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Max Marian

Maschinenbauingenieur

Name	Max Marian
Time	2021 (Wirkungsdaten)
Place	Fürth (Bayern) (Geburtsort) Deutschland
Gender	männlich
Academic degree	Dr.-Ing. (an der Technischen Fakultät der Friedrich-Alexander-Universität Erlangen-Nürnberg) (2021)
Profession	Maschinenbauingenieur (characteristic profession)
Related	Gottfried Wilhelm Leibniz Universität Hannover Pontificia Universidad Católica de Chile Friedrich-Alexander-Universität Erlangen-Nürnberg
Further information	Diss. Technische Fakultät der Univ. Erlangen-Nürnberg
Record type	Person
GND-Identifier	1240161689
Record ID	1240161689
Involved in show all Recent Advances in Machine Learning in Tribology Subject-specific tribo-contact conditions in total knee replacements: a simulation framework across scales Wear Mechanism of Superhard Tetrahedral Amorphous Carbon (ta‐C) Coatings for Biomedical Applications Predicting EHL film thickness parameters by machine learning approaches Numerical micro-texture optimization for lubricated contacts—A critical discussion A Semantic Annotation Pipeline towards the Generation of Knowledge Graphs in Tribology Layered 2D Nanomaterials to Tailor Friction and Wear in Machine Elements—A Review Amorphous Carbon Coatings for Total Knee Replacements—Part I: Deposition, Cytocompatibility, Chemical and Mechanical Properties Amorphous Carbon Coatings for Total Knee Replacements—Part II: Tribological Behavior Current Trends and Applications of Machine Learning in Tribology—A Review Geometrical Optimization of the EHL Roller Face/Rib Contact for Energy Efficiency in Tapered Roller Bearings Numerische Auslegung von Oberflächenmikrotexturen für geschmierte tribologische Kontakte Numerische Auslegung von Oberflächenmikrotexturen für geschmierte tribologische Kontakte Non-Dimensional Groups, Film Thickness Equations and Correction Factors for Elastohydrodynamic Lubrication: A Review Numerical Modeling of Wear in a Thrust Roller Bearing under Mixed Elastohydrodynamic Lubrication The Use of Artificial Intelligence in Tribology—A Perspective tribAIn—Towards an Explicit Specification of Shared Tribological Understanding On Friction Reduction by Surface Modifications in the TEHL Cam/Tappet-Contact-Experimental and Numerical Studies

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Max Marian

Recent Advances in Machine Learning in Tribology

Subject-specific tribo-contact conditions in total knee replacements: a simulation framework across scales

Wear Mechanism of Superhard Tetrahedral Amorphous Carbon (ta‐C) Coatings for Biomedical Applications

Predicting EHL film thickness parameters by machine learning approaches

Numerical micro-texture optimization for lubricated contacts—A critical discussion

A Semantic Annotation Pipeline towards the Generation of Knowledge Graphs in Tribology

Layered 2D Nanomaterials to Tailor Friction and Wear in Machine Elements—A Review

Amorphous Carbon Coatings for Total Knee Replacements—Part I: Deposition, Cytocompatibility, Chemical and Mechanical Properties

Amorphous Carbon Coatings for Total Knee Replacements—Part II: Tribological Behavior

Current Trends and Applications of Machine Learning in Tribology—A Review

Geometrical Optimization of the EHL Roller Face/Rib Contact for Energy Efficiency in Tapered Roller Bearings

Numerische Auslegung von Oberflächenmikrotexturen für geschmierte tribologische Kontakte

Numerische Auslegung von Oberflächenmikrotexturen für geschmierte tribologische Kontakte

Non-Dimensional Groups, Film Thickness Equations and Correction Factors for Elastohydrodynamic Lubrication: A Review

Numerical Modeling of Wear in a Thrust Roller Bearing under Mixed Elastohydrodynamic Lubrication

The Use of Artificial Intelligence in Tribology—A Perspective

tribAIn—Towards an Explicit Specification of Shared Tribological Understanding

On Friction Reduction by Surface Modifications in the TEHL Cam/Tappet-Contact-Experimental and Numerical Studies