Programmers Develop Computer Tool to Detect Chemical Compounds for use in Rare-Earth Processing

11 June 2017

The modern world is dependent on electronic devices and appliances; without them, populations would riot.

Modern appliances, meanwhile, are dependent on rare earth elements in their electronic components to significantly improve their electromagnetic properties. Everything from vacuum cleaners to refrigerators, from mobile phones to laptops, needs these rare earth minerals.

Currently 95% of world production of rare earth elements is in China, which gained its near monopoly towards the end of the 20th century. In the year 2000, the situation came to a head when a trade dispute at the WTO flared up. China began setting quotas and export licenses, and the cost of production and exports skyrocketed.

As a result, the U.S. chose to renew its mining and production operations, intent on maintaining a source of a highly strategic material. Without rare-earth elements a nation cannot make satellites, military command and control systems, a space program or even a modern army.

The U.S. Department of Energy’s Critical Materials Institute (CMI) was assigned a primary goal of finding environmentally friendly and cheaper ways of sourcing rare-earth minerals. This research is now bearing fruit, and may lead to cheaper rare-earth minerals, and even cheaper electronics.

For recently the CMI reported that it has developed a computer program that will dramatically reduce the time and money it takes to identify promising chemical compounds that are used in rare-earth processing methods. As software designer and CMI scientist Federico Zahariev explains, “Traditional, quantum mechanical methods of predicting the molecular design and behavior of these extractants are too computationally expensive, and take too long for the timescale needed. So we developed a program that could create a simpler classical mechanical model which would still reflect the accuracy of the quantum mechanical model.”

The research team have named this computer program ParFit, “a Python-Based Object-Oriented Program for Fitting Molecular Mechanics Parameters to ab Initio Data.”

Reporting on the development, the online scientific journal Phys.org, notes that, “ParFit uses traditional and advanced methods to train the classical mechanical model to fit quantum mechanical information from a training set. These classical models can then be used to predict the shape of new extractants and how they bind to metals.”

“Roughly speaking, think of the molecule’s shape and structure as a system of springs, where there might need to be a lot of small tightening or loosening of different connections to make it work correctly,” said CMI Scientist Theresa Windus. “It’s the same way in which we apply the quantum mechanical calculations to create these classical mechanical models—it’s a tedious, error-prone, and lengthy process. ParFit makes this as quick as possible, automates the fitting of those parameters, and accurately reproduces the quantum mechanical energies.”

The researchers have published their results in the Journal of Chemical Information and Modelling, where they describe the program as follows; “ParFit uses a hybrid of deterministic and stochastic genetic algorithms. ParFit can simultaneously handle several molecular-mechanics parameters in multiple molecules and can also apply symmetric and antisymmetric constraints on the optimized parameters. The simultaneous handling of several molecules enhances the transferability of the fitted parameters.”

While this outlines the more scientific side of the development, the team can also appreciate the practical application of the program, as they state in the publication that, “As an example, a series of phosphine oxides, important for metal extraction chemistry, are parametrized using ParFit.”

Interestingly, they also note that, “ParFit is in an open source program available for free on GitHub (https://github.com/fzahari/ParFit).”

“The program’s capabilities enable the researchers to model an almost unlimited number of new extractants,” says software developer and CMI Scientist Marilu Dick-Perez. For example, the classical models used in the software code, HostDesigner – developed by Benjamin Hay of Supramolecular Design Institute, creates and quickly assesses possible extractants for viability and targets extractants that are best suited for further research. “We’ve reduced the computational work from 2-3 years down to three months,” she said. “We’ve incorporated as much expert knowledge into this program as possible, so that even a novice user can navigate the program.”

Given the free access to the program and its alleged ease of use, the impact that this program may have on rare-earth mineral sourcing could be huge. While it is unlikely to break China’s near-monopoly on production, it could still reduce costs, and with Beijing further embracing market economics, this development may lead to cheaper chemical exports of the vital rare-earth elements that we all use.

Photo credit: Saskatchewan Research Council