Search

Chalcogenide material-based integrated photonic devices have garnered widespread attention due to their unique wideband transparency. Despite their recognized CMOS compatibility, the fabrication of these devices relies predominantly on lithography techniques. However, chalcogenide thin films are highly susceptible to oxidation, necessitating customized process flows and complex protective measures during lithography. These requirements are hardly compatible with current commercial CMOS manufacturing platforms designed for silicon photonics, significantly limiting the practical applications of chalcogenide photonic devices. In this work, we ingeniously exploit the ease of oxidation of chalcogenide materials, presenting a novel laser-induced localized oxidation technique for spatial patterning on chalcogenide thin films, enabling concise lithography-free fabrication of chalcogenide integrated photonic devices. Using Sb2S3 as an example, we experimentally demonstrate localized multi-level oxidation with a sizable overall refractive index contrast of 0.7 at near-infrared, featuring a high spatial resolution of 0.6 um. Based on this technique, multiple integrated photonic devices are demonstrated, showing versatile functionalities, including color printing at visible and metasurface-based spatial light modulation at near-infrared regions. Leveraging the inherent phase-change property of Sb2S3, an active Fresnel zone plate, enabling switchable beam focusing, is further demonstrated, indicating the feasibility of concise fabrication of active photonic devices. Our work offers a brand-new modulation dimension for chalcogenide materials and provides a significantly simplified approach for realizing chalcogenide-integrated photonic devices.

Nitrate reduction to ammonia has attracted much attention for nitrate (NO3-) removal and ammonia (NH3) production. Identifying promising catalyst for active nitrate electroreduction reaction (NO3RR) is critical to realize efficient upscaling synthesis of NH3 under low-temperature condition. For this purpose, by means of spin-polarized first-principles calculations, the NO3RR performance on a series of graphitic carbon nitride (g-CN) supported double-atom catalysts (denoted as M1M2@g-CN) are systematically investigated. The synergistic effect of heterogeneous dual-metal sites can bring out tunable activity and selectivity for NO3RR. Amongst 21 candidates examined, FeMo@g-CN and CrMo@g-CN possess a high performance with low limiting potentials of -0.34 and -0.39 V, respectively. The activities can be attributed to a synergistic effect of the M1M2 dimer d orbitals coupling with the anti-bonding orbital of NO3-. The dissociation of deposited FeMo and CrMo dimers into two separated monomers is proved to be difficult, ensuring the kinetic stability of M1M2@g-CN. Furthermore, the dual-metal decorated on g-CN significantly reduces the bandgap of g-CN and broadens the adsorption window of visible light, implying its great promise for photocatalysis. This work opens a new avenue for future theoretical and experimental design related to NO3RR photo-/electrocatalysts.

Patterning antidots ("voids") into well-defined antidot lattices creates an intriguing class of artificial structures for the periodic modulation of 2D electron systems, leading to anomalous transport properties and exotic quantum phenomena as well as enabling the precise bandgap engineering of 2D materials to address technological bottleneck issues. However, realizing such atomic-scale quantum antidots (QADs) is infeasible by current nanolithographic techniques. Here, we report an atomically-precise bottom-up fabrication of a series of atomic-scale QADs with elegantly engineered quantum states through a controllable assembly of a chalcogenide single vacancy (SV) in 2D PtTe2, a type-II Dirac semimetal. Te SVs as atomic-scale "antidots" undergo thermal migration and assembly into highly-ordered SV lattices spaced by a single Te atom, reaching the ultimate downscaling limit of antidot lattices. Increasing the number of SVs in QADs strengthens the cumulative repulsive potential and consequently enhances collective interference of multiple-pocket scattered quasiparticles inside QADs, creating multi-level quantum hole states with tunable gap from telecom to far-infrared regime. Moreover, precisely engineered quantum hole states of QADs are symmetry-protected and thus survive upon atom-by-atom oxygen substitutional doping. Therefore, SV-assembled QADs exhibit unprecedented robustness and property tunability, which not only holds the key to their future applications but also embody a wide variety of material technologies.

Lead-free tin-based perovskites are highly appealing for the next generation of solar cells due to their intriguing optoelectronic properties. However, the tendency of Sn2+ oxidation to Sn4+ in the tin-based perovskites induces serious film degradation and performance deterioration. Herein, we demonstrate, through the density functional theory based first-principle calculations in a surface slab model, that the surface defects of the Sn-based perovskite FASnI3 (FA = NH2CHNH2+) could be effectively passivated by the Lewis base molecules. The passivation performance of Lewis base molecules in tin-based perovskite is tightly correlated with their molecular hardness. We reveal that the degree of hardness of Lewis adsorbate governs the stabilization via dual effects: first, changing the stubborn spatial distribution of tin vacancy (VSn) by triggering charge redistribution; second, saturating the dangling states while simultaneously reducing the amounts of deep band gap states. Specifically, the hard Lewis base molecules like edamine (N-donor group) and Isatin-Cl (Cl-donor group) would show a better healing effect than other candidates on the defects-contained tin-based perovskite surface with a somehow hard Lewis acid nature. Our research provides a general strategy for additive engineering and fabricating stable and high-efficiency lead-free Sn-based perovskite solar cells.

