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434 records · Page 18

Experimental Validation of a Modular All-Electric Power Take-Off Topology for Wave Energy Converter Enabling Marine Renewable Energy Interconnection

Power electronic converters are an enabling technology for the emerging marine energy applications, such as using ocean waves to produce electricity. This paper outlines the power take-off system and its key components used in a wave energy converter offering modularity and scalability to generate power efficiently. The proposed power take-off system was implemented based on a modular multilevel converter and could be deployed to convert any alternating current electrical energy to a different alternating current for interconnection to grid or non-grid applications. Examples of widespread deployment are supplying electricity to coastal communities or producing clean drinking water. The analysis using both the simulation tests and laboratory experiments verified the design objectives and basic functionality of the developed power take-off system. An acceptable response using a field programmable gate array-based controlled laboratory testbench was achieved, complying with guidelines specified in the prevalent industry standards. Seamless operation during steady-state and transients for the studied wave energy converter was achieved as supported by the obtained results. The key findings of this work were experimentally examined under different load conditions, direct current bus voltage fluctuations, and generator speed–torque regulation. The ability of the power take-off system to generate high-power quality of the waveforms, e.g., against adhering to the IEEE 519-2022 standard for total harmonic distortion limits, is also confirmed.

Engineering

Exploiting ν-dependence of projected energy correlators in HICs

We extend the recently derived factorization formula for energy-energy correlators to study the analytic structure of general ν-point projected energy correlators in heavy ion collisions. The ν-point projected energy correlators (or, ν-correlators) are an analytically continued family of the integer N-point projected energy correlators, which probe correlations between N final-state particles. By tracking the largest separation (χ) between the N particles, in vacuum, their structure is closely related to the DGLAP splitting functions and exhibits a classical scaling behavior ∼ 1/χ which is modified by resummation through the anomalous dimensions. We show that, in a thermal medium, the ν-correlators display non-trivial angular scaling already at the leading order in perturbation theory. We find that for non-integer values, particularly ν < 1, medium-induced jet function is enhanced compared to ν > 1. This is particularly manifested in the ratios of ν-correlators with respect to the two-point energy correlator, which encodes intrinsic angular information for ν < 1 when compared to large ν values. Moreover, for small-ν values, the ν-correlators appear to saturate at ν = 0.01 . We further confirm our leading-order numerical computations against simulated events from JEWEL for the parton-level production cross-section. Finally, we qualitatively discuss the effect of BFKL resummation for various values of ν.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Phonon-mediated ultrafast dynamics in self-assembled monolayers of 4-mercaptobenzoic acid on gold

Non-equilibrium interactions between plasmonic metals and adsorbed molecules lie at the heart of emerging applications such as plasmonic photocatalysis and sensing, though the ultrafast charge and energy transfer mechanisms arising from these interactions are not well understood. Herein, we investigate the ultrafast dynamics of Au nano-islands tethered with a self-assembled monolayer (SAM) of electron-withdrawing 4-mercaptobenzoic acid (4MBA) molecules. Ultrafast UV-visible transient absorption spectroscopy following excitation of the interband transition in Au reveals three well-known, characteristic time constants that quantify electron–electron (el–el), electron–phonon (el–ph) and phonon–phonon (ph–ph) scattering lifetimes. When comparing the dynamics of bare Au and 4MBA-Au, we find that the el–ph and ph–ph scattering lifetimes are notably longer in 4MBA-Au. Density functional perturbation theory calculations ascribe the elongation in el–ph lifetimes in 4MBA-Au to the significant coupling of acoustic phonon modes of Au with certain molecular vibrations of 4MBA, leading to decreased spatial overlap between carrier electronic states and the acoustic modes. We speculate that the elongation of ph–ph scattering lifetimes in 4MBA-Au arises due to poor thermal conductivity of the SAM which disrupts efficient energy dissipation from Au to the environment, thus slowing down the thermalization of phonons. This work provides a glimpse into how molecular adsorbates modify the charge carrier and phonon dynamics of Au and sets the stage for further systematic exploration of plasmonic metal–molecule interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Theoretical design and performance of three-dimensional, pillared FeS 2 cathodes

