Hierarchical Synthesis for Energy, Information, and Functionality
This theme aims to achieve energy efficiency and energy transduction in systems that employ hierarchical synthesis and materials design at the nanoscale. It combines synthesis and nanofabrication across different scales and aims to use both self-assembly and top-down approaches.
In this theme, research seeks to identify new pathways in energy and information transduction, including propagation of charge, spin and collective phenomena. Work in this theme also includes the development of new ways for materials to adaptively respond to the environment. Implementation of this theme is intimately connected to, and relies on, the natural developments arising from the other themes.
The following programs are undertaken within this theme.
We study natural processes to develop and improve hybrid nanomaterials and architectures, not found in nature, but that are still guided by nature’s principles. For this purpose, we design and assemble energy gradient architectures composed of peptides, nanoparticles and proteins that enable distance-dependent charge and energy transfer. Investigation of these structures involves X-ray nanoimaging and in-situ liquid transmission electron microscopy, hyperspectral time-resolved optical spectroscopy and droplet microfluidics.
This work focuses on hybrid organic-inorganic nano-architectures with controlled porosities for selective filtration and absorption—areas with significant potential in the energy sector.
Examples include new combinations of polymers and inorganic precursor species examined using a combination of in-situ spectroscopy, a quartz crystal microbalance, and density functional theory, in order to establish a a broad library of hybrid composite materials. Researchers at the CNM also investigate self-assembled, free-standing membranes made of nanoparticles showing high mechanical strength and demonstrating controlled transport.
To achieve the next revolution in computing technologies, the CNM is working to develop new neuromorphic, computational architectures for manipulating information efficiently. Biologically inspired, but in form and function much closer to the inorganic world, these architectures require new materials and devices whose properties can encode the functionality of neuromorphic components such as neurons and synapses. The goal is to provide the underlying materials science and understanding of the nanomaterials and structures that will underpin neuromorphic information processing engines of the future.
2D Materials—Borophene and Beyond
As pioneers in the experimental discovery of borophenes (the first synthetic 2D material and new boron allotrope), we are rapidly expanding our understanding and development of low-dimensional borophenes to allow synthesis on new substrates, the creation of heterostructures, the study of exotic physical properties (quasi-particle interference, charge density waves (CDWs), and superconductivity), as well as the fabrication of isotopically pure borophenes.