4.6 Article

Machine Learning Boosts the Design and Discovery of Nanomaterials

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。
Review Chemistry, Physical

2D Materials Bridging Experiments and Computations for Electro/Photocatalysis

Xu Zhang et al.

Summary: The exploration of catalysts for energy conversion is crucial for sustainable development, with a focus on the unique properties of 2D materials investigated through a combination of experiments and computations. Recent advances have led to the development and design of 2D electro/photocatalysts, bridging the gap between experimental and computational methods. Challenges in computations and experiments for 2D catalysts are also discussed.

ADVANCED ENERGY MATERIALS (2022)

Article Nanoscience & Nanotechnology

Machine-Learning-Based Approach to Decode the Influence of Nanomaterial Properties on Their Interaction with Cells

Ajay Vikram Singh et al.

Summary: In this study, a machine-learning based approach was proposed to analyze cell-NP interactions using tight junction protein ZO-1 mediated alterations in cell/nuclei phenotype. It was found that physicochemical descriptors of different nanomaterials play a critical role in determining the intracellular uptake or cell membrane interactions in epithelial cells. Correlation functions were used to successfully predict cell and nuclei shapes and polarity functions, providing a valuable tool for assessing the safety of nanomaterials used in consumer products and nanomedicine.

ACS APPLIED MATERIALS & INTERFACES (2021)

Review Chemistry, Multidisciplinary

A Review of Piezoelectric and Magnetostrictive Biosensor Materials for Detection of COVID-19 and Other Viruses

Fumio Narita et al.

Summary: This article reviews the current state of research on biosensor materials for virus detection, including a general description of virus detection principles, a critique of experimental work on various virus sensors, and a summary of their detection limitations.

ADVANCED MATERIALS (2021)

Article Chemistry, Analytical

Covid-19 Automated Diagnosis and Risk Assessment through Metabolomics and Machine Learning

Jeany Delafiori et al.

Summary: COVID-19 continues to pose a heavy burden worldwide, emphasizing the importance of patient screening and risk management. Our integration of machine learning algorithms with mass spectrometry led to the development of a rapid platform for distinguishing COVID-19 in plasma samples and providing tools for risk assessment, aiding in patient management and decision-making.

ANALYTICAL CHEMISTRY (2021)

Article Multidisciplinary Sciences

Deep learning for in vivo near-infrared imaging

Zhuoran Ma et al.

Summary: This study utilized artificial neural networks to transform fluorescence images in the shorter-wavelength NIR window to images resembling NIR-IIb window, achieving high signal-to-background ratio in vivo lymph node imaging with human-approved molecular probes. Translation of PD-L1 or EGFR imaging greatly enhanced tumor-to-normal tissue ratio and improved tumor margin localization, showcasing the potential of deep learning in enhancing noninvasive NIR imaging and microscopy. Deep learning equipped NIR imaging could facilitate basic biomedical research and clinical diagnostics and imaging-guided surgery.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2021)

Article Chemistry, Medicinal

Induction of Protective Response Associated with Expressional Alterations in Neuronal G Protein-Coupled Receptors in Polystyrene Nanoparticle Exposed Caenorhabditis elegans

Yunhan Yang et al.

Summary: The study investigated the role of expressional alterations in neuronal G protein-coupled receptors (GPCRs) in inducing a protective response to polystyrene nanoparticles (PS-NPs) in Caenorhabditis elegans. The findings suggest that specific GPCRs in neuronal cells regulate the toxicity of PS-NPs through different signaling pathways, providing important insights into the protective response mechanisms.

CHEMICAL RESEARCH IN TOXICOLOGY (2021)

Article Environmental Sciences

Evaluating the cytotoxicity of a large pool of metal oxide nanoparticles to Escherichia coli: Mechanistic understanding through In Vitro and In Silico studies

Supratik Kar et al.

Summary: The toxic effects of eight metal oxide nanoparticles on Escherichia coli were experimentally evaluated, with Er2O3 and Gd2O3 identified as the most toxic. Machine learning algorithms were employed for toxicity modeling, with the linear discriminant analysis model showing the best performance. Identified properties can help understand nanotoxicity mechanisms and predict environmental risks.

