It was broadly known that the addition of a small amount of sulfur into the reactor drastically changes the behavior of single-walled carbon nanotube (SWCNT) growth. However, due to the lack of in situ characterization technologies and the limitations of computational approaches, our understanding of the role of sulfur in SWCNT growth remains very poor. To resolve the long-term mystery of the carbon society, we employed a highly accurate machine learning force field (MLFF)-based molecular dynamics (MD) approach to explore the role of sulfur in SWCNT growth from Fe catalyst particles. We successfully grew defect-free SWCNTs on Fe catalyst particles with different sulfur contents via MLFF-MD simulations, and through systematic studies, we found that sulfur atoms are prone to passivate the surface of Fe clusters first. The sulfur-passivated Fe cluster surface is less active for carbon adsorption and SWCNT nucleation. Thus, the addition of both sulfur and carbon onto an Fe cluster during SWCNT growth leads to the formation of a sulfur-rich region and a carbon-rich region on the Fe catalyst surface, which facilitates the nucleation and growth of smaller SWCNTs from the carbon-rich regions. Consequently, more sulfur addition results in a smaller carbon-rich region and the growth of smaller SWCNTs, but an excessive amount of sulfur may poison the catalysts. This insightful understanding agrees very well with most experimental observations, and thus, the long-term mystery of the carbon society was successfully resolved by the artificial intelligence (AI)-assisted computational approach. These deep insights offer a strategy for synthesizing SWCNTs with controlled diameters through proper catalyst passivation, and they also show that the mechanism of SWCNT growth can be revealed via advanced theoretical studies powered by AI.

Transition metal dichalcogenides (TMDs) exhibit polymorphism with distinct electronic properties, where the semiconducting H-phase is thermodynamically more stable than the metallic T-phase. Despite the inherent instability of the T-phase, its transition to the H-phase is remarkably hindered even under elevated temperatures—a phenomenon that remains poorly understood. Here, we elucidate this paradox through a combined First-principles and molecular dynamics study of MoS2 phase transitions. Our results reveal that both nucleation and migration pathways for T/T'→H conversion are governed by substantial energy barriers at initial stages, with nucleation requiring an exceptionally high barrier of 0.17 eV/unit. This kinetic bottleneck originates from the “binary stability” of the T-phase, namely, the bonding stability and the structural perfection of the lattice. The disruption of this perfect lattice dramatically lowers transition barriers, enabling rapid phase propagation. These findings establish a universal kinetic trapping mechanism for metastable T-phases in TMDs, providing critical insights for phase-controlled material design.

We predict a novel 2D non-centrosymmetric Al2O3 (NCS-Al2O3) structure using first-principles calculations combined with the MAGUS structure search package. This puckered hexagonal structure, featuring an "O-Al-O-Al-O" stacking sequence, exhibits exceptional stability with a formation energy of -2.88 eV per atom, surpassing that of a previously reported planar monolayer phase (-2.39 eV per atom) and closer to the bulk α-Al2O3 value (-3.16 eV per atom). It is an indirect bandgap semiconductor (3.98 eV) with intermediate mechanical stiffness and relatively strong anisotropy (AU ∼ 7.99). Crucially, the broken inversion symmetry enables strong in-plane piezoelectricity (∼0.6 C m-2). Most significantly, an out-of-plane electric field can reversibly switch the NCS-Al2O3 structure between centrosymmetric and non-centrosymmetric states by modulating a low energy barrier (∼0.11 eV). This unique electric-field-responsive behavior, coupled with its high stability and piezoelectricity, positions NCS-Al2O3 as a promising candidate for applications in 2D electronics, in-plane piezoelectric sensors, and electric-field-gated non-volatile memory devices.

Leveraging the inherent advantages of biomass, being renewable, biodegradable, environment friendly, and lowcost, its unique and modifiable structure enables diverse roles in supercapacitors. Herein, we develop a highperformance deep eutectic solvent (DES)-based gel electrolyte reinforced by lignin nanoparticles (LNPs) through enhanced hydrogen-bonding network and strengthened non-covalent interactions. The optimized eutectogel electrolyte exhibits an excellent ionic conductivity of 13.53 mS cm- 1, with outstanding mechanical strength, adhesiveness, self-healing ability, and cryogenic adaptability (-24 degrees C), while maintaining high conductivity across a wide temperature range (10 to 85 degrees C) and a voltage window of 2.8 V (-1.5 to 1.3 V). Furthermore, the eutectogel demonstrates superior flexibility and reliable stress-sensing performance during human movement. A fabricated quasi-solid-state supercapacitor with LNPs-derived carbon aerogel electrodes and this electrolyte delivers a high specific capacitance of 104 F g- 1 at 0.5 A g- 1 and a maximum energy density of 36.98 W h kg- 1, underscoring lignin's great potential as a prominent candidate for next-generation energy storage devices.

