Progna Banerjee, Ph.D.
My Aim: "Nanomaterial design for batteries using wet chemistry, physics, and machine learning"
Highlight: My research on superionic solids (co-first author) featured on several science and general news outlets including Smithsonian magazine, R&D Magazine, AzoNanao, CEMag, Phys.Org, EurekAlert, UIUC News Bureau etc. Read the excerpt from Smithsonian placing our studies in perspective with the emerging technologies in solid state battery technology here (Credit for the image: mattjeacock/iStock).
RESEARCH HIGHLIGHT
What would the nanomaterials discovery landscape look like if we can utilize artificial synthetic chemistry platforms to handle permutations, formulation selection, nanoparticle assembly on chip, and subsequent analyses? Can we couple this system with machine learning based algorithmic materials selection to predict unconventional phases and properties in these nanomaterials? To explore the realization of these systems I am working on the materials chemistry and physics experiments coupled with predictive modeling and guided design principles from our theory collaborators at NST, Argonne that inform our scientific perspectives.
Previously, my dissertation at the University of Illinois at Urbana-Champaign was focused on the synthetic discovery of the chalcogenide nanocrystals in unusual phases that support physicochemical behavior which cannot be predicted from a linear scaling of such properties from their bulk counterparts.
SUPERIONIC SOLID STATE ELECTROLYTES THROUGH NANOCRYSTAL DISCOVERY
Superionic conductors (top left of embedded figure) are realized with several orders of degrees of higher ionic conductivities where the cationic sublattice "melts" above a phase transition temperature (top right cartoon, Cu ions shown as a blue sea around the red Se anionic sublattice) driving the free movement of cations in the lattice.
In my dissertation work on copper selenide nanoparticles derived from cadmium selenide quantum dots through a topotactic post-synthetic method called "cation exchange", the stabilization of the superionic state was shown at ambient temperatures (bottom panels showing differential scanning calorimetry results in utrasmall copper selenide nanocrystals compared to "bulk"). This work was extended to incorporate lithium ions in copper selenide nanocrystals in superionic state for the first time under ambient conditions, compared to hundreds of degrees of temperature required over a prolonged period of time in bulk state to mix lithium with copper selenide powder through conventional methods. The presence of lithium in superionic copper selenide can be useful for reducing the redox potential at the solid electrolyte/anode interface in solid state batteries. This work is being extended with the help of machine learning to explore nanomaterials in unconventional phases and compositions.
TOPOLOGICAL INSULATING PROPERTIES INDUCED IN NANOCRYSTALS VIA SYMMETRY BREAKING
Topological insulating (TI) properties with conducting surface states but bulk insulating behavior are observed in a few classes of chalcogenides such as Sb-doped Bi2Se3, (Sb, V)2Te3, HgTe and Bi2Se3 etc in single crystals and films. However, in the case of HgSe which exists as a zinc blende crystal structure with semi-metallic properties and a zero band gap, TI properties are not expected. Using cation exchange under ambient conditions, we show the symmetry of the crystal structure can be reduced effectively opening up a non-negligible band gap with current studies using STM-STS techniques underway to confirm the TI behavior in these nanomaterials.
Using post-synthetic cation exchange from CdSe quantum dots in wurtzite crystal structure in colloidal state, Hg ions can be introduced in a topotactic manner to retain the crystal symmetry throughout the exchange process. The nanocrystals with compositions in the range of Hgx(Cd1-x)Se (0.3<x<0.5, experimentally deduced) are shown through band structure calculations to possess a non-negligible band gap. Currently together with colleagues from the Quantum Energy Materials (QEM) group at Argonne NST, I am working to experimentally prove the existence of the TI properties in these nanocrystals using techniques such as STM-STS (Scanning Tunneling Microscopy-Scanning Tunneling Spectroscopy) and related techniques.
MATERIALS TECHNOLOGY ENABLED THROUGH HIGH-THROUGHPUT AUTONOMOUS ROBOTS
I am working on the high throughput synthesis of nanomaterials using an autonomous liquid handling robot to provide rapid mapping of various parameters in the synthesis space. Involved in this effort are colleagues from NST at Argonne working on the robotics, AI and instrumentation aspects to create a self-driving nanomaterials discovery platform.
AI assisted nanomaterials discovery: My current efforts at Argonne NST comprises of using a autonomous liquid-handling robotic platform to design nanomaterials in unusual phases, crystal symmetries and compositions. Material discovery is an arduous process which requires years worth of hard work and thousands of experiments to barely scratch the parameter space for a chosen combination of materials and operating conditions. Using nanoscale transformations and microfluidic technologies, we are striving to create a self-operating lab platform starting with colloidal sample handling, mixing, reactors, followed by in-built characterization tools for quality assessment and measurements of crucial physicochemical properties.
BIOINSPIRED MATERIALS
Insects produce/secrete fascinating biomaterials which are only starting to be investigated mechanistically through biomimetic manufacturing processes and find suitable applications. As part of the ARO-funded MURI team, I studied brochosomes, which are spheroidal nanostructures produced by leafhopper insects that exhibit superhydrophobicity, antireflectivity, and other properties.
Bioinspired materials: My research on investigating the mechanistic insights of light-matter interaction in leafhopper brochosomes using a finite element method computation technique coupled with optical experiments attributes the ultra-high antireflective behavior in these nanoscale biomaterials to a Fano resonance induced coupling. The studies on the origin of anti-reflectivity is being extended to other insect species.
DISSEMINATION OF PLASMONIC MODES USING EELS DATA IN NANOCRYSTAL ARRAYS USING FINITE-ELEMENT SIMULATIONS
The metals and semiconductor nanomaterials produced through ion exchange are studied for their near-field plasmonic behavior. Electron energy loss spectroscopy (EELS) is a nanoscale hyperspectral technique used to understand the optical response and compositional attributes in these nanocrystals.
There has been a recent push for new experimental methodologies that can provide comprehensive information about a complex system at the nanoscale, while concurrently being time efficient and resulting in high fidelity data. Here, through the use of my computational expertise I am collaborating with the ORNL team on disseminating the plasmonic modes resulting from the surface, bulk, edge etc. of a single plasmonic nanomaterial and comparing
PLASMONIC NEAR-FIELD INTERACTIONS VISUALIZED USING SPECTROSCOPY, MICROSCOPY AND SIMULATIONS
Scanning tunneling spectroscopy is another technique applied recently at the single particle level to visualize the near-field distribution in plasmonic nanoparticles.
Single particle STS applied to Au nanoislands can effectively map the charge density around the proximity and hence provide a quantitative estimate of the strength of the near-field interaction. Using computational techniques I provided qualitative proofs in such studies by making a correlation between the experimentally obtained charge maps with simulated near-field intensity distributions.