About

Shabnam Akhtari is a professor at the Pennsylvania State University, based in the McAllister Building. Her research interests include Number Theory, Geometry of Numbers, and Diophantine Analysis. Her work focuses on these areas, contributing to the understanding of their underlying mathematical structures and properties.

Research topics

• Chemistry
• Computational chemistry
• Nanotechnology
• Organic chemistry
• Materials science
• Computer Science
• Data science
• Management science
• Chemical physics
• Optics
• Combinatorial chemistry
• Computational science
• Engineering
• Polymer chemistry
• Physics
• Simulation
• Thermodynamics

Selected publications

• Vibrational Spectroscopy of Ionic Liquids Electrochemically Intercalated into Multilayer Graphene

  ACS Applied Materials & Interfaces · 2026-05-14

  article

  We report insights into the reversible electrochemical intercalation of ionic liquids into multilayer graphene (MLG) using attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy. The studied device is comprised of an MLG/alumina membrane/copper stack, where the nanoporous alumina membrane is filled with ionic liquid [DEME+][TFSI–], forming a compact electrochemical cell. Upon application of a positive voltage, [TFSI–] anions intercalate into the interlayer regions of the MLG, despite the anion’s diameter (0.9 nm) being nearly 3 times the typical graphene interlayer spacing (0.355 nm). Pronounced spectral changes accompany this poorly understood intercalation. We observe a blue-shift of up to 21.2 cm–1 in several [TFSI–] vibrational modes, attributed to mechanical compression within the confined graphene layers and/or ion–ion interactions. Additionally, an infrared peak emerges at 1384 cm–1, corresponding to the symmetric bending mode of methyl (−CH3) groups, whose appearance suggests that symmetry breaking within the confined electrochemical environment activates otherwise forbidden transitions in the [DEME+] cation. These findings reveal the nanoscale structural and electronic perturbations induced by ionic liquid intercalation, identifying spectroscopic signatures to track intercalation dynamics in layered materials. Raman shifts observed in the graphene indicate doping levels on the order of 1021 cm–1, corresponding to a roughly 100-fold increase in free carrier concentration, thus providing evidence consistent with intercalation. However, these observations challenge our previous interpretation of the complete intercalation of ionic liquids into graphene. We additionally used density-functional tight-binding (DFTB) simulations to qualitatively determine the behavior of the [TFSI–] anion sandwiched between two graphene sheets for different separation distances from 7 to 10 Å with a 0.5 Å increment. The resulting frequency shifts at smaller separation distances exhibit qualitative agreement with experimental observations, and in the case of greater separation, the peak shifts diminish and plateau, transitioning toward the bulk anion.

  PublisherDOI

• Exploring charge-transfer effects at metal–molecule interfaces through modeling surface-enhanced Raman spectroscopy (SERS)

  Faraday Discussions · 2026-01-01

  articleOpen accessSenior authorCorresponding

  Understanding charge transfer (CT) at metal-molecule interfaces is central to the design of new materials for catalysis, sensing, and energy applications. Surface-enhanced Raman spectroscopy (SERS) provides a powerful technique to probe metal-molecule interfaces since the SERS spectra reflect changes in geometry, orientation, and electronic structure which are influenced by CT. While CT can either be intrinsic or excitation-driven, we will focus on how the former contributes to SERS. However, it remains difficult to model these effects since it requires electronic structure methods capable of treating large systems. In this study, we present an efficient model to study these effects by combining a simplified time-dependent density functional theory (TDDFT) approach with a Raman bond model. The first-principles Raman bond model partitions Raman intensities into bond contributions such that the chemical mechanism in SERS can be interpreted as interatomic charge-flow modulations. Using this new model, we will examine how molecular orientation and intermolecular interactions affect the interfacial CT, employing N-heterocyclic carbenes (NHCs) as a model system. Using the Raman bond model, we will characterize the degree to which the interfacial charge flow is influenced by these effects. We then apply this model to characterize how charge flow affects molecular imaging using tip-enhanced Raman scattering (TERS). Using TERS, it is possible to image single molecules with sub-nanometer resolution. However, the role of CT in this process remains to be elucidated. We will show how the Raman bond model can characterize the importance of interfacial CT in TERS imaging. Overall, our results demonstrate that the Raman bond model, when combined with efficient first-principles calculations, offers a powerful approach for interpreting SERS spectra and providing new insights into interfacial CT.

