arXiv subjects

Vikram Pande

Publications and source records attributed to Vikram Pande.

11 recordsLinked to original sources

arXiv2024

LOLgorithm: Integrating Semantic,Syntactic and Contextual Elements for Humor Classification

This paper explores humor detection through a linguistic lens, prioritizing syntactic, semantic, and contextual features over computational methods in Natural Language Processing. We categorize features into syntactic, semantic, and contextual dimensions, including lexicons, structural statistics, Word2Vec, WordNet, and phonetic style. Our proposed model, Colbert, utilizes BERT embeddings and parallel hidden layers to capture sentence congruity. By combining syntactic, semantic, and contextual features, we train Colbert for humor detection. Feature engineering examines essential syntactic and semantic features alongside BERT embeddings. SHAP interpretations and decision trees identify influential features, revealing that a holistic approach improves humor detection accuracy on unseen data. Integrating linguistic cues from different dimensions enhances the model's ability to understand humor complexity beyond traditional computational methods.

cs.CL↗

arXiv2019

Vulnerabilities of Electric Vehicle Battery Packs to Cyberattacks

Electric Vehicles (EVs), like all modern vehicles, are entirely controlled by electronic devices embedded within networks that are exposed to the threat of cyberattacks. Cyber vulnerabilities are magnified with EVs due to unique risks associated with EV battery packs. Current batteries have well-known issues with specific energy, cost and fire-related safety risks. In this study, we develop a systematic framework to assess the impact of cyberattacks on EVs. While the current focus of automotive cyberattacks is on short-term physical safety, it is crucial to consider long-term cyberattacks that aim to cause financial losses through accrued impact, especially in the context of EVs. Faulty components of battery management systems such as a compromised voltage regulator could lead to cyberattacks that can overdischarge or overcharge the battery. Overdischarge could lead to failures such as internal shorts in the timescale of minutes through cyberattacks that compromise energy-intensive EV subsystems like auxiliary components. Attacks that overcharge the pack could shorten the lifetime of a new battery pack to less than a year. Further, such attacks also pose physical safety risks via the triggering of thermal (fire) events. Attacks on auxiliary components lead to battery drain, which could be up to 20% of the state-of-charge per hour. Lastly, we develop a heuristic for the stealthiness of a cyberattack to augment traditional threat models. The methodology presented here will help in building the foundational principles of electric vehicle cybersecurity: a nascent but critical topic in the coming years.

cs.CR↗

arXiv2019

Computational Screening of Current Collectors for Enabling Anode-free Lithium Metal Batteries

Lithium metal cells are key towards achieving high specific energy and energy density for electrification of transportation and aviation. Anode-free cells are the limiting case of lithium metal cells involving no excess lithium and the highest possible specific energy. In addition, anode-free cells are easier, cheaper and safer as they avoid handling and manufacturing of lithium metal foils. Issues related to dendrite growth and poor cycling are magnified in anode-free cells due to lack of excess lithium. Electrolyte and current collector surface play a crucial role in affecting the cycling performance of anode-free cells. In this work, we have computationally screened for candidate current collectors that can nucleate lithium effectively and allow uniform growth. These are determined by the free energy of lithium adsorption and lithium surface diffusion barrier on candidate current collectors. Using density functional theory calculations, we show that Li-alloys possess ideal characteristics for Li nucleation and growth. These can lead to vastly improved specific energy compared to current transition metal current collectors.

cond-mat.mtrl-sci↗

arXiv2019

Descriptors for Electrolyte-Renormalized Oxidative Stability of Solvents in Lithium-ion Batteries

Electrolyte stability against oxidation is one of the important factors limiting the development of high energy density batteries. HOMO level of solvent molecules has been successfully used for understanding trends in their oxidative stability but assumes a non-interacting environment. However, solvent HOMO levels are renormalized due to molecules in their solvation shells. In this work, we first demonstrate an inexpensive and accurate method to determine the HOMO level of solvent followed by simple descriptors for renormalization of HOMO level due to different electrolyte components. The descriptors are based on Gutmann Donor and Acceptor numbers of solvent and other components. The method uses fast GGA-level DFT calculations compared to previously used expensive, experimental data dependent methods. This method can be used to screen for unexplored stable solvents among the large number of known organic compounds to design novel high voltage stable electrolytes.

physics.chem-ph↗

arXiv2019

Design Principles for Self-forming Interfaces Enabling Stable Lithium Metal Anodes