Three-dimensional (3D) electrode design can provide improved capacities and rate capabilities over conventional two-dimensional electrodes by enhancing electrical and ionic transport. Here, expanding upon our previous modeling efforts for conversion chemistry lithium-ion batteries, we develop a pseudo-four-dimensional (P4D) approach that is subsequently used to investigate the design of a pillared FeS 2 electrode. The model considers transport in three dimensions with an additional “fourth” dimension corresponding to the solid-state lithium transport within the active material particles. Additionally, we allow for expansion of the active material during the conversion reaction to understand how internal stresses impact the electrochemical performance of the cell. By optimizing the model with respect to areal capacity, we are able to predict areal capacities up to 16.8 mAh/cm 2 for an areal current density of 1.78 mA/cm 2 and a 103% improvement for the three-dimensional electrodes over planar electrodes of equal volume. Despite the promising results, our simulations suggest that 3D design may be difficult for conversion cathode materials due to the large internal stresses that arise during conversion. Nevertheless, the model is robust and adaptable to other materials that may be more suitable for 3D electrodes due to a lesser change in volume during discharge.

Conversion cathode materials

A Chemist’s Guide to Solid-State Qubits: Diamond Color Centers as Embedded Vacancy-Centered Molecules

Diamond point defects or color centers are at the crux of solid-state quantum technology applications, from computing to sensing. Modeling molecular qubits has advanced by leaps and bounds mainly due to the advanced quantum mechanical (QM) tools in the arsenal of quantum chemists for modeling (isolated) molecular systems, which should be easily translatable for analogous systems in the solid state. Here, we simulate a series of diamond defects: a carbon vacancy (V C ) and second row substitutions that are adjacent to a V C or D C V C , with D = B, N, and O, to evaluate their magnetic and optical properties. We applied molecular orbital principles, an embedded cluster method, and a multiconfigurational QM theory to computationally characterize the above-mentioned defects for a multitude of spin, charge, and excited states. Our computational approach delivered high-quality QM insights that compare well with experiments. Furthermore, with this framework, we confirm the spin-triplets B C V C – and O C V C 0 to be analogous to N C V C – , with calculated bright transitions that respectively correspond to UV (3.80 eV) and blue (2.65 eV) light absorption and emission lifetimes (τ) of 2.3 and 5.6 ns, which are higher in energy and more short-lived (and thus brighter) than that for N C V C – : green (2.26 eV), τ = 9.5 ns.

Martirez, John Mark P. [Princeton Plasma Physics L

Secondary-Side Active Rectifier Synchronization and Control in LCC-LC Compensated Inductive Power Transfer Systems

This paper proposes a communication-less synchronization and output power control strategy for LCC-LC compensated inductive power transfer systems with a secondaryside active rectifier. By replacing the passive rectifier with an active bridge, the proposed architecture eliminates the need for a separate secondary-side DC-DC converter and enables direct regulation of battery power. The key challenge in such a system is achieving robust synchronization of the secondary active bridge with the primary inverter without access to primary-side signals. To address this issue, the secondary-side variables are analyzed and the current through the secondary series inductor is identified as a load-independent synchronization variable with a fixed phase relationship to the primary excitation. A fixed-frequency second order generalized (SOGI)-based phase locked loop (PLL) is used to estimate the switching phase and frequency, and a phase-shift-based output power controller is developed using a phasor-transformer model of the active bridges. A modified control formulation is further introduced to remove phase-dependent loop-gain variation and simplify controller design. Simulation results validate the proposed method under both fixed and varying switching-frequency conditions, demonstrating successful frequency tracking from 82 kHz to 88 kHz and accurate output power regulation over a wide operating range. The proposed method offers a compact and effective solution for high-power IPT systems by enabling secondary-side synchronization and control without wireless communication or an additional DC-DC conversion stage.

Fernandes, Arnold Anthony [ORNL] (ORCID:0009000631

Revealing the evolution of order in materials microstructures using multi-modal computer vision

The development of high-performance materials for microelectronics, energy storage, and extreme environments depends on our ability to describe and direct property-defining microstructural order. Our present understanding is typically derived from laborious manual analysis of imaging and spectroscopy data, which is difficult to scale, challenging to reproduce, and lacks the ability to reveal latent associations needed for mechanistic models. Here, we demonstrate a multi-modal machine learning (ML) approach to describe order from electron microscopy analysis of the complex oxide La 1−x Sr x FeO 3 . We construct a hybrid pipeline based on fully and semi-supervised classification, allowing us to evaluate both the characteristics of each data modality and the value each modality adds to the ensemble. We observe distinct differences in the performance of uni- and multi-modal models, from which we draw general lessons in describing crystal order using computer vision.