CHEMOSPHERE (2021)

Article Multidisciplinary Sciences

Using artificial intelligence to improve COVID-19 rapid diagnostic test result interpretation

David-A Mendels et al.

Summary: This study developed a smartphone application called xRCovid, which uses machine learning to classify SARS-CoV-2 serological RDT results, improving the accuracy and reliability of RDT testing. The app can replace manual reading, reduce subjectivity in interpretation, and bring more confidence to patient self-testing and clinicians.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2021)

Article Multidisciplinary Sciences

Fast and precise single-cell data analysis using a hierarchical autoencoder

Duc Tran et al.

Summary: Accurate analysis of single-cell RNA sequencing (scRNA-seq) data is crucial for various research fields, but is often hindered by technical noise and high dropout rates. The hierarchical autoencoder, scDHA, introduced in this study, outperforms existing methods in various aspects of scRNA-seq analysis, including cell segregation and classification.

NATURE COMMUNICATIONS (2021)

Article Environmental Sciences

Induction of protective response to polystyrene nanoparticles associated with methylation regulation in Caenorhabditis elegans

Shuting Wang et al.

Summary: The study revealed that exposure to polystyrene nanoparticles led to decreased expression of MET-2 in Caenorhabditis elegans, reflecting a protective response. This protective response was confirmed in both intestinal and germline cells. Furthermore, MET-2 was found to regulate the toxicity induction process of PS-NPs in intestinal cells and germline cells.

CHEMOSPHERE (2021)

Article Environmental Sciences

Induction of protective response to polystyrene nanoparticles associated with dysregulation of intestinal long non-coding RNAs in Caenorhabditis elegans

Yingyue Zhao et al.

Summary: Intestinal barrier in nematode Caenorhabditis elegans plays a crucial role in response to polystyrene nanoparticles (PS-NPs) by controlling specific long non-coding RNAs (lncRNAs). These lncRNAs regulate transcription factors to mediate a protective response to PS-NPs.

ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY (2021)

Article Multidisciplinary Sciences

Deep exploration of random forest model boosts the interpretability of machine learning studies of complicated immune responses and lung burden of nanoparticles

Fubo Yu et al.

Summary: This study successfully predicts the pulmonary immune responses and lung burden of nanoparticles using a tree-based random forest feature importance and feature interaction network analysis framework (TBRFA), overcoming feature importance bias brought by small datasets.

SCIENCE ADVANCES (2021)

Article Nanoscience & Nanotechnology

Machine Learning Enabled Tailor-Made Design of Application-Specific Metal-Organic Frameworks

Xiangyu Zhang et al.

ACS APPLIED MATERIALS & INTERFACES (2020)

Article Chemistry, Physical

General Approach for Machine Learning-Aided Design of DNA-Stabilized Silver Clusters

Stacy M. Copp et al.

CHEMISTRY OF MATERIALS (2020)

Article Biophysics

Graphene aerogel nanoparticles for in-situ loading/pH sensitive releasing anticancer drugs

Hossein Ayazi et al.

COLLOIDS AND SURFACES B-BIOINTERFACES (2020)

Article Chemistry, Multidisciplinary

A Universal Machine Learning Algorithm for Large-Scale Screening of Materials

George S. Fanourgakis et al.

JOURNAL OF THE AMERICAN CHEMICAL SOCIETY (2020)

Review Chemistry, Multidisciplinary

Machine Learning in Nanoscience: Big Data at Small Scales

Keith A. Brown et al.

NANO LETTERS (2020)

Article Multidisciplinary Sciences

Expert-augmented machine learning

Efstathios D. Gennatas et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2020)

Article Chemistry, Physical

Machine learning maximized Anderson localization of phonons in aperiodic superlattices

Prabudhya Roy Chowdhury et al.

NANO ENERGY (2020)

Review Green & Sustainable Science & Technology

Simulation optimisation towards energy efficient green buildings: Current status and future trends

Vincent J. L. Gan et al.

JOURNAL OF CLEANER PRODUCTION (2020)

Article Materials Science, Multidisciplinary

Predicting compressive strength of consolidated molecular solids using computer vision and deep learning

Brian Gallagher et al.

