Mikko Karttunen

Professor / Canada Research Chair (Tier 1) in Computational Materials and Biomaterials Research

Western University

Canada

Research Interests

Explore related searches

Professors in Canada

Contact this professor

ORCID

Google Scholar

Academic Page

Articles (19)

Chemoselective Staudinger Reactivity of Bis(azido)phosphines Supported with a π-Donating Imidazolin-2-iminato Ligand

Article Link

Year:

2024

Non-Stokesian dynamics of magnetic helical nanoswimmers under confinement

Article Link

Year:

2024

Characterization of partial wetting by CMAS droplets using multiphase many-body dissipative particle dynamics and data-driven discovery based on PINNs

Article Link

Year:

2024

A Molecular Dynamics Simulation Study of the Effects of βGln114 Mutation on the Dynamic Behavior of the Catalytic Site of the Tryptophan Synthase

Article Link

Year:

2024

Designing architectured ceramics for transient thermal applications using finite element and deep learning

Article Link

Year:

2024

A computational investigation of eumelanin–drug binding in aqueous solutions

Article Link

Year:

2024

Cholesterol inhibits oxygen permeation through biological membranes: mechanism against double-bond peroxidation

Article Link

Year:

2024

Reply to: On the existence of collective interactions reinforcing the metal-ligand bond in organometallic compounds

Article Link

Year:

2023

A framework based on symbolic regression coupled with eXtended Physics-Informed Neural Networks for gray-box learning of equations of motion from data

Article Link

Year:

2023

Identification of Catechins’ Binding Sites in Monomeric Aβ42 through Ensemble Docking and MD Simulations

Article Link

Year:

2023

Identification of Catechins' Binding Sites in Monomeric A beta(42) through Ensemble Docking and MD Simulations

Article Link

Year:

2023

Combining Finite Element and Machine Learning Methods to Predict Structures of Architectured Interlocking Ceramics

Article Link

Year:

2023

Combining Finite Element and Machine Learning Methods to Predict Structures of Architectured Interlocking Ceramics

Article Link

Year:

2023

Combining Finite Element and Machine Learning Methods to Predict Structures of Architectured Interlocking Ceramics

Article Link

Year:

2023

Machine learning-driven process of alumina ceramics laser machining

Article Link

Year:

2023

Machine learning-driven process of alumina ceramics laser machining

Article Link

Year:

2023

Elucidating lipid conformations in the ripple phase: Machine learning reveals four lipid populations

Article Link

Year:

2023

Accurately Predicting Protein pKa Values Using Nonequilibrium Alchemy

Article Link

Year:

2023

Effect of substrate heterogeneity and topology on epithelial tissue growth dynamics

Article Link

Year:

2023

Collaborators (5)

Hossein Ravanbakhsh

Assistant Professor

University of Akron

UNITED STATES

Behnaz Bagheri

Eindhoven University of Technology

NETHERLANDS

Paul J. Ragogna

University of Western Ontario

CANADA

Zhen Li

Assistant Professor

Clemson University

UNITED STATES

Angel Martín Pendás

Professor

University of Oviedo

SPAIN

Mikko Karttunen

Research Interests

Explore related searches

Contact this professor

Articles (19)

Chemoselective Staudinger Reactivity of Bis(azido)phosphines Supported with a π-Donating Imidazolin-2-iminato Ligand

Non-Stokesian dynamics of magnetic helical nanoswimmers under confinement

Characterization of partial wetting by CMAS droplets using multiphase many-body dissipative particle dynamics and data-driven discovery based on PINNs

A Molecular Dynamics Simulation Study of the Effects of βGln114 Mutation on the Dynamic Behavior of the Catalytic Site of the Tryptophan Synthase

Designing architectured ceramics for transient thermal applications using finite element and deep learning

A computational investigation of eumelanin–drug binding in aqueous solutions

Cholesterol inhibits oxygen permeation through biological membranes: mechanism against double-bond peroxidation

Reply to: On the existence of collective interactions reinforcing the metal-ligand bond in organometallic compounds

A framework based on symbolic regression coupled with eXtended Physics-Informed Neural Networks for gray-box learning of equations of motion from data

Identification of Catechins’ Binding Sites in Monomeric Aβ42 through Ensemble Docking and MD Simulations

Identification of Catechins' Binding Sites in Monomeric A beta(42) through Ensemble Docking and MD Simulations

Combining Finite Element and Machine Learning Methods to Predict Structures of Architectured Interlocking Ceramics

Combining Finite Element and Machine Learning Methods to Predict Structures of Architectured Interlocking Ceramics

Combining Finite Element and Machine Learning Methods to Predict Structures of Architectured Interlocking Ceramics

Machine learning-driven process of alumina ceramics laser machining

Machine learning-driven process of alumina ceramics laser machining

Elucidating lipid conformations in the ripple phase: Machine learning reveals four lipid populations

Accurately Predicting Protein pKa Values Using Nonequilibrium Alchemy

Effect of substrate heterogeneity and topology on epithelial tissue growth dynamics

Collaborators (5)

Hossein Ravanbakhsh

Behnaz Bagheri

Paul J. Ragogna

Zhen Li

Angel Martín Pendás

How do I reach out?

Meet Kite AI