36 MATERIALS SCIENCE

Complex orders and chirality in the classical Kitaev-Γ model

It is well recognized that the low-energy physics of many Kitaev materials is governed by two dominant energy scales, the Ising-type Kitaev coupling 𝐾 and the symmetric off-diagonal Γ coupling. An understanding of the interplay between these two scales is therefore the natural starting point toward a quantitative description that includes subdominant perturbations that are inevitably present in real materials. This study focuses on the classical 𝐾−Γ model on the honeycomb lattice, with a specific emphasis on the region 𝐾< 0 and Γ > 0 , which is the most relevant for the available materials and which remains enigmatic in both quantum and classical limits, despite much effort. We employ large-scale Monte Carlo simulations on specially designed finite-size clusters and unravel the presence of a complex multisublattice magnetic order in a wide region of the phase diagram, whose structure is characterized in detail. We show that this order can be quantified in terms of a coarse-grained scalar-chirality order, featuring a counterrotating modulation on the two spin sublattices. Here, we also provide a comparison to previous studies and discuss the impact of quantum fluctuations on the phase diagram.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Future Projection of Tropical Upper-Tropospheric Troughs and Implications for Tropical Cyclone Activity

Summertime tropical upper-tropospheric troughs (TUTTs) provide a unified framework to better understand how extratropical and tropical forcings jointly modulate basin-scale tropical cyclone (TC) activity. In this study, we examine future changes in TUTTs and their implications for TC activity. Multimodel ensemble-mean projections from 45 Coupled Model Intercomparison Project phase 6 (CMIP6) models suggest a contraction of the Pacific TUTT and an expansion of the Atlantic TUTT as the climate warms. Consistently, future changes in environment-based TC indices indicate that the large-scale conditions will become more favorable for TC genesis and intensification over the central North Pacific but less favorable over the tropical North Atlantic and Gulf of Mexico. Utilizing a TC-permitting large-ensemble dataset [i.e., the Database for Policy Decision-Making for Future Climate Change (d4PDF)] that adequately captures the observed interannual TUTT–TC relationships, we further confirm the impacts of projected TUTT changes on the TC activity in a warmer climate. In contrast, the TUTT–TC relationship is poorly represented in most CMIP6 High-Resolution Model Intercomparison Project (HighResMIP) models; such deficiencies call for caution when assessing future TC risk based on explicitly tracked TCs in these models. Additionally, CMIP6 projections show large intermodel spread in TUTT changes, implying uncertainty in projected TC activity, especially over the central-to-eastern Pacific and the North Atlantic. This intermodel spread is associated with interhemispheric sea surface temperature warming asymmetry, which leads to a meridional shift of the intertropical convergence zone (ITCZ) and the simultaneous weakening or strengthening of TUTTs in the North Pacific and North Atlantic. The potential contributions of anthropogenic aerosol forcing and oceanic circulation to this interhemispheric warming asymmetry are briefly examined.

Climate Change

Fluorophilic Sigma(σ)‐Lock Self‐Healable Copolymers

Although F-Containing molecules and macromolecules are often used in molecular biology to increase the binding with Lewis acidic groups by introducing favorable C−F dipoles, there is virtually no experimental evidence and limited understanding of the nature of these interactions, especially their role in synthetic polymeric materials. These studies elucidate the molecular origin of inter- and intra-Chain interactions responsible for self-healing of F-Containing copolymers composed of pentafluorostyrene and n-butyl acrylate units (p(PFS/nBA). Guided by dynamic surface oscillating force (SOF) and spectroscopic measurements supported by molecular dynamics (MD) simulations, these studies show that the reformation of σ-σ orbitals in −C−F of PFS and CH 3 CH 2 − of nBA units enables the recovery of entropic energy via fluorophilic-σ-lock van der Waals forces when PFS/nBA molar ratios are ~50/50. The strength of these interactions determined experimentally for self-healable PFS/nBA compositions is in the order ~0.3 kcal/mol which primarily comes from fluorophilic-σ-lock (~70 %) contributions. These interactions are significantly diminished for non-self-healable counterparts. Strongly polarized −C−F σ orbitals create lateral dipolar forces enhancing the affinity towards −C−H orbitals, facilitating energetically favorable interactions. Entropic recovery driven by non-Covalent bonding offers a valuable tool in designing materials with unique functionalities, particularly self-healable batteries and energy storage devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Micrometer: Micromechanics transformer for predicting full field mechanical responses of heterogeneous materials

