Strategic Objectives
• Master global optimization techniques to predict structures without prior geometric data.
• Understand the mechanics of evolutionary algorithms and particle swarm optimization.
• Navigate the complex energy landscapes of potential energy surfaces.
• Accelerate the discovery of high-pressure phases and new functional materials.
The Core Challenge
Traditional materials science relies on trial-and-error, but finding the most stable atomic arrangement from scratch is a needle-in-a-haystack problem.
01
The Quest for the Absolute Minimum
02
The Geometry of Solids
03
Mapping the Energy Terrain
04
The Global Optimization Challenge
05
Survival of the Fittest Structures
06
Collective Intelligence
07
The Engine of Discovery
08
Simulated Annealing
09
Basin Hopping Techniques
10
First-Principles Accuracy
11
Computational Cost Management
12
The Geometry of Space Groups
13
Thermodynamics of Stability
14
Predicting Matter Under Pressure
15
Machine Learning Integration
16
Ab Initio Methods
17
The Diversity Problem
18
Polymorphism and Metastability
19
Software Ecosystems
20
Validation and Experiment
21