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In the present study, by adopting the advantage of ultrasonic techniques, we developed a Multichannel Pulsed Ultrasonic Doppler Velocimetry (MPUDV) to measure the 2D2C velocity fields of liquid metal flow. Due to the specially designed Ultrasonic host and post-processing scheme, the MPUDV system can reach a high spatiotemporal resolution of 50 Hz and 3 mm. The flow loop contains a cavity test section to ensure a classical recirculating flow was built to validate the accuracy of MPUDV in velocity field measurement. In the initial phase of the study, water with tracer particles was selected as the working liquid to ensure the velocity field measurements by the well-developed Particle Image Velocimetry (PIV). A comparison of the data obtained from the PIV and MPUDV methods revealed less than 3 differences in the 2D2C velocity field between the two techniques during simultaneous measurements of the same flow field. This finding strongly demonstrates the reliability of the MPUDV method developed in this paper. Moreover, the ternary alloy GaInSn was selected as the working liquid in the flow loop to validate the efficacy of the MPUDV in measuring 2D-2C velocity fields. A series of tests were conducted in the cavity at varying Reynolds numbers, ranging from 9103 to 24123. The measurements demonstrated that the MPUDV could accurately measure the flow structures characterized by a central primary circulation eddy and two secondary eddies in the opaque liquid metal. Furthermore, it was found that the vortex center of the primary circulating eddy and the size of the secondary eddies undergo significant alterations with varying Reynolds numbers, indicating the influence of inertial force on the flow characteristics in the recirculating flow. It is therefore demonstrated that the current MPUDV methodology is applicable for measuring a 2D2C velocity field in opaque liquid metal flows., Comment: 23 pages, 12 figures

Rechargeable Zn batteries offer safe, inexpensive energy storage, but when deeply discharged to compete with lithium-ion batteries, they are plagued by parasitic reactions at the Zn anodes. We apply super-concentrated alkaline electrolytes to suppress two key parasitic reactions, hydrogen evolution and ZnO passivation. An electrolyte with 15 M KOH displays a broad electrochemical window (>2.5 V on Au), a high ZnO solubility (>1.5 M), and an exceptionally high ionic conductivity (>0.27 S/cm at 25 C). Spectroscopies and ab-initio molecular dynamics simulation suggest K+-OH- pairs and a tightened water network to underpin the stability. The simulation further reveals unique triggered proton hopping that offsets the lack of water wires to sustain the conductivity. Low hydrogen evolution, confirmed via online mass spectroscopy, and slow passivation enable a NiOOH||Zn battery to deliver a cumulative capacity of 8.4 Ah cm-2 and a Zn-air battery to last for over 110 hours.

How life started on Earth is an unsolved mystery. There are various hypotheses for the location ranging from outer space to the seafloor, subseafloor or potentially deeper. Here, we applied extensive ab initio molecular dynamics (AIMD) simulations to study chemical reactions between NH$_3$, H$_2$O, H$_2$, and CO at pressures (P) and temperatures (T) approximating the conditions of Earth's upper mantle (i.e. 10-13 GPa, 1000-1400 K). Contrary to the previous assumptions that larger organic molecules might readily disintegrate in aqueous solutions at extreme P-T conditions, we found that many organic compounds formed without any catalysts and persisted in C-H-O-N fluids under these extreme conditions, including glycine, ribose, urea, and uracil-like molecules. Particularly, our free energy calculations showed that the C-N bond is thermodynamically stable at 10 GPa and 1400 K. Moreover, while the pyranose (six-membered-ring) form of ribose is more stable than the furanose (five-membered-ring) form at ambient conditions, we observed the predominant formation of the five-membered-ring form of ribose at extreme conditions, which is consistent with the exclusive incorporation of $\beta$-D-ribofuranose in RNA. We have uncovered a previously unexplored pathway through which the building blocks of biomolecules may have originated in early Earth and other planets. Our findings contribute to an evolving understanding of the fundamental conditions necessary for life to arise., Comment: 18 pages, 6 figures, 1 table

