4.7 Article

Predicting mechanical properties of newly generated two-dimensional materials with minimum uncertainty

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Chemistry, Physical

High-Throughput Discovery and Investigation of Auxetic TwoDimensional Crystals

Chen Qian et al.

Summary: This study discovers 108 stable 2D crystals with negative Poisson's ratios using high-throughput computations, and finds additional 92 stable 2D crystals through first-principles calculations and deep learning models. These crystals demonstrate potential for applications in nanoelectronics with band gaps ranging from 0 to 5.7 eV.

CHEMISTRY OF MATERIALS (2022)

Review Nanoscience & Nanotechnology

Computational Discovery of New 2D Materials Using Deep Learning Generative Models

Yuqi Song et al.

Summary: A deep learning generative model combined with a random forest-based classifier was used to discover a large number of new 2D materials compositions, with some crystal structures successfully predicted and confirmed for stability through DFT calculations.

ACS APPLIED MATERIALS & INTERFACES (2021)

Review Materials Science, Multidisciplinary

Transfer of large-scale two-dimensional semiconductors: challenges and developments

Adam J. Watson et al.

Summary: Two-dimensional materials provide opportunities for exploring fundamental science and applications at atomic thickness limits. The family of 2D semiconductors, particularly the group-VI transition metal dichalcogenides (TMDs), have attracted attention for their potential in high on-off ratio transistors and optoelectronic devices. Methods for transferring 2D films, especially those grown by chemical vapor deposition (CVD), are crucial for further investigation and improvement of device performance.

2D MATERIALS (2021)

Article Nanoscience & Nanotechnology

Searching for Mechanically Superior Solid-State Electrolytes in Li-Ion Batteries via Data-Driven Approaches

Eunseong Choi et al.

Summary: In this study, a machine learning regression algorithm was used to screen for mechanically superior Li-ion solid-state electrolytes among a large number of candidates. The model accurately predicted elastic properties, and by adding new data sets to reduce prediction uncertainty, the accuracy was significantly improved.

ACS APPLIED MATERIALS & INTERFACES (2021)

Article Chemistry, Physical

Active-Learning-Based Generative Design for the Discovery of Wide-Band-Gap Materials

Rui Xin et al.

Summary: The study introduces an active generative inverse design method that combines active learning with deep autoencoder neural network and generative adversarial deep neural network model to discover new materials with a target property in the whole chemical design space. This approach led to the discovery of new thermodynamically stable materials with high band gap and semiconductors with specified band gap ranges, which were verified by first-principles DFT calculations.

JOURNAL OF PHYSICAL CHEMISTRY C (2021)

Article Materials Science, Multidisciplinary

Recent progress of the computational 2D materials database (C2DB)

Morten Niklas Gjerding et al.

Summary: The Computational 2D Materials Database (C2DB) is a curated open database with properties for over 4000 2D materials. New materials and properties have been added, including monolayers, bilayers, defects, and various characteristics. With open access, detailed documentation, and rich data, C2DB is a unique resource for advancing the science of atomically thin materials.

2D MATERIALS (2021)

Article Chemistry, Physical

Deep learning framework for material design space exploration using active transfer learning and data augmentation

Yongtae Kim et al.

Summary: In this study, a deep neural network-based forward design approach is proposed to efficiently search for superior materials beyond the domain of the initial training set by gradually updating the neural network with active transfer learning and data augmentation methods. This approach compensates for the weak predictive power of neural networks on unseen domains.

NPJ COMPUTATIONAL MATERIALS (2021)

Article Chemistry, Physical

Benchmarking graph neural networks for materials chemistry

Victor Fung et al.

Summary: The study found that in the materials field, graph neural networks perform better and have more flexibility in input with compositionally diverse datasets compared to traditional models. However, GNNs also have some weaknesses, such as high data requirements, which need further improvement.

NPJ COMPUTATIONAL MATERIALS (2021)

Review Engineering, Electrical & Electronic

A Comprehensive Review on Recent Advances in Two-Dimensional (2D) Hexagonal Boron Nitride

Mohammad Jafar Molaei et al.

Summary: 2D-hBN is an emerging 2D material with exceptional properties, which can be integrated with other 2D materials for next-generation electronic and optoelectronic devices. Various synthesis methods are available, and it finds versatile applications in graphene electronics, tunneling barrier, sensors, etc.

