Overview of Computational Methods and Machine Learning: Panel Talks

By Brett Matthew Savoie1; Pradeep Kumar Gurunathan2; Peilin Liao3; Xiulin Ruan4; Guang Lin4

1. Chemical Engineering, Purdue University, West Lafayette, IN 2. Chemistry, Purdue University, West Lafayette, IN 3. Materials Engineering, Purdue University, West Lafayette, IN 4. Mechanical Engineering, Purdue University, West Lafayette, IN

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Abstract

The Panel Discussion which follows these individual presentations can be found here.

Individucal Presentations:
Theory and Machine Learning in the Chemical Sciences, Brett Matthew Savoie;
Divide and Conquer with QM/MM Methods, Pradeep Kumar Gurunathan;
Computational Chemistry/Materials, Peilin Liao;
Optimizing Thermal Transport using a Genetic Algorithm, Xiulin Ruan;
Computational Methods & Machine Learning Algorithms, Guang Lin;

Sponsored by

Netork for Computational Nanotechnology

Cite this work

Researchers should cite this work as follows:

  • Brett Matthew Savoie, Pradeep Kumar Gurunathan, Peilin Liao, Xiulin Ruan, Guang Lin (2019), "Overview of Computational Methods and Machine Learning: Panel Talks," https://nanohub.org/resources/30760.

    BibTex | EndNote

Time

Location

Burton Morgan, Room 121, Purdue University, West Lafayette, IN

Tags

  1. algorithms
  2. chemistry
  3. computational chemistry
  4. machine learning
  5. NCN Group - Machine Learning
  6. QM/MM methods
Panel Talks: Overview of Computational Methods and Machine Learning
  • Theory and Machine Learning in the Chemical Sciences 1. Theory and Machine Learning in… 0
    00:00/00:00
  • Accelerating Materials Development 2. Accelerating Materials Develop… 149.44944944944945
    00:00/00:00
  • Case Study: Novel Radical Polymers 3. Case Study: Novel Radical Poly… 363.2632632632633
    00:00/00:00
  • Case Study: Novel Radical Polymers 4. Case Study: Novel Radical Poly… 421.52152152152155
    00:00/00:00
  • Case Study: Novel Radical Polymers 5. Case Study: Novel Radical Poly… 470.70403737070404
    00:00/00:00
  • Case Study: Novel Radical Polymers 6. Case Study: Novel Radical Poly… 503.16983650316985
    00:00/00:00
  • Case Study: Novel Radical Polymers 7. Case Study: Novel Radical Poly… 532.16549883216555
    00:00/00:00
  • Scale is Changing the Computational Paradigm 8. Scale is Changing the Computat… 578.07807807807808
    00:00/00:00
  • Scale is Changing the Computational Paradigm 9. Scale is Changing the Computat… 676.14280947614282
    00:00/00:00
  • Scale is Changing the Computational Paradigm 10. Scale is Changing the Computat… 757.52419085752422
    00:00/00:00
  • TAFFI: High-throughput MD and DFT Database 11. TAFFI: High-throughput MD and … 790.79079079079077
    00:00/00:00
  • TAFFI: High-throughput MD and DFT Database 12. TAFFI: High-throughput MD and … 800.33366700033366
    00:00/00:00
  • Machine Learning in the Physical Science 13. Machine Learning in the Physic… 811.911911911912
    00:00/00:00
  • Final Thoughts 14. Final Thoughts 908.24157490824166
    00:00/00:00
  • Divide and Conquer with QM/MM Methods 15. Divide and Conquer with QM/MM … 952.05205205205209
    00:00/00:00
  • Theoretical / Computational Chemistry 16. Theoretical / Computational Ch… 972.17217217217217
    00:00/00:00
  • Multiscale Modeling 17. Multiscale Modeling 1018.3183183183184
    00:00/00:00
  • Quantum Mechanics / Molecular Mechanics 18. Quantum Mechanics / Molecular … 1086.5865865865867
    00:00/00:00
  • Question! 19. Question! 1217.3840507173841
    00:00/00:00
  • Hybrid QM/MM simulations 20. Hybrid QM/MM simulations 1299.0990990990993
    00:00/00:00
  • MM Parameters 21. MM Parameters 1329.1624958291625
    00:00/00:00
  • Solution: Supervised Machine Learning 22. Solution: Supervised Machine L… 1375.709042375709
    00:00/00:00
  • Results: Linear Regression Model 23. Results: Linear Regression Mod… 1434.5345345345345
    00:00/00:00
  • Summary 24. Summary 1474.5412078745412
    00:00/00:00
  • Computational Chemistry/Materials 25. Computational Chemistry/Materi… 1527.1604938271605
    00:00/00:00
  • Discpline vs. Length Scale 26. Discpline vs. Length Scale 1655.1551551551552
    00:00/00:00
  • Solid state chemistry 27. Solid state chemistry 1702.0687354020688
    00:00/00:00
  • Metal-organic frameworks 28. Metal-organic frameworks 1849.3159826493161
    00:00/00:00
  • Metal-organic frameworks 29. Metal-organic frameworks 2024.7247247247249
    00:00/00:00
  • Skills 30. Skills 2115.5488822155489
    00:00/00:00
  • Optimizing Thermal Transport using a Genetic Algorithm 31. Optimizing Thermal Transport u… 2159.4928261594928
    00:00/00:00
  • Motivation 32. Motivation 2226.3596930263598
    00:00/00:00
  • Thermal transport in multilayer structures 33. Thermal transport in multilaye… 2286.8201534868203
    00:00/00:00
  • Calculating thermal conductivity using MD 34. Calculating thermal conductivi… 2347.1805138471805
    00:00/00:00
  • The design space for multilayer nanostructures 35. The design space for multilaye… 2381.2145478812145
    00:00/00:00
  • Optimization of multilayer structures 36. Optimization of multilayer str… 2447.9479479479483
    00:00/00:00
  • Genetic Algorithm based Optimization 37. Genetic Algorithm based Optimi… 2476.60994327661
    00:00/00:00
  • GA based Optimization Tool – Process flow 38. GA based Optimization Tool –… 2507.4074074074074
    00:00/00:00
  • Tool user interface – in progress 39. Tool user interface – in pro… 2543.476810143477
    00:00/00:00
  • How Crossovers and Mutations are Generated? 40. How Crossovers and Mutations a… 2570.1701701701704
    00:00/00:00
  • Optimized Results 41. Optimized Results 2627.2272272272271
    00:00/00:00
  • Acknowledgements 42. Acknowledgements 2733.3333333333335
    00:00/00:00
  • Computational Methods & Machine learning algorithms 43. Computational Methods & Machin… 2746.47981314648
    00:00/00:00
  • Computational Methods from Molecular, Mesoscale to Continuum system 44. Computational Methods from Mol… 2767.2672672672675
    00:00/00:00
  • My Research Group's Research 45. My Research Group's Research 2932.3656990323657
    00:00/00:00
  • Two types of energy computation methods 46. Two types of energy computatio… 2991.0243576910243
    00:00/00:00
  • Why do we need better empirical potential? 47. Why do we need better empirica… 3022.98965632299
    00:00/00:00
  • What is the objective of this study? 48. What is the objective of this … 3067.1004337671006
    00:00/00:00
  • H-H Binding energy 49. H-H Binding energy 3100.3670337003673
    00:00/00:00
  • H-H Binding energy 50. H-H Binding energy 3133.2999666333003
    00:00/00:00
  • What graduate students will learn in my group? 51. What graduate students will le… 3168.1681681681684
    00:00/00:00
  • Thank you 52. Thank you 3201.7017017017019
    00:00/00:00
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