Electron Drag Effect on Thermal Conductivity in Two-Dimensional Semiconductors.

Two-dimensional (2D) materials have shown great potential in applications as transistors, where thermal dissipation becomes crucial because of the increasing energy density. Although the thermal conductivity of 2D materials has been extensively studied, interactions between nonequilibrium electrons and phonons, which can be strong when high electric fields and heat current coexist, are not considered. In this work, we systematically study the electron drag effect, where nonequilibrium electrons impart momenta to phonons and influence the thermal conductivity, in 2D semiconductors using ab initio simulations. We find that, at room temperature, electron drag can significantly increase thermal conductivity by decreasing phonon-electron scattering in 2D semiconductors while its impact in three-dimensional semiconductors is negligible. We attribute this difference to the large electron-phonon scattering phase space and larger contribution to thermal conductivity by drag-active phonons. Our work elucidates the fundamental physics underlying coupled electron-phonon transport in materials of various dimensionalities.

Lattice Dynamics and Thermal Transport in Semiconductors with Anti-Bonding Valence Bands.

Achieving high thermoelectric performance requires efficient manipulation of thermal conductivity and a fundamental understanding of the microscopic mechanisms of phonon transport in crystalline solids. One of the major challenges in thermal transport is achieving ultralow lattice thermal conductivity. In this study, we use the anti-bonding character of the highest-occupied valence band as an efficient descriptor for discovering new materials with an ultralow thermal conductivity. We first examined the relationship between anti-bonding valence bands (ABVBs) and low lattice thermal conductivity in model systems PbTe and CsPbBr3. Then, we conducted a high-throughput search in the Materials Project database and identified over 600 experimentally stable binary semiconductors with an anti-bonding character in their valence bands. From our candidate list, we conducted a comprehensive analysis of the chemical bonds and the thermal transport in the XS family, where X = K, Rb, and Cs are alkaline metals. These materials all exhibit ultralow thermal conductivities less than 1 W/(m K) at room temperature despite simple structures. We attributed the ultralow thermal conductivity to the weakened bonds and increased phonon anharmonicity due to their ABVBs. Our results provide chemical intuitions to understand lattice dynamics in crystals and open up a convenient venue toward searching for materials with an intrinsically low lattice thermal conductivity.

Indirect Exchange Interaction Leads to Large Lattice Contribution to Magnetocaloric Entropy Change.

Materials with a large magnetocaloric response are highly desirable for magnetic cooling applications. It is suggested that a strong spin-lattice coupling tends to generate a large magnetocaloric effect, but no microscopic mechanism has been proposed. In this Letter, we use spin-lattice dynamics simulation to examine the lattice contribution to the magnetocaloric entropy change in bcc iron (Fe) and hcp gadolinium (Gd) with exchange interaction parameters determined from ab initio calculations. We find that indirect Ruderman-Kittel-Kasuya-Yosida (RKKY) exchange interaction in hcp Gd leads to longer-range spin-lattice coupling and more strongly influences the low-frequency long-wavelength phonons. This results in a higher lattice contribution toward the total magnetocaloric entropy change as compared to bcc Fe with short-range direct exchange interactions. Our analysis provides a framework for understanding the magnetocaloric effect in magnetic materials with strong spin-lattice couplings. Our finding suggests that long-range indirect RKKY-type exchange gives rise to a larger lattice contribution to the magnetocaloric entropy change and is, thus, beneficial for magnetocaloric materials.

Transient Strain-Induced Electronic Structure Modulation in a Semiconducting Polymer Imaged by Scanning Ultrafast Electron Microscopy.

Understanding the optoelectronic properties of semiconducting polymers under external strain is essential for their applications in flexible devices. Although prior studies have highlighted the impact of static and macroscopic strains, assessing the effect of a local transient deformation before structural relaxation occurs remains challenging. Here, we employ scanning ultrafast electron microscopy (SUEM) to image the dynamics of a photoinduced transient strain in the semiconducting polymer poly(3-hexylthiophene) (P3HT). We observe that the photoinduced SUEM contrast, corresponding to the local change of secondary electron emission, exhibits an unusual ring-shaped profile. We attribute the observation to the electronic structure modulation of P3HT caused by a photoinduced strain field owing to its low modulus and strong electron-lattice coupling, supported by a finite-element analysis. Our work provides insights into tailoring optoelectronic properties using transient mechanical deformation in semiconducting polymers and demonstrates the versatility of SUEM to study photophysical processes in diverse materials.

