Boltzmann transport equation (BTE). The PINNs are trained by minimizing the residual of the governing equations and boundary/initial conditions to predict phonon energy distributions. The results show excellent agreement with analytical and numerical solutions. After offline training, the PINNs can be used for online evaluation of transient heat conduction, providing instantaneous results such as temperature distribution. The trained model can predict phonon transport in arbitrary values in the parameter space, making it a promising tool for practical applications such as thermal management design of microelectronics.
NPJ COMPUTATIONAL MATERIALS
(2023)
