The dependence of the structure of planet-opened gaps in protoplanetary disks on radiative cooling

Planets can excite density waves and open annular gas gaps in protoplanetary disks. The depth of gaps is influenced by the evolving angular momentum carried by density waves. While the impact of radiative cooling on the evolution of density waves has been studied, a quantitative correlation to connect gap depth with the cooling timescale is lacking. To address this gap in knowledge, we employ the grid-based code Athena++ to simulate disk-planet interactions, treating cooling as a thermal relaxation process. We establish quantitative dependences of steady-state gap depth (Eq. 36) and width (Eq. 41) on planetary mass, Shakura-Sunyaev viscosity, disk scale height, and thermal relaxation timescale $(\beta)$. We confirm previous results that gap opening is the weakest when thermal relaxation timescale is comparable to local dynamical timescale. Significant variations in gap depth, up to an order of magnitude, are found with different $\beta$. In terms of width, a gap is at its narrowest around $\beta=1$, approximately $10\%$ to $20\%$ narrower compared to the isothermal case. When $\beta\sim100$, it can be $\sim20\%$ wider, and higher viscosity enhances this effect. We derive possible masses of the gas gap-opening planets in AS 209, HD 163296, MWC 480, and HL Tau, accounting for the uncertainties in local thermal relaxation timescale.Comment: 19 pages, 16 figures, 4 tables, accepted for publication in Ap

Atmospheric Recyling of Volatiles by Pebble-Accreting Planets

Planets, embedded in their natal discs, harbour hot envelopes. When pebbles are accreted by these planets, the contained volatile components may sublimate, enriching the envelope and potentially changing its thermodynamical properties. However, the envelopes of embedded planets actively exchange material with the disc, which would limit the buildup of a vapour-rich atmosphere. To properly investigate these processes, we have developed a new phase change module to treat the sublimation process with hydrodynamical simultions. Combined with the recently developed multi-dust fluid approach, we conduct 2D self-consistent hydrodynamic simulations to study how pebble sublimation influences the water content of super-Earths and sub-Neptunes. We find the extent and the amount of vapour that a planet is able to hold on to is determined by the relative size of the sublimation front and the atmosphere. When the sublimation front lies far inside the atmosphere, vapour tends to be locked deep in the atmosphere and keeps accumulating through a positive feedback mechanism. On the other hand, when the sublimation front exceeds the (bound) atmosphere, the ice component of incoming pebbles can be fully recycled and the vapour content reaches a low, steady value. Low disc temperature, small planet mass and high pebble flux (omitting accretion heating by pebbles) render the planet atmosphere vapour-rich while the reverse changes render it vapour-poor. The phase change module introduced here can in future studies also be employed to model the chemical composition of the gas in the vicinity of accreting planets and around snowlines.Comment: 21 pages, 16 figures. Accepted for publication in MNRAS on June 5th 202

Learning to Check Contract Inconsistencies

Contract consistency is important in ensuring the legal validity of the contract. In many scenarios, a contract is written by filling the blanks in a precompiled form. Due to carelessness, two blanks that should be filled with the same (or different)content may be incorrectly filled with different (or same) content. This will result in the issue of contract inconsistencies, which may severely impair the legal validity of the contract. Traditional methods to address this issue mainly rely on manual contract review, which is labor-intensive and costly. In this work, we formulate a novel Contract Inconsistency Checking (CIC) problem, and design an end-to-end framework, called Pair-wise Blank Resolution (PBR), to solve the CIC problem with high accuracy. Our PBR model contains a novel BlankCoder to address the challenge of modeling meaningless blanks. BlankCoder adopts a two-stage attention mechanism that adequately associates a meaningless blank with its relevant descriptions while avoiding the incorporation of irrelevant context words. Experiments conducted on real-world datasets show the promising performance of our method with a balanced accuracy of 94.05% and an F1 score of 90.90% in the CIC problem.Comment: Accepted by AAAI 202

Efficient and bright warm-white electroluminescence from lead-free metal halides.

Solution-processed metal-halide perovskites are emerging as one of the most promising materials for displays, lighting and energy generation. Currently, the best-performing perovskite optoelectronic devices are based on lead halides and the lead toxicity severely restricts their practical applications. Moreover, efficient white electroluminescence from broadband-emission metal halides remains a challenge. Here we demonstrate efficient and bright lead-free LEDs based on cesium copper halides enabled by introducing an organic additive (Tween, polyethylene glycol sorbitan monooleate) into the precursor solutions. We find the additive can reduce the trap states, enhancing the photoluminescence quantum efficiency of the metal halide films, and increase the surface potential, facilitating the hole injection and transport in the LEDs. Consequently, we achieve warm-white LEDs reaching an external quantum efficiency of 3.1% and a luminance of 1570 cd m-2 at a low voltage of 5.4 V, showing great promise of lead-free metal halides for solution-processed white LED applications

DeePMD-kit v2: A software package for Deep Potential models

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, Deep Potential - Range Correction (DPRc), Deep Potential Long Range (DPLR), GPU support for customized operators, model compression, non-von Neumann molecular dynamics (NVNMD), and improved usability, including documentation, compiled binary packages, graphical user interfaces (GUI), and application programming interfaces (API). This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, the article benchmarks the accuracy and efficiency of different models and discusses ongoing developments.Comment: 51 pages, 2 figure