  PublisherOA PDFDOI

• Quantifying Electrostatic Contributions to the Nonresonant Chemical SERS Enhancement

  The Journal of Physical Chemistry C · 2025-11-19

  articleSenior authorCorresponding

  Molecules near metal surfaces experience an enhancement of Raman scattering signals. This is termed as surface-enhanced Raman scattering (SERS) and has two enhancement mechanisms: the electromagnetic mechanism and the chemical mechanism. In this work, we present a systematic study of the nonresonant chemical mechanism (CHEM) for CO, N2, CS, and pyridine interacting with Cux, Agx, and Aux clusters ranging in size from x = 4–80 atoms. We show that CHEM scales as 1 + Akm|qinter|4, where |qinter| is the induced charge flow between the molecules and the metal clusters, and Akm is a molecular- and vibration-specific scaling parameter. Surprisingly, we find that the scaling parameter is smallest for the shortest adsorption bond lengths and that for different modes, it scales with the electron–phonon coupling. In addition, we show that CHEM can be decomposed into an electrostatic contribution arising from polarizing the metal cluster and a contribution due to electron density reorganization from the binding of the molecule to the cluster. This electrostatic contribution can be quantified using an atomistic electrodynamics/quantum mechanical model and is shown to account for about 1 order of magnitude of enhancement. The remaining enhancement due to electron density reorganization is likewise found to contribute about 1 order of magnitude. For molecules with shorter adsorption bond lengths, we find that the electrostatic contribution increases, while the electron density reorganization contribution decreases, explaining why stronger bonding does not lead to greater enhancement. Finally, this decomposition enables the identification of vibrational modes that are more likely to be sensitive to the chemical mechanism. In summary, this work provides new insights into the chemical enhancement of SERS by decomposing CHEM into an electrostatic contribution and a contribution due to electron density reorganization between the molecule and the metal cluster.

  PublisherDOI

• Efficient Simulation of Surface-Enhanced Raman Scattering with a Simplified Damped Response Theory

  Journal of Chemical Theory and Computation · 2025-02-19 · 3 citations

  articleSenior authorCorresponding

  Theoretical studies on enhancement mechanisms of surface-enhanced Raman scattering (SERS) are usually carried out with full quantum mechanical methods to capture the specific interactions between molecules and substrates. However, due to the computational costs of methods like time-dependent density functional theory (TDDFT), simplified model systems are commonly adopted. In the framework of TDDFT, the damped response theory is usually invoked to give a unified description of both on- and off-resonance Raman spectra based on the calculation of polarizability derivatives. However, the computational costs of full TDDFT allow for modeling SERS spectra only using small metal clusters. In this work, we demonstrate the implementation of an efficient method that simplifies the damped response calculations for the simulation of both on- and off-resonance SERS spectra. This simplified damped response method is named as TBAOResponse. We first compare the absorption spectra of a regular small system calculated with TBAOResponse and full TDDFT to benchmark the new method. Then, we demonstrate the efficiency and accuracy of the new method by comparing the on- and off-resonance SERS spectra calculated with different methods. Compared to full TDDFT, while significant improvement of efficiency is achieved, the simplified damped response maintains good accuracy for SERS calculation. We further showcase the efficiency of TBAOResponse by calculating the SERS spectra for a system that is computationally demanding with full TDDFT. This new method is promising for modeling SERS systems when a full quantum mechanical description of both the substrate and the molecule is necessary.

