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Theoretical and Computational Chemistry

Working Paper

Conformational Dynamics of the Pyrene Excimer

Giovanni Parolin, Bidhan Chandra Garain, Saikat Mukherjee, Giovanni Granucci, Stefano Corni, Mario Barbatti

Version 1 posted 14 October 2024

144

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Analytical Chemistry

Working Paper

Automated Analysis of Nano-Impact Single-Entity Electrochemistry Signals using Unsupervised Machine Learning and Template Matching

Ziwen Zhao, Arunava Naha, Sagar Ganguli, Alina Sekretareva

Version 1 posted 23 June 2023

265

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Earth, Space, and Environmental Chemistry

Working Paper

A Machine Learning Approach for Predicting Defluorination of Per- and Polyfluoroalkyl Substances (PFAS) for Their Efficient Treatment and Removal

Akber Raza, Lihua Xu, Sharma Yamijala, Chao Lian, Hyuna Kwon, Bryan Wong

Version 1 posted 03 September 2019

899

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Earth, Space, and Environmental Chemistry

Working Paper

Harnessing Semi-Supervised Machine Learning to Automatically Predict Bioactivities of Per- and Polyfluoroalkyl Substances (PFASs)

Hyuna Kwon, Zulfikhar Ali, Bryan Wong

Version 1 posted 24 August 2022

111

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1

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Theoretical and Computational Chemistry

Working Paper

The Principal Component Analysis of the Ring Deformation in the Nonadiabatic Surface Hopping Dynamics

Yifei Zhu, Jiawei Peng, Xu Kang, Chao Xu, Zhenggang Lan

Version 1 posted 29 June 2022

170

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Nanoscience

Working Paper

Unsupervised Analysis of Optical Imaging Data for the Discovery of Reactivity Patterns in Metal Alloy

Rui Li, Aleksei Makogon, Tatiana Galochkina, Jean-François Lemineur, Frédéric Kanoufi, Viacheslav Shkirskiy

Version 2 posted 09 June 2023

276

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Analytical Chemistry

Working Paper

Unsupervised pharmaceutical polymorph identification and multicomponent particle mapping of ToF-SIMS data by non-negative matrix factorization

Thomas P. Forbes, Greg Gillen, Amanda J. Souna, Jeffrey Lawrence

Version 1 posted 05 September 2022

270

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Materials Chemistry

Working Paper

Unsupervised Machine Learning for Unbiased Chemical Classification in X-ray Absorption Spectroscopy and X-ray Emission Spectroscopy

Samantha Tetef, Niranjan Govind, Gerald Seidler

Version 1 posted 21 June 2021

822

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Materials Science

Working Paper

Sampling real-time atomic dynamics in metal nanoparticles by combining experiments, simulations, and machine learning

Matteo Cioni, Massimo Delle Piane, Daniela Polino, Daniele Rapetti, Martina Crippa, Ece Arslan Irmak, Sandra Van Aert, Sara Bals, Giovanni Maria Pavan

Version 2 posted 15 September 2023

245

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Analytical Chemistry

Working Paper

Is Unsupervised Dimensionality Reduction Sufficient to Decode the Complexities of Electrochemical Impedance Spectra?

Aleksei Makogon, Frédéric Kanoufi, Viacheslav SHKIRSKIY

Version 2 posted 10 January 2024

458

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Refine Search

10 results in unsupervised machine learning in Keywords: unsupervised machine learning

Conformational Dynamics of the Pyrene Excimer

Automated Analysis of Nano-Impact Single-Entity Electrochemistry Signals using Unsupervised Machine Learning and Template Matching

A Machine Learning Approach for Predicting Defluorination of Per- and Polyfluoroalkyl Substances (PFAS) for Their Efficient Treatment and Removal

Harnessing Semi-Supervised Machine Learning to Automatically Predict Bioactivities of Per- and Polyfluoroalkyl Substances (PFASs)

The Principal Component Analysis of the Ring Deformation in the Nonadiabatic Surface Hopping Dynamics

Unsupervised Analysis of Optical Imaging Data for the Discovery of Reactivity Patterns in Metal Alloy

Unsupervised pharmaceutical polymorph identification and multicomponent particle mapping of ToF-SIMS data by non-negative matrix factorization

Unsupervised Machine Learning for Unbiased Chemical Classification in X-ray Absorption Spectroscopy and X-ray Emission Spectroscopy

Sampling real-time atomic dynamics in metal nanoparticles by combining experiments, simulations, and machine learning

Is Unsupervised Dimensionality Reduction Sufficient to Decode the Complexities of Electrochemical Impedance Spectra?

10 results in Keywords: unsupervised machine learning