Engineering topics

Dandu, Naveen

Publications and source records attributed to Dandu, Naveen.

13 records

DOE OSTI2024

Interfacial solvation-structure regulation for stable Li metal anode by a desolvation coating technique

Rechargeable lithium (Li) metal batteries face challenges in achieving stable cycling due to the instability of the solid electrolyte interphase (SEI). The Li-ion solvation structure and its desolvation process are crucial for the formation of a stable SEI on Li metal anodes and improving Li plating/stripping kinetics. This research introduces an interfacial desolvation coating technique to actively modulate the Li-ion solvation structure at the Li metal interface and regulate the participation of the electrolyte solvent in SEI formation. Through experimental investigations conducted using a carbonate electrolyte with limited compatibility to Li metal, the optimized desolvation coating layer, composed of 12-crown-4 ether-modified silica materials, selectively displaces strongly coordinating solvents while simultaneously enriching weakly coordinating fluorinated solvents at the Li metal/electrolyte interface. This selective desolvation and enrichment effect reduce solvent participation to SEI and thus facilitate the formation of a LiF-dominant SEI with greatly reduced organic species on the Li metal surface, as conclusively verified through various characterization techniques including XPS, quantitative NMR, operando NMR, cryo-TEM, EELS, and EDS. The interfacial desolvation coating technique enables excellent rate cycling stability (i.e., 1C) of the Li metal anode and prolonged cycling life of the Li||LiCoO 2 pouch cell in the conventional carbonate electrolyte (E/C 2.6 g/Ah), with 80% capacity retention after 333 cycles.

42 ENGINEERING↗

DOE OSTI2023

Light- and Chemical-Doping-Induced Magnetic Behavior of Eu Molecular Systems

Variable temperature electron paramagnetic resonance (VT-EPR) was used to investigate the role of the environment and oxidation states of several coordinated Eu compounds. We find that while Eu(III) chelating complexes are diamagnetic, simple chemical reduction results in the formation of paramagnetic species. In agreement with the distorted D 3h symmetry of Eu molecular complexes investigated in this study, the EPR spectrum of reduced complexes showed axially symmetric signals (g ⊥ = 2.001 and g ∥ = 1.994) that were successfully simulated with two Eu isotopes with nuclear spin 5/2 ( 151 Eu and 153 Eu with 48% and 52% natural abundance, respectively) and nuclear g-factors 151 Eu/ 153 Eu = 2.27. Illumination of water-soluble complex Eu(dipic) 3 at 4 K led to the ligand-to-metal charge transfer (LMCT) that resulted in the formation of Eu(II) in a rhombic environment (g x = 2.006, g y = 1.995, g z = 1.988). The existence of LMCT affects the luminescence of Eu(dipic) 3 , and pre-reduction of the complex to Eu(II)(dipic) 3 reversibly reduces red luminescence with the appearance of a weak CT blue luminescence. Furthermore, encapsulation of a large portion of the dipic ligand with Cucurbit[7]uril, a pumpkin-shaped macrocycle, inhibited ligand-to-metal charge transfer, preventing the formation of Eu(II) upon illumination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

A KMnO 4 -Generated Colloidal Electrolyte for Redox Mediation and Anode Protection in a Li–Air Battery

The rechargeable lithium-oxygen (Li-O 2 ) battery has the highest theoretical specific energy density of any rechargeable batteries and could transform energy storage systems if a practical device could be attained. However, among numerous challenges, which are all interconnected, are polarization due to sluggish kinetics, low cycle life, small capacity, and slow rates. Here, in this study, we report on use of KMnO 4 to generate a colloidal electrolyte made up of MnO 2 nanoparticles. The resulting electrolyte provides a redox mediator for reducing the charge potential and lithium anode protection to increase cycle life. This electrolyte in combination with a stable binary transition metal dichalcogenide alloy, Nb 0.5 Ta 0.5 S 2 , as the cathode enables the operation of a Li-O 2 battery at a current density of 1 mA center dot cm -2 and specific capacity ranging from 1000 to 10000 mA center dot h center dot g -1 (corresponding to 0.1-1 mA center dot h center dot cm -2 ) in a dry air environment with a cycle life of up to 150. This colloidal electrolyte provides a robust approach for advancing Li-air batteries.