  PublisherDOI

• Δ-Machine Learning of Polarizability Tensors Using a Dipole Interaction Model

  Journal of Chemical Theory and Computation · 2025-07-09 · 1 citations

  articleSenior authorCorresponding

  As a fundamental response property, the molecular polarizability is responsible for a wide variety of physical phenomena relevant for understanding light-matter and intermolecular interactions. Therefore, it is important to have accurate and efficient methods to calculate the polarizability tensor. In this work, we introduce a model that combines a polarizable dipole interaction model (PIM) with Δ-machine learning to predict polarizability tensors, which we refer to as ΔPIMCCSD. To describe the rotational symmetry, we adapt a unique reference geometry obtained by diagonalizing the PIM polarizability tensor. A major benefit is that only the diagonal elements of the polarizability tensor needs to be learned. The model was parameterized to the coupled cluster singles and doubles (CCSD) polarizabilities from the QM7b data set and was used to predict the polarizabilities for various systems, such as small molecules and molecules from the QM9 data set. We show that the ΔPIMCCSD is comparable in accuracy to density-functional theory with the B3LYP exchange correlation functional (DFT/B3LYP) at a lower cost for molecules with similar chemical composition as the QM7b data set. For the QM9 data set, this was also found, although only after correcting for the smaller basis set used for calculating the polarizabilities in this data set. For molecules smaller and chemically more diverse than the training set, we find that the model performs worse than DFT/B3LYP. Ultimately, our work suggests that larger and more chemically diverse data sets with polarizabilities obtained at a high level of theory are needed. Finally, our results suggest that the model can be improved by incorporating atom-specific polarizabilities into PIM to better account for local environments. In summary, the combination of PIM with Δ-machine learning provides a simple and promising approach for predicting polarizability tensors.

  PublisherDOI

• The Amsterdam Modeling Suite

  The Journal of Chemical Physics · 2025-04-22 · 104 citations

  articleOpen access

  In this paper, we present the Amsterdam Modeling Suite (AMS), a comprehensive software platform designed to support advanced molecular and materials simulations across a wide range of chemical and physical systems. AMS integrates cutting-edge quantum chemical methods, including Density Functional Theory (DFT) and time-dependent DFT, with molecular mechanics, fluid thermodynamics, machine learning techniques, and more, to enable multi-scale modeling of complex chemical systems. Its design philosophy allows for seamless coupling between components, facilitating simulations that range from small molecules to complex biomolecular and solid-state systems, making it a versatile tool for tackling interdisciplinary challenges, both in industry and in academia. The suite also emphasizes user accessibility, with an intuitive graphical interface, extensive scripting capabilities, and compatibility with high-performance computing environments.

  PublisherOA PDFDOI

• Angiogenesis, signaling pathways, and animal models

  Chinese Medical Journal · 2025-04-21 · 4 citations

  reviewOpen access1st author

  ABSTRACT: The vasculature plays a critical role in homeostasis and health as well as in the development and progression of a wide range of diseases, including cancer, cardiovascular diseases, metabolic diseases (and their complications), chronic inflammatory diseases, ophthalmic diseases, and neurodegenerative diseases. As such, the growth of the vasculature mediates normal development and physiology, as well as disease, when pathologically induced vessels are morphologically and functionally altered owing to an imbalance of angiogenesis-stimulating and angiogenesis-inhibiting factors. This review offers an overview of the angiogenic process and discusses recent findings that provide additional interesting nuances to this process, including the roles of intussusception and angiovasculogenesis, which may hold promise for future therapeutic interventions. In addition, we review the methodology, including those of in vitro and in vivo assays, which has helped build the vast amount of knowledge on angiogenesis available today and identify important remaining knowledge gaps that should be bridged through future research.

  PublisherDOI

• Beyond Wingtips: Backbone Alkylation Affects the Orientation of N-Heterocyclic Carbenes on Gold Nanoparticles