Spatiotemporal Imaging of Thickness-Induced Band-Bending Junctions.

van der Waals materials exhibit naturally passivated surfaces and an ability to form versatile heterostructures to enable an examination of carrier transport mechanisms not seen in traditional materials. Here, we report a new type of homojunction termed a "band-bending junction" whose potential landscape depends solely on the difference in thickness between the two sides of the junction. Using MoS2 on Au as a prototypical example, we find that surface potential differences can arise from the degree of vertical band bending in thin and thick regions. Furthermore, by using scanning ultrafast electron microscopy, we examine the spatiotemporal dynamics of charge carriers generated at this junction and find that lateral carrier separation is enabled by differences in the band bending in the vertical direction, which we verify with simulations. Band-bending junctions may therefore enable new optoelectronic devices that rely solely on band bending arising from thickness variations to separate charge carriers.

Electron mean-free-path filtering in Dirac material for improved thermoelectric performance.

Recent advancements in thermoelectric materials have largely benefited from various approaches, including band engineering and defect optimization, among which the nanostructuring technique presents a promising way to improve the thermoelectric figure of merit (zT) by means of reducing the characteristic length of the nanostructure, which relies on the belief that phonons' mean free paths (MFPs) are typically much longer than electrons'. Pushing the nanostructure sizes down to the length scale dictated by electron MFPs, however, has hitherto been overlooked as it inevitably sacrifices electrical conduction. Here we report through ab initio simulations that Dirac material can overcome this limitation. The monotonically decreasing trend of the electron MFP allows filtering of long-MFP electrons that are detrimental to the Seebeck coefficient, leading to a dramatically enhanced power factor. Using SnTe as a material platform, we uncover this MFP filtering effect as arising from its unique nonparabolic Dirac band dispersion. Room-temperature zT can be enhanced by nearly a factor of 3 if one designs nanostructures with grain sizes of ∼10 nm. Our work broadens the scope of the nanostructuring approach for improving the thermoelectric performance, especially for materials with topologically nontrivial electronic dynamics.

Probing Surface Photovoltage Effect Using Photoassisted Secondary Electron Emission.

While the properties of surfaces and interfaces are crucial to modern devices, they are commonly difficult to explore since the signal from the bulk often masks the surface contribution. Here we introduce a methodology based on scanning electron microscopy (SEM) coupled with a pulsed laser source, which offers the capability to sense the topmost layer of materials, to study the surface photovoltage (SPV) related effects. This method relies on a pulsed optical laser to transiently induce an SPV and a continuous primary electron beam to produce secondary electron (SE) emission and monitor the change of the SE yield under laser illumination. We observe contrasting behaviors of the SPV-induced SE yield change on n-type and p-type semiconductors. We further study the dependence of the SPV-induced SE yield on the primary electron beam energy, the optical fluence, and the modulation frequency of the optical excitation, which reveal the details of the dynamics of the photocarriers in the presence of the surface built-in potential. This fast, contactless, and bias-free technique offers a convenient and robust platform to probe surface electronic phenomena, with great promise to probe nanoscale effects with a high spatial resolution. Our result further provides a basis to understand the contrast mechanisms of emerging time-resolved electron microscopic techniques, such as the scanning ultrafast electron microscopy.

Electron-phonon interaction and superconductivity in the high-pressure cI16 phase of lithium from first principles.

Superconductivity in different phases of lithium (Li) under high pressure has been widely studied both experimentally and theoretically, whereas detailed first-principles investigation of the microscopic mechanism has been limited to the fcc and bcc phases below 40 GPa. Here, we study the electron-phonon interaction and superconductivity in one interesting high-pressure phase of Li (cI16) between 45 GPa and 76 GPa using first-principles calculations and the Wannier interpolation technique. The nature of superconductivity in the cI16 phase is examined by solving the Eliashberg equations, and the superconducting transition temperature Tc of the Li-cI16 in the range of 45-76 GPa is calculated. We analyze the electron-phonon coupling (EPC) effect on the electronic bands, phonon dispersions, the Fermi surface topology (nesting ξq) and the Eliashberg spectral function α2F(ω) at different pressures. In particular, α2F(ω) shows an anomalous trend in spectral weight at a low-frequency region with increasing pressure, which originates from the reduction of the nesting function ξq. The trend of the EPC strength from each phonon branch with pressure is also presented in detail. Another interesting phenomenon from our calculation is the tendency of a metal-to-semiconductor transition with structural optimization at different pressures, which have been reported by previous experiments. Our theoretical studies demonstrate clearly the mechanism behind the anomalous superconducting properties of the high-pressure Li-cI16 phase.

Ab initio optimization of phonon drag effect for lower-temperature thermoelectric energy conversion.

