Chinese Physics B

The physical fundamentals and influences upon electrode materials' open-circuit voltage (OCV) and the spatial distribution of electrochemical potential in the full cell are briefly reviewed. We hope to illustrate that a better understanding of these scientific problems can help to develop and design high voltage cathodes and interfaces with low Ohmic drop. OCV is one of the main indices to evaluate the performance of lithium ion batteries (LIBs), and the enhancement of OCV shows promise as a way to increase the energy density. Besides, the severe potential drop at the interfaces indicates high resistance there, which is one of the key factors limiting power density.

The prediction of chemical synthesis pathways plays a pivotal role in materials science research. Challenges, such as the complexity of synthesis pathways and the lack of comprehensive datasets, currently hinder our ability to predict these chemical processes accurately. However, recent advancements in generative artificial intelligence (GAI), including automated text generation and question–answering systems, coupled with fine-tuning techniques, have facilitated the deployment of large-scale AI models tailored to specific domains. In this study, we harness the power of the LLaMA2-7B model and enhance it through a learning process that incorporates 13878 pieces of structured material knowledge data. This specialized AI model, named MatChat, focuses on predicting inorganic material synthesis pathways. MatChat exhibits remarkable proficiency in generating and reasoning with knowledge in materials science. Although MatChat requires further refinement to meet the diverse material design needs, this research undeniably highlights its impressive reasoning capabilities and innovative potential in materials science. MatChat is now accessible online and open for use, with both the model and its application framework available as open source. This study establishes a robust foundation for collaborative innovation in the integration of generative AI in materials science.

We review the recent, mainly theoretical, progress in the study of topological nodal line semimetals in three dimensions. In these semimetals, the conduction and the valence bands cross each other along a one-dimensional curve in the three-dimensional Brillouin zone, and any perturbation that preserves a certain symmetry group (generated by either spatial symmetries or time-reversal symmetry) cannot remove this crossing line and open a full direct gap between the two bands. The nodal line(s) is hence topologically protected by the symmetry group, and can be associated with a topological invariant. In this review, (i) we enumerate the symmetry groups that may protect a topological nodal line; (ii) we write down the explicit form of the topological invariant for each of these symmetry groups in terms of the wave functions on the Fermi surface, establishing a topological classification; (iii) for certain classes, we review the proposals for the realization of these semimetals in real materials; (iv) we discuss different scenarios that when the protecting symmetry is broken, how a topological nodal line semimetal becomes Weyl semimetals, Dirac semimetals, and other topological phases; and (v) we discuss the possible physical effects accessible to experimental probes in these materials.

The emerging perovskite solar cells have been recognized as one of the most promising new-generation photovoltaic technologies owing to their potential of high efficiency and low production cost. However, the current perovskite solar cells suffer from some obstacles such as non-radiative charge recombination, mismatched absorption, light induced degradation for the further improvement of the power conversion efficiency and operational stability towards practical application. The rare-earth elements have been recently employed to effectively overcome these drawbacks according to their unique photophysical properties. Herein, the recent progress of the application of rare-earth ions and their functions in perovskite solar cells were systematically reviewed. As it was revealed that the rare-earth ions can be coupled with both charge transport metal oxides and photosensitive perovskites to regulate the thin film formation, and the rare-earth ions are embedded either substitutionally into the crystal lattices to adjust the optoelectronic properties and phase structure, or interstitially at grain boundaries and surface for effective defect passivation. In addition, the reversible oxidation and reduction potential of rare-earth ions can prevent the reduction and oxidation of the targeted materials. Moreover, owing to the presence of numerous energetic transition orbits, the rare-earth elements can convert low-energy infrared photons or high-energy ultraviolet photons into perovskite responsive visible light, to extend spectral response range and avoid high-energy light damage. Therefore, the incorporation of rare-earth elements into the perovskite solar cells have demonstrated promising potentials to simultaneously boost the device efficiency and stability.

Quantum information processing based on Rydberg atoms emerged as a promising direction two decades ago. Recent experimental and theoretical progresses have shined exciting light on this avenue. In this concise review, we will briefly introduce the basics of Rydberg atoms and their recent applications in associated areas of neutral atom quantum computation and simulation. We shall also include related discussions on quantum optics with Rydberg atomic ensembles, which are increasingly used to explore quantum computation and quantum simulation with photons.

