Directed Nanoscale Transformations
Seeks to illuminate the basic scientific questions of how matter can be transformed locally and will thus enable novel nanofabrication approaches.
A foundational promise of nanoscience is the deterministic control of matter to create novel 1D-3D nanoscale structures with desired form and function. While it has always been possible to observe material transformations using different microscopy platforms, advances over the past few years in scanning electron/ion/probe-microscopy techniques now enables us to move beyond pure observation and into the regime of precision manipulation, fabrication and control. This exquisite control of the energy source (e.g., beam or probe), in combination with advances in computation and theory with scalable ab initio calculations and machine learning approaches, makes now the opportune moment for delivering on this promise. The overarching goal of the DNT theme is to dynamically control changes of chemical and structural states that materials undergo in confined and non-equilibrium conditions to structure new materials from atoms up. The fundamental challenge in achieving this goal lies in understanding the dynamic processes that give rise to atomic transformation and building a framework to control it in order to achieve a directed nanoscale transformation. To overcome this challenge, three correlated research aims that are focused on understanding the interplay of energy and matter governing material transformations and feedback for direct control:
- Understanding Energy Transfer: Determine the role of energy transfer from beams of energetic particles (electrons, ions, lasers) and external fields (scanning probes) into materials to enable control over highly localized transformations by altering bonds at the atomic and molecular level into excited metastable states.
- Understanding the Role of Energy Landscape: Determine how energy landscape parameters can be locally and globally tuned in order to guide the directed fabrication and atomic manipulation of functional 1D-3D nanostructures on demand from the single atom level up.
- Guided Energy Flow for Controlling Transformations: Develop ML methods for bottom-up descriptions of transformations and reinforced learning to predict and guide transformations.
The starting point for this work is the observation that experimental platforms to visualize structure and function, such as electron, ion, and scanning probe microscopes and associated spectroscopies, can also be used to induce transformation, thus enabling the study and control of the processes guiding highly localized structural, chemical, and electrochemical changes. The understanding gained here will enable us to direct matter with atomic precision to create 3D nanoscale structures with desired form and function.
The expertise in controlling scanning probes, electron beams, and ion beams is crucial to the success of this work. CNMS has attained strong leadership in this area through its work in functional imaging of materials and through LDRD efforts in atomic-scale fabrication. The ability to manipulate and study matter in a tight research loop at the atomic and nanoscale will be of key interest to a broad user community, including those from the QIS field.