Predicting mechanical responses of heterogeneous materials across scales remains a significant challenge. Traditional computational methods often struggle with complex and multiscale nature of these materials, limiting their effectiveness in real-world applications. Here, in this paper, we introduce Micrometer, a vision transformer based deep learning model designed to predict full field mechanical responses of heterogeneous materials, bridging the gap between computer vision and solid mechanics problems. We show that Micrometer, trained on a large-scale high-resolution dataset of 2D fiber-reinforced composites, can achieve state-of-the-art performance in predicting microscale strain fields across a wide range of material properties and loading conditions. Our model demonstrates accuracy and computational efficiency in applications such as computational homogenization and multiscale modeling, reducing computational time by up to two orders of magnitude compared to conventional numerical solvers while maintaining less than 1 % errors in predicting macroscale stress fields. Furthermore, we showcase Micrometer’s adaptability through transfer learning experiments on new materials with limited data, highlighting its potential to tackle diverse scenarios in computational solid mechanics. These results represent a significant step towards AI-driven innovation in materials science, addressing the limitations of traditional numerical methods and paving the way for more efficient simulations of heterogeneous materials across various industrial applications.

Composite materials

Transition from Vehicular to Structural Ionic Transport in Electrified Alkali Aqueous Solutions

A molecular understanding of the solvation and dynamics of ions under static electric fields is crucial for modelling a wide range of natural and technological processes. Yet, traditional simulation methods suffer from a trade-off that has to be made between accuracy and statistical convergence. To bridge this gap, herein we extend our recently introduced Perturbed Neural Network Potential Molecular Dynamics (PNNP MD) approach to investigate the solvation structures and ionic transport mechanisms of electrified alkali cationic solutions. We obtain ionic conductivities for Li+, Na+ and Cs+ from the field dependence of the ionic current density in good agreement with experiment. Surprisingly, the migration mechanism is found to be strikingly different for the three ions despite their similar ionic conductivities. While Li+ conducts predominantly through vehicular migration of a stable 4-fold coordinated ion at all field strengths, Cs+ conducts strictly through a structural diffusion mechanism, where 9-12 transient first shell water coordination bonds are broken and renewed. Notably, aqueous Na+ emerges as a “Goldilocks” ion: its ion-water interactions are strong enough to maintain distinct 5-6 fold coordination shells at zero field (unlike Cs+) yet labile enough to be strongly perturbed by electric fields (unlike Li+). As a consequence, we observe an electric field-induced transition from vehicular to structural ionic transport for Na+ that is accompanied by a marked increase in the ionic current density. Our results imply that the conductance mechanism of ions with moderate ion-solvent interactions can be effectively tuned by external electric fields.

Joll, Kit

Self‐Propelling Macroscale Sheets Powered by Enzyme Pumps

Nanoscale enzymes anchored to surfaces act as chemical pumps by converting chemical energy released from enzymatic reactions into spontaneous fluid flow that propels entrained nano‐ and microparticles. Enzymatic pumps are biocompatible, highly selective, and display unique substrate specificity. Utilizing these pumps to trigger self‐propelled motion on the macroscale has, however, constituted a significant challenge and thus prevented their adaptation in macroscopic fluidic devices and soft robotics. Using experiments and simulations, we herein show that enzymatic pumps can drive centimeter‐scale polymer sheets along directed linear paths and rotational trajectories. In these studies, the sheets are confined to the air/water interface. With the addition of appropriate substrate, the asymmetric enzymatic coating on the sheets induces chemically driven, buoyancy flows that controllably propel the sheet's motion on the air/water interface. The directionality and speed of the motion can be tailored by changing the pattern of the enzymatic coating, type of enzyme, and nature and concentration of the substrate. This work highlights the utility of biocompatible enzymes for generating motion in macroscale fluidic devices and robotics and indicates their potential utility for in vivo applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Unraveling interphase-driven failure pathways in LiMn0.6Fe0.4PO4/graphite pouch cells