MATERIALS & DESIGN (2020)

Article Multidisciplinary Sciences

Machine learning predicts the functional composition of the protein corona and the cellular recognition of nanoparticles

Zhan Ban et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2020)

Article Chemistry, Physical

Discovery of Novel Two-Dimensional Photovoltaic Materials Accelerated by Machine Learning

Hao Jin et al.

JOURNAL OF PHYSICAL CHEMISTRY LETTERS (2020)

Article Chemistry, Physical

Practical Deep-Learning Representation for Fast Heterogeneous Catalyst Screening

Geun Ho Gu et al.

JOURNAL OF PHYSICAL CHEMISTRY LETTERS (2020)

Article Multidisciplinary Sciences

Quantitative prediction of grain boundary thermal conductivities from local atomic environments

Susumu Fujii et al.

NATURE COMMUNICATIONS (2020)

Article Materials Science, Multidisciplinary

Discovery of superionic conductors by ensemble-scope descriptor

Seiji Kajita et al.

NPG ASIA MATERIALS (2020)

Article Chemistry, Physical

High-throughput discovery of high Curie point two-dimensional ferromagnetic materials

Arnab Kabiraj et al.

NPJ COMPUTATIONAL MATERIALS (2020)

Article Nanoscience & Nanotechnology

Automated phenotyping of Caenorhabditis elegans embryos with a high-throughput-screening microfluidic platform

Huseyin Baris Atakan et al.

MICROSYSTEMS & NANOENGINEERING (2020)

Article Nanoscience & Nanotechnology

Graphene/CuO2 Nanoshuttles with Controllable Release of Oxygen Nanobubbles Promoting Interruption of Bacterial Respiration

Marziyeh Jannesari et al.

ACS APPLIED MATERIALS & INTERFACES (2020)

Article Biochemistry & Molecular Biology

Predicting In Vitro Neurotoxicity Induced by Nanoparticles Using Machine Learning

Irini Furxhi et al.

INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES (2020)

Review Chemistry, Multidisciplinary

Exploring chemical compound space with quantum-based machine learning

O. Anatole von Lilienfeld et al.

NATURE REVIEWS CHEMISTRY (2020)

Article Physics, Multidisciplinary

Mode-assisted unsupervised learning of restricted Boltzmann machines

Haik Manukian et al.

COMMUNICATIONS PHYSICS (2020)

Article Nanoscience & Nanotechnology

Differentially charged nanoplastics demonstrate distinct accumulation inArabidopsis thaliana

Xiao-Dong Sun et al.

NATURE NANOTECHNOLOGY (2020)

Editorial Material Multidisciplinary Sciences

Machine learning for chemical discovery

Alexandre Tkatchenko

NATURE COMMUNICATIONS (2020)

Article Environmental Sciences

Predicting nanotoxicity by an integrated machine learning and metabolomics approach

Ting Peng et al.

ENVIRONMENTAL POLLUTION (2020)

Article Multidisciplinary Sciences

Two-dimensional vacancy platelets as precursors for basal dislocation loops in hexagonal zirconium

Si-Mian Liu et al.

NATURE COMMUNICATIONS (2020)

Article Chemistry, Multidisciplinary

Artificial intelligence: the silver bullet for sustainable materials development

Rifan Hardian et al.

GREEN CHEMISTRY (2020)

Review Nanoscience & Nanotechnology

Electrochemical SARS-CoV-2 Sensing at Point-of-Care and Artificial Intelligence for Intelligent COVID-19 Management

Ajeet Kumar Kaushik et al.

ACS APPLIED BIO MATERIALS (2020)

Article Green & Sustainable Science & Technology

Machine learning exploration of the critical factors for CO2 adsorption capacity on porous carbon materials at different pressures

Xinzhe Zhu et al.

JOURNAL OF CLEANER PRODUCTION (2020)

Review Biochemistry & Molecular Biology

Deep metabolome: Applications of deep learning in metabolomics

Yotsawat Pomyen et al.

COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL (2020)

Review Computer Science, Artificial Intelligence

From shallow feature learning to deep learning: Benefits from the width and depth of deep architectures

Guoqiang Zhong et al.

WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY (2019)

Article Multidisciplinary Sciences

Agency plus automation: Designing artificial intelligence into interactive systems

Jeffrey Heer

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2019)

Article Multidisciplinary Sciences

Computational geometry analysis of dendritic spines by structured illumination microscopy

Yutaro Kashiwagi et al.