The planar Hall effect (PHE), which originates from anisotropic magnetoresistance, presents a qualitative and simple approach to characterize electronic structures of quantum materials by applying an in-plane rotating magnetic field to induce identical oscillations in both longitudinal and transverse resistances. In this review, we focus on the recent research on the PHE in various quantum materials, including ferromagnetic materials, topological insulators, Weyl semimetals, and orbital anisotropic matters. Firstly, we briefly introduce the family of Hall effect and give a basic deduction of PHE formula with the second-order resistance tensor, showing the mechanism of the characteristic π-period oscillation in trigonometric function form with a π/4 phase delay between the longitudinal and transverse resistances. Then, we will introduce the four main mechanisms to realize PHE in quantum materials. After that, the origin of the anomalous planar Hall effect (APHE) results, of which the curve shapes deviate from that of PHE, will be reviewed and discussed. Finally, the challenges and prospects for this field of study are discussed.

The performance of optical interconnection has improved dramatically in recent years. Silicon-based optoelectronic heterogeneous integration is the key enabler to achieve high performance optical interconnection, which not only provides the optical gain which is absent from native Si substrates and enables complete photonic functionalities on chip, but also improves the system performance through advanced heterogeneous integrated packaging. This paper reviews recent progress of silicon-based optoelectronic heterogeneous integration in high performance optical interconnection. The research status, development trend and application of ultra-low loss optical waveguides, high-speed detectors, high-speed modulators, lasers and 2D, 2.5D, 3D and monolithic integration are focused on.

Thermoelectric materials, enabling the directing conversion between heat and electricity, are one of the promising candidates for overcoming environmental pollution and the upcoming energy shortage caused by the over-consumption of fossil fuels. Bi₂Te₃-based alloys are the classical thermoelectric materials working near room temperature. Due to the intensive theoretical investigations and experimental demonstrations, significant progress has been achieved to enhance the thermoelectric performance of Bi₂Te₃-based thermoelectric materials. In this review, we first explored the fundamentals of thermoelectric effect and derived the equations for thermoelectric properties. On this basis, we studied the effect of material parameters on thermoelectric properties. Then, we analyzed the features of Bi₂Te₃-based thermoelectric materials, including the lattice defects, anisotropic behavior and the strong bipolar conduction at relatively high temperature. Then we accordingly summarized the strategies for enhancing the thermoelectric performance, including point defect engineering, texture alignment, and band gap enlargement. Moreover, we highlighted the progress in decreasing thermal conductivity using nanostructures fabricated by solution grown method, ball milling, and melt spinning. Lastly, we employed modeling analysis to uncover the principles of anisotropy behavior and the achieved enhancement in Bi₂Te₃, which will enlighten the enhancement of thermoelectric performance in broader materials

With the need of the internet of things, big data, and artificial intelligence, creating new computing architecture is greatly desired for handling data-intensive tasks. Human brain can simultaneously process and store information, which would reduce the power consumption while improve the efficiency of computing. Therefore, the development of brain-like intelligent device and the construction of brain-like computation are important breakthroughs in the field of artificial intelligence. Memristor, as the fourth fundamental circuit element, is an ideal synaptic simulator due to its integration of storage and processing characteristics, and very similar activities and the working mechanism to synapses among neurons which are the most numerous components of the brains. In particular, memristive synaptic devices with optoelectronic responding capability have the benefits of storing and processing transmitted optical signals with wide bandwidth, ultrafast data operation speed, low power consumption, and low cross-talk, which is important for building efficient brain-like computing networks. Herein, we review recent progresses in optoelectronic memristor for neuromorphic computing, including the optoelectronic memristive materials, working principles, applications, as well as the current challenges and the future development of the optoelectronic memristor.