LiMnxFe1−xPO4 (LMFP) is a promising high-voltage, thermally stable, and earth-abundant cathode material, yet its practical application is limited by interphase instability and Mn dissolution. In this work, we systematically evaluate LiMn0.6Fe0.4PO4/graphite pouch cells using three electrolyte formulations including control carbonate electrolyte, control + 2 wt% vinylene carbonate (VC), and control + 2 wt% VC + 1 wt% 1,3,2-dioxathiolane 2,2-dioxide (DTD), to establish how electrolyte composition governs interphase chemistry and long-term degradation. Electrochemical testing shows that both additives are preferentially reduced prior to ethylene carbonate (EC) during cell formation, generating robust cathode-electrolyte interphase (CEI) and solid-electrolyte interphase (SEI) layers that suppress gas evolution and raise the first-cycle coulombic efficiency to 89.3%. Additionally, the dual-additive electrolyte delivers the most stable performance, retaining over 85% capacity after 600 cycles while minimizing impedance growth under long-term cycling at C/3 and 40 °C. Soft X-ray absorption spectroscopy confirms that VC + DTD effectively suppresses electrolyte oxidation at the cathode surface, and micro-X-ray fluorescence shows substantially reduced Mn dissolution and deposition on the graphite anode. Density functional theory simulations further provided insights into the structural and energetic influences of alkoxide species on the cathode surface, proposing a Mn2+ extraction mechanism. The combined experimental and computational findings establish a mechanistic link between electrolyte composition and interphase evolution, highlighting the effectiveness of electrolyte engineering for extending the operational lifetime of LMFP-based lithium-ion batteries.

Chak, Chanmonirath Michael

Investigating the Combustion Performance of Dual Fuel Combustion with Diesel and Port Injected Hydrogen in a Large Bore Locomotive Engine

The heavy-duty transportation sector has primarily relied on conventional diesel combustion engines given their reliability and high thermal efficiency relative to spark ignition engines, but increased focus on reducing greenhouse gas emissions has led to investigation into alternative fuels. Gaseous hydrogen fuel has garnered a great deal of recent interest in the engine community given it has zero carbon, but hydrogen is not available at the scale and cost that petroleum fuels are currently available, and this is a barrier to adoption for industries that are looking to decarbonize their operations. Because of the fuel flexibility provided, dual fuel technology offers a pathway for some industries to adopt hydrogen as a fuel source while maintaining sufficient flexibility in times and locations where the new fuel is not yet available. This computational study investigates dual fuel combustion in a large bore locomotive engine architecture using direct injected diesel and port injected gaseous hydrogen fuel. With an optimal port fuel injection configuration from previous work, simulations of varying substitution ratio, compression ratio, manifold air temperature, diesel injection timing, and diesel injection pressure were performed to understand their effect on combustion performance. Results indicated that both increased substitution ratio and higher intake air temperature accelerates hydrogen flame propagation and can result in high peak cylinder pressures. Additionally, diesel injection timing and injection pressure were demonstrated as effective methods for controlling dual fuel combustion heat release rates.