Achieving efficient and sustainable lithium extraction from silicate ores remains a major challenge due to the high temperatures and complex phase transformations required in conventional processes. Here, we report a microwave-assisted alkali roasting strategy that enables near-complete lithium recovery under mild conditions (~250 °C and 1 atm). Microwave irradiation selectively couples with alkali and α-spodumene, activating the roasting reaction to form soluble lithium-bearing phases without the energy-intensive phase transition in conventional routes. Subsequent ultrasound-enhanced leaching achieves nearly 100% lithium extraction, markedly higher than the 57.5% obtained via conventional roasting under identical conditions, while minimizing solid residue generation. The leachate undergoes gradient precipitation purification in ultrasonic field, removing over 99% of impurity elements (Si, Al etc.) with minimal lithium loss, yielding industrial-grade Li2CO3 with an overall recovery of 98.86%. This integrated microwave-ultrasound process reduces solid waste generation by ~20%–35% relative to traditional acid-based routes. Beyond spodumene, this approach is readily extendable to other lithium-bearing minerals, offering a green and energy-efficient pathway for sustainable lithium production.

Using DFT and global structure search, a new non-centrosymmetric Al 2 O 3 is predicted. The structure can be tuned by using an external electric field. These results offer a pathway toward electric-field-gated non-volatile memory devices.

Single-walled carbon nanotubes (SWCNTs) act as one-dimensional (1D) nanoreactors capable of stabilizing reactive species and unique low-dimensional phases. Here, we report the synthesis of an unprecedented 1D Sc3Cl8 phase formed via the confinement-induced structural reconstruction of bulk ScCl3 within SWCNTs. The atomic structure of the Sc3Cl8@SWCNT heterostructure is determined by combining aberration-corrected electron microscopy (HRTEM/STEM) with machine-learning force field (MLFF) global structure searches. This reconstruction yields a metal-rich phase that exhibits two anomalous properties. First, unlike typical halide fillers that induce p-type doping, the Sc3Cl8 chain acts as a potent electron donor, driving a strong n-type charge transfer to the nanotube host (a phenomenon we term "redox inversion"). Second, spin-polarized density functional theory (DFT) predicts that the confined chain possesses a ferromagnetic ground state, emerging from a diamagnetic bulk precursor. These results identify Sc3Cl8@SWCNTs as a model heterostructure where confinement simultaneously inverts doping polarity and unlocks magnetic potential, offering a new platform for carbon-based spintronics.

Bio-inspired synaptic devices have demonstrated considerable potential in neuromorphic computing and intelligent sensing, owing to their remarkable ability to mimic the efficient multimodal integration of biological neural systems. However, the development of high-performance artificial synaptic devices that integrate both sensing and computing functions remains a significant challenge. In this study, we present a bio-inspired synaptic device based on Si@BP that utilizes silicon-doped black phosphorus (BP) to enhance both the stability and photodetection capability of BP. This device integrates optical sensing with selective detection capabilities in environments characterized by extremely low ammonia concentrations (as low as 20 ppm), and further enables cross-modal perception at the neuromorphic level. This enables the associative integration of visual and olfactory signals, effectively mimicking advanced cognitive behaviors of biological synapses. Furthermore, a spiking neural network constructed with this device achieved 91.17% accuracy on the MNIST classification task via unsupervised learning, validating its computational capability. This study not only confirms the application potential of Si@BP synaptic devices in optoelectronic neuromorphic systems, but more importantly, by realizing visual-olfactory co-sensing and efficient computing, provides novel insights for developing multimodal intelligent perception and significantly advances the development of bioinspired sensing-computing integration technologies.