We propose a variational modelling method with differentiable temperature for canonical ensembles. Using a deep generative model, the free energy is estimated and minimized simultaneously in a continuous temperature range. At optimal, this generative model is a Boltzmann distribution with temperature dependence. The training process requires no dataset, and works with arbitrary explicit density generative models. We applied our method to study the phase transitions (PT) in the Ising and XY models, and showed that the direct-sampling simulation of our model is as accurate as the Markov Chain Monte Carlo (MCMC) simulation, but more efficient. Moreover, our method can give thermodynamic quantities as differentiable functions of temperature akin to an analytical solution. The free energy aligns closely with the exact one to the second-order derivative, so this inclusion of temperature dependence enables the otherwise biased variational model to capture the subtle thermal effects at the PTs. These findings shed light on the direct simulation of physical systems using deep generative models, Comment: Main text: 4.5 pages, 2 figures. Supplement: 9 pages

In this study, we introduce CT-LLM, a 2B large language model (LLM) that illustrates a pivotal shift towards prioritizing the Chinese language in developing LLMs. Uniquely initiated from scratch, CT-LLM diverges from the conventional methodology by primarily incorporating Chinese textual data, utilizing an extensive corpus of 1,200 billion tokens, including 800 billion Chinese tokens, 300 billion English tokens, and 100 billion code tokens. This strategic composition facilitates the model's exceptional proficiency in understanding and processing Chinese, a capability further enhanced through alignment techniques. Demonstrating remarkable performance on the CHC-Bench, CT-LLM excels in Chinese language tasks, and showcases its adeptness in English through SFT. This research challenges the prevailing paradigm of training LLMs predominantly on English corpora and then adapting them to other languages, broadening the horizons for LLM training methodologies. By open-sourcing the full process of training a Chinese LLM, including a detailed data processing procedure with the obtained Massive Appropriate Pretraining Chinese Corpus (MAP-CC), a well-chosen multidisciplinary Chinese Hard Case Benchmark (CHC-Bench), and the 2B-size Chinese Tiny LLM (CT-LLM), we aim to foster further exploration and innovation in both academia and industry, paving the way for more inclusive and versatile language models.

Large Language Models (LLMs) for code are rapidly evolving, with code editing emerging as a critical capability. We introduce CodeEditorBench, an evaluation framework designed to rigorously assess the performance of LLMs in code editing tasks, including debugging, translating, polishing, and requirement switching. Unlike existing benchmarks focusing solely on code generation, CodeEditorBench emphasizes real-world scenarios and practical aspects of software development. We curate diverse coding challenges and scenarios from five sources, covering various programming languages, complexity levels, and editing tasks. Evaluation of 19 LLMs reveals that closed-source models (particularly Gemini-Ultra and GPT-4), outperform open-source models in CodeEditorBench, highlighting differences in model performance based on problem types and prompt sensitivities. CodeEditorBench aims to catalyze advancements in LLMs by providing a robust platform for assessing code editing capabilities. We will release all prompts and datasets to enable the community to expand the dataset and benchmark emerging LLMs. By introducing CodeEditorBench, we contribute to the advancement of LLMs in code editing and provide a valuable resource for researchers and practitioners.