The path toward Li-ion batteries with higher energy-densities will likely involve use of thin lithium metal (Li) anode (<50 $μ$m in thickness), whose cyclability today remains limited by dendrite formation and low Coulombic efficiency. Previous studies have shown that the solid-electrolyte-interface (SEI) of Li metal plays a crucial role in Li electrodeposition and stripping. However, design rules for optimal SEIs on lithium metal are not well-established. Here, using integrated experimental and modeling studies on a series of structurally-similar SEI-modifying compounds as model systems, we reveal the relationship between SEI compositions, Li deposition morphology and coulombic efficiency, and identify two key descriptors (ionicity and compactness) for high performance SEIs through integrated experimental and modeling studies. Using this understanding, we design a highly ionic and compact SEI that shows excellent cycling performance in LiCoO$_2$-Li full cells at practical current densities. Our results provide guidance for the rational selection and optimization of SEI modifiers to further improve Li metal anodes.

physics.app-ph↗

arXiv2019

Theoretical Characterization of Structural Disorder in the Tetramer Model Structure of Eumelanin

Eumelanin is regarded to be an attractive candidate material for biomedical applications. Despite many theoretical studies exploring the structure of eumelanin, an exact mapping of the energetic landscape of the very large phase space of eumelanin is still elusive. In this work, we implement a piecewise Ising Model to predict formation enthalpies of Eumelanin single and double tetramers, and demonstrate its superior predictive and generalizable capabilities. We believe this model will prove very useful in theoretically characterizing the many unique properties attributed to its disorder. The modular nature of the predictive Ising model built up in this work is well-suited for analysis and characterization of a larger phase space of eumelanin polymers, including hexamers and octomers, as well as larger stacked structures, such as potential triple and quadruple eumelanin tetramers. Absorbance data can be incorporated with population-wide predictions of polymer abundance to produce weighted-average predictions of broadband absorbance of bulk eumelanin.

physics.chem-ph↗

arXiv2018

Robust high-fidelity DFT study of the lithium-graphite phase diagram

Graphite is the most widely used and among the most widely-studied anode materials for lithium-ion batteries. With increasing demands on lithium batteries to operate at lower temperatures and higher currents, it is crucial to understand lithium intercalation in graphite due to issues associated with lithium plating. Lithium intercalation into graphite has been extensively studied theoretically using density functional theory (DFT) calculations, complemented by experimental studies through X-ray diffraction, spectroscopy, optical imaging and other techniques. In this work, we present a first principles based model using DFT calculations, employing the BEEF-vdW as the exchange correlation functional, and Ising model to determine the phase transformations and subsequently, the thermodynamic intercalation potential diagram. We explore a configurational phase space of about 1 billion structures by accurately determining the important interactions for the Ising model. The BEEF-vdW exchange correlation functional employed accurately captures a range of interactions including vdW, covalent and ionic interactions. We incorporate phonon contributions at finite temperatures and configurational entropy to get high accuracy in free energy and potentials. We utilize the built-in error estimation capabilities of the BEEF-vdW exchange correlation functional and to develop a methodological framework for determining the uncertainty associated with DFT calculated phase diagrams and intercalation potentials. The framework also determines the confidence of each predicted stable phase. The confidence value of a phase can help us to identify regions of solid solutions and phase transformations accurately.

cond-mat.mtrl-sci↗

arXiv2018

Quantifying Confidence in DFT Predicted Surface Pourbaix Diagrams of Transition Metal Electrode-Electrolyte Interfaces

Density Functional Theory (DFT) calculations have been widely used to predict the activity of catalysts based on the free energies of reaction intermediates. The incorporation of the state of the catalyst surface under the electrochemical operating conditions while constructing the free energy diagram is crucial, without which even trends in activity predictions could be imprecisely captured. Surface Pourbaix diagrams indicate the surface state as a function of the pH and the potential. In this work, we utilize error-estimation capabilities within the BEEF-vdW exchange correlation functional as an ensemble approach to propagate the uncertainty associated with the adsorption energetics in the construction of Pourbaix diagrams. Within this approach, surface-transition phase boundaries are no longer sharp and are therefore associated with a finite width. We determine the surface phase diagram for several transition metals under reaction conditions and electrode potentials relevant for the Oxygen Reduction Reaction (ORR). We observe that our surface phase predictions for most predominant species are in good agreement with cyclic voltammetry experiments and prior DFT studies. We use the OH$^*$ intermediate for comparing adsorption characteristics on Pt(111), Pt(100), Pd(111), Ir(111), Rh(111), and Ru(0001) since it has been shown to have a higher prediction efficiency relative to O$^*$, and find the trend Ru>Rh>Ir>Pt>Pd for (111) metal facets, where Ru binds OH$^*$ the strongest. We robustly predict the likely surface phase as a function of reaction conditions by associating c-values to quantifying the confidence in predictions within the Pourbaix diagram. We define a confidence quantifying metric using which certain experimentally observed surface phases and peak assignments can be better rationalized.

