Picture of Michael Rinderle

Michael Rinderle, M.Sc.

Technical University of Munich

Place of employment

Associate Professorship of Computational Photonics (Prof. Jirauschek)

Work:
Hans-Piloty-Str. 1(5901)/II
85748 Garching b. München

Google Scholar & ORCID

Google scholar

ORCID ID

Supervising & Tutoring

Supervising and Tutoring


MA: Master Thesis, BA: Bachelor Thesis, DA: Diploma Thesis,
FP: Forschungspraxis, IP: Ingenieurpraxis


Publications at Computational Photonics, Prof. Christian Jirauschek

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Publications at Simulation of Nanosystems for Energy Conversion, Prof. Alessio Gagliardi

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2023

  • Michaels, Hannes; Rinderle, Michael; Benesperi, Iacopo; Freitag, Richard; Gagliardi, Alessio; Freitag, Marina: Emerging indoor photovoltaics for self-powered and self-aware IoT towards sustainable energy management. Chemical Science 14 (20), 2023, 5350-5360 more… BibTeX Full text ( DOI )

2022

  • F. Mayr, M. Harth, I. Kouroudis, M. Rinderle, A. Gagliardi: Machine Learning and Optoelectronic Materials Discovery: A Growing Synergy. The Journal of Physical Chemistry Letters 13 (8), 2022, 1940-1951 more… BibTeX Full text ( DOI )
  • H. Michaels, M. Rinderle, R. Freitag, I. Benesperi, A. Gagliardi: Dynamic energy management through photovoltaic-powered IoT sensors. Digitala Vetenskapliga Arkivet DIVA 2022-03, 2022 more… BibTeX

2021

  • Rinderle, M.; Gagliardi, A.: Machine Learning & multiscale simulations: toward fast screening of organic semiconductor materials. International Conference on Numerical Simulation of Optoelectronic Devices (NUSOD), IEEE Explore Library, 2021Torino, Italy 13-17 Sep 2021-09 more… BibTeX Full text ( DOI )

2020

  • Michaels, H.; Rinderle, M.; Freitag, R.; Benesperi, I.; Edvinsson, T.; Socher, R.; Gagliardi, A.; Freitag, M.: Dye-sensitized solar cells under Ambient Light Powering Machine Learning: Towards autonomous smart sensors for Internet of Things. Chem. Sci., Accepted Manuscript 2020-02, 2020, 1-34 more… BibTeX Full text ( DOI )
  • Rinderle, M.; Kaiser, W.; Mattoni, A.; Gagliardi, A.: Machine Learned Charge Transfer Integrals for Multiscale Simulations in Organic Thin Films. J. Phys. Chem. C, XXXX, XXX, XXX-XXX 2020-07, 2020, 1-34 more… BibTeX Full text ( DOI )

2019

  • Rinderle, M.; Lederer, J.; Kaiser, W.; Gagliardi, A.: Machine learning for predicting charge transfer integrals in organic thin films. European Materials Research Society Spring Meeting, Presentation AA.6.2, 2019Nice, France, 27-31 May 2019-05 more… BibTeX
  • Rinderle, M.; Speckbacher, M.; Tornow, M.; Gagliardi, A.: A kinetic Monte Carlo simulation of filament formation in memristive devices. European Materials Research Society Spring Meeting, Poster AA.P.44, 2019, 2019Nice, France, 27-31 May 2019-05 more… BibTeX
  • Speckbacher, M.; Rinderle, M.; Kaiser, W.; Osman, E.A.; Chryssikos, D.; Cattani‐Scholz, A.; Gibbs, J.M.; Gagliardi, A.; Tornow, M.: Directed Assembly of Nanoparticle Threshold‐Selector Arrays. Adv. Electron. Mater. 1900098 2019-05, 2019, 1-9 more… BibTeX Full text ( DOI )

2018

  • Kaiser, W.; Popp, J.; Rinderle, M.; Albes, T.; Gagliardi, A.: Generalized Kinetic Monte Carlo Framework for Organic Electronics. Algorithms 11(4), 37 (This article belongs to the Special Issue Monte Carlo Methods and Algorithms) 2018-03, 2018, 37 more… BibTeX Full text ( DOI )
  • Kaiser, w.; Rinderle, M.; Gagliardi, A.: Impact of the Level and Orientation of Crystallinity on Charge Transport in Semi-Crystalline Organic Semiconductors. IEEE 18th International Conference on Nanotechnology (IEEE-NANO), IEEE Xplore Digital Library, 2018Cork, Ireland, 23-26 July 2018-07 more… BibTeX Full text ( DOI )