NATURE COMMUNICATIONS (2019)

Article Multidisciplinary Sciences

Machine-learning guided discovery of a new thermoelectric material

Yuma Iwasaki et al.

SCIENTIFIC REPORTS (2019)

Article Chemistry, Physical

Deep learning analysis of defect and phase evolution during electron beam-induced transformations in WS2

Artem Maksov et al.

NPJ COMPUTATIONAL MATERIALS (2019)

Article Biochemistry & Molecular Biology

A White-Box Machine Learning Approach for Revealing Antibiotic Mechanisms of Action

Jason H. Yang et al.

Article Chemistry, Multidisciplinary

Supervised Learning and Mass Spectrometry Predicts the in Vivo Fate of Nanomaterials

James Lazarovits et al.

ACS NANO (2019)

Article Engineering, Environmental

Adsorption characteristics of supercritical CO2/CH4 on different types of coal and a machine learning approach

Meng Meng et al.

CHEMICAL ENGINEERING JOURNAL (2019)

Article Chemistry, Physical

Data Driven Determination in Growth of Silver from Clusters to Nanoparticles and Bulk

Keisuke Takahashi et al.

JOURNAL OF PHYSICAL CHEMISTRY LETTERS (2019)

Article Chemistry, Multidisciplinary

Identifying Active Sites for CO2 Reduction on Dealloyed Gold Surfaces by Combining Machine Learning with Multiscale Simulations

Yalu Chen et al.

JOURNAL OF THE AMERICAN CHEMICAL SOCIETY (2019)

Article Multidisciplinary Sciences

Assessing micrometastases as a target for nanoparticles using 3D microscopy and machine learning

Benjamin R. Kingston et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2019)

Article Multidisciplinary Sciences

Revealing the intrinsic nature of the mid-gap defects in amorphous Ge2Sb2Te5

Konstantinos Konstantinou et al.

NATURE COMMUNICATIONS (2019)

Review Chemistry, Physical

Recent advances and applications of machine learning in solid-state materials science

Jonathan Schmidt et al.

NPJ COMPUTATIONAL MATERIALS (2019)

Article Chemistry, Physical

Interpretable deep learning for guided microstructure-property explorations in photovoltaics

Balaji Sesha Sarath Pokuri et al.

NPJ COMPUTATIONAL MATERIALS (2019)

Article Nanoscience & Nanotechnology

Accelerated Design of Catalytic Water-Cleaning Nanomotors via Machine Learning

Minxiang Zeng et al.

ACS APPLIED MATERIALS & INTERFACES (2019)

Article Multidisciplinary Sciences

Definitions, methods, and applications in interpretable machine learning

W. James Murdoch et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2019)

Article Chemistry, Physical

Identification of advanced spin-driven thermoelectric materials via interpretable machine learning

Yuma Iwasaki et al.

NPJ COMPUTATIONAL MATERIALS (2019)

Article Chemistry, Physical

Reliable and explainable machine-learning methods for accelerated material discovery

Bhavya Kailkhura et al.

NPJ COMPUTATIONAL MATERIALS (2019)

Article Chemistry, Multidisciplinary

Probing Atomic Distributions in Mono- and Bimetallic Nanoparticles by Supervised Machine Learning

Janis Timoshenko et al.

NANO LETTERS (2019)

Article Multidisciplinary Sciences

Data-driven design of metal-organic frameworks for wet flue gas CO2 capture

Peter G. Boyd et al.

NATURE (2019)

Article Computer Science, Artificial Intelligence

Predicting disease-associated mutation of metal-binding sites in proteins using a deep learning approach

Mohamad Koohi-Moghadam et al.

NATURE MACHINE INTELLIGENCE (2019)

Review Chemistry, Physical

Machine learning for renewable energy materials

Geun Ho Gu et al.

JOURNAL OF MATERIALS CHEMISTRY A (2019)

Article Chemistry, Multidisciplinary

Deep-Learning-Enabled On-Demand Design of Chiral Metamaterials

Wei Ma et al.

ACS NANO (2018)

Article Chemistry, Multidisciplinary

Chemical Pressure-Driven Enhancement of the Hydrogen Evolving Activity of Ni2P from Nonmetal Surface Doping Interpreted via Machine Learning

Robert B. Wexler et al.