Although the thermoelectric figure of merit zT above 300 K has seen significant improvement recently, the progress at lower temperatures has been slow, mainly limited by the relatively low Seebeck coefficient and high thermal conductivity. Here we report, for the first time to our knowledge, success in first-principles computation of the phonon drag effect--a coupling phenomenon between electrons and nonequilibrium phonons--in heavily doped region and its optimization to enhance the Seebeck coefficient while reducing the phonon thermal conductivity by nanostructuring. Our simulation quantitatively identifies the major phonons contributing to the phonon drag, which are spectrally distinct from those carrying heat, and further reveals that although the phonon drag is reduced in heavily doped samples, a significant contribution to Seebeck coefficient still exists. An ideal phonon filter is proposed to enhance zT of silicon at room temperature by a factor of 20 to ∼ 0.25, and the enhancement can reach 70 times at 100 K. This work opens up a new venue toward better thermoelectrics by harnessing nonequilibrium phonons.

Spatial-Temporal Imaging of Anisotropic Photocarrier Dynamics in Black Phosphorus.

As an emerging single elemental layered material with a low symmetry in-plane crystal lattice, black phosphorus (BP) has attracted significant research interest owing to its unique electronic and optoelectronic properties, including its widely tunable bandgap, polarization-dependent photoresponse and highly anisotropic in-plane charge transport. Despite extensive study of the steady-state charge transport in BP, there has not been direct characterization and visualization of the hot carriers dynamics in BP immediately after photoexcitation, which is crucial to understanding the performance of BP-based optoelectronic devices. Here we use the newly developed scanning ultrafast electron microscopy (SUEM) to directly visualize the motion of photoexcited hot carriers on the surface of BP in both space and time. We observe highly anisotropic in-plane diffusion of hot holes with a 15 times higher diffusivity along the armchair (x-) direction than that along the zigzag (y-) direction. Our results provide direct evidence of anisotropic hot carrier transport in BP and demonstrate the capability of SUEM to resolve ultrafast hot carrier dynamics in layered two-dimensional materials.

Photon-Induced Near-Field Electron Microscopy of Eukaryotic Cells.

Photon-induced near-field electron microscopy (PINEM) is a technique to produce and then image evanescent electromagnetic fields on the surfaces of nanostructures. Most previous applications of PINEM have imaged surface plasmon-polariton waves on conducting nanomaterials. Here, the application of PINEM on whole human cancer cells and membrane vesicles isolated from them is reported. We show that photons induce time-, orientation-, and polarization-dependent evanescent fields on the surfaces of A431 cancer cells and isolated membrane vesicles. Furthermore, the addition of a ligand to the major surface receptor on these cells and vesicles (epidermal growth factor receptor, EGFR) reduces the intensity of these fields in both preparations. We propose that in the absence of plasmon waves in biological samples, these evanescent fields reflect the changes in EGFR kinase domain polarization upon ligand binding.

High thermoelectric performance by resonant dopant indium in nanostructured SnTe.

From an environmental perspective, lead-free SnTe would be preferable for solid-state waste heat recovery if its thermoelectric figure-of-merit could be brought close to that of the lead-containing chalcogenides. In this work, we studied the thermoelectric properties of nanostructured SnTe with different dopants, and found indium-doped SnTe showed extraordinarily large Seebeck coefficients that cannot be explained properly by the conventional two-valence band model. We attributed this enhancement of Seebeck coefficients to resonant levels created by the indium impurities inside the valence band, supported by the first-principles simulations. This, together with the lower thermal conductivity resulting from the decreased grain size by ball milling and hot pressing, improved both the peak and average nondimensional figure-of-merit (ZT) significantly. A peak ZT of ∼1.1 was obtained in 0.25 atom % In-doped SnTe at about 873 K.

Significant reduction of lattice thermal conductivity by the electron-phonon interaction in silicon with high carrier concentrations: a first-principles study.

The electron-phonon interaction is well known to create major resistance to electron transport in metals and semiconductors, whereas fewer studies are directed to its effect on phonon transport, especially in semiconductors. We calculate the phonon lifetimes due to scattering with electrons (or holes), combine them with the intrinsic lifetimes due to the anharmonic phonon-phonon interaction, all from first principles, and evaluate the effect of the electron-phonon interaction on the lattice thermal conductivity of silicon. Unexpectedly, we find a significant reduction of the lattice thermal conductivity at room temperature as the carrier concentration goes above 10(19) cm(-3) (the reduction reaches up to 45% in p-type silicon at around 10(21) cm(-3)), a range of great technological relevance to thermoelectric materials.

Generalized two-temperature model for coupled phonon-magnon diffusion.

