Publications de Nicholas John Browning

Applications of Artificial Intelligence to Computational Chemistry

The calculation of the electronic structure of chemical systems, necessitates computationally expensive approximations to the time-independent electronic Schrödinger equation in order to yield static properties in good agreement with experimental results. ...

EPFL2019

A genetic algorithm based design and experimental characterization of a highly thermostable metalloprotein

Ursula Röthlisberger, Rudolf Hovius, Esra Bozkurt, Marta Andreia Da Silva Perez, Nicholas John Browning

The development of thermostable and solvent-tolerant metalloproteins is a long-sought goal for many applica- tions in synthetic biology and biotechnology. In this work, we were able to engineer a highly thermo- and organic solvent- stable metallo variant o ...

2018

Nonadiabatic effects in electronic and nuclear dynamics

Majed Chergui, Ursula Röthlisberger, Jiri Vanicek, Martin Peter Bircher, Tomas Zimmermann, Elisa Liberatore, Aurélien Kevin Fabrice Patoz, Nicholas John Browning

Due to their very nature, ultrafast phenomena are often accompanied by the occurrence of nonadiabatic effects. From a theoretical perspective, the treatment of nonadiabatic processes makes it necessary to go beyond the (quasi) static picture provided by th ...

2017

Genetic Optimization of Training Sets for Improved Machine Learning Models of Molecular Properties

Ursula Röthlisberger, Anatole von Lilienfeld, Nicholas John Browning

The training of molecular models of quantum mechanical properties based on statistical machine learning requires large data sets which exemplify the map from chemical structure to molecular property. Intelligent a priori selection of training examples is o ...

2017

Lessons from Nature: Computational Design of Biomimetic Compounds and Processes

Ursula Röthlisberger, Pablo Campomanes Ramos, Elizabeth Claire Brunk, Negar Ashari Astani, Esra Bozkurt, Marta Andreia Da Silva Perez, Nicholas John Browning

Through millions of years of evolution, Nature has accomplished the development of highly efficient and sustainable processes and the idea to understand and copy natural strategies is therefore very appealing. However, in spite of intense experimental and ...

2014