The combination of different nanostructures can hinder phonons transmission in a wide frequency range and further reduce the thermal conductivity (TC). This will benefit the improvement and application of thermoelectric conversion, insulating materials and thermal barrier coatings, etc. In this work, the effects of nanopillars and Ge nanoparticles (GNPs) on the thermal transport of Si nanowire (SN) are investigated by nonequilibrium molecular dynamics (NEMD) simulation. By analyzing phonons transport behaviors, it is confirmed that the introduction of nanopillars leads to the occurrence of low-frequency phonons resonance, and nanoparticles enhance high-frequency phonons interface scattering and localization. The results show that phonons transport in the whole frequency range can be strongly hindered by the simultaneous introduction of nanopillars and nanoparticles. In addition, the effects of system length, temperature, sizes and numbers of nanoparticles on the TC are investigated. Our work provides useful insights into the effective regulation of the TC of nanomaterials.

Photon tunneling effects give rise to surface waves, amplifying radiative heat transfer in the near-field regime. Recent research has highlighted that the introduction of nanopores into materials creates additional pathways for heat transfer, leading to a substantial enhancement of near-field radiative heat transfer (NFRHT). Being a direct bandgap semiconductor, GaN has high thermal conductivity and stable resistance at high temperatures, and holds significant potential for applications in optoelectronic devices. Indeed, study of NFRHT between nanoporous GaN films is currently lacking, hence the physical mechanism for adding nanopores to GaN films remains to be discussed in the field of NFRHT. In this work, we delve into the NFRHT of GaN nanoporous films in terms of gap distance, GaN film thickness and the vacuum filling ratio. The results demonstrate a 27.2% increase in heat flux for a 10 nm gap when the nanoporous filling ratio is 0.5. Moreover, the spectral heat flux exhibits redshift with increase in the vacuum filling ratio. To be more precise, the peak of spectral heat flux moves from ω = 1.31 × 10¹⁴ rad⋅s⁻¹ to ω = 1.23 × 10¹⁴ rad⋅s⁻¹ when the vacuum filling ratio changes from f = 0.1 to f = 0.5; this can be attributed to the excitation of surface phonon polaritons. The introduction of graphene into these configurations can highly enhance the NFRHT, and the spectral heat flux exhibits a blueshift with increase in the vacuum filling ratio, which can be explained by the excitation of surface plasmon polaritons. These findings offer theoretical insights that can guide the extensive utilization of porous structures in thermal control, management and thermal modulation.

Thermal illusion aims to create fake thermal signals or hide the thermal target from the background thermal field to mislead infrared observers, and illusion thermotics was proposed to regulate heat flux with artificially structured metamaterials for thermal illusion. Most theoretical and experimental works on illusion thermotics focus on two-dimensional materials, while heat transfer in real three-dimensional (3D) objects remains elusive, so the general 3D illusion thermotics is urgently demanded. In this study, we propose a general method to design 3D thermal illusion metamaterials with varying illusions at different sizes and positions. To validate the generality of the 3D method for thermal illusion metamaterials, we realize thermal functionalities of thermal shifting, splitting, trapping, amplifying and compressing. In addition, we propose a special way to simplify the design method under the condition that the size of illusion target is equal to the size of original heat source. The 3D thermal illusion metamaterial paves a general way for illusion thermotics and triggers the exploration of illusion metamaterials for more functionalities and applications.

Zinc oxide (ZnO) shows great potential in electronics, but its large intrinsic thermal conductivity limits its thermoelectric applications. In this work, we explore the significant carrier transport capacity and diameter-dependent thermoelectric characteristics of wurtzite-ZnO 〈0001〉 nanowires based on first-principles and molecular dynamics simulations. Under the synergistic effect of band degeneracy and weak phonon–electron scattering, P-type (ZnO)₇₃ nanowires achieve an ultra-high power factor above 1500 μW⋅cm⁻¹⋅K⁻² over a wide temperature range. The lattice thermal conductivity and carrier transport properties of ZnO nanowires exhibit a strong diameter size dependence. When the ZnO nanowire diameter exceeds 12.72 Å, the carrier transport properties increase significantly, while the thermal conductivity shows a slight increase with the diameter size, resulting in a ZT value of up to 6.4 at 700 K for P-type (ZnO)₇₃. For the first time, the size effect is also illustrated by introducing two geometrical configurations of the ZnO nanowires. This work theoretically depicts the size optimization strategy for the thermoelectric conversion of ZnO nanowires.