JOURNAL OF THE AMERICAN CHEMICAL SOCIETY (2018)

Article Multidisciplinary Sciences

Noninvasive detection of macrophage activation with single-cell resolution through machine learning

Nicolas Pavillon et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2018)

Article Multidisciplinary Sciences

A machine learning model with human cognitive biases capable of learning from small and biased datasets

Hidetaka Taniguchi et al.

SCIENTIFIC REPORTS (2018)

Article Chemistry, Multidisciplinary

Meta-analysis of Daphnia magna nanotoxicity experiments in accordance with test guidelines

Hyun Kil Shin et al.

ENVIRONMENTAL SCIENCE-NANO (2018)

Article Chemistry, Multidisciplinary

Machine learning provides predictive analysis into silver nanoparticle protein corona formation from physicochemical properties

Matthew R. Findlay et al.

ENVIRONMENTAL SCIENCE-NANO (2018)

Article Chemistry, Physical

A strategy to apply machine learning to small datasets in materials science

Ying Zhang et al.

NPJ COMPUTATIONAL MATERIALS (2018)

Article Chemistry, Physical

Machine learning hydrogen adsorption on nanoclusters through structural descriptors

Marc O. J. Jager et al.

NPJ COMPUTATIONAL MATERIALS (2018)

Review Genetics & Heredity

Deep Learning and Its Applications in Biomedicine

Chensi Cao et al.

GENOMICS PROTEOMICS & BIOINFORMATICS (2018)

Article Chemistry, Multidisciplinary

Fluorescence Color by Data-Driven Design of Genomic Silver Clusters

Stacy M. Copp et al.

ACS NANO (2018)

Review Multidisciplinary Sciences

Machine learning for molecular and materials science

Keith T. Butler et al.

NATURE (2018)

Article Multidisciplinary Sciences

Accelerated discovery of stable lead-free hybrid organic-inorganic perovskites via machine learning

Shuaihua Lu et al.

NATURE COMMUNICATIONS (2018)

Article Nanoscience & Nanotechnology

Cationic graphene oxide nanoplatform mediates miR-101 delivery to promote apoptosis by regulating autophagy and stress

Akram Assali et al.

INTERNATIONAL JOURNAL OF NANOMEDICINE (2018)

Article Chemistry, Multidisciplinary

Machine-Learning Prediction of CO Adsorption in Thiolated, Ag-Alloyed Au Nanoclusters

Gihan Panapitiya et al.

JOURNAL OF THE AMERICAN CHEMICAL SOCIETY (2018)

Article Multidisciplinary Sciences

Comparing continual task learning in minds and machines

Timo Flesch et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2018)

Article Multidisciplinary Sciences

Noninvasive diagnostic imaging using machine-learning analysis of nanoresolution images of cell surfaces: Detection of bladder cancer

I. Sokolov et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2018)

Article Multidisciplinary Sciences

A machine learning approach for online automated optimization of super-resolution optical microscopy

Audrey Durand et al.

NATURE COMMUNICATIONS (2018)

Proceedings Paper Optics

Machine learning approaches for small data in sensor fusion applications

Dinesh Verma et al.

GROUND/AIR MULTISENSOR INTEROPERABILITY, INTEGRATION, AND NETWORKING FOR PERSISTENT ISR IX (2018)

Article Chemistry, Multidisciplinary

Synthesis, Characterization, and Photocatalytic Application of Iron Oxalate Capped Fe, Fe-Cu, Fe-Co, and Fe-Mn Oxide Nanomaterial

Kasturi Sarmah et al.

ACS SUSTAINABLE CHEMISTRY & ENGINEERING (2017)

Article Chemistry, Medicinal

Machine Learning for Silver Nanoparticle Electron Transfer Property Prediction

Baichuan Sun et al.

JOURNAL OF CHEMICAL INFORMATION AND MODELING (2017)

Article Chemistry, Physical

Predicting Catalytic Activity of Nanoparticles by a DFT-Aided Machine-Learning Algorithm

Ryosuke Jinnouchi et al.

JOURNAL OF PHYSICAL CHEMISTRY LETTERS (2017)

Article Chemistry, Physical

Supervised Machine-Learning-Based Determination of Three-Dimensional Structure of Metallic Nanoparticles

Janis Timoshenko et al.