ODonnell, Patrick Christopher

Electrolyte-Induced Restructuring of Acid-Stable Oxygen Evolution Catalysts

Crystalline metal oxide catalysts operating under oxygen evolution reaction (OER) conditions invariably restructure, resulting in active sites with hydroxo/oxo species in an amorphous environment. An increase in the population of terminal hydroxo/oxo species (i.e., edge sites) facilitates proton-coupled electron-transfer (PCET) kinetics for oxygen generation and thus improves catalyst competency. While amorphous films benefit from a greater density of active sites, they suffer from diminished charge transport as compared to that of extended crystalline lattices. Managing this amorphous–crystalline dichotomy is essential when designing OER catalysts, which we highlight with the examination of electrodeposited PbO x materials, which historically are very poor OER catalysts. Along these lines, the presence of phosphate during PbO x electrodeposition truncates the growth of an extended lattice owing to its strong bonding to oxide surfaces to afford an amorphous catalyst film (A-PbO x ) with significant charge-transfer resistance (138 ± 42 Ω) and poor OER kinetics (420 ± 105 mV dec –1 Tafel slope). Conversely, electrodeposition of Pb 2+ in the presence of less coordinating electrolytes such as nitrate affords crystalline β-PbO2 with improved charge-transfer resistance (42.6 ± 1.1 Ω), though still poor OER kinetics (134 ± 36 mV dec –1 Tafel slope). By operating amorphous A-PbOx in less coordinating electrolytes, however, a new partially crystalline material can be generated (μc-PbO x ) with further reduced charge-transfer resistance (33.0 ± 1.4 Ω) and improved OER kinetics (70 ± 15 mV dec –1 Tafel slope). The enhanced OER activity of μc-PbO x is the result of coupling the high edge-site population of an amorphous PbOx phase with crystalline-like charge transport properties. Finally, the ability to use an electrolyte to induce OER activity in an inactive amorphous form of PbO x highlights the benefits of optimizing the amorphous–crystalline phase compositions in the design of active OER catalysts.

catalysts

32 examples of LLM applications in materials science and chemistry: towards automation, assistants, agents, and accelerated scientific discovery

Abstract Large language models (LLMs) are reshaping many aspects of materials science and chemistry research, enabling advances in molecular property prediction, materials design, scientific automation, knowledge extraction, and more. Recent developments demonstrate that the latest class of models are able to integrate structured and unstructured data, assist in hypothesis generation, and streamline research workflows. To explore the frontier of LLM capabilities across the research lifecycle, we review applications of LLMs through 32 total projects developed during the second annual LLM hackathon for applications in materials science and chemistry, a global hybrid event. These projects spanned seven key research areas: (1) molecular and material property prediction, (2) molecular and material design, (3) automation and novel interfaces, (4) scientific communication and education, (5) research data management and automation, (6) hypothesis generation and evaluation, and (7) knowledge extraction and reasoning from the scientific literature. Collectively, these applications illustrate how LLMs serve as versatile predictive models, platforms for rapid prototyping of domain-specific tools, and much more. In particular, improvements in both open source and proprietary LLM performance through the addition of reasoning, additional training data, and new techniques have expanded effectiveness, particularly in low-data environments and interdisciplinary research. As LLMs continue to improve, their integration into scientific workflows presents both new opportunities and new challenges, requiring ongoing exploration, continued refinement, and further research to address reliability, interpretability, and reproducibility.

Computer Science

Novel Zwitterionic Polyurethane-in-Salt Electrolytes with High Ion Conductivity, Elasticity, and Adhesion for High-Performance Solid-State Lithium Metal Batteries

This study presents a novel polymer-in-salt (PIS) zwitterionic polyurethane-based solid polymer electrolyte (zPU-SPE) that offers high ionic conductivity, strong interaction with electrodes, and excellent mechanical and electrochemical stabilities, making it promising for high-performance all solid-state lithium batteries (ASSLBs). The zPU-SPE exhibits remarkable lithium-ion (Li+) conductivity (3.7 × 10⁻⁴ S cm−1 at 25 °C), enabled by exceptionally high salt loading of up to 90 wt.% (12.6 molar ratio of Li salt to polymer unit) without phase separation. It addresses the limitations of conventional SPEs by combining high ionic conductivity with a Li+ transference number of 0.44, achieved through the incorporation of zwitterionic groups that enhance ion dissociation and transport. The high surface energy (338.4 J m−2) and elasticity ensure excellent adhesion to Li anodes, reducing interfacial resistance and ensuring uniform Li+ flux. When tested in Li||zPU||LiFePO₄ and Li||zPU||S/C cells, the zPU-SPE demonstrated remarkable cycling stability, retaining 76% capacity after 2000 cycles with the LiFePO4 cathode, and achieving 84% capacity retention after 300 cycles with the S/C cathode. Molecular simulations and a range of experimental characterizations confirm the superior structural organization of the zPU matrix, contributing to its outstanding electrochemical performance. The findings strongly suggest that zPU-SPE is a promising candidate for next-generation ASSLBs.

Wang, Kun