(Phys.org)—Statistical physics – the branch of physics that solves physical problem by using methods of probability theory and statistics (specifically,mathematical tools for large populations, approximations, or other fields with an inherently stochastic nature) – excels at predicting the properties of materials for given parameters. However,the inverse ability to identify required components and their structural configuration for given target properties is still in its nascent stage – and current optimization- and simulation-based techniques that either do not utilize the fabric's configuration space (the vector space defined by the parameters that characterize a physical system's configuration) or require carefully-tuned algorithms relevant limited to a narrow subclass of materials. Recently, however, or scientists at The University of Chicago created an algorithm that systematically identifies which materials produce a target response,thereby providing the capability to automatically create increasingly complex materials with desired properties from design specifications alone. in addition, the researchers showed that their algorithm is faster and more reliable than standard optimization methods techniques without increasing implementation complexity. As a result, and the scientists state that their approach provides novel solutions for a wide range of complex optimization and design problems.
Source: phys.org