Electrocatalysts of nitrogen reduction reaction (NRR) have attracted ever-growing attention due to its application for renewable energy alternative to fossil fuels. However, activation of inert N-N bond requires multiple complex charge injection which complicates the design of the catalysts. Here via combining atomic-scale screening and machine learning (ML) methods we explore the rational design of NRR single-atom catalysts (SACs) supported by molybdenum disulfide (MoS2). Our work reveals that the activity of NRR SACs is highly dependent on the number of unpaired d electrons of TM: positive samples with high activity favoring higher values while negative cases distributing at lower values, both varying with the doping conditions of the host. We find that the substitution of sulfur with boron can activate the intrinsic NRR activity of some TMs such as Ti and V which are otherwise inactive above pristine MoS2. Importantly, among the various de-scriptors used in ML, the charged state of adsorbed TM plays a key role in donating electron to pi-anti-bonding orbital of N2 via the back-donation mechanism. Our work shows a feasible strategy for rational design of NRR SACs and retrieval of the decisive feature of active catalysts.

Two-dimensional (2D) layered lead iodide (PbI2) is an important precursor and common residual species during the synthesis of lead-halide perovskites. There currently exist some debates and uncertainties about the effect of excess PbI2 on the efficiency and stability of the solar cell with respect to its energy alignment and energetics of defects. Herein, by applying the first-principles calculations, we investigate the energetics, changes of work function and the defective levels associated with the iodine vacancy (VI) and interstitial iodine (II) defects of monolayer PbI2 (ML-PbI2). We find that the PbI2 has a very low formation energy of VI of 0.77 and 0.19 eV for dilute and high concentration, respectively, reflecting coalescence tendency of isolated VI, much lower than that of vacancies in other 2D materials like phosphorene. Similar to VI, a low formation energy of II of 0.65 eV is found, implying a high population of such defects. Both defects generate in-gap defective levels which are mainly due to the unsaturated chemical bonds of p-orbitals of exposed Pb or inserted I. Such rich defective levels allow the VI and II as the reservoir or sinks of electron/hole carriers in PbI2. Our results suggest that the remnant PbI2 in perovskite MAPbI3 (or FAPbI3) would play dual opposite roles in affecting the efficiency of the perovskite: (1) Forming Schottky-type interface with MAPbI3 (or FAPbI3) in which the built-in potential would facilitate the electron-hole separation and prolong the carrier lifetime; (2) Acting as the recombination centers due to the deep defective levels. To promote the efficiency by the Schottky effect, our work reveals that the II defect is favored, and to reduce the recombination centers the VI defect should be suppressed. Our results shall be beneficial in improving strategies for the related optoelectronics applications.

We consider the active Brownian particle (ABP) model for a two-dimensional microswimmer with fixed speed, whose direction of swimming changes according to a Brownian process. The probability density for the swimmer evolves according to a Fokker-Planck equation defined on the configuration space, whose structure depends on the swimmer's shape, center of rotation and domain of swimming. We enforce zero probability flux at the boundaries of configuration space. We derive a reduced equation for a swimmer in an infinite channel, in the limit of small rotational diffusivity, and find that the invariant density depends strongly on the swimmer's precise shape and center of rotation. We also give a formula for the mean reversal time: the expected time taken for a swimmer to completely reverse direction in the channel. Using homogenization theory, we find an expression for the effective longitudinal diffusivity of a swimmer in the channel, and show that it is bounded by the mean reversal time., Comment: 46 pages, 24 figures. AMSart style

Artificial Neural Networks (ANNs) replaced conventional software systems in various domains such as machine translation, natural language processing, and image processing. So, why do we need an repository for artificial neural networks? Those systems are developed with labeled data and we have strong dependencies between the data that is used for training and testing our network. Another challenge is the data quality as well as reuse-ability. There we are trying to apply concepts from classic software engineering that is not limited to the model, while data and code haven't been dealt with mostly in other projects. The first question that comes to mind might be, why don't we use GitHub, a well known widely spread tool for reuse, for our issue. And the reason why is that GitHub, although very good in its class is not developed for machine learning appliances and focuses more on software reuse. In addition to that GitHub does not allow to execute the code directly on the platform which would be very convenient for collaborative work on one project., Comment: tool paper https://github.com/ghofrani85/RAN2 7 pages