25 ENERGY STORAGE↗

DOE OSTI2022

IMPROVING THE ACCURACY OF COMPOSITE METHODS: A G4MP2 METHOD WITH G4-LIKE ACCURACY AND IMPLICATIONS FOR MACHINE LEARNING

G4MP2 theory has proven to be a reliable and accurate quantum chemical composite method for the calculation of molecular energies using an approximation based on second-order perturbation theory to lower computational costs compared to G4 theory. However, it has been found to have significantly increased errors when applied to larger organic molecules with 10 or more nonhydrogen atoms. We report here on an investigation of the cause of the failure of G4MP2 theory for such larger molecules. One source of error is found to be the "higher-level correction (HLC)", which is meant to correct for deficiencies in correlation contributions to the calculated energies. This is because the HLC assumes that the contribution is independent of the element and the type of bonding involved, both of which become more important with larger molecules. We address this problem by adding an atom-specific correction, dependent on atom type but not bond type, to the higher-level correction. We find that a G4MP2 method that incorporates this modification of the higher-level correction, referred to as G4MP2A, becomes as accurate as G4 theory (for computing enthalpies of formation) for a test set of molecules with less than 10 nonhydrogen atoms as well as a set with 10-14 such atoms, the set of molecules considered here, with a much lower computational cost. The G4MP2A method is also found to significantly improve ionization potentials and electron affinities. Finally, we implemented the G4MP2A energies in a machine learning method to predict molecular energies.

Dandu, Naveen↗

DOE OSTI2022

Unprecedented Multifunctionality in 1D Nb 1- x Ta x S 3 Transition Metal Trichalcogenide Alloy

One-dimensional (1D) van der Waals materials, such as nanofibers or nanoribbons are considered as the future ultimate limit of downscaling for modern electrical and electrochemical devices. Here, for the first time, we successfully synthesize nanofibers of a solid solution transition metal trichalcogenide (TMTC), Nb 1-x Ta x S 3 , with outstanding electrical, thermal, and electrochemical characteristics rivaling the performance of the-state-of-the art materials for each application. This material shows nearly unchanged sheet resistance (≈740 Ω/sq -1 ) versus bending cycles tested up to 90 cycles, stable sheet resistance in ambient conditions tested up to 60 days, remarkably high electrical breakdown current density of ≈ 30 MA cm -2 , strong evidence of successive charge density wave (CDW) transitions, and outstanding thermal stability up to ≈900 K. Additionally, this material demonstrates excellent activity and selectivity for CO2 conversion to CO reaching ≈ 350 mA cm -2 at – 0.8 V vs RHE with an outstanding turnover frequency number of 25 for CO formation. It also exhibits an excellent performance in a high-rate Li-air battery with the specific capacity of 3000 mAhg -1 at a high current density of 0.3 mAcm -2 . This study uncovers the multifunctionality in 1D TMTC alloys for a wide range of high-impact applications and opens a new direction for the design of the next generation of low-dimensional materials with high performance.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Concentration-dependent ion correlations impact the electrochemical behavior of calcium battery electrolytes.

Ion interactions strongly determine the solvation environments of multivalent electrolytes even at concentrations below that required for practical battery-based energy storage. This statement is particularly true of electrolytes utilizing ethereal solvents due to their low dielectric constants. These solvents are among the most commonly used for multivalent batteries based on reactive metals (Mg, Ca) due to their reductive stability. Recent developments in multivalent electrolyte design have produced a variety of new salts for Mg2+ and Ca2+ that test the limits of weak coordination strength and oxidative stability. Such electrolytes have great potential for enabling full-cell cycling of batteries based on these working ions. However, the ion interactions in these electrolytes exhibit significant and non-intuitive concentration relationships. In this work, we investigate a promising exemplar, calcium tetrakis(hexafluoroisopropoxy)borate (Ca(BHFIP)(2)), in the ethereal solvents 1,2-dimethoxyethane (DME) and tetrahydrofuran (THF) across a concentration range of several orders of magnitude. Surprisingly, we find that effective salt dissociation is lower at relatively dilute concentrations (e.g. 0.01 M) than at higher concentrations (e.g. 0.2 M). Combined experimental and computational dielectric and X-ray spectroscopic analyses of the changes occurring in the Ca2+ solvation environment across these concentration regimes reveals a progressive transition from well-defined solvent-separated ion pairs to de-correlated free ions. This transition in ion correlation results in improvements in both conductivity and calcium cycling stability with increased salt concentration. Comparison with previous findings involving more strongly associating salts highlights the generality of this phenomenon, leading to important insight into controlling ion interactions in ether-based multivalent battery electrolytes.

Hahn, Nathan T.↗

DOE OSTI2021

Graph-Based Approaches for Predicting Solvation Energy in Multiple Solvents: Open Datasets and Machine Learning Models

The solvation properties of molecules, often estimated using quantum chemical simulations, are important in the synthesis of energy storage materials, drugs, and industrial chemicals. Here, we develop machine learning models of solvation energies to replace expensive quantum chemistry calculations with inexpensive-to-compute message-passing neural network models that require only the molecular graph as inputs. Our models are trained on a new database of solvation energies for 130,258 molecules taken from the QM9 dataset computed in five solvents (acetone, ethanol, acetonitrile, dimethyl sulfoxide, and water) via an implicit solvent model. Our best model achieves a mean absolute error of 0.5 kcal/mol for molecules with nine or fewer non-hydrogen atoms and 1 kcal/mol for molecules with between 10 and 14 non-hydrogen atoms. We make the entire dataset of 651,290 computed entries openly available and provide simple web and programmatic interfaces to enable others to run our solvation energy model on new molecules. This model calculates the solvation energies for molecules using only the SMILES string and also provides an estimate of whether each molecule is within the domain of applicability of our model. We envision that the dataset and models will provide the functionality needed for the rapid screening of large chemical spaces to discover improved molecules for many applications.