ACS APPLIED ELECTRONIC MATERIALS (2021)

Article Chemistry, Multidisciplinary

Van der Waals Epitaxy of III-Nitride Semiconductors Based on 2D Materials for Flexible Applications

Jiadong Yu et al.

ADVANCED MATERIALS (2020)

Review Chemistry, Physical

2D Materials for Large-Area Flexible Thermoelectric Devices

Kaito Kanahashi et al.

ADVANCED ENERGY MATERIALS (2020)

Review Chemistry, Multidisciplinary

Two-Dimensional Materials to Address the Lithium Battery Challenges

Ramin Rojaee et al.

ACS NANO (2020)

Article Chemistry, Physical

An artificial intelligence-aided virtual screening recipe for two-dimensional materials discovery

Murat Cihan Sorkun et al.

NPJ COMPUTATIONAL MATERIALS (2020)

Article Nanoscience & Nanotechnology

Sub-picosecond photo-induced displacive phase transition in two-dimensional MoTe2

Bo Peng et al.

NPJ 2D MATERIALS AND APPLICATIONS (2020)

Article Chemistry, Physical

The Earth Mover's Distance as a Metric for the Space of Inorganic Compositions

Cameron J. Hargreaves et al.

CHEMISTRY OF MATERIALS (2020)

Article Chemistry, Physical

The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design

Kamal Choudhary et al.

NPJ COMPUTATIONAL MATERIALS (2020)

Article Chemistry, Physical

Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals

Chi Chen et al.

CHEMISTRY OF MATERIALS (2019)

Article Multidisciplinary Sciences

Efficient Prediction of Structural and Electronic Properties of Hybrid 2D Materials Using Complementary DFT and Machine Learning Approaches

Sherif Abdulkader Tawfik et al.

ADVANCED THEORY AND SIMULATIONS (2019)

Article Nanoscience & Nanotechnology

Two-dimensional materials from high-throughput computational exfoliation of experimentally known compounds

Nicolas Mounet et al.

NATURE NANOTECHNOLOGY (2018)

Article Physics, Condensed Matter

Graphene and its elemental analogue: A molecular dynamics view of fracture phenomenon

Tawfiqur Rakib et al.

PHYSICA B-CONDENSED MATTER (2017)

Review Materials Science, Multidisciplinary

Two dimensional hexagonal boron nitride (2D-hBN): synthesis, properties and applications

Kailiang Zhang et al.

JOURNAL OF MATERIALS CHEMISTRY C (2017)

Article Materials Science, Multidisciplinary

Including crystal structure attributes in machine learning models of formation energies via Voronoi tessellations

Logan Ward et al.

PHYSICAL REVIEW B (2017)

Article Chemistry, Analytical

2D Hexagonal Boron Nitride (2D-hBN) Explored for the Electrochemical Sensing of Dopamine

Aamar F. Khan et al.

ANALYTICAL CHEMISTRY (2016)

Article Biotechnology & Applied Microbiology

The inhibition of epidermal growth factor receptor signaling by hexagonal selenium nanoparticles modified by SiRNA

L. Kamrani Moghaddam et al.

CANCER GENE THERAPY (2016)

Review Geography, Physical

Random forest in remote sensing: A review of applications and future directions

Mariana Belgiu et al.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2016)

Review Chemistry, Physical

The high-throughput highway to computational materials design

Stefano Curtarolo et al.

NATURE MATERIALS (2013)

Article Chemistry, Physical

Efficient creation and convergence of surface slabs

Wenhao Sun et al.

SURFACE SCIENCE (2013)

Review Chemistry, Multidisciplinary

Graphene Photonics, Plasmonics, and Broadband Optoelectronic Devices

Qiaoliang Bao et al.

ACS NANO (2012)

Article Chemistry, Multidisciplinary

Synthesis of Graphene Aerogel with High Electrical Conductivity

Marcus A. Worsley et al.

JOURNAL OF THE AMERICAN CHEMICAL SOCIETY (2010)

Article Chemistry, Multidisciplinary

Superior thermal conductivity of single-layer graphene

Alexander A. Balandin et al.

NANO LETTERS (2008)

Article Multidisciplinary Sciences

Measurement of the elastic properties and intrinsic strength of monolayer graphene

Changgu Lee et al.

SCIENCE (2008)