We generalize the two-temperature model [Sanders and Walton, Phys. Rev. B 15, 1489 (1977)] for coupled phonon-magnon diffusion to include the effect of the concurrent magnetization flow, with a particular emphasis on the thermal consequence of the magnon flow driven by a nonuniform magnetic field. Working within the framework of the Boltzmann transport equation, we derive the constitutive equations for coupled phonon-magnon transport driven by gradients of both temperature and external magnetic fields, and the corresponding conservation laws. Our equations reduce to the original Sanders-Walton two-temperature model under a uniform external field, but predict a new magnon cooling effect driven by a nonuniform magnetic field in a homogeneous single-domain ferromagnet. We estimate the magnitude of the cooling effect in an yttrium iron garnet, and show it is within current experimental reach. With properly optimized materials, the predicted cooling effect can potentially supplement the conventional magnetocaloric effect in cryogenic applications in the future.

Extraordinary Thermoelectric Properties of Topological Surface States in Quantum-Confined Cd3As2 Thin Films.

Topological insulators and semimetals have been shown to possess intriguing thermoelectric properties promising for energy harvesting and cooling applications. However, thermoelectric transport associated with the Fermi arc topological surface states on topological Dirac semimetals remains less explored. This work systematically examines thermoelectric transport in a series of topological Dirac semimetal Cd3As2 thin films grown by molecular beam epitaxy. Surprisingly, significantly enhanced Seebeck effect and anomalous Nernst effect are found at cryogenic temperatures when the Cd3As2 layer is thin. In particular, a peak Seebeck coefficient of nearly 500 µV K-1 and a corresponding thermoelectric power factor over 30 mW K-2 m-1 are observed at 5 K in a 25-nm-thick sample. Combining angle-dependent quantum oscillation analysis, magnetothermoelectric measurement, transport modeling, and first-principles simulation, the contributions from bulk and surface conducting channels are isolated and the unusual thermoelectric properties are attributed to the topological surface states. The analysis showcases the rich thermoelectric transport physics in quantum-confined topological Dirac semimetal thin films and suggests new routes to achieving high thermoelectric performance at cryogenic temperatures.

Virtual node graph neural network for full phonon prediction.

Understanding the structure-property relationship is crucial for designing materials with desired properties. The past few years have witnessed remarkable progress in machine-learning methods for this connection. However, substantial challenges remain, including the generalizability of models and prediction of properties with materials-dependent output dimensions. Here we present the virtual node graph neural network to address the challenges. By developing three virtual node approaches, we achieve Γ-phonon spectra and full phonon dispersion prediction from atomic coordinates. We show that, compared with the machine-learning interatomic potentials, our approach achieves orders-of-magnitude-higher efficiency with comparable to better accuracy. This allows us to generate databases for Γ-phonon containing over 146,000 materials and phonon band structures of zeolites. Our work provides an avenue for rapid and high-quality prediction of phonon band structures enabling materials design with desired phonon properties. The virtual node method also provides a generic method for machine-learning design with a high level of flexibility.

Voting based double-weighted deterministic extreme learning machine model and its application.

This study introduces an intelligent learning model for classification tasks, termed the voting-based Double Pseudo-inverse Extreme Learning Machine (V-DPELM) model. Because the traditional method is affected by the weight of input layer and the bias of hidden layer, the number of hidden layer neurons is too large and the model performance is unstable. The V-DPELM model proposed in this paper can greatly alleviate the limitations of traditional models because of its direct determination of weight structure and voting mechanism strategy. Through extensive simulations on various real-world classification datasets, we observe a marked improvement in classification accuracy when comparing the V-DPELM algorithm to traditional V-ELM methods. Notably, when used for machine recognition classification of breast tumors, the V-DPELM method demonstrates superior classification accuracy, positioning it as a valuable tool in machine-assisted breast tumor diagnosis models.

Advances on intelligent algorithms for scientific computing: an overview.

The field of computer science has undergone rapid expansion due to the increasing interest in improving system performance. This has resulted in the emergence of advanced techniques, such as neural networks, intelligent systems, optimization algorithms, and optimization strategies. These innovations have created novel opportunities and challenges in various domains. This paper presents a thorough examination of three intelligent methods: neural networks, intelligent systems, and optimization algorithms and strategies. It discusses the fundamental principles and techniques employed in these fields, as well as the recent advancements and future prospects. Additionally, this paper analyzes the advantages and limitations of these intelligent approaches. Ultimately, it serves as a comprehensive summary and overview of these critical and rapidly evolving fields, offering an informative guide for novices and researchers interested in these areas.