Dissolution of CO$_2$ in water followed by the subsequent hydrolysis reactions is of great importance to the global carbon cycle, and carbon capture and storage. Despite enormous previous studies, the reactions are still not fully understood at the atomistic scale. Here, we combined ab initio molecular dynamics simulations with Markov state models to elucidate the reaction mechanisms and kinetics of CO$_2$ in supercritical water both in the bulk and nanoconfined states. The integration of unsupervised learning with first-principles data allows us to identify complex reaction coordinates and pathways automatically instead of a priori human speculation. Interestingly, our unbiased modelling found a novel pathway of dissolving CO$_2$(aq) under graphene nanoconfinement, involving the pyrocarbonate anion (C$_2$O$_5^{2-}$(aq)) as an intermediate state. The pyrocarbonate anion was previously hypothesized to have a fleeting existence in water; however our study reveals that it is a crucial reaction intermediate and stable carbon species in the nanoconfined solutions. We even observed the formation of pyrocarbonic acid (H$_2$C$_2$O$_5$(aq)), which was unknown in water. The unexpected appearance of pyrocarbonates is related to the superionic behavior of the confined solutions. We also found that carbonation reactions involve collective proton transfer along transient water wires, which exhibits concerted behavior in the bulk solution but proceeds stepwise under nanoconfinement. Our study highlights the importance of large oxocarbons in aqueous carbon reactions, with great implications for the deep carbon cycle and the sequestration of CO$_2$.

The nanoconfinement of water can result in dramatic differences in its physical and chemical properties compared to bulk water. However, a detailed molecular-level understanding of these properties is still lacking. Vibrational spectroscopy, such as Raman and infrared, is a popular experimental tool for studying the structure and dynamics of water, and is often complemented by atomistic simulations to interpret experimental spectra, but there have been few theoretical spectroscopy studies of nanoconfined water using first-principles methods at ambient conditions, let alone under extreme pressure-temperature conditions. Here, we computed the Raman and IR spectra of water nanoconfined by graphene at ambient and extreme pressure-temperature conditions using ab intio simulations. Our results revealed alterations in the Raman stretching and low-frequency bands due to the graphene confinement. We also found spectroscopic evidence indicating that nanoconfinement considerably changes the tetrahedral hydrogen bond network, which is typically found in bulk water. Furthermore, we observed an unusual bending band in the Raman spectrum at ~10 GPa and 1000 K, which is attributed to the unique molecular structure of confined ionic water. Additionally, we found that at ~20 GPa and 1000 K, confined water transformed into a superionic fluid, making it challenging to identify the IR stretching band. Finally, we computed the ionic conductivity of confined water in the ionic and superionic phases. Our results highlight the efficacy of Raman and IR spectroscopy in studying the structure and dynamics of nanoconfined water in a large pressure-temperature range. Our predicted Raman and IR spectra can serve as a valuable guide for future experiments.

The unusual properties of superconductivity in magic-angle twisted bilayer graphene (MATBG) have sparked enormous research interest. However, despite the dedication of intensive experimental efforts and the proposal of several possible pairing mechanisms, the origin of its superconductivity remains elusive. Here, using angle-resolved photoemission spectroscopy with micrometer spatial resolution, we discover replicas of the flat bands in superconducting MATBG unaligned with its hexagonal boron nitride (hBN) substrate, which are absent in non-superconducting MATBG aligned with the hBN substrate. Crucially, the replicas are evenly spaced in energy, separated by 150 +- 15 meV, signalling the strong coupling of electrons in MATBG to a bosonic mode of this energy. By comparing our observations to simulations, the formation of replicas is attributed to the presence of strong inter-valley electron-phonon coupling to a K-point phonon mode. In total, the observation of these replica flat bands and the corresponding phonon mode in MATBG could provide important information for understanding the origin and the unusual properties of its superconducting phase., Comment: 17 pages, 4 figures

Deep speaker embeddings have shown promising results in speaker recognition, as well as in other speaker-related tasks. However, some issues are still under explored, for instance, the information encoded in these representations and their influence on downstream tasks. Four deep speaker embeddings are studied in this paper, namely, d-vector, x-vector, ResNetSE-34 and ECAPA-TDNN. Inspired by human voice mechanisms, we explored possibly encoded information from perspectives of identity, contents and channels; Based on this, experiments were conducted on three categories of speaker-related tasks to further explore impacts of different deep embeddings, including discriminative tasks (speaker verification and diarization), guiding tasks (target speaker detection and extraction) and regulating tasks (multi-speaker text-to-speech). Results show that all deep embeddings encoded channel and content information in addition to speaker identity, but the extent could vary and their performance on speaker-related tasks can be tremendously different: ECAPA-TDNN is dominant in discriminative tasks, and d-vector leads the guiding tasks, while regulating task is less sensitive to the choice of speaker representations. These may benefit future research utilizing speaker embeddings.

