A robust metadata database called the Collaborative Chemistry Database Tool (CCDBT) for massive amounts of computational chemistry raw data has been designed and implemented. It performs data synchronization and simultaneously extracts the meta data. The indexed meta data can be used for data analysis and data mining. A novel tree growth - hybrid genetic algorithm (TG-HGA) was developed to search the global minimum of small clusters. In the TG algorithm, the clusters grow from a small seed to the size of interest stepwise. New atoms are added to the smaller cluster from the previous step, by analogy to new leaves grown by a tree. The initial structures for the search for the global minimum of TiO_2 nanoclusters were generated by TG-HGA, and...
Reactivity studies on catalytic transition metal clusters are usually performed on a single global m...
We first report a global optimization approach based on GPU accelerated Deep Neural Network (DNN) fi...
We have developed and implemented a new global optimization technique based on a Lamarckian genetic ...
This thesis presents computational studies of the geometric and electronic structures and energetic ...
Virtual high throughput screening, typically driven by first-principles, density functional theory c...
We have performed a genetic algorithm search on the tight-binding interatomic potential energy surfa...
We have performed a genetic algorithm search on the tight-binding interatomic potential energy surfa...
In order to design clusters with desired properties, we have implemented a suite of genetic algorith...
Virtual high throughput screening, typically driven by first-principles, density functional theory c...
Due to the inherent need for atomic-scale resolution, reaction mechanisms have -for the longest time...
Computational chemistry approaches have been used to study the reactivity of Group IVB and VIB trans...
Being progressively applied in the design of highly active catalysts for energy devices, machine lea...
Composition, atomic structure, and electronic properties of TMxMgyOz clusters [transition metal (TM)...
The development of powerful computer algorithms that are specialized at exploring the energy landsca...
Recent transformative advances in computing power and algorithms have made computational chemistry c...
Reactivity studies on catalytic transition metal clusters are usually performed on a single global m...
We first report a global optimization approach based on GPU accelerated Deep Neural Network (DNN) fi...
We have developed and implemented a new global optimization technique based on a Lamarckian genetic ...
This thesis presents computational studies of the geometric and electronic structures and energetic ...
Virtual high throughput screening, typically driven by first-principles, density functional theory c...
We have performed a genetic algorithm search on the tight-binding interatomic potential energy surfa...
We have performed a genetic algorithm search on the tight-binding interatomic potential energy surfa...
In order to design clusters with desired properties, we have implemented a suite of genetic algorith...
Virtual high throughput screening, typically driven by first-principles, density functional theory c...
Due to the inherent need for atomic-scale resolution, reaction mechanisms have -for the longest time...
Computational chemistry approaches have been used to study the reactivity of Group IVB and VIB trans...
Being progressively applied in the design of highly active catalysts for energy devices, machine lea...
Composition, atomic structure, and electronic properties of TMxMgyOz clusters [transition metal (TM)...
The development of powerful computer algorithms that are specialized at exploring the energy landsca...
Recent transformative advances in computing power and algorithms have made computational chemistry c...
Reactivity studies on catalytic transition metal clusters are usually performed on a single global m...
We first report a global optimization approach based on GPU accelerated Deep Neural Network (DNN) fi...
We have developed and implemented a new global optimization technique based on a Lamarckian genetic ...