25 ENERGY STORAGE↗

DOE OSTI2021

High-Rate Long Cycle-Life Li-Air Battery Aided by Bifunctional InX3 (X = I and Br) Redox Mediators

Redox mediators (RMs) are solution-based additives that have been extensively used to reduce the charge potential and increase the energy efficiency of Li–oxygen (Li–O 2 ) batteries. However, in the presence of RMs, achieving a long cycle-life operation of Li–O 2 batteries at a high current rate is still a major challenge. In this study, we discover a novel synergy among InX 3 (X = I and Br) bifunctional RMs, molybdenum disulfide (MoS 2 ) nanoflakes as the air electrode, dimethyl sulfoxide/ionic liquid hybrid electrolyte, and LiTFSI as a salt to achieve long cycle-life operations of Li–O 2 batteries in a dry air environment at high charge–discharge rates. Our results indicate that batteries with InI3 operate up to 450 cycles with a current density of 0.5 A g –1 and 217 cycles with a current density of 1 A g –1 at a fixed capacity of 1 A h g –1 . Batteries with InBr 3 operate up to 600 cycles with a current density of 1 A g –1 . These batteries can also operate at a higher charge rate of 2 A g –1 up to 200 cycles (for InBr 3 ) and 160 cycles (for InI 3 ). Our experimental and computational results reveal that while X 3 – is the source of the redox mediator, LiX at the MoS 2 cathode, In 3+ reacts on the lithium anode side to form a protective layer on the surface, thus acting as an effective bifunctional RM in a dry air environment. This evidence for a simultaneous improvement in the current rates and cycle life of a battery in a dry air atmosphere opens a new direction for research for advanced energy storage systems.

25 ENERGY STORAGE↗

DOE OSTI2021

Surface-Induced Deprotonation of Thiol Ligands Impacts the Optical Response of CdS Quantum Dots

Cadmium chalcogenide quantum dots (QDs) passivated by thiol-based ligands exhibit several advantages in their applications in lighting, sensing, and imaging technologies. However, their emission is sensitive to thiol concentrations, pH conditions, and temperatures. Using calculations based on the density functional theory, we identify conditions for thiol/thiolate equilibrium at the CdS QD surface that either eliminate or introduce optically inactive hole trap states favoring or disfavoring the emission. Our calculations indicate much weaker interactions between the QD and protonated species (thiols), compared to their deprotonated counterparts (thiolates). Additionally, the surface of CdS QD facilitates the partial deprotonation of thiols, leading to the formation of an additional stable networking conformation where the proton is shared between the ligand and the QD surface. Thiolates strongly reduce the optical intensity of low-energy transitions in CdS QDs, contributing thiolate-localized hole trap states at the QD band gap. However, networking between the thiols and the surface, as well as the presence of native ligands such as primary amines, stabilize such trap states brightening the lowest optical transitions. This explains the increased emission of thiol-passivated QDs at lower concentrations in neutral or acidic solutions. Surface-mediated bias toward deprotonated species and their contribution to optically inactive states also rationalizes irreversible emission quenching and bleaching in the CdSe/CdS QDs exposed to high temperatures or intensive laser pulse.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Molecular Engineering to Enable High-Voltage Lithium-Ion Battery: From Propylene Carbonate to Trifluoropropylene Carbonate

Molecular engineering of electrolyte structures has led to the successful application of trifluoropropylene carbonate (TFPC), a fluorinated derivative of propylene carbonate (PC), in next-generation high-voltage high-energy lithium-ion cell. Additionally, in contrast to a PC-based electrolyte which cointercalates in the form of Li + -solvated species into the graphene layer and exfoliates a graphite anode, a TFPC-based electrolyte is highly compatible with a graphite anode at low potential. Additionally, it shows exceptional oxidation stability on the charged cathode surface owing to the presence of the -CF 3 group. An all-fluorinated electrolyte, that is, 1.0 M LiPF 6 TFPC/2,2,2-trifluoroethyl carbonate (FEMC) (1/1 volume ratio) + FEC additive, was formulated and demonstrated excellent cycling stability in a high-voltage LiNi 0.5 Mn 0.3 Co 0.2 O 2 /graphite cell cycled between 3.0 and 4.6 V.

25 ENERGY STORAGE↗

DOE OSTI2020

Passivating Nucleobases Bring Charge Transfer Character to Optically Active Transitions in Small Silver Nanoclusters

DNA-wrapped silver nanoclusters (DNA–AgNCs) are known for their efficient luminescence. However, their emission is highly sensitive to the DNA sequence, the cluster size, and its charge state. To get better insights into photophysics of these hybrid systems, simulations based on density functional theory (DFT) are performed. Our calculations elucidate the effect of the structural conformations, charges, solvent polarity, and passivating bases on optical spectra of DNA–AgNCs containing five and six Ag atoms. It is found that inclusion of water in calculations as a polar solvent media results in stabilization of nonplanar conformations of base-passivated clusters, while their planar conformations are more stable in vacuum, similar to the bare Ag5 and Ag6 clusters. Cytosines and guanines interact with the cluster twice stronger than thymines, due to their larger dipole moments. In addition to the base–cluster interactions, hydrogen bonds between bases notably contribute to the structure stabilization. While the relative intensity, line width, and the energy of absorption peaks are slightly changing depending on the cluster charge, conformations, and base types, the overall spectral shape with five well-resolved bands at 2.5–5.5 eV is consistent for all structures. Independent of the passivating bases and the cluster size and charge, the low energy optical transitions at 2.5–3.5 eV exhibit a metal to ligand charge transfer (MLCT) character with the main contribution emerging from Ag-core to the bases. Cytosines facilitate the MLCT character to a larger degree comparing to the other bases. However, the doublet transitions in clusters with the open shell electronic structure (Ag5 and Ag6 + ) result in appearance of additional red-shifted (<2.5 eV) and optically weak band with negligible MLCT character. The passivated clusters with the closed shell electronic structure (Ag5 + and Ag6) exhibit higher optical intensity of their lowest transitions with much higher MLCT contribution, thus having better potential for emission, than their open shell counterparts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

A Comparative Study of Redox Mediators for Improved Performance of Li-Oxygen Batteries.

Redox meditators (RMs) are soluble catalysts located in an electrolyte that can improve the energy efficiency (reduced overpotential) and cyclability of Li-oxygen (Li-O-2) batteries. In this work, 20 RMs within a Li-O-2 system with dimethyl sulfoxide and tetraethylene glycol dimethyl ether electrolytes are studied and their electrochemical features such as redox potential, the separation of cathodic and anodic peaks, and their current intensities are measured using cyclic voltammetry (CV) experiments. Six RMs are selected as "primary" choices based on their electrochemical performance, and stability tests are then performed to examine their electrochemical responses after consecutive cycles. Moreover, galvanostatic cycling tests are performed within a Li-O-2 battery system assembled with selected six RMs for real case consistency investigations. It is found that results from CV to galvanostatic cycling tests are consistent for halides and organometallic RMs, where the former exhibit much higher stability. However, the organic RMs show high reversibility in CV but low in battery cycling results. Density functional theory calculations are carried out to gain more understanding of the stability and redox potentials of the RMs. This study provides comparative information to select the most reliable RMs for Li-O-2 batteries along with new fundamental understanding of their electrochemical activity and stability.

cyclic voltammetry↗

DOE OSTI2020

Quantum-Chemically Informed Machine Learning: Prediction of Energies of Organic Molecules with 10 to 14 Non-hydrogen Atoms

High-fidelity quantum-chemical calculations can provide accurate predictions of molecular energies, but their high computational costs limit their utility, especially for larger molecules. We have shown in previous work that machine learning models trained on high-level quantum-chemical calculations (G4MP2) for organic molecules with one to nine non-hydrogen atoms can provide accurate predictions for other molecules of comparable size at much lower costs. Here we demonstrate that such models can also be used to effectively predict energies of molecules larger than those in the training set. To implement this strategy, we first established a set of 191 molecules with 10–14 non-hydrogen atoms having reliable experimental enthalpies of formation. We then assessed the accuracy of computed G4MP2 enthalpies of formation for these 191 molecules. The error in the G4MP2 results was somewhat larger than that for smaller molecules, and the reason for this increase is discussed. Two density functional methods, B3LYP and ωB97X-D, were also used on this set of molecules, with ωB97X-D found to perform better than B3LYP at predicting energies. The G4MP2 energies for the 191 molecules were then predicted using these two functionals with two machine learning methods, the FCHL-Δ and SchNet-Δ models, with the learning done on calculated energies of the one to nine non-hydrogen atom molecules. The better-performing model, FCHL-Δ, gave atomization energies of the 191 organic molecules with 10–14 non-hydrogen atoms within 0.4 kcal/mol of their G4MP2 energies. Thus, this work demonstrates that quantum-chemically informed machine learning can be used to successfully predict the energies of large organic molecules whose size is beyond that in the training set.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