We propose a highly efficient and accurate numerical scheme named Truncated Atomic Plane Wave (TAPW) method to determine the subband structure of Twisted Bilayer Graphene (TBG) inspired by BM model. Our method utilizes real space information of carbon atoms in the moir\'e unit cell and projects the full tight binding Hamiltonian into a much smaller subspace using atomic plane waves. We present accurate electronic band structures of TBG in a wide range of twist angles together with detailed moir\'e potential and screened Coulomb interaction at the first magic angle using our new method. Furthermore, we generalize our formalism to solve the problem of low frequency moir\'e phonons in TBG.

The reactions of CO$_2$ in water under extreme pressure-temperature conditions are of great importance to the carbon storage and transport below Earth's surface, which substantially affect the carbon budget in the atmosphere. We applied ab initio molecular dynamics simulations to study aqueous carbon solutions nanoconfined by graphene and stishovite (SiO$_2$) at 10 GPa and 1000$\sim$1400 K. We found that CO$_2$(aq) reacts more in nanoconfinement than in bulk. The stishovite-water interface makes the solutions more acidic, which shifts the chemical equilibria, and the interface chemistry also affects the reaction mechanisms. Our findings suggest that CO$_2$(aq) in deep Earth may be more active than previously thought, and confining CO$_2$ and water in nanopores may enhance the efficiency of mineral carbonation.

This paper presents a novel surrogate-based cross-correlation (SBCC) framework to improve the correlation performance for practical particle image velocimetry~(PIV). The basic idea is that an optimized surrogate filter/image, replacing one raw image, will produce a more accurate and robust correlation signal. Specifically, the surrogate image is encouraged to generate perfect Gaussian-shaped correlation map to tracking particles (PIV image pair) while producing zero responses to image noise (context images). And the problem is formularized with an objective function composed of surrogate loss and consistency loss. As a result, the closed-form solution provides an efficient multivariate operator that could consider other negative context images. Compared with the state-of-the-art baseline methods (background subtraction, robust phase correlation, etc.), our SBCC method exhibits significant performance improvement (accuracy and robustness) on the synthetic dataset and several challenging experimental PIV cases. Besides, our implementation with experimental details (\url{https://github.com/yongleex/SBCC}) is also available for interested researchers., Comment: 12 pages, 13 figures

Recently, topological quantum materials have emerged as a promising electrocatalyst for hydrogen evolution reaction (HER). However, most of their performance largely lags behind noble metals such as benchmark platinum (Pt). In this work, a Pd(20nm)/SnTe(70nm) heterostructure, fabricated by molecular beam epitaxy and electron beam evaporation, is found to display much higher electrocatalytic activity than that of a pure Pd(20nm) thin film and even higher than that of a commercial Pt foil. This heterostructure adopts an extracted turnover frequency value more than two times higher than that of the Pd(20nm) thin film at a potential of 0.2 V, indicating a much higher intrinsic activity per Pd site. Density functional theory calculations show that the conventional d-band theory, which works well for many transition metal heterostructures, cannot explain the enhancement of electrocatalytic performance. Instead, we found that the topological surface states (TSSs) of the SnTe (001) underlayer play a key role; electrons transfer from both the Pd surface and the adsorbed H atoms to the TSSs of SnTe (001), resulting in weaker Pd-H binding strength and more favorable hydrogen adsorption free energies. Our work demonstrates for the first time that a metal/topological quantum material heterostructure could be a prominent catalyst to enjoy HER activity outperforming that of a commercial Pt foil and offers a promising direction to optimize the performance of electrocatalysts based on topological quantum materials., Comment: 40 pages, 17 figures. arXiv admin note: text overlap with arXiv:2102.08062

