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Chemistry

D-Index
62
Citations
16536
World Ranking
8718
National Ranking
283

Overview

Maciej Haranczyk is affiliated with the Madrid Institute for Advanced Studies in Spain. Their research primarily intersects materials science and engineering, with a focus on several subfields including materials chemistry, inorganic chemistry, computational theory and mathematics, electrical and electronic engineering, and polymers and plastics.

Their work spans multiple scientific topics, with a strong emphasis on machine learning applications within materials science. Key topics they have investigated include:

  • Machine Learning in Materials Science
  • Metal-Organic Frameworks: Synthesis and Applications
  • X-ray Diffraction in Crystallography
  • Computational Drug Discovery Methods
  • Additive Manufacturing and 3D Printing Technologies
  • Advancements in Battery Materials
  • Flame retardant materials and properties

Maciej Haranczyk has contributed to a number of peer-reviewed papers published in recognized venues, including journals and archives. Notable recent publications are:

  • Fast and Accurate Machine Learning Strategy for Calculating Partial Atomic Charges in Metal-Organic Frameworks, 2021, Journal of Chemical Theory and Computation
  • Flame retardant properties of metal hydroxide-based polymer composites: A machine learning approach, 2023, Composites Communications
  • Machine learning using host/guest energy histograms to predict adsorption in metal-organic frameworks: Application to short alkanes and Xe/Kr mixtures, 2021, The Journal of Chemical Physics
  • High-rate and ultralong-life Mg-Li hybrid batteries based on highly pseudocapacitive dual-phase TiO2 nanosheet cathodes, 2021, Journal of Power Sources
  • CoRE MOF DB: A curated experimental metal-organic framework database with machine-learned properties for integrated material-process screening, 2025, Matter

The scientist has collaborated frequently with colleagues such as De-Yi Wang, Christina Schenk, Randall Q. Snurr, Giulia Lo Dico, and Miguel Hernández-del-Valle. These collaborations suggest an active engagement in interdisciplinary efforts related to materials science and computational modeling.

Their publications have appeared regularly in venues including:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Digital Discovery
  • Computational Materials Science
  • SSRN Electronic Journal

Through this body of work, Maciej Haranczyk addresses diverse scientific challenges such as designing new materials via machine learning, exploring the properties of metal-organic frameworks, improving battery technologies, and understanding flame retardant polymer composites.

Best Publications

  • Algorithms and tools for high-throughput geometry-based analysis of crystalline porous materials

    Thomas F Willems;Chris Rycroft;Chris Rycroft;Michael Kazi;Michael Kazi;Juan Colin Meza

  • Correction: Corrigendum: Kinetically tuned dimensional augmentation as a versatile synthetic route towards robust metal–organic frameworks

    Dawei Feng;Kecheng Wang;Zhangwen Wei;Ying-Pin Chen

  • Advances, Updates, and Analytics for the Computation-Ready, Experimental Metal–Organic Framework Database: CoRE MOF 2019

    Yongchul G. Chung;Emmanuel Haldoupis;Benjamin J. Bucior;Maciej Haranczyk

  • Computation-Ready, Experimental Metal–Organic Frameworks: A Tool To Enable High-Throughput Screening of Nanoporous Crystals

    Yongchul G. Chung;Jeffrey Camp;Maciej Haranczyk;Benjamin J. Sikora

  • In silico screening of carbon-capture materials

    Li-Chiang Lin;Adam H. Berger;Richard L. Martin;Jihan Kim

  • Metal-organic framework with optimally selective xenon adsorption and separation.

    Debasis Banerjee;Cory M. Simon;Anna M. Plonka;Radha K. Motkuri

  • Kinetically tuned dimensional augmentation as a versatile synthetic route towards robust metal-organic frameworks

    Dawei Feng;Kecheng Wang;Zhangwen Wei;Ying-Pin Chen

  • The materials genome in action: identifying the performance limits for methane storage

    Cory M. Simon;Jihan Kim;Diego A. Gomez-Gualdron;Jeffrey S. Camp

  • Progress in ab initio QM/MM free-energy simulations of electrostatic energies in proteins: accelerated QM/MM studies of pKa, redox reactions and solvation free energies.

    Shina C. L. Kamerlin;Maciej Haranczyk;Arieh Warshel

  • pyIAST: Ideal adsorbed solution theory (IAST) Python package

    Cory M. Simon;Cory M. Simon;Berend Smit;Berend Smit;Maciej Haranczyk

  • An assessment of strategies for the development of solid-state adsorbents for vehicular hydrogen storage

    Mark D. Allendorf;Zeric Hulvey;Zeric Hulvey;Thomas Gennett;Thomas Gennett;Alauddin Ahmed

  • What Are the Best Materials To Separate a Xenon/Krypton Mixture?

    Cory M. Simon;Rocio Mercado;Sondre Kvalvåg Schnell;Berend Smit

  • Addressing challenges of identifying geometrically diverse sets of crystalline porous materials.

    Richard Luis Martin;Berend Smit;Maciej Haranczyk

  • Materials Genome in Action: Identifying the Performance Limits of Physical Hydrogen Storage

    Aaron William Thornton;Cory M. Simon;Jihan Kim;Ohmin Kwon

  • Xenon Gas Separation and Storage Using Metal-Organic Frameworks

    Debasis Banerjee;Cory M. Simon;Sameh K. Elsaidi;Maciej Haranczyk;Maciej Haranczyk

  • Capturing chemical intuition in synthesis of metal-organic frameworks

    Seyed Mohamad Moosavi;Arunraj Chidambaram;Leopold Talirz;Maciej Haranczyk

  • Accurate Characterization of the Pore Volume in Microporous Crystalline Materials.

    Daniele Ongari;Peter G. Boyd;Senja Barthel;Matthew Witman

  • Systematic Tuning and Multifunctionalization of Covalent Organic Polymers for Enhanced Carbon Capture

    Zhonghua Xiang;Rocio Mercado;Johanna M. Huck;Hui Wang

  • On the Flexibility of Metal–Organic Frameworks

    Lev Sarkisov;Richard L. Martin;Maciej Haranczyk;Berend Smit;Berend Smit

  • Evaluating different classes of porous materials for carbon capture

    Johanna M. Huck;Johanna M. Huck;Li-Chiang Lin;Adam H. Berger;Mahdi Niknam Shahrak

  • Identification Schemes for Metal-Organic Frameworks To Enable Rapid Search and Cheminformatics Analysis

    Benjamin J. Bucior;Andrew S. Rosen;Maciej Haranczyk;Zhenpeng Yao

Frequent Co-Authors

Berend Smit
Berend Smit University of California, Berkeley
Maciej Gutowski
Maciej Gutowski Heriot-Watt University
Richard L. Martin
Richard L. Martin Los Alamos National Laboratory
Kit H. Bowen
Kit H. Bowen Johns Hopkins University
Mark Asta
Mark Asta University of California, Berkeley
Li-Chiang Lin
Li-Chiang Lin The Ohio State University
Randall Q. Snurr
Randall Q. Snurr Northwestern University
Jeffrey R. Long
Jeffrey R. Long Lawrence Berkeley National Laboratory
James A. Sethian
James A. Sethian University of California, Berkeley
Ben Slater
Ben Slater University College London

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