Engineering topics

Dandu, Naveen K.

Publications and source records attributed to Dandu, Naveen K..

6 records

DOE OSTI2024

Hybrid polymer network cathode-enabled soluble-polysulfide-free lithium–sulfur batteries

Among the emerging 'beyond lithium-ion' technologies for maximized sustainability, lithium-sulfur (Li-S) is a favoured chemistry because of its exceptional energy density from the conversion of sulfur, an element in abundant supply. However, the dissolution of several intermediate polysulfides formed during conversion leads to rapid performance degradation over cycling. Here, in this study, we address this issue by sulfurizing a hybrid polymer network with polyphosphazene and carbon as a cathode for Li-S batteries. With rich sites to re-bond and adsorb dissociative sulfur species, this hybrid polymer network circumvents the formation of soluble polysulfides and enables a unique, reversible inserting conversion reaction. Thus, our cathode delivers both high capacity (~900 mAh g -1 cathode ) and excellent cycling stability in Li-S coin cells, with a pouch cell demonstration of projected energy density of ~300 Wh kg -1 and 84.9% capacity retention after 150 cycles. The strategy can be extended to other cost-effective, recyclable polymers, advancing sulfur-based batteries towards practical energy storage application.

25 ENERGY STORAGE↗

DOE OSTI2024

2D Ionic Liquid-Like State of Charged Rare-Earth Clusters on a Metal Surface

Rare-earth complexes are vital for separation chemistry and useful in many advanced applications including emission and energy upconversion. Here, 2D rare-earth clusters having net charges are formed on a metal surface, enabling investigations of their structural and electronic properties on a one-cluster-at-a-time basis using scanning tunneling microscopy. While these ionic complexes are highly mobile on the surface at ≈100 K, their mobility is greatly reduced at 5 K and reveals stable and self-limiting clusters. In each cluster, a pair of charged rare-earth complexes formed by electrostatic and dispersive interactions act as a basic unit, and the clusters are chiral. Unlike other non-ionic molecular clusters formed on the surfaces, these rare-earth clusters show mechanical stability. Moreover, their high mobility on the surface suggests that they are in a 2D liquid-like state.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Single-phase local-high-concentration solid polymer electrolytes for lithium-metal batteries

Solid polymers are promising electrolytes for Li-metal batteries, but they have limitations: they cannot simultaneously achieve high ionic conductivity, good mechanical strength and compatibility with high-voltage cathodes while suppressing Li dendrites. Here, we design a class of locally high-concentration solid polymer electrolytes based on polymer blends, which are termed Li-polymer in F diluter (LPIFD). The Li-polymer (polymer-in-salt) ensures continuous Li-ion conduction channels and contributes to the solid electrolyte interphase (SEI), and the F diluter (inert fluorinated polymer) adds mechanical strength. Studies reveal that a single-phase LPIFD, which is based on a miscible polymer blend, lacks phase boundaries and forms an organic-less and LiF-rich SEI, effectively suppressing lithium dendrites. The single-phase LPIFD delivers ionic conductivity of 3.0 x 10 -4 S cm -1 and enables the Li anode to reach a high coulombic efficiency of 99.1% and a critical current density of 3.7 mA cm -2 . Furthermore, the ability to form an F-rich cathode electrolyte interphase allows LiNi 0.8 Co 0.1 Mn 0.1 O 2 ||Li cells to achieve a cycle life of 450 cycles at a high operating voltage of 4.5 V. In conclusion, this design will inspire efforts to commercialize polymer electrolytes for high-energy Li-metal batteries.

25 ENERGY STORAGE↗

DOE OSTI2023

Accurate Prediction of Adiabatic Ionization Potentials of Organic Molecules using Quantum Chemistry Assisted Machine Learning

In previous work (Dandu et al., J. Phys. Chem. A, 2022, 126, 4528–4536), we were successful in predicting accurate atomization energies of organic molecules using machine learning (ML) models, obtaining an accuracy as low as 0.1 kcal/mol compared to the G4MP2 method. In this work, we extend the use of these ML models to adiabatic ionization potentials on data sets of energies generated using quantum chemical calculations. Atomic specific corrections that were found to improve atomization energies from quantum chemical calculations have also been used in this study to improve ionization potentials. Here, the quantum chemical calculations were performed on 3405 molecules containing eight or fewer non-hydrogen atoms derived from the QM9 data set, using the B3LYP functional with the 6–31G(2df,p) basis set for optimization. Low-fidelity IPs for these structures were obtained using two density functional methods: B3LYP/6–31+G(2df,p) and ωB97XD/6–311+G(3df,2p). Highly accurate G4MP2 calculations were performed on these optimized structures to obtain high-fidelity IPs to use in ML models based on the low-fidelity IPs. Our best performing ML methods gave IPs of organic molecules within a mean absolute deviation of 0.035 eV from the G4MP2 IPs for the whole data set. This work demonstrates that ML predictions assisted by quantum chemical calculations can be used to successfully predict IPs of organic molecules for use in high throughput screening.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Characterization of just one atom using synchrotron X-rays

Since the discovery of X-rays by Roentgen in 1895, its use has been ubiquitous, from medical and environmental applications to materials sciences. X-ray characterization requires a large number of atoms and reducing the material quantity is a long-standing goal. Here we show that X-rays can be used to characterize the elemental and chemical state of just one atom. Using a specialized tip as a detector, X-ray-excited currents generated from an iron and a terbium atom coordinated to organic ligands are detected. The fingerprints of a single atom, the L 2,3 and M 4,5 absorption edge signals for iron and terbium, respectively, are clearly observed in the X-ray absorption spectra. The chemical states of these atoms are characterized by means of near-edge X-ray absorption signals, in which X-ray-excited resonance tunnelling (X-ERT) is dominant for the iron atom. The X-ray signal can be sensed only when the tip is located directly above the atom in extreme proximity, which confirms atomically localized detection in the tunnelling regime. Finally, our work connects synchrotron X-rays with a quantum tunnelling process and opens future X-rays experiments for simultaneous characterizations of elemental and chemical properties of materials at the ultimate single-atom limit.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2023

Microkinetic insights into the role of catalyst and water activity on the nucleation, growth, and dissolution during COF-5 synthesis

The chemical pathway for synthesizing covalent organic frameworks (COFs) involves a complex medley of reaction sequences over a rippling energy landscape that cannot be adequately described using existing theories. Even with the development of state-of-the-art experimental and computational tools, identifying primary mechanisms of nucleation and growth of COFs remains elusive. Other than empirically, little is known about how the catalyst composition and water activity affect the kinetics of the reaction pathway. In this work, for the first time, we employ time-resolved in situ Fourier transform infrared spectroscopy (FT-IR) coupled with a six-parameter microkinetic model consisting of ~10 million reactions and over 20 000 species. The integrated approach elucidates previously unrecognized roles of catalyst pK a on COF yield and water on growth rate and size distribution. COF crystalline yield increases with decreasing pK a of the catalysts, whereas the effect of water is to reduce the growth rate of COF and broaden the size distribution. The microkinetic model reproduces the experimental data and quantitatively predicts the role of synthesis conditions such as temperature, catalyst, and precursor concentration on the nucleation and growth rates. Furthermore, the model also validates the second-order reaction mechanism of COF-5 and predicts the activation barriers for classical and non-classical growth of COF-5 crystals. The microkinetic model developed here is generalizable to different COFs and other multicomponent systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