Electrically interfacing atomically thin transition metal dichalcogenide semiconductors (TMDSCs) with metal leads is challenging because of undesired interface barriers, which have drastically constrained the electrical performance of TMDSC devices for exploring their unconventional physical properties and realizing potential electronic applications. Here we demonstrate a strategy to achieve nearly barrier-free electrical contacts with few-layer TMDSCs by engineering interfacial bonding distortion. The carrier-injection efficiency of such electrical junction is substantially increased with robust ohmic behaviors from room to cryogenic temperatures. The performance enhancements of TMDSC field-effect transistors are well reflected by the ultralow contact resistance (down to 90 Ohm um in MoS2, towards the quantum limit), the ultrahigh field-effect mobility (up to 358,000 cm2V-1s-1 in WSe2) and the prominent transport characteristics at cryogenic temperatures. This method also offers new possibilities of the local manipulation of structures and electronic properties for TMDSC device design.

Molecular dynamics calculations were preformed on organic crystals 4-N,N-dimethylamino-4'-N'-methyl-stilbazolium tosylate (DAST) and 4-N,N-dimethylamino-4'-N'-methylstilbazolium 2,4,6-trimethylbenzenesulfonate (DSTMS). Vibrational modes of the structures were investigated to examine the single unit cell phononic contribution of the organic crystals to their terahertz generating capabilities. Linear optical properties were also calculated from snapshots of the molecular dynamics structures through Green-Kubo relations, and compared with experimental transmission., Comment: 6 pages, 5 figures

Hydrocarbons are of great importance in carbon-bearing fluids in deep Earth and in ice giant planets at extreme pressure (P)-temperature (T) conditions. Raman spectroscopy is a powerful tool to study the chemical speciation of hydrocarbons; however, it is challenging to interpret Raman data at extreme conditions. Here, we performed ab initio molecular dynamics simulations coupled with the modern theory of polarization to calculate Raman spectra of methane, ethane, and propane up to 48 GPa and 2000 K. Our method includes anharmonic temperature effects. We studied the pressure and temperature effects on the Raman bands, and identified the characteristic Raman modes for the C-C and C-C-C bonds. Our result may help to interpret in-situ Raman data of hydrocarbons at extreme P-T conditions, with important implications for understanding the deep carbon cycle inside Earth and the compositions of ice giant planets.

The surface orientation dependence on the hydrogen evolution reaction (HER) performance of topological crystalline insulator (TCI) SnTe thin films is studied. Their intrinsic activities are determined by linear sweep voltammetry and cyclic voltammetry measurements. It is found that SnTe (001) and (111) surfaces exhibit intrinsic activities significantly larger than the (211) surface. Density functional theory calculations reveal that pure (001) and (111) surfaces are not good electrocatalysts, while those with Sn vacancies or partially oxidized surfaces, with the latter as evidenced by X-ray photoelectron spectroscopy, have high activity. The calculated overall performance of the (001) and (111) surfaces with robust topological surface states (TSSs) is better than that of the lowly symmetric (211) surface with fragile or without TSSs, which is further supported by their measured weak antilocalization strength. The high HER activity of SnTe (001) and (111) is attributed to the enhanced charge transfer between H atoms and TSSs. We also address the effect of possible surface facets and the contrast of the HER activity of the available active sites among the three samples. Our study demonstrates that the TSSs and mirror symmetry of TCIs expedite their HER activity., Comment: 78 pages, 35 figures, 4 tables

Lithium (Li) is the simplest metal and the lightest solid element. Here we report the first demonstration of controlled growth of two-dimensional (2D) ultrathin Li nanosheets with large lateral dimensions up to several hundreds of nanometres and thickness limited to just a few nanometres by in-situ transmission electron microscopy (TEM). The nanoscale dynamics of nanosheets growth were unravelled by real-time TEM imaging, which, in combination with density function theory (DFT) calculations indicates that the growth of bcc structured Li into 2D nanosheets is a consequence of kinetic control as mediated by preferential oxidization of the (111) surfaces due to the trace amount of O2 (~10-6 Pa) within TEM chamber. The plasmonic optical properties of the as-grown Li nanosheets were probed by cathodoluminescence (CL) spectroscopy equipped within TEM, and a broadband visible emission was observed that contains contributions of both in-plane and out-of-plane plasmon resonance modes.

