Fullrmc opens a new dimension of modeling the atomic structure of complex physical systems.  

Prof. Valeri Petkov

Dept. Physics Central Michigan University

Atomic modeling practitioner since 1995

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Fullrmc has been an indispensable tool in my research group.  The user interface is very intuitive, which has been helpful in training new PhD students, especially those from non-physics/materials background that we tend to get in chemical engineering. Our group has used several features that are either enhanced by comparison to other RMC-like codes, or completely unique to fullrmc to model a range of materials, such as multimetallic nanoparticles, 2D heterostructures, single-atom catalysts, and polymer derived ceramics (to name a few).  The versatility to test multiple hypothesis in parallel or succession, especially through the use of cloud computing resources, makes analysis such much more efficient.  Most importantly, fullrmc support team has been extremely helpful when my group has questions. 

Dr. Nicholas Bedford

Senior Lecturer, University of New South Wales, Chemical Engineering

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Fullrmc is essential in every computational chemist and material scientist's toolbox. I use it to model amorphous phases of thin films. It is handy for generating initial amorphous states, which were difficult to generate prior. Furthermore, the ease with which it is possible to define the constraints and work with experimental data makes it very convenient. Because our team works with large molecular boxes (ten thousand atoms and more), MC methods are our best option, and the results we get so far were not possible to achieve with MD or QM so quickly. Lastly, the support team is excellent and answers questions quickly (and at odd times, if needed).

Daniel Khaykelson

Ph.D. Student, Weizmann Institute of Science

Department of Molecular Chemistry and Material Science

Fullrmc provides all the features needed to understand a complex polymeric system and apply Reverse Monte Carlo simulation into my research project. The software can get information about the local structure of my samples without any long-range order requirements, something that was not possible through conventional modeling. Another positive factor is the friendly interface, especially for people that are not familiar with the Python language.  Additionally, there are definitions for each feature, facilitating the selection of suitable constraints. fullrmc offers detailed tutorial videos that helped me at the initial stage, but the support is not limited to that; it is possible to find information about each session in the Frequently Asked Questions (FAQ) session. The software has been the key to my research development; I definitely recommend it!

Haira G. Hackbarth

Ph.D. Student, University of New South Wales, Chemical Engineering