Ultraviolet (UV) photodetectors play a critical role in a wide range of applications, including environmental monitoring and optical communication systems. However, a significant challenge remains in enabling band-selective and adaptive detection across distinct UV spectral regions─specifically UVA (320-400 nm) and UVC (200-280 nm)─within a single, compact device. To address this limitation, we present a novel dual-band UV photodetector based on a single SiC/SiO2/Ga2O3 core-shell-satellite nanowire heterojunction. In this radial configuration, a SiC nanowire functions as the central core, an amorphous SiO2 layer is formed via in situ thermal oxidation, and gallium oxide (Ga2O3) nanoparticles serve as satellite sensitizers. By precisely engineering the energy band alignment of the heterostructure, the device achieves selective detection of UVA and UVC radiation. Under 365 nm (UVA) illumination, photon absorption and photocurrent generation occur exclusively in the SiC core (bandgap ∼2.4 eV). In contrast, upon exposure to 254 nm (UVC) irradiation, a synergistic photoresponse is activated between the Ga2O3 satellites (bandgap ∼4.7 eV) and the SiC core, resulting in significantly enhanced performance: a responsivity of 1547 A/W, an external quantum efficiency of 5.3 × 105%, and rapid response and recovery times of 98 and 93 ms, respectively. This superior UVC performance is attributed to efficient carrier separation and transport within the heterojunction, enabled by the intermediate SiO2 layer, which serves dual roles as a passivation layer and a carrier tunneling medium. This study not only introduces a novel material framework for advanced UV photodetectors but also offers valuable insights into the photophysical mechanisms underlying complex heterojunction systems, thereby contributing to the advancement of adaptive and multifunctional optoelectronic technologies.

Anisotropic materials with intrinsic one-dimensional architectures, where chains or tubes align along a crystallographic axis, exhibit direction-dependent optical responses and serve as ideal building blocks for polarization-sensitive optoelectronics. While progress exists in engineered compounds, discovering elemental crystals with naturally ordered one-dimensional building blocks exhibiting giant optical anisotropy remains challenging. Here, we report the synthesis of a direct-bandgap semiconducting one-dimensional phosphorus single crystal composed of unique wavy polygonal tubes. The monoclinic lattice structure is revealed by single-crystal X-ray diffraction and advanced transmission electron microscopy. The crystal exhibits giant birefringence in the visible and near-infrared regions, stemming from electron localization and anisotropic transitions of the phosphorus 3p orbital along the tube axis. The low-symmetry structure endows remarkable linear and nonlinear optical anisotropies, including orientation-dependent photoluminescence, Raman scattering, and second-harmonic generation. This study establishes a paradigm for designing giant optical anisotropies, opening avenues for on-chip polarization devices and nonlinear photonic circuits.

Monitoring arc discharges in power devices is critical for identifying early insulation degradation and avoiding eventual insulation failure. Deep-ultraviolet (UV) signals from discharge arcs offer low background noise and anti-interference capability, making UV detection a standard approach for arc discharge identification. However, in enclosed metal switchgear, the UV optical path is often blocked, rendering conventional single-mode UV sensors ineffective and necessitating a method that works under optically obstructed conditions. To this end, an adaptive dual-mode heterojunction device based on a vertically aligned 4H-SiC nanowire array (NWA) was fabricated, which integrates both solar-blind UV detection and electromagnetic (EM) pulse detection capabilities on a single chip. When the optical path is clear, the device operates in solar-blind UV detection mode: the vertically aligned 4H-SiC NWAs absorbs 254 nm and 365 nm UV light, and the built-in electric field efficiently separates photogenerated carriers, delivering a high detectivity of 1.2 × 1010 Jones. When the optical path is blocked or when longer-range monitoring is needed, the device adaptively responds to EM pulse detection mode. In this mode, the conductive network acts as a broadband antenna to capture arc-induced EM pulses, which are then rectified by the graphene oxide/silver Schottky junction, achieving a response time of 630 ms. The simultaneous availability of both sensing modalities on a single compact device not only provides resilience to optical obstruction but also enables cross-validation of UV and EM signatures. This adaptive dual-mode design offers a space-saving solution for online arc monitoring in smart grids and enhancing early fault warning capability.

