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Wang, Han

Publications and source records attributed to Wang, Han.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

DeePKS-kit: A package for developing machine learning-based chemically accurate energy and density functional models

We introduce DeePKS-kit, an open-source software package for developing machine learning based energy and density functional models. DeePKS-kit is interfaced with PyTorch, an open-source machine learning library, and PySCF, an ab initio computational chemistry program that provides simple and customized tools for developing quantum chemistry codes. It supports the DeePHF and DeePKS methods. In addition to explaining the details in the methodology and the software, we also provide an example of developing a chemically accurate model for water clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

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 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, DP-range correction, DP long range, graphics processing unit support for customized operators, model compression, non-von Neumann molecular dynamics, and improved usability, including documentation, compiled binary packages, graphical user interfaces, and application programming interfaces. This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, this article presents a comprehensive procedure for conducting molecular dynamics as a representative application, benchmarks the accuracy and efficiency of different models, and discusses ongoing developments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Interface synergism and engineering of Pd/Co@N-C for direct ethanol fuel cells

Direct ethanol fuel cells have been widely investigated as nontoxic and low-corrosive energy conversion devices with high energy and power densities. It is still challenging to develop high-activity and durable catalysts for a complete ethanol oxidation reaction on the anode and accelerated oxygen reduction reaction on the cathode. The materials’ physics and chemistry at the catalytic interface play a vital role in determining the overall performance of the catalysts. Herein, we propose a Pd/Co@N-C catalyst that can be used as a model system to study the synergism and engineering at the solid-solid interface. Particularly, the transformation of amorphous carbon to highly graphitic carbon promoted by cobalt nanoparticles helps achieve the spatial confinement effect, which prevents structural degradation of the catalysts. The strong catalyst-support and electronic effects at the interface between palladium and Co@N-C endow the electron-deficient state of palladium, which enhances the electron transfer and improved activity/durability. The Pd/Co@N-C delivers a maximum power density of 438 mW cm -2 in direct ethanol fuel cells and can be operated stably for more than 1000 hours. This work presents a strategy for the ingenious catalyst structural design that will promote the development of fuel cells and other sustainable energy-related technologies.

25 ENERGY STORAGE↗
DOE OSTI2023

X-ray free electron laser studies of electron and phonon dynamics of graphene adsorbed on copper

Here, we report optical pumping and x-ray absorption spectroscopy experiments at the Pohang Accelerator Laboratory free electron laser that probes the electron dynamics of a graphene monolayer adsorbed on copper in the femtosecond regime. By analyzing the results with ab initio theory we infer that the excitation of graphene is dominated by indirect excitation from hot electron-hole pairs created in the copper by the optical laser pulse. However, once the excitation is created in graphene, its decay follows a similar path as in many previous studies of graphene adsorbed on semiconductors, i.e., rapid excitation of strongly coupled optical phonons and eventual thermalization. It is likely that the lifetime of the hot electron-hole pairs in copper governs the lifetime of the electronic excitation of the graphene.

36 MATERIALS SCIENCE↗
DOE OSTI2022

DeePKS + ABACUS as a Bridge between Expensive Quantum Mechanical Models and Machine Learning Potentials

Recently, the development of machine learning (ML) potentials has made it possible to perform large-scale and long-time molecular simulations with the accuracy of quantum mechanical (QM) models. However, for different levels of QM methods, such as density functional theory (DFT) at the meta-GGA level and/or with exact exchange, quantum Monte Carlo, etc., generating a sufficient amount of data for training an ML potential has remained computationally challenging due to their high cost. In this work, we demonstrate that this issue can be largely alleviated with Deep Kohn–Sham (DeePKS), an ML-based DFT model. DeePKS employs a computationally efficient neural network-based functional model to construct a correction term added upon a cheap DFT model. Upon training, DeePKS offers closely matched energies and forces compared with high-level QM method, but the number of training data required is orders of magnitude less than that required for training a reliable ML potential. As such, DeePKS can serve as a bridge between expensive QM models and ML potentials: one can generate a decent amount of high-accuracy QM data to train a DeePKS model and then use the DeePKS model to label a much larger amount of configurations to train an ML potential. Further, this scheme for periodic systems is implemented in a DFT package ABACUS, which is open source and ready for use in various applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Gate-tunable modulation of the optical properties of multilayer graphene by the reversible intercalation of ionic liquid anions

We demonstrate a substantial modulation of the optical properties of multilayer graphene (~100 layers) using a simple device consisting of a multilayer graphene/polymer electrolyte membrane/gold film stack. Applying a voltage of 3–4 V drives the intercalation of anion [TFSI] - [ion liquid diethylmethyl(2-methoxyethyl)ammonium bis(trifluoromethylsulfonyl)imide [DEME][TFSI]] resulting in the reversible modulation of the properties of this optically dense material. Upon intercalation, we observe an abrupt shift of 35 cm -1 in the G band Raman mode, an abrupt increase in FTIR reflectance over the wavelength range from 1.67 to 5 $μ$m (2000–6000 cm -1 ), and an abrupt increase in luminescent background observed in the Raman spectra of graphene. Furthermore, all of these abrupt changes in the optical properties of this material arise from the intercalation of the TFSI - ion and the associated change in the free carrier density (Δ$n$ = 10 20 cm -3 ). Suppression of the 2D band Raman mode observed around 3 V corresponds to Pauli blocking of the double resonance Raman process and indicates a modulation of the Fermi energy of Δ$E$ F = 1.1 eV.

42 ENGINEERING↗
DOE OSTI2022

A deep potential model with long-range electrostatic interactions

Machine learning models for the potential energy of multi-atomic systems, such as the deep potential (DP) model, make molecular simulations with the accuracy of quantum mechanical density functional theory possible at a cost only moderately higher than that of empirical force fields. However, the majority of these models lack explicit long-range interactions and fail to describe properties that derive from the Coulombic tail of the forces. To overcome this limitation, we extend the DP model by approximating the long-range electrostatic interaction between ions (nuclei + core electrons) and valence electrons with that of distributions of spherical Gaussian charges located at ionic and electronic sites. The latter are rigorously defined in terms of the centers of the maximally localized Wannier distributions, whose dependence on the local atomic environment is modeled accurately by a deep neural network. In the DP long-range (DPLR) model, the electrostatic energy of the Gaussian charge system is added to short-range interactions that are represented as in the standard DP model. The resulting potential energy surface is smooth and possesses analytical forces and virial. Missing effects in the standard DP scheme are recovered, improving on accuracy and predictive power. By including long-range electrostatics, DPLR correctly extrapolates to large systems the potential energy surface learned from quantum mechanical calculations on smaller systems. We illustrate the approach with three examples: the potential energy profile of the water dimer, the free energy of interaction of a water molecule with a liquid water slab, and the phonon dispersion curves of the NaCl crystal.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Rising CO 2 and warming reduce global canopy demand for nitrogen

Nitrogen (N) limitation has been considered as a constraint on terrestrial carbon uptake in response to rising CO 2 and climate change. By extension, it has been suggested that declining carboxylation capacity (V cmax ) and leaf N content in enhanced-CO 2 experiments and satellite records signify increasing N limitation of primary production. We predicted Vcmax using the coordination hypothesis and estimated changes in leaf-level photosynthetic N for 1982–2016 assuming proportionality with leaf-level V cmax at 25°C. The whole-canopy photosynthetic N was derived using satellite-based leaf area index (LAI) data and an empirical extinction coefficient for V cmax , and converted to annual N demand using estimated leaf turnover times. The predicted spatial pattern of V cmax shares key features with an independent reconstruction from remotely sensed leaf chlorophyll content. Predicted leaf photosynthetic N declined by 0.27% yr -1 , while observed leaf (total) N declined by 0.2–0.25% yr -1 . Predicted global canopy N (and N demand) declined from 1996 onwards, despite increasing LAI. Leaf-level responses to rising CO 2 , and to a lesser extent temperature, may have reduced the canopy requirement for N by more than rising LAI has increased it. This finding provides an alternative explanation for declining leaf N that does not depend on increasing N limitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Spin–Phonon Coupling in Ferromagnetic Monolayer Chromium Tribromide

Novel 2D magnets exhibit intrinsic electrically tunable magnetism down to the monolayer limit, which has significant value for nonvolatile memory and emerging computing device applications. In these compounds, spin–phonon coupling (SPC) typically plays a crucial role in magnetic fluctuations, magnon dissipation, and ultimately establishing long-range ferromagnetic order. However, a systematic understanding of SPC in 2D magnets that combines theory and experiment is still lacking. Here in this work, monolayer chromium tribromide is studied to investigate SPC in 2D magnets via Raman spectroscopy and first principle calculations. The experimental Curie temperature and phonon shifts are found to be in good agreement with the numerical simulations. Specifically, it is demonstrated how magnetic exchange interactions affect phonon vibrations, which helps establish design fundamentals for 2D magnetic materials and other related devices.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Monolayer Sc 2 CF 2 as a Potential Selective and Sensitive NO 2 Sensor: Insight from First-Principles Calculations

Two-dimensional materials with excellent surface–volume ratios and massive reaction sites recently have been receiving attention for gas sensing. With first-principles calculations, we explored the performance of monolayer Sc 2 CF 2 as a gas sensor. We investigated how molecule adsorption affects its electronic structure and optical properties. It is found that a large charge transfer quantity happens between Sc 2 CF 2 and NO 2 , which results from the fact that the lowest unoccupied molecular orbital (LUMO) of NO 2 is below the valence band maximum (VBM) of Sc 2 CF 2 . Moreover, the MD simulation shows that NO 2 can adsorb on the Sc 2 CF 2 surface stably at room temperature. We explored the effect of biaxial strain on the adsorption energy and charge transfer quantity of each system, and the results show that the biaxial strain can enhance both the adsorption energy and charge transfer quantity of the NO 2 system and thus can improve the sensitivity of Sc 2 CF 2 in detecting the NO 2 molecule. Furthermore, we investigated the adsorption behavior and charge transfer of polar polyatomic molecules at the Sc 2 CF 2 surface with h-BN as a substrate, and the results demonstrate that the h-BN substrate can hardly modify the main results. Our result predicts that Sc 2 CF 2 can be a promising selective and sensitive sensor to detect the NO 2 molecule, and could also give a theoretical guide for other terminated MXenes used for gas sensors or detectors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Enhanced valley splitting of WSe 2 in twisted van der Waals WSe 2 /CrI 3 heterostructures

Van der Waals (vdW) heterostructures composed of different two-dimensional (2D) materials offer an easily accessible way to combine properties of individual materials for applications. Owing to the discovery of a set of unanticipated physical phenomena, the twisted 2D vdW heterostructures have gained considerable attention recently. Here, we report enhanced valley splitting in twisted 2D vdW WSe 2 /CrI 3 heterostructures. In particular, the splitting can be 1200% (or 5.18 meV) of the value for a non-twisted heterostructure. According to the $k ∙ p$ model, this value is equivalent to a ~20T external magnetic field applied perpendicular to the 2D sheet. The thermodynamic stability of 2D vdW WSe 2 /CrI 3 heterostructures, on the other hand, depends linearly on the interlayer twisting angle.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Mechanistic Advantages of Organotin Molecular EUV Photoresists

Here, extreme ultraviolet (EUV)-induced radiation exposure chemistry in organotin-oxo systems, represented by the archetypal [(R-Sn) 12 O 14 (OH) 6 ](A) 2 cage, has been investigated with density functional theory. Upholding existing experimental evidence of Sn-C cleavage-dominant chemistry, computations have revealed that either electron attachment or ionization can single-handedly trigger tin-carbon bond cleavage, partially explaining the current EUV sensitivity advantage of metal oxide systems. We have revealed that tin atoms at different parts of the molecule react differently to ionization and electron attachment and have identified such selectivity as a result of local coordination chemistry instead of the macro geometry of the molecule. An ionization-deprotonation pathway has also been identified to explain the observed evolution of an anion conjugate acid upon exposure and anion mass dependence in resist sensitivity.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