This paper introduces the quantum control of Lyapunov functions based on the state distance, the mean of imaginary quantities and state errors. In this paper, the specific control laws under the three forms are given. Stability is analyzed by the LaSalle invariance principle and the numerical simulation is carried out in a 2D test system. The calculation process for the Lyapunov function is based on a combination of the average of virtual mechanical quantities, the particle swarm algorithm and a simulated annealing algorithm. Finally, a unified form of the control laws under the three forms is given.

The anomalous valley Hall effect (AVHE) can be used to explore and utilize valley degrees of freedom in materials, which has potential applications in fields such as information storage, quantum computing and optoelectronics. AVHE exists in two-dimensional (2D) materials possessing valley polarization (VP), and such 2D materials usually belong to the hexagonal honeycomb lattice. Therefore, it is necessary to achieve valleytronic materials with VP that are more readily to be synthesized and applicated experimentally. In this topical review, we introduce recent developments on realizing VP as well as AVHE through different methods, i.e., doping transition metal atoms, building ferrovalley heterostructures and searching for ferrovalley materials. Moreover, 2D ferrovalley systems under external modulation are also discussed. 2D valleytronic materials with AVHE demonstrate excellent performance and potential applications, which offer the possibility of realizing novel low-energy-consuming devices, facilitating further development of device technology, realizing miniaturization and enhancing functionality of them.

Besides the diverse investigations on the interactions between intense laser fields and molecular systems, extensive research has been recently dedicated to exploring the response of nanosystems excited by well-tailored femtosecond laser fields. Due to the fact that nanostructures hold peculiar effects when illuminated by laser pulses, the underlying mechanisms and the corresponding potential applications can make significant improvements in both fundamental research and development of novel techniques. In this review, we provide a summarization of the strong field ionization occurring on the surface of nanosystems. The molecules attached to the nanoparticle surface perform as the precursor in the ionization and excitation of the whole nanosystem, the fundamental processes of which are yet to be discovered. We discuss the influence on nanoparticle constituents, geometric shapes and sizes, as well as the specific waveforms of the excitation laser fields. The intriguing characteristics observed in surface ion emission reflect how enhanced near field affects the localized ionizations and nanoplasma expansions, thereby paving the way for further precision controls on the light-and-matter interactions in the extreme spatial temporal levels.

AI development has brought great success to upgrading the information age. At the same time, the large-scale artificial neural network for building AI systems is thirsty for computing power, which is barely satisfied by the conventional computing hardware. In the post-Moore era, the increase in computing power brought about by the size reduction of CMOS in very large-scale integrated circuits (VLSIC) is challenging to meet the growing demand for AI computing power. To address the issue, technical approaches like neuromorphic computing attract great attention because of their feature of breaking Von-Neumann architecture, and dealing with AI algorithms much more parallelly and energy efficiently. Inspired by the human neural network architecture, neuromorphic computing hardware is brought to life based on novel artificial neurons constructed by new materials or devices. Although it is relatively difficult to deploy a training process in the neuromorphic architecture like spiking neural network (SNN), the development in this field has incubated promising technologies like in-sensor computing, which brings new opportunities for multidisciplinary research, including the field of optoelectronic materials and devices, artificial neural networks, and microelectronics integration technology. The vision chips based on the architectures could reduce unnecessary data transfer and realize fast and energy-efficient visual cognitive processing. This paper reviews firstly the architectures and algorithms of SNN, and artificial neuron devices supporting neuromorphic computing, then the recent progress of in-sensor computing vision chips, which all will promote the development of AI.

