Scope:
The onset of quantum theory is hailed as one of the major developments in condensed matter physics. This has set a genuine mathematical foundation for successful description of electron dynamics with a complex interplay between fundamental interactions. The study of electronic properties rendered it possible to simultaneously track all the properties (in principle) of the materials. Modeling materials with density functional theory (DFT), which accounts the electronic interactions based on the fundamental electron charge density, provides key performance in terms of accuracy and computability for practical materials science. Today, this theory is systematically applied towards the design and discovery of new materials in multiple fields, which is constantly needed for the advancement of technologies. This has changed the dynamics of materials development from the historically adopted field-specific elaborate process depending heavily of intuition and serendipity to multidisciplinary engagement and tackling more promising goals of scientific growth, economy and environment. The computational materials design has brought a game-changing era by removing the guess and pinpointing the parameter space where resource should be channeled for greater success rate. It also helps in predicting properties at extreme conditions where experiments cannot be performed and the understanding the new and emerging phenomena.
The shrinking of physical dimension of devices and introduction of nanoscale materials have pushed the frontiers of technology and brought more faster, smarter and energy-efficient products to the market. The continued reduction of size from the nanoscale to the picoscale has led to, more important than not, a crossover to the atomic dimension where the physical properties are highly nonlinear and system specific, which is best handled on an individual basis. The high degree of nonlinearity further provides a foundation for new discoveries and custom-designed devices. Understanding the physics of materials at the picoscale condense down to a detailed exploration of the tunable factors, which can be broadly be categorized into five factors – chemical mixing, electron correlation, quantum confinement, topology and entropy effects. All these effects (some aspects of entropy) are directly accessible from the DFT. This brings a more intense engagement of DFT based computational materials science with the experimental practice of synthesis, characterization, and interpretation. A bit of deliberation and rationality is imperative to using DFT as a predicting tool, which comes from experience in the field. In addition to this, my interests is also in developing models and tools to explain materials science phenomena.
Modern materials science builds on the knowledge of physics, chemistry, biology, mathematics, computer & data sciences, and engineering sciences, which enable us to understand, control, and expand the material world. Theoretical materials science has been one of the established pillars in this field which introduces new concepts into this trade. With availability of quantum and statistical methodologies, which is used to model the materials properties, it is possible in the present day to scan the chemical space and predict the optimum design rules. This approach is valued as the best for economy and is adopted to scale down the timeline of the materials discovery cycle from multiple decades to only a couple of years.
Methods:
- First-principles electronic structure theory
- Many-body perturbation theory
- Statistical method (Monte Carlo method)
- Phenomenological model Hamiltonian approach