A huge amount of water at supercritical conditions exists in Earth's interior, where its dielectric properties play a critical role in determining how it stores and transports materials. However, it is very challenging to obtain the static dielectric constant of water, $\epsilon_0$, in a wide pressure-temperature (P-T) range as found in deep Earth either experimentally or by first-principles simulations. Here, we introduce a neural network dipole model, which, combined with molecular dynamics, can be used to compute P-T dependent dielectric properties of water as accurately as first-principles methods but much more efficiently. We found that $\epsilon_0$ may vary by one order of magnitude in Earth's upper mantle, suggesting that the solvation properties of water change dramatically at different depths. There is a subtle interplay between the molecular dipole moment and the dipolar angular correlation in governing the change of $\epsilon_0$. We also calculated the frequency-dependent dielectric constant of water in the microwave range, which, to the best of our knowledge, has not been calculated from first principles, and found that temperature affects the dielectric absorption more than pressure. Our results are of great use in many areas, e.g., modelling water-rock interactions in geochemistry. The computational approach introduced here can be readily applied to other molecular fluids., Comment: The trained NND model is openly available at https://github.com/angstrom-group/NN-Dipole-Model

The chemistry of carbon in aqueous fluids at extreme pressure and temperature conditions is of great importance to Earth's deep carbon cycle, which substantially affects the carbon budget at Earth's surface and global climate change. At ambient conditions, the concentration of carbonic acid in water is negligible, so aqueous carbonic acid was simply ignored in previous geochemical models. However, by applying extensive ab initio molecular dynamics simulations at pressure and temperature conditions similar to those in Earth's upper mantle, we found that carbonic acid can be the most abundant carbon species in aqueous CO$_2$ solutions at ~10 GPa and 1000 K. The mole percent of carbonic acid in total dissolved carbon species increases with increasing pressure along an isotherm, while its mole percent decreases with increasing temperature along an isobar. In CO$_2$-rich solutions, we found significant proton transfer between carbonic acid molecules and bicarbonate ions, which may enhance the conductivity of the solutions. The effects of pH buffering by carbonic acid may play an important role in water-rock interactions in Earth's interior. Our findings suggest that carbonic acid is an important carbon carrier in the deep carbon cycle.

The hexagonal boron nitride (hBN) encapsulation has been widely used in the electronics applications of 2D materials to improve device performance by protecting 2D materials against contamination and degradation. It is often assumed that hBN layers as a dielectric would not affect the electronic structure of encapsulated 2D materials. Here we studied few-layer MoS$_2$ encapsulated in hBN flakes by using a combination of theoretical and experimental Raman spectroscopy. We found that after the encapsulation the out-of-plane A$_{1g}$ mode is upshifted, while the in-plane E$_{2g}^1$ mode is downshifted. The measured downshift of the E$_{2g}^1$ mode does not decrease with increasing the thickness of MoS$_2$, which can be attributed to tensile strains in bilayer and trilayer MoS$_2$ caused by the typical experimental process of the hBN encapsulation. We estimated the strain magnitude and found that the induced strain may cause the K-Q crossover in the conduction band of few-layer MoS$_2$, so greatly modifies its electronic properties as an n-type semiconductor. Our study suggests that the hBN encapsulation should be used with caution, as it may affect the electronic properties of encapsulated few-layer 2D materials., Comment: Accepted by J. Phys. Chem. C, 18 pages and 5 figures