Aqueous-phase reforming of methanol (APRM) is a promising pathway for sustainable hydrogen production. However, achieving high hydrogen yields with minimal CO by-products remains challenging due to insufficient control over active facet exposure and weak metal-support interaction (MSI). In this work, MgO supports with fully exposed (111) facets were synthesized via a synergistic hydrothermal-ball milling approach and loaded with Pt nanoparticles. Catalytic evaluation at 190 degrees C demonstrated that Pt-MgO(111) achieved a hydrogen production rate of 170 mmol g-1 h-1, while maintaining markedly ultra-low CO selectivity of 0.01% owing to enhanced water-gas shift (WGS) activity. Density functional theory (DFT) calculations revealed that MgO(111) forms stronger MSI with Pt and increases their electronic reactivity, thereby promoting key reaction steps. Integrated mechanistic studies, combining control experiments and in situ CO-DRIFTS, confirmed that methanol cleavage occurs at the Pt/MgO interface, the WGS reaction takes place on MgO(111) facets, and methanation occurs on metallic Pt. This work provides mechanistic insights into MSI-driven site cooperation and offers a general strategy for the rational design of facet-engineered oxide-supported catalysts for low-temperature hydrogen production.

High illumination power and high temperature can severely impact the photoresponse performance and operational stability of SiC nanowire-based UV photodetectors (PDs) due to the increased carrier recombination, saturation absorption, and thermal degradation. To overcome these limitations, a novel single-nanowire UV photodetector based on a SiC/amorphous BN (a-BN) core-shell heterostructure is successfully constructed, which efficiently improves surface passivation, thermal stability, and separation of photoexcited carriers. Under intense 365 nm illumination, the device exhibits a remarkable superlinear photoresponse of 2.39, far exceeding the typical sublinear behavior of SiC PDs, accompanied by high responsivity (2541.87 A W-1), detectivity (2.08 & times; 10(10) Jones), external quantum efficiency (EQE) (8.65 & times; 10(5)%), and rapid rise/decay times (76/83 ms). Even at 200 degrees C, it maintains robust performance with a responsivity of 226 A W-1, detectivity of 1.48 & times; 10(9) Jones, and EQE of 0.77 & times; 10(5)%, demonstrating the excellent thermal endurance. Theoretical analysis attributes this robust superlinear response to enhanced carrier separation and transport, rapid saturation of interfacial states, accelerated detrapping, and suppressed recombination within the SiC/a-BN and Au-SiC/a-BN heterojunctions. This study provides a solid foundation for the development of thermally stable superlinear UV PDs with potential for high-resolution imaging in harsh environments.

To address the high-temperature degradation of conventional Pd-based hydrogen sensors, this study proposes a Pd/SiC@C core-shell nanowire heterostructure. Under UV irradiation, the localized surface plasmon resonance effect in Pd nanoparticles significantly enhances hydrogen adsorption and diffusion. At 300 degrees C, the sensor achieves a response of 27% to 20 ppm H2, with response and recovery times of 3.5 s and 6.2 s, respectively. It maintains high sensitivity across a wide operating temperature range (50-300 degrees C) and H2 concentration range (20-200 ppm). Notably, after 30 consecutive days of operation at 300 degrees C, the device exhibits negligible performance degradation. First-principles calculations confirm strong H2 adsorption and significant interfacial charge transfer at the Pd(111)/SiC(111) interface, supporting the proposed electronic sensitization mechanism. This work establishes a robust design strategy for high-temperature, high-performance hydrogen sensors.

Atomically confined metals inside single-walled carbon nanotubes (SWCNTs) offer an underexplored route to modulate the electronic properties of the carbon host for complementary nanoelectronics. Here, we employ vapor-phase filling and confined H2 reduction to construct metallic yttrium (Y) nanostructures within SWCNTs. Aberration-corrected scanning transmission electron microscopy (STEM) and high-resolution TEM (HRTEM) resolve diameter-dependent face-centered cubic (fcc) Y motifs and packing configurations under confinement, revealing confinement-induced stabilization of a phase otherwise thermodynamically unfavorable in bulk yttrium. Furthermore, in situ environmental TEM (ETEM) directly visualizes the shielding effect of the sp2 carbon lattice, which protects the highly reactive yttrium guest from oxidation. Combining density functional theory (DFT) calculations and Raman spectroscopy, we demonstrate that encapsulated Y donates electrons to the SWCNT host (e.g., ∼8.6 e per supercell for a (14, 0)SWCNT), driving host metallization and metallic-like phonon responses. Crucially, we uncover a diameter-dependent trade-off between Y structural continuity and total electron donation that governs this electronic reconstruction. By leveraging electron-rich metallic Y@SWCNT segments as air-stable composite-contact extensions, we fabricate top-gated field-effect transistors (FETs) that exhibit contact-induced n-type-dominated transport. This work bridges confined configurations, colossal charge transfer, and air-stable device performance, providing a strategy for Fermi-level engineering and n-type contact architectures in carbon nanoelectronics.