JOURNAL OF PHYSICAL CHEMISTRY LETTERS (2017)

Article Multidisciplinary Sciences

Machine learning unifies the modeling of materials and molecules

Albert P. Bartok et al.

SCIENCE ADVANCES (2017)

Article Chemistry, Physical

Learning surface molecular structures via machine vision

Maxim Ziatdinov et al.

NPJ COMPUTATIONAL MATERIALS (2017)

Article Chemistry, Physical

Geometrical features can predict electronic properties of graphene nanoflakes

Michael Fernandez et al.

CARBON (2016)

Article Materials Science, Biomaterials

Influence of heavy nanocrystals on spermatozoa and fertility of mammals

Omid Akhavan et al.

MATERIALS SCIENCE & ENGINEERING C-MATERIALS FOR BIOLOGICAL APPLICATIONS (2016)

Article Nanoscience & Nanotechnology

Meta-analysis of cellular toxicity for cadmium-containing quantum dots

Eunkeu Oh et al.

NATURE NANOTECHNOLOGY (2016)

Article Chemistry, Physical

Autonomy in materials research: a case study in carbon nanotube growth

Pavel Nikolaev et al.

NPJ COMPUTATIONAL MATERIALS (2016)

Article Chemistry, Multidisciplinary

Robust Prediction of Personalized Cell Recognition from a Cancer Population by a Dual Targeting Nanoparticle Library

Tu C. Le et al.

ADVANCED FUNCTIONAL MATERIALS (2015)

Article Chemistry, Physical

C-elegans as a tool for in vivo nanoparticle assessment

L. Gonzalez-Moragas et al.

ADVANCES IN COLLOID AND INTERFACE SCIENCE (2015)

Review Chemistry, Multidisciplinary

The nanoparticle biomolecule corona: lessons learned - challenge accepted?

D. Docter et al.

CHEMICAL SOCIETY REVIEWS (2015)

Article Chemistry, Physical

What Are the Best Materials To Separate a Xenon/Krypton Mixture?

Cory M. Simon et al.

CHEMISTRY OF MATERIALS (2015)

Article Materials Science, Biomaterials

Curcumin-reduced graphene oxide sheets and their effects on human breast cancer cells

Shadie Hatamie et al.

MATERIALS SCIENCE & ENGINEERING C-MATERIALS FOR BIOLOGICAL APPLICATIONS (2015)

Article Physics, Multidisciplinary

Big Data of Materials Science: Critical Role of the Descriptor

Luca M. Ghiringhelli et al.

PHYSICAL REVIEW LETTERS (2015)

Article Chemistry, Multidisciplinary

Nanograined Half-Heusler Semiconductors as Advanced Thermoelectrics: An Ab Initio High-Throughput Statistical Study

Jesus Carrete et al.

ADVANCED FUNCTIONAL MATERIALS (2014)

Article Chemistry, Physical

Cytotoxicity of protein corona-graphene oxide nanoribbons on human epithelial cells

Doris A. Mbeh et al.

APPLIED SURFACE SCIENCE (2014)

Article Chemistry, Multidisciplinary

Cyto and genotoxicities of graphene oxide and reduced graphene oxide sheets on spermatozoa

Ehsan Hashemi et al.

RSC ADVANCES (2014)

Article Biochemical Research Methods

A microfluidic impedance flow cytometer for identification of differentiation state of stem cells

Hongjun Song et al.

LAB ON A CHIP (2013)

Article Chemistry, Multidisciplinary

Intrinsic Structural Defects in Monolayer Molybdenum Disulfide

Wu Zhou et al.

NANO LETTERS (2013)

Article Chemistry, Multidisciplinary

Graphene Nanomesh Promises Extremely Efficient In Vivo Photothermal Therapy

Omid Akhavan et al.

Article Chemistry, Physical

Melatonin as a powerful bio-antioxidant for reduction of graphene oxide

A. Esfandiar et al.

JOURNAL OF MATERIALS CHEMISTRY (2011)

Article Chemistry, Multidisciplinary

Quantitative Nanostructure-Activity Relationship Modeling

Denis Fourches et al.

ACS NANO (2010)