Exploring the realms of physics that extend beyond thermal equilibrium has emerged as a crucial branch of condensed matter physics research. It aims to unravel the intricate processes involving the excitations, interactions, and annihilations of quasi- and many-body particles, and ultimately to achieve the manipulation and engineering of exotic non-equilibrium quantum phases on the ultrasmall and ultrafast spatiotemporal scales. Given the inherent complexities arising from many-body dynamics, it therefore seeks a technique that has efficient and diverse detection degrees of freedom to study the underlying physics. By combining high-power femtosecond lasers with real- or momentum-space photoemission electron microscopy (PEEM), imaging excited state phenomena from multiple perspectives, including time, real space, energy, momentum, and spin, can be conveniently achieved, making it a unique technique in studying physics out of equilibrium. In this context, we overview the working principle and technical advances of the PEEM apparatus and the related laser systems, and survey key excited-state phenomena probed through this surface-sensitive methodology, including the ultrafast dynamics of electrons, excitons, plasmons, spins, etc., in materials ranging from bulk and nano-structured metals and semiconductors to low-dimensional quantum materials. Through this review, one can further envision that time-resolved PEEM will open new avenues for investigating a variety of classical and quantum phenomena in a multidimensional parameter space, offering unprecedented and comprehensive insights into important questions in the field of condensed matter physics.

Valleytronics is an emergent discipline in condensed matter physics and offers a new way to encode and manipulate information based on the valley degree of freedom in materials. Among the various materials being studied, Kekulé distorted graphene has emerged as a promising material for valleytronics applications. Graphene can be artificially distorted to form the Kekulé structures rendering the valley-related interaction. In this work, we review the recent progress of research on Kekulé structures of graphene and focus on the modified electronic bands due to different Kekulé distortions as well as their effects on the transport properties of electrons. We systematically discuss how the valley-related interaction in the Kekulé structures was used to control and affect the valley transport including the valley generation, manipulation, and detection. This article summarizes the current challenges and prospects for further research on Kekulé distorted graphene and its potential applications in valleytronics.

We have investigated the flux symmetry on the capsule in a six-cylinder-port hohlraum for improving the design of the hohlraum. The influence factors of drive symmetry on the capsule in the hohlraum are studied, including laser power, laser beams arrangement, hohlraum geometric parameters, plasma condition, capsule convergence, etc. The x-ray radiation flux distribution on the capsule is obtained based on the three-dimensional view factor model. In the six-cylinder-port hohlraum, the main drive asymmetry is the C₄₀ mode asymmetry. When the C₄₀ mode asymmetry approaches zero, the drive symmetry on the capsule is optimal. Our results demonstrate that in order to have a high flux symmetry on the capsule in the laser main-pulse stage, more negative initial C₄₀ modes are needed, which can be realized by adjusting the hohlraum geometry parameters. The hohlraum with column length L_H = 4.81 mm has an optimal symmetry in the laser main-pulse stage.

The structural phase transitions of bismuth under rapid compression has been investigated in a dynamic diamond anvil cell using time-resolved synchrotron x-ray diffraction. As the pressure increases, the transformations from phase I, to phase II, to phase III, and then to phase V have been observed under different compression rates at 300 K. Compared with static compression results, no new phase transition sequence appears under rapid compression at compression rate from 0.20 GPa/s to 183.8 GPa/s. However, during the process across the transition from phase III to phase V, the volume fraction of product phase as a function of pressure can be well fitted by a compression-rate-dependent sigmoidal curve. The resulting parameters indicate that the activation energy related to this phase transition, as well as the onset transition pressure, shows a compression-rate-dependent performance. A strong dependence of over-pressurization on compression rate occurs under rapid compression. A formula for over-pressure has been proposed, which can be used to quantify the over-pressurization.

Topological Dirac semimetals (DSMs) present a kind of topologically nontrivial quantum state of matter, which has massless Dirac fermions in the bulk and topologically protected states on certain surfaces. In superconducting DSMs, the effects of their nontrivial topology on superconducting pairing could realize topological superconductivity in the bulk or on the surface. As superconducting pairing takes place at the Fermi level E_F, to make the effects possible, the Dirac points should lie in the vicinity of E_F so that the topological electronic states can participate in the superconducting paring. Here, we show using angle-resolved photoelectron spectroscopy that in a series of (Ir_1−xPt_x)Te₂ compounds, the type-II Dirac points reside around E_F in the superconducting region, in which the bulk superconductivity has a maximum T_c of ∼ 3 K. The realization of the coexistence of bulk superconductivity and low-energy Dirac fermions in (Ir_1−xPt_x)Te₂ paves the way for studying the effects of the nontrivial topology in DSMs on the superconducting state.