Conventional PI films exhibit excellent thermal stability; however, their weak self-healing under electrical and mechanical stress limits operational reliability. Herein, a machine-learning-guided screening strategy is employed to predict the Eb of sulfur-modulated PI systems, enabling the rapid identification of optimal disulfide incorporation. As a result, a series of PI films with varying disulfide contents (0-30 wt.%) are fabricated. The results reveal a non-monotonic dependence of Eb on disulfide content, with an optimal composition (PI-15) achieving a high Eb of 700 kV mm-1 and a Wdis of 10.02 J cm-3 at RT, together with 670 kV mm-1 and 6.64 J cm-3 at 150°C. Notably, after self-healing, PI-15 retains high performance, with Eb recovering to 675 and 640 kV mm-1 and Wdis to 8.59 and 6.02 J cm-3 at RT and 150°C, respectively. In addition, the films exhibit excellent operational stability under temperature, frequency, and fatigue cycling at 500 kV mm-1. Mechanistically, disulfide incorporation enables a synergistic coupling of strengthened intermolecular interactions and dynamic bond exchange, suppressing charge transport and local field concentration while facilitating structural rearrangement. This work demonstrates new working mechanisms for designing high-performance PI, providing strong potential for high-temperature capacitive energy storage under harsh operating conditions.

In recent years, mixed-dimensional p-n heterojunctions have exhibited promising optoelectronic properties. With the advancement of optoelectronic devices, unbiased (self-powered) photodetectors can better meet the requirements of specific scenarios. However, under zero-bias operation, the photocurrent is typically small, resulting in limited detectivity. To address this issue, this paper constructed a BP/n-GaN heterojunction photodetector through mechanical exfoliation, successfully increasing the performance of the GaN photodetector by 4-6 orders of magnitude. First, black phosphorus (BP) was synthesized via chemical vapor transport (CVT) and subsequently transferred onto an /n-GaN film to construct a BP/n-GaN heterojunction. Then, the I-V characteristics, light response and other key performances of the self-powered ultraviolet photoelectric detector based on the BP/n-GaN heterostructure were investigated. It was found that under no external bias and 365 nm illumination, the heterostructure device exhibits good rectification behavior, with a responsivity of 0.023 A/W and a detectivity is 2.9 & times; 10(11) Jones. Compared to the GaN photoelectric detector fabricated in this paper, the performance of the heterostructure device has improved by 4 orders of magnitude in terms of detection rate and response rate. Moreover, the UPS, ultraviolet-visible absorption spectroscopy tests and theoretical calculations determined the type II band alignment of the BP/n-GaN heterojunction, which can effectively separate photogenerated carriers. This study indicates that this BP/n-GaN heterojunction photodetector leverages the high carrier mobility of black phosphorus to enhance carrier transport and collection under zero bias, providing an emerging low-power UV photodetection platform relevant to nanophotonics-oriented UV sensing and communication.

The structural evolution of gold clusters has been investigated by numerous density functional theory (DFT) studies. However, due to the slow computational efficiency of DFT, these studies tend to be scattered and lack systematicness. We have developed a robust machine learning force field (MLFF) of gold. The accuracy and robustness of the MLFF were validated by comparing DFT results. By integrating the highly efficient MLFF, which is about 1000,000 times faster than DFT calculations, with the CALYPSO global search method, we systematically explored Aun clusters spanning a wide range of sizes (n = 2-55) and uncovered several key issues: (i) revealing the critical transition points from planar to 3D structures (n = 14) and from cage-like to core-shell structures (n > 26); (ii) discovering new stable cluster structures; (iii) conducting an in-depth analysis of the core-shell model. This study shows that MLFF can be used to study complex structural systems like clusters and address systematic issues related to larger clusters. It also indicates the potential of MLFF in tackling more complex problems, including mixed and ligand-protected clusters.