  ChemRxiv · 2025-08-11

  articleOpen access

  The effect of wingtip groups on the orientation of N-heterocyclic carbene (NHC)–based self-assembled monolayers (SAMs) on a variety of metal surfaces has received considerable attention. However, the influence of backbone substituents on orientation has received virtually no attention, despite the fact that backbone interactions are critical for upright orientation of thiolate-based SAMs and that backbone functionalization is important for many applications. To address this question, a series of gold nanoparticles (NPs) supported by NHCs featuring symmetrical or asymmetrical long alkyl backbone substituents and ethyl and isopropyl wingtips were synthesized. The gold NPs were characterized using UV-Vis spectroscopy, electron microscopy, mass spectrometry, and surface-enhanced Raman spectroscopy (SERS). Experimental SER spectra were compared to simulated spectra, illustrating that both ethyl and isopropyl NHCs with symmetrical dodecyl long chains in the backbone adopt a primarily vertical configuration on the gold surface. However, the ethyl NHC with a single hexyloxy backbone substituent adopts mainly a flat configuration on the gold NP surface based on combined SERS and scanning tunneling microscopy (STM) results. This is attributed to on-surface interactions between long alkyl chains, which provide an unanticipated source of stability favoring the flat-lying orientation. Lastly, the thermal stability of the NHC-functionalized gold NPs at elevated temperatures was investigated. The dodecyloxy-functionalized NHC AuNPs remain thermally stable for 72 hours at 100°C, representing a significant improvement over state-of-the-art NHC-AuNPs. NHCs containing isopropyl wingtip groups provide NPs with higher levels of stability than diethyl-substituted NHCs, regardless of backbone substituents. Taken together, our results highlight critical synthetic considerations for NHC ligand design, enabling control of ligand orientation and nanomaterial stability by tuning NHC backbone substituents.

  PublisherOA PDFDOI

• Enhancing cancer radiotherapy efficacy using NanOx, a novel oxygenating perfluorocarbon nanoemulsion that reverses tumour hypoxia

  Cancer Letters · 2024-12-21 · 3 citations

  article
  PublisherDOI

• A Combined Quantum Mechanics and Molecular Mechanics Approach for Simulating the Optical Properties of DNA-Stabilized Silver Nanoclusters

  Journal of Chemical Theory and Computation · 2024-01-02 · 6 citations

  article

  DNA-stabilized silver nanoclusters have emerged as an intriguing type of nanomaterial due to their unique optical and electronic properties, with potential applications in areas such as biosensing and imaging. The development of efficient methods for modeling these properties is paramount for furthering the understanding and utilization of these clusters. In this study, a hybrid quantum mechanical and molecular mechanical approach for modeling the optical properties of a DNA-templated silver nanocluster is evaluated. The influence of different parameters, including ligand fragmentation, damping, embedding potential, basis set, and density functional, is investigated. The results demonstrate that the most important parameter is the type of atomic properties used to represent the ligands, with isotropic dipole-dipole polarizabilities outperforming the rest. This underscores the importance of an appropriate representation of the ligands, particularly through the selection of the properties used to represent them. Moreover, the results are compared to experimental data, showing that the applied methodology is reliable and effective for the modeling of DNA-stabilized silver nanoclusters. These findings offer valuable insights that may guide future computational efforts to explore and harness the potential of these novel systems.

  PublisherDOI

Recent grants

• CAREER: Theoretical studies of optical properties of molecules near metal nanostructures

  NSF · $613k · 2010–2014

• Computational Methods for Ensemble Averaged Surface-Enhanced Raman Scattering

  NSF · $526k · 2023–2027

• Collaborative Research: A Mechanistic Study of Chemical Enhancement in Surface Enhanced Raman Spectroscopy and Graphene Enhanced Raman Spectroscopy

  NSF · $195k · 2017–2021

• Collaborative Research: Detailed Mechanistic Pathways of Surface Catalysis using SERS Spectroscopy: A Joint Theoretical and Experimental Synergistic Approach

  NSF · $230k · 2021–2024

• Surface-enhanced linear and nonlinear vibrational spectroscopy from first-principles

  NSF · $407k · 2014–2019

Frequent coauthors

• Kurt V. Mikkelsen

  73 shared

• Per‐Olof Åstrand

  Norwegian University of Science and Technology

  58 shared

• Amar H. Flood

  Indiana University Bloomington

  54 shared

• Tony Jun Huang

  Duke University

  43 shared

• Yuebing Zheng

  Walker (United States)

  42 shared

• Bala Krishna Juluri

  Paulsson (United States)

  41 shared

• Paul S. Weiss

  California NanoSystems Institute

  32 shared

• Ying‐Wei Yang

  Jilin University

  28 shared

Awards & honors

• ACS Early-Career Award in Theoretical Chemistry (2017)
• Otto Mønsted-Guest Professorship (2015)
• ACS OpenEye Outstanding Junior Faculty Award (2012)
• Presidential Early Career Award for Scientists and Engineers…
• NSF Career Award (2010)