cond-mat.mtrl-sci↗

arXiv2018

Understanding Ion Pairing in High Salt Concentration Electrolytes using Classical Molecular Dynamics Simulations and its Implications for Nonaqueous Li-O$_2$ Batteries

A precise understanding of solvation is essential for rational search and design of electrolytes that can meet performance demands in Li-ion and beyond Li-ion batteries. In the context of Li-O$_2$ batteries, ion pairing is decisive in determining battery capacity via the solution mediated discharge mechanism without compromising heavily on electrolyte stability. We argue that models based on coordination numbers of the counterion in the first solvation shell are inadequate at describing the extent of ion pairing, especially at higher salt concentrations, and are often not consistent with experimental observations. In this study, we use classical molecular dynamics simulations for several salt anions (NO$_3^-$, BF$_4^-$, CF$_3$SO$_3^-$, (CF$_3$SO$_2$)$_2$N$^-$) and nonaqueous solvent (DMSO, DME, ACN, THF, DMA) combinations to improve the understanding of ion paring with the help of a new metric of ion-pairing. We proposed a metric that defines the degree of clustering of a cation by its counterions and solvent molecules on a continuous scale, the limits if which are based on a simple and intuitive condition of charge neutrality. Using these metrics, we identify the extent of ion pairing in good agreement with experimental solvation phase diagrams and further discuss its usefulness in understanding commonly employed measures of salt and solvent donicity such as the Gutmann donor number.

physics.chem-ph↗

arXiv2017

The role of disorder in NaO$_2$ and its implications for Na-O$_2$ batteries

We present a DFT study utilizing the Hubbard U correction to probe structural and magnetic disorder in $\mathrm{NaO_{2}}$, primary discharge product of Na-O$_2$ batteries. We show that $\mathrm{NaO_{2}}$ exhibits a large degree of rotational and magnetic disorder; a 3-body Ising Model is necessary to capture the subtle interplay of this disorder. MC simulations demonstrate that energetically favorable, FM phases near room temperature consist of alternating bands of orthogonally-oriented $\mathrm{O_{2}}$ dimers. We find that bulk structures are insulating, with a subset of FM structures showing a moderate gap ($<2$ eV) in one spin channel.

cond-mat.mtrl-sci↗

arXiv2015

Enhancing electrochemical intermediate solvation through electrolyte anion selection to increase nonaqueous Li-O$_2$ battery capacity

Among the 'beyond Li-ion' battery chemistries, nonaqueous Li-O$_2$ batteries have the highest theoretical specific energy and as a result have attracted significant research attention over the past decade. A critical scientific challenge facing nonaqueous Li-O$_2$ batteries is the electronically insulating nature of the primary discharge product, lithium peroxide, which passivates the battery cathode as it is formed, leading to low ultimate cell capacities. Recently, strategies to enhance solubility to circumvent this issue have been reported, but rely upon electrolyte formulations that further decrease the overall electrochemical stability of the system, thereby deleteriously affecting battery rechargeability. In this study, we report that a significant enhancement (greater than four-fold) in Li-O$_2$ cell capacity is possible by appropriately selecting the salt anion in the electrolyte solution. Using $^7$Li nuclear magnetic resonance and modeling, we confirm that this improvement is a result of enhanced Li$^+$ stability in solution, which in turn induces solubility of the intermediate to Li$_2$O$_2$ formation. Using this strategy, the challenging task of identifying an electrolyte solvent that possesses the anti-correlated properties of high intermediate solubility and solvent stability is alleviated, potentially providing a pathway to develop an electrolyte that affords both high capacity and rechargeability. We believe the model and strategy presented here will be generally useful to enhance Coulombic efficiency in many electrochemical systems (e.g. Li-S batteries) where improving intermediate stability in solution could induce desired mechanisms of product formation.

physics.chem-ph↗