Exploring High Pressure Science at the Extremes Through Experiment and Computation

The High Pressure Gordon Conference is one of the longest-running GRCs: the first took place in 1955. Over the past six decades, the scientific community has evolved and expanded from the traditional high-pressure areas of earth interior, phase diagrams of the elements and the synthesis of ultra-hard materials, to planetary science, chemistry beyond the traditional rules, pushing materials properties to new limits and quantum behavior at high density.

Since the turn of the 21st century, we have witnessed our capacity to discover new materials and reveal novel phenomena enhanced by a much stronger interaction between experiment and computation. The meeting will provide a forum to address the latest advances and discoveries in high pressure research, with emphasis on the ways in which the combination of theory, advanced computational methods and experiment are shaping the future of our field. The investigation of the stability of novel binary compounds under pressure (super-hydrides, He compounds, N-rich compounds, ices in planetary interiors) has led to remarkable achievements, such as record superconducting temperatures and capacities for storage of chemical energy. An upcoming challenge of the field is to explore the stability of ternary and quaternary compounds, that will require novel experimental and computational strategies. A next step also is to produce valuable data to address the various time and length scale phenomena at play in planetary interiors.

Some sessions will focus on the presentation of the most advanced tools and methods currently in the portfolio of the high pressure field. The discussion here will focus on how new information, ranging from the discovery of novel remarkable compounds to the revelation of new properties in known substances, is provided by these state-of-the-art techniques. Other sessions will be more prospective in presenting the first steps to tackle complexity at extremes, with a related question of how big data and machine learning based approaches may be adapted to our research strategy, both in treating the huge data output of large facilities and by optimizing the exploration of the phase space of multicomponent materials.