About

Yaroslava Yingling is a Professor and Associate Faculty member of Chemistry at NC State University. She holds the title of Kobe Steel Distinguished Professor and serves as Associate Department Head in the Department of Materials Science and Engineering. Her research focuses on areas within chemistry and materials science, although specific research areas are not detailed on the page. She is involved in departmental leadership and contributes to the academic community through her faculty role, supporting undergraduate and graduate programs. Her contact information is provided, indicating her active engagement in the university's academic and research activities.

Research topics

• Computer Science
• Chemistry
• Biochemistry
• Physics
• Biology
• Materials science
• Genetics
• Biophysics
• Computational chemistry
• Chemical physics
• Biomedical engineering
• Crystallography
• Nanotechnology
• Medicine
• Organic chemistry
• Botany
• Radiology
• Quantum mechanics
• Nuclear magnetic resonance

Selected publications

• Efficient and reversible chirality induction between protein and achiral plasmonic assemblies

  Nature Materials · 2026-04-15

  articleOpen access

  Chiral molecules in nature usually show optical activity only in the deep ultraviolet, whereas artificial chiral plasmonic nanostructures can generate much stronger responses at visible and near-infrared wavelengths. An important challenge is whether the abundant biomolecular chirality in nature can be directly transferred to achiral plasmonic systems without elaborate three-dimensional nanofabrication. Here we show that the mechanical stretching of protein molecules anchored within achiral gold nanoparticle assemblies strongly enhances and reversibly modulates plasmon-coupled circular dichroism. Stretching amplifies the chiroptical response to an ellipticity of 1.18° and a dissymmetry factor of 0.2, far exceeding conventional hotspot-based strategies. Repeated stretching and relaxation further enable reversible switching over more than 100 cycles. Simulations and in situ spectroscopy indicate that the deformation of protein changes its conformation and dipole alignment, thereby strengthening the plasmonic chiral response. These findings establish a route to achieve dynamically controllable chiroptical activity in achiral plasmonic assemblies, revealing how small biomolecular deformations can strongly influence plasmonic responses of much larger nanostructures.

  PublisherOA PDFDOI

• Efficient and reversible chirality induction between protein and achiral plasmonic assemblies

  TUHH Open Research · 2026-04-15

  articleOpen access

  Chiral molecules in nature usually show optical activity only in the deep ultraviolet, whereas artificial chiral plasmonic nanostructures can generate much stronger responses at visible and near-infrared wavelengths. An important challenge is whether the abundant biomolecular chirality in nature can be directly transferred to achiral plasmonic systems without elaborate three-dimensional nanofabrication. Here we show that the mechanical stretching of protein molecules anchored within achiral gold nanoparticle assemblies strongly enhances and reversibly modulates plasmon-coupled circular dichroism. Stretching amplifies the chiroptical response to an ellipticity of 1.18° and a dissymmetry factor of 0.2, far exceeding conventional hotspot-based strategies. Repeated stretching and relaxation further enable reversible switching over more than 100 cycles. Simulations and in situ spectroscopy indicate that the deformation of protein changes its conformation and dipole alignment, thereby strengthening the plasmonic chiral response. These findings establish a route to achieve dynamically controllable chiroptical activity in achiral plasmonic assemblies, revealing how small biomolecular deformations can strongly influence plasmonic responses of much larger nanostructures.

  PublisherDOI

• A Comprehensive Dataset and Workflow for Building Large-Scale, Highly Oxidized Graphene Oxide Models

  Data · 2026-01-13

  articleOpen accessSenior authorCorresponding

  Graphene (GRA) and graphene oxide (GO) have drawn significant attention in materials science, chemistry, and nanotechnology because of their tunable physicochemical properties and wide range of potential uses in biomedical and environmental applications. Building reliable, large-scale molecular models of GRA and GO is essential for molecular simulations of wetting, adsorption, and catalytic behavior. However, current methods often struggle to generate large, chemically consistent sheets at high oxidation levels. In addition, the resulting structures are frequently incompatible across different simulation packages. This work introduces a step-by-step protocol with custom Tool Command Language (Tcl) and modified Python version 3.12 scripts for building large-scale, AMBER-compatible GO structures with oxidation levels from 0% to 68%. The workflow applies a systematic surface modification strategy combined with post-processing and atom-type assignment routines to ensure chemical accuracy and force field consistency. The dataset includes fifteen MOL2 format files of 20 × 20 nm2 GO sheets, ranging from pristine to highly oxidized surfaces, each validated through oxidation-ratio analysis and structural integrity checks. Together, the dataset and protocol provide a design of scalable and chemically reliable GO molecular models for molecular dynamics simulations.

  PublisherOA PDFDOI

• Partially Fluorinated Copolymers as Oxygen Sensitive 19F MRI Agents

  UNC Libraries · 2026-04-14

  articleOpen access

  Effective diagnosis of disease and its progression can be aided by ¹⁹ F magnetic resonance imaging (MRI) techniques. Specifically, the inherent sensitivity of the spin-lattice relaxation time (T₁ ) of ¹⁹ F nuclei to oxygen partial pressure makes ¹⁹ F MRI an attractive non-invasive approach to quantify tissue oxygenation in a spatiotemporal manner. However, there are only few materials with the adequate sensitivity to be used as oxygen-sensitive ¹⁹ F MRI agents at clinically relevant field strengths. Motivated by the limitations in current technologies, we report highly fluorinated monomers that provide a platform approach to realize water-soluble, partially fluorinated copolymers as ¹⁹ F MRI agents with the required sensitivity to quantify solution oxygenation at clinically relevant magnetic field strengths. The synthesis of a systematic library of partially fluorinated copolymers enabled a comprehensive evaluation of copolymer structure-property relationships relevant to ¹⁹ F MRI. The highest-performing material composition demonstrated a signal-to-noise ratio that corresponded to an apparent ¹⁹ F density of 220 mm, which surpasses the threshold of 126 mm ¹⁹ F required for visualization on a three Tesla clinical MRI. Furthermore, the T₁ of these high performing materials demonstrated a linear relationship with solution oxygenation, with oxygen sensitivity reaching 240×10^-5 mmHg^-1 s^-1 . The relationships between material composition and ¹⁹ F MRI performance identified herein suggest general structure-property criteria for the further improvement of modular, water-soluble ¹⁹ F MRI agents for quantifying oxygenation in environments relevant to medical imaging.

  PublisherDOI

• Mapping the Morphological Landscape of Oligomeric Di-block Peptide Polymer Amphiphiles

  UNC Libraries · 2026-04-07

  articleOpen access

  Peptide polymer amphiphiles (PPAs) are highly tunable hybrid materials that achieve complex, protein-like assembly landscapes by combining sequence-dependent properties of peptides with structural diversity of polymers. Despite their promise as functional biomimetic materials, determining how polymer and peptide properties simultaneously affect PPA self-assembly remains challenging. We herein present a systematic study of critical components within the PPA design space that dictate the self-assembled morphologies. PPAs containing hydrophobic oligo(ethyl acrylate) were used to interrogate the role of polymer molecular weight and dispersity in addition to peptide length and charge density on self-assembly. We observed that PPAs predominantly formed spherical particles (micelles and vesicles), with both polymer molecular weight and peptide hydrophilicity determining morphology. Additionally, peptide charge and polymer dispersity influence particle size. These key benchmarks will facilitate the rational design of PPAs that expand the scope of biomimetic and biocompatible functionality within assembled soft materials.

  PublisherDOI

• Data integration and data fusion approaches in self-driving labs: A perspective

  APL Machine Learning · 2025-10-29

  articleOpen accessSenior author

  Self-driving laboratories (SDLs) are transforming materials discovery by combining automation, machine learning, and real-time feedback. Yet, their success depends on robust data integration and fusion methods capable of handling materials data that are heterogeneous, sparse, and multi-scale. Such data span theoretical models, simulations, and experimental techniques across diverse spatial and temporal scales, creating significant challenges for interoperability and analysis. This perspective reviews the state-of-the-art techniques, including knowledge graphs, structured pipelines, multimodal machine learning, and physics-informed models, that are enabling materials science and SDLs to unify and learn from disparate data sources, identify critical challenges, and propose forward-looking directions to enhance data readiness, interoperability, and predictive power in SDLs. We also highlight emerging methods such as transformer architectures, zero-shot learning, and real-time stream processing, and discuss the critical need for more scalable, interpretable, and adaptive solutions to fully realize autonomous materials innovation. By mapping out both the current landscape and future opportunities, we argue that next-generation data integration and fusion are not just enablers but essential pillars for achieving fully autonomous, adaptive, and intelligent SDL systems capable of addressing the complexities of hierarchical and multifunctional materials.

  PublisherDOI

• Agglomeration of Nanoparticles Inhibits Solvent‐Driven Ligand Stripping

  Advanced Materials Interfaces · 2025-07-06 · 1 citations

  articleOpen accessSenior authorCorresponding

  Abstract The colloidal stability of nanoparticles (NPs) is significantly affected by complex solvent‐ligand interactions, with poor solvents often inducing NP agglomeration and ligand desorption from the surface. Despite the frequent occurrence of these phenomena in post‐synthetic experiments, the underlying mechanisms remain elusive. In this study, dynamic light scattering (DLS), thermogravimetric analysis (TGA), and large‐scale all‐atom molecular dynamics (MD) simulations are used to investigate solvent‐driven oleylamine ligand removal from Fe 3 O 4 NPs. Eight experimentally relevant NP systems under replicated solvent conditions are modeled, enabling direct comparison and yielding deep insights into solvent‐mediated ligand stripping with excellent agreement. These findings reveal that ethanol's ability to strip oleylamine ligands from Fe 3 O 4 NPs is impeded by NP agglomeration, where stripped and interdigitated ligands create a steric barrier, preventing solvent molecules from accessing the NP surface. This effect becomes more pronounced with increasing NP size due to the greater ligand surface density that enhances interdigitation. Moreover, the presence of a threshold concentration of the poor solvent in binary mixtures is identified, below which the maximum number of ligands can be stripped without initiating agglomeration. These insights provide a framework for optimizing solvent‐mediated ligand exchange, with implications for NP applications in catalysis, energy storage, optoelectronics, and biomedical engineering.

  PublisherOA PDFDOI

• Editorial: Recent advancements in RNA technologies, diagnostics, and therapeutics

  Frontiers in Bioengineering and Biotechnology · 2025-02-04 · 1 citations

  editorialOpen access

  IntroductionRNA technology is an emerging field that exploits the unique structural and functional properties of RNA to build nanoscale structures and regulate complex biological systems (Stewart, 2024). RNA has been shown to assemble into structures with various shapes, sizes, and complexities, enabling applications in molecular sensing, drug delivery, immunomodulation, and cellular activity regulation (Chandler et al., 2021). This foundational work shows the significant potential of RNA molecules and their chemical analogs as a biomaterial for developing personalized diagnostic and therapeutic applications, as evidenced by numerous in vitro and in vivo studies and exemplified by several FDA approved formulations. However, critical challenges such as nuclease stability, targeted delivery of RNA therapies, regulation of their immune response, and lowering detection limits that must be further addressed to fully translate RNA nanotechnology into clinical applications.This Research Topic highlights recent advancements and innovative work in RNA technologies for diagnostics and therapeutics of various classes of RNAs. This collection features six review and research articles curated by international leaders in the fields of nucleic acid technologies, drug delivery, and computational studies. All manuscripts present a wide range of innovative technologies encompassing the design and optimization of gene therapies, production of RNAs, logic gating, tissue engineering and verifications of new therapeutic targets. MicroRNA for regenerative medicineOver 30 years ago, the first microRNA (miRNA) was identified in Caenorhabditis elegans (Lee et al., 1993; Wightman et al., 1993) and provided insights into how RNA can regulate gene expression. MicroRNAs (miRNAs) are small non-coding RNAs, ~22 nucleotides in length, that function as key regulators of gene expression. Through their regulatory activity, miRNAs can modulate several biological processes, including cellular differentiation, proliferation, and apoptosis (O'Brien et al., 2018). miRNAs are a promising strategy for advancing regenerative medicine, however, it is imperative to further elucidate miRNA regulatory mechanisms and pathways for clinical applications. Shahin et al. investigated the regulatory role and regenerative functions of microRNA (miR-155) in skin wound repair. The authors performed computational analysis of differentially expressed miRNAs in adipose-derived mesenchymal stem cells (AD-MSCs) and keratinocytes. hsa-miR-155 was identified and experimentally validated as having an enhanced immunomodulatory effect of AD-MSCs through regulating key wound healing proteins FGF2, FGF7, CCL2, and VCAM1. Castañón-Cortés et al. highlighted recent advancements in integrating miRNA into tissue-engineering scaffolds for optimized tissue repair and regeneration. The authors summarize the use of tissue-engineered scaffolds in combination with miRNAs applied to skin, musculoskeletal, nervous, and cardiovascular systems. Additionally, the study emphasizes the need for further experiments to understand fundamental miRNA-mediated mechanisms of action for specific tissue regeneration and minimal off-target effects. Lastly, the current challenges of cellular uptake and localized delivery are outlined.Optimizing design approaches for RNA synthesis and gene expressionEngineering molecular machinery and RNA sequences are a practical approach for efficient RNA synthesis and gene regulation capabilities. Circular RNAs (circRNAs) are a highly stable class of non-coding RNAs with diverse biological roles, including acting as miRNA sponges, transcriptional regulation, protein recruitment, and enhancing protein activity (Kristensen at al., 2019). He et al. developed a one-pot process for circRNA synthesis by introducing specific mutations to T7 RNA polymerase (RNAP) to yield a thermostable variant that combines transcription and cyclization in a single reaction. The authors used consensus and folding free energy calculations for hotspot selections to construct a multisite mutant T7 RNAP. The engineered polymerase demonstrated stable activity at 45°C for over an hour, introducing new techniques for efficient circRNA production via a one-pot transcription and cyclization. RNA sequence design is another approach that can be used to tune gene expression. Codons are trinucleotide sequences that determine a specific amino acid. Due to the redundancy of the genetic code, synonymous codons can encode the same amino acid. However, these synonymous codons are not used equally, causing a codon bias (Novoa et al., 2012). Paremskaia et al. presented a comprehensive analysis of current metrics for codon optimization for clinical use for gene therapy. The authors categorize methods to generate optimized sequences variants and protocols to experimentally verify mRNA stability and protein expression. The study concludes with persistent challenges of unintended effects on protein function and complexities in evaluating codon effectiveness.Synthetic circuitsRNA molecules such as RNA aptamers, ribozymes, and riboswitches can organize to form networks that can perform complex functions including gene regulation, signal amplification, and logic operations for diagnostics and therapeutics (Pfeifer et al., 2023). Tian et al. engineered Boolean logic gates in the yeast Saccharomyces cerevisiae by reintroducing the naturally absent RNA interference (RNAi) pathway. The authors found that promoter leakage of pGAL1 inhibited logic behavior. Promoter leakage was reduced when the DNA fragment was placed between the two promoter regions, vastly improving the circuit reliability and performance. Armstrong and Isalan discussed using RNA-based circuits for the development of bacterial theranostics. The authors emphasized the use of mRNA and riboregulatory to construct circuits and program bacteria to sense and respond to physiochemical signals. The study closes with current issues of safety and proving a promising outlook for developing precise and versatile therapeutic systems.OutlookRNA technologies offer innovative approaches for therