Article
Nanoscience & Nanotechnology
Xin He, Chenhui Zhang, Dongxing Zheng, Peng Li, John Q. Xiao, Xixiang Zhang
Summary: With the recent advancements in two-dimensional ferromagnets, it is now feasible to develop high-quality all-2D spintronic devices. In this study, nonlocal spin valves were successfully fabricated using Fe3GeTe2 as the spin source and detector and multilayer graphene as the spin transport channel. The spin transport signal strongly depended on temperature and vanished below the Curie temperature of the Fe3GeTe2 flakes. Our results suggest potential applications of van der Waals heterostructures in spintronic devices.
ACS APPLIED MATERIALS & INTERFACES
(2023)
Article
Chemistry, Physical
Shuhui Zhang, Yuanyuan Wang, Shuhua Wang, Baibiao Huang, Ying Dai, Wei Wei
Summary: The study demonstrates novel electronic properties of Janus TiClI materials, showing valley spin splitting and large valley polarization. Additionally, TiClI bilayers exhibit semiconductormetal transitions in different stacking structures, with doping concentration tunable by altering the interlayer distance.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
(2021)
Article
Chemistry, Multidisciplinary
Hyung Keun Gweon, Sang Yeop Lee, Hee Young Kwon, Juyoung Jeong, Hye Jung Chang, Kyoung-Whan Kim, Zi Qiang Qiu, Hyejin Ryu, Chaun Jang, Jun Woo Choi
Summary: Research has found that vdW ferromagnet Fe3GeTe2 exhibits an exchange bias effect due to antiferromagnetic oxide layer, with magnitude and thickness dependence differing from typical thin-film systems. By proposing a potential mechanism, the distinct properties of vdW magnets are demonstrated.
Review
Chemistry, Multidisciplinary
Hao Wang, Jianmei Chen, Yanping Lin, Xiaohan Wang, Jianmin Li, Yao Li, Lijun Gao, Labao Zhang, Dongliang Chao, Xu Xiao, Jong-Min Lee
Summary: This review critically examines the progress of non-vdW 2D electrocatalysts, with a special emphasis on electronic structure modulation and performance enhancement. Strategies such as heteroatom doping, vacancy engineering, pore creation, alloying, and heterostructure engineering are analyzed for tuning electronic structures to achieve higher electrocatalytic performance. A roadmap for the future development of non-vdW 2D electrocatalysts is provided from material, mechanism, and performance perspectives.
ADVANCED MATERIALS
(2021)
Review
Chemistry, Multidisciplinary
Xiangdong Guo, Wei Lyu, Tinghan Chen, Yang Luo, Chenchen Wu, Bei Yang, Zhipei Sun, F. Javier Garcia de Abajo, Xiaoxia Yang, Qing Dai
Summary: 2D monolayers can be vertically stacked in van der Waals heterostructures to support a wide range of confined polaritons. This offers advantages in terms of controlling the constituent layers, stacking sequence, and twist angles. These heterostructures have extended the performance and functions of polaritons, and potential applications include nanophotonic integrated circuits.
ADVANCED MATERIALS
(2023)
Article
Chemistry, Multidisciplinary
Youn Sung Na, June-Chul Shin, Eunji Ji, Woong Huh, Inhyuk Im, Kenji Watanabe, Takashi Taniguchi, Ho Won Jang, Chul-Ho Lee, Gwan-Hyoung Lee
Summary: 2D materials have intriguing properties but are highly sensitive to external conditions, requiring passivation to maintain stability. This study demonstrates a novel method for fabricating stable irreversible conductive filament contacts on hBN-passivated 2D channels.
ADVANCED FUNCTIONAL MATERIALS
(2022)
Article
Chemistry, Multidisciplinary
Jiali Wang, Xiuwen Zhao, Guichao Hu, Junfeng Ren, Xiaobo Yuan
Summary: This study investigated the electronic and optical properties of MoSTe/MoGe2N4 vdWH under different configurations and found that it exhibits both semimetal and direct band gap semiconductor behaviors. The absorption coefficient of MoSTe/MoGe2N4 vdWH significantly increases compared to the two monolayers, and its electronic structure and absorption coefficient can be manipulated by applying biaxial strains and changing interlayer distances. MoSTe/MoGe2N4 vdWH is considered as an excellent candidate for high-performance optoelectronic devices.
Article
Materials Science, Multidisciplinary
Kazutoshi Miwa
Summary: This paper presents the linear-response approach using the nonlocal van der Waals density functionals, considering three types of perturbations: atomic displacements, uniform electric fields, and strain. Formulas for calculating the response to strain are derived for both the van der Waals density functionals and the generalized gradient approximation. The linear-response method is implemented within the ultrasoft pseudopotential scheme. The method is applied to weakly coupled layered materials, such as graphite and MoS2, and the results confirm the validity of the derived formulas and demonstrate the utility of the linear-response method for weakly coupled van der Waals systems.
Article
Multidisciplinary Sciences
A. J. Sternbach, S. H. Chae, S. Latini, A. A. Rikhter, Y. Shao, B. Li, D. Rhodes, B. Kim, P. J. Schuck, X. Xu, X-Y Zhu, R. D. Averitt, J. Hone, M. M. Fogler, A. Rubio, D. N. Basov
Summary: Layered crystals, such as tungsten diselenide, can exhibit unconventional optical properties that allow for the propagation of subdiffractional waveguide modes with hyperbolic dispersion. This study demonstrates optically induced hyperbolicity in WSe2 and explores the role of quantum transitions of excitons in the observed polaritonic response.
Article
Chemistry, Multidisciplinary
Tianle Zhang, Yujun Zhang, Mingyuan Huang, Bo Li, Yinghui Sun, Zhe Qu, Xidong Duan, Chengbao Jiang, Shengxue Yang
Summary: In this study, the exchange bias effect in Fe3GeTe2 (FGT)/CrOCl heterostructures is investigated through anomalous Hall effect (AHE) and reflective magnetic circular dichroism (RMCD) measurements. The exchange bias field (H-EB) is successfully tuned by changing the FGT/CrOCl thickness and the cooling field. A larger H-EB in RMCD measurements is observed, which is proposed to be related to the distribution of uncompensated spins at the interface.
Article
Multidisciplinary Sciences
Yongjia Zheng, Akihito Kumamoto, Kaoru Hisama, Keigo Otsuka, Grace Wickerson, Yuta Sato, Ming Liu, Taiki Inoue, Shohei Chiashi, Dai-Ming Tang, Qiang Zhang, Anton Anisimov, Esko Kauppinen, Yan Li, Kazu Suenaga, Yuichi Ikuhara, Shigeo Maruyama, Rong Xiang
Summary: This work focuses on synthesizing one-dimensional van der Waals heterostructures, where different atomic layers encase a single-walled carbon nanotube to form a crystalized structure. The unconventional growth process requires nucleation on a curved surface and shell-by-shell extension, sparking interest in understanding the formation mechanism. Through comprehensive studies using TEM, edge structures and crystal relationships are identified, revealing the importance of surface cleanliness and isolation for perfect 1D heterostructure formation. The correlation between the SWCNT template and BNNT crystals is also elucidated, providing insights into crystal growth on highly curved atomic substrates.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2021)
Article
Chemistry, Multidisciplinary
Xiaoli Ma, Shaohua Fu, Jianwei Ding, Meng Liu, Ang Bian, Fang Hong, Jiatao Sun, Xiaoxian Zhang, Xiaohui Yu, Dawei He
Summary: Researchers have successfully achieved quantitative tuning of intralayer excitons in WS2/ MoSe2 heterostructures and observed the transition from intralayer excitons to interlayer excitons. The energy of interlayer excitons is in a locked or superstable state, unaffected by pressure.
Article
Chemistry, Multidisciplinary
Xiaoqian Zhang, Wenqing Liu, Wei Niu, Qiangsheng Lu, Wei Wang, Ali Sarikhani, Xiaohua Wu, Chunhui Zhu, Jiabao Sun, Mitchel Vaninger, Paul F. Miceli, Jianqi Li, David J. Singh, Yew San Hor, Yue Zhao, Chang Liu, Liang He, Rong Zhang, Guang Bian, Dapeng Yu, Yongbing Xu
Summary: This research reports a method to engineer antiferromagnetic magnets in an ultra-high vacuum-free condition. By introducing interstitial Cr atoms in the vdW gaps, interlayer antiferromagnetic coupling is achieved, leading to giant magnetoresistance effect and switching between states at moderate magnetic fields. This work provides a new approach for studying 2D magnetism and constructing low-power devices.
ADVANCED FUNCTIONAL MATERIALS
(2022)
Review
Chemistry, Multidisciplinary
Hui-Lei Hou, Cosimo Anichini, Paolo Samori, Alejandro Criado, Maurizio Prato
Summary: In the past 15 years, 2D materials have revolutionized materials science and become powerful components for high-performance chemical sensors. By forming van der Waals heterostructures (VDWHs), the individual drawbacks of 2D materials can be overcome, leading to superior sensitivities, selectivity, and stability. This review discusses the latest developments in chemical sensors based on VDWHs of 2D materials, including sensing mechanisms and future directions with potential impact in environmental sciences and biomedical applications.
ADVANCED FUNCTIONAL MATERIALS
(2022)
Article
Chemistry, Multidisciplinary
Alessandro De Vita, Thao Thi Phuong Nguyen, Roberto Sant, Gian Marco Pierantozzi, Danila Amoroso, Chiara Bigi, Vincent Polewczyk, Giovanni Vinai, Loi T. Nguyen, Tai Kong, Jun Fujii, Ivana Vobornik, Nicholas B. Brookes, Giorgio Rossi, Robert J. Cava, Federico Mazzola, Kunihiko Yamauchi, Silvia Picozzi, Giancarlo Panaccione
Summary: This research investigates the ground state electronic properties of CrI3 and VI3 and reveals the stability of different electronic phases and the influence of dimensionality effects.
Article
Physics, Multidisciplinary
Alexandre Tkatchenko, Dmitry V. Fedorov
Summary: Quantum electrodynamic fields exhibit fluctuations in the form of particle-antiparticle dipoles, characterized by a nonvanishing polarizability density. In this study, a quantum scaling law is extended to describe the volumetric and radial polarizability density of a quantum field associated with electrons and positrons, and the Casimir self-interaction energy density (E over bar SIE) of the field is derived in terms of the fine-structure constant. The proposed model satisfies the cosmological equation of state w = -1 and the calculated E over bar SIE falls within the range of the recent measurements of the cosmological constant ? obtained by the Planck Mission and the Hubble Space Telescope.
PHYSICAL REVIEW LETTERS
(2023)
Article
Multidisciplinary Sciences
M. T. Entwistle, Z. Schaetzle, P. A. Erdman, J. Hermann, F. Noe
Summary: Deep neural networks can accurately learn and represent electronic ground and excited states, enabling the modeling of various excited-state processes for atoms and molecules.
NATURE COMMUNICATIONS
(2023)
Article
Multidisciplinary Sciences
Stefan Chmiela, Valentin Vassilev-Galindo, Oliver T. Unke, Adil Kabylda, Huziel E. Sauceda, Alexandre Tkatchenko, Klaus-Robert Mueller
Summary: We have developed an exact iterative approach to train global symmetric gradient domain machine learning (sGDML) force fields, which can accurately describe complex molecular systems and materials. We evaluated the accuracy and efficiency of sGDML on a newly developed MD22 benchmark dataset containing molecules from 42 to 370 atoms.
Article
Multidisciplinary Sciences
Adil Kabylda, Valentin Vassilev-Galindo, Stefan Chmiela, Igor Poltavsky, Alexandre Tkatchenko
Summary: Machine learning force fields (MLFFs) are being optimized to enable molecular dynamics simulations with ab initio accuracy but at a fraction of the computational cost. Challenges remain in developing efficient descriptors for non-local interatomic interactions and reducing dimensionality of descriptors for enhanced applicability and interpretability. An automatized approach is proposed to reduce interatomic descriptor features while maintaining accuracy and efficiency of MLFFs. The results show the importance of non-local features in preserving overall accuracy and reducing the required features to a comparable number with local interatomic features.
NATURE COMMUNICATIONS
(2023)
Article
Chemistry, Physical
Z. Schaetzle, P. B. Szabo, M. Mezera, J. Hermann, F. Noe
Summary: Computing accurate and efficient approximations to solve the Schrödinger equation in computational chemistry has been a challenge for decades. Quantum Monte Carlo methods, with their highly parallel and scalable algorithm, show promise in achieving high accuracy in a variety of molecular systems. The use of machine-learned parametrizations, relying on neural networks as universal function approximators, has further improved the accuracy of these methods. The development of software libraries like DEEPQMC aims to provide a common framework for future investigations and make this field accessible to practitioners from both the quantum chemistry and machine learning communities.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Article
Chemistry, Physical
Almaz Khabibrakhmanov, Dmitry V. Fedorov, Alexandre Tkatchenko
Summary: This study presents a universal parameterization method for quantum-mechanical van der Waals (vdW) potentials based on two free-atom properties, namely the static dipole polarizability and the dipole-dipole C-6 dispersion coefficient. The derived vdW-QDO potential accurately predicts vdW binding energy curves for noble-gas dimers and exhibits correct asymptotic behavior. It is also shown to accurately describe vdW interactions in dimers consisting of group II elements. The applicability of the atom-in-molecule vdW-QDO model for predicting dispersion energies for molecular systems is demonstrated. This work is an important step toward constructing universal vdW potentials for (bio)molecular computational studies.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2023)
Article
Chemistry, Physical
Szabolcs Goger, Almaz Khabibrakhmanov, Ornella Vaccarelli, Dmitry V. Fedorov, Alexandre Tkatchenko
Summary: The quantum Drude oscillator (QDO) is an efficient coarse-grained approach used to model electronic and optical response properties of atoms and molecules. An optimized parametrization (OQDO) is presented in this study, where the parameters are fixed using only dipolar properties. The OQDO accurately reproduces atomic polarization potentials and multipolar dispersion coefficients for the periodic table of elements and small molecules, showing great potential in the development of next-generation quantum-mechanical force fields for (bio)molecular simulations.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
(2023)
Correction
Multidisciplinary Sciences
Adil Kabylda, Valentin Vassilev-Galindo, Stefan Chmiela, Igor Poltavsky, Alexandre Tkatchenko
NATURE COMMUNICATIONS
(2023)
Review
Chemistry, Multidisciplinary
Jan Hermann, James Spencer, Kenny Choo, Antonio Mezzacapo, W. M. C. Foulkes, David Pfau, Giuseppe Carleo, Frank Noe
Summary: Deep learning methods have surpassed human capabilities in pattern recognition and data processing, and have become increasingly important in scientific discovery. In molecular science, a key application of machine learning is to learn potential energy surfaces or force fields from ab initio solutions of the electronic Schrodinger equation obtained with various quantum chemistry methods. This review discusses a complementary approach that uses machine learning to directly solve quantum chemistry problems from first principles, focusing on quantum Monte Carlo methods with neural-network ansatzes to solve the electronic Schrodinger equation.
NATURE REVIEWS CHEMISTRY
(2023)
Article
Chemistry, Multidisciplinary
Victor G. Ruiz, Christian Wagner, Friedrich Maass, Hadi H. Arefi, Stephan Stremlau, Petra Tegeder, F. Stefan Tautz, Alexandre Tkatchenko
Summary: The authors accurately characterized the adsorption energy of perylene-tetracarboxylic dianhydride molecules on Au(111) using temperature-programmed desorption, single-molecule atomic force microscopy, and non-local density-functional theory. Studying inorganic/organic hybrid systems is crucial for designing complex interfaces.
COMMUNICATIONS CHEMISTRY
(2023)
Article
Chemistry, Multidisciplinary
Leonardo Medrano Sandonas, Johannes Hoja, Brian G. Ernst, Alvaro Vazquez-Mayagoitia, Robert A. Distasio, Alexandre Tkatchenko
Summary: The rational design of molecules with specific quantum-mechanical properties requires an understanding of the relationships between structure-property and property-property in chemical compound space. In this study, the analysis of a comprehensive dataset revealed a high degree of flexibility in designing molecules with desired properties or a set of distinct molecules with various properties. Using multi-objective optimization, non-trivial paths through chemical compound space were identified that lead to molecules with optimal combinations of polarizabilities and HOMO-LUMO gaps.
Article
Chemistry, Physical
Szabolcs Goger, Leonardo Medrano Sandonas, Carolin Mueller, Alexandre Tkatchenko
Summary: Understanding the correlations - or lack thereof - between molecular properties is crucial for efficient molecular design. This study explores the relationship between electronic structure and chemical properties in molecular systems, specifically the energy gap and dipole polarizability. Through analysis of a comprehensive dataset and molecular composition, it is demonstrated that there is no correlation between polarizability and HOMO-LUMO gap for sufficiently diverse chemical compounds. The lack of correlation allows for the design of novel materials, exemplified by the case of organic photodetector candidates.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS
(2023)
Article
Physics, Multidisciplinary
Mario Galante, Alexandre Tkatchenko
Summary: The modeling of conformations and dynamics is crucial for understanding the properties of (bio)polymers in soft matter. Noncovalent interactions, rather than short-range interactions, play a dominant role in determining the global conformations. Considering many-body effects in van der Waals (vdW) dispersion has been shown to guide the conformation towards globally optimized structures by reducing the roughness of the energy landscape and promoting global spatial symmetries.
PHYSICAL REVIEW RESEARCH
(2023)
Article
Physics, Multidisciplinary
Matthieu Sarkis, Alessio Fallani, Alexandre Tkatchenko
Summary: Noncovalent interactions play a crucial role in determining the structure, stability, and dynamics of materials, molecules, and biological complexes. However, accurately modeling these interactions on classical computers is challenging. In this study, we demonstrate the potential of the Coulomb-coupled quantum Drude oscillator (cQDO) model for simulating noncovalent interactions on a photonic quantum computer. We calculate the binding energy curve of diatomic systems using Xanadu's STRAWBERRY FIELDS photonics library. Our findings significantly expand the application of quantum computing to atomistic modeling, beyond the standard electronic-structure problem of small molecules. We also propose efficient functional forms for cQDO wave functions that can be optimized on classical computers and capture the bonded-to-noncovalent transition with increasing interatomic distances.
PHYSICAL REVIEW RESEARCH
(2023)
Article
Chemistry, Multidisciplinary
Alex M. Maldonado, Igor Poltavsky, Valentin Vassilev-Galindo, Alexandre Tkatchenko, John A. Keith
Summary: Gradient-domain machine learning (GDML) force fields show excellent accuracy, data efficiency, and applicability for molecules, and a many-body approach opens the possibility of increased transferability to molecular ensembles.