From the atom up!
Our team is interested in engineering systems through defects and disorder on the picoscale (10-12 m). As the development and discovery of advanced systems and materials are needed to keep pace with the ever-changing societal demands. Instead of the trial and error approach, we utilize a multi-modal framework in-situ and feedback loops between 3D atomic coordinate information with picometer precision, state-of-the-art spectroscopy, and microscopy techniques with quantum mechanical computational methods to understand and discover new advanced materials from the atom up. Our group will focus on applications in thermal, energy, semiconductor, and quantum sciences.
Below is a figure of the feedback loops my research group will utilize to study materials in-situ. For more information about techniques used or previous work, refer to the Publications page.
Research Topic Areas
sAET of Re-doped MoS2
3D atomic model of the Re-doped MoS2 monolayer determined by sAET, consisting of 1381 S (in yellow), 686 Mo (in blue), 21 Re atoms (in black) and 15 S vacancies (in pink). Compared to an ideal MoS2 atomic model (in white saturated colors), the experimental model shows 3D crystal defects, atomic displacements and full strain tensors of the 2D material. (Nat. Mater 19, pages 867–873 (2020))
AET of an amorphous Pd nanoparticle
Experimental 3D atomic model of the amorphous Ta thin film. The reconstructed volume of the thin film consists of 6,615 disordered atoms (in blue) with several crystal nuclei of 1,669 atoms on the surface (in grey). (Nat. Mater. 21, pages 95–102 (2022))
Techniques and methods
Atomic Electron Tomography (AET)
Atomic electron tomography, which combines high-resolution electron imaging with in-house computational algorithms, can achieve true three-dimensional quantitative atomic structures at picometer precision without assuming crystallinity.
Science 353, aaf2157 (2016).Quantitative Spectroscopy and Microscopy
The study of condensed phases has benefited from the advancements in electron, x-ray, and neutron scattering techniques. The high brightness from X-ray and neutron sources to aberration correctors, monochromators, and direct electron pixel detectors allow for the probe of structure, dynamics, and excitations. The majority of our work is performed on state-of-the-art microscopes on campus (UF Research Service Centers) with specialized in-situ holders. But we will often travel to use national user facilities as well.
Nanoscale Research FacilityComputational Methods
Our Team uses an array of classical and quantum simulation methods to study the atomistic chemistry and physics of materials, develop artificial intelligence and machine learning models, analyze data, and perform tomographic reconstructions. We commonly use modern GPU-accelerated density functional theory (DFT) software packages and excited-state molecular dynamics codes. The group has access to an abundance of high-performance GPUs and CPU cores on UF’s HiPerGator supercomputing cluster.
HiPerGatorFunding
Framework for Unified Simulation in Epitaxial/Crystal Bonding (FUSE)
DARPA-ARCS-CRYSTAL (PI)
Heterogeneous integration of multifunctional single-crystal thin films is critical for next-generation photonics, quantum computing, and advanced sensing. Wafer bonding, combined with layer-transfer methods such as ion-cut, enables the assembly of complex multi-material systems, yet process development remains largely empirical, costly, and difficult to generalize to emerging materials. The FUSE program (Framework for Unified Simulation in Epitaxial/Crystal Bonding) develops a predictive, physics-based framework that bridges the quantum-mechanical description of the chemical bond and wafer-scale thermomechanics. It couples density functional theory (DFT), machine-learned interatomic potentials (MLIPs), crystal orbital Hamilton population (COHP) bonding analysis, and finite-element multiphysics to describe ion implantation, amorphization, temperature- and pressure-dependent thermal expansion, and interfacial bonding in a lithium niobate on silica model system, with in-house wafer-bonding experiments providing validation. In recent work, we constructed and stabilized crystalline and amorphous LiNbO3 interfaces from first principles and computed temperature- and pressure-dependent bonding (COHP) across the interface. Initial results indicate that the covalent Nb-O network is the primary load-bearing interaction and a likely control point for adhesion and ion-cut splitting. Together, DFT, QM/MM, and MLIPs form a pipeline that lowers cost and enables larger, transferable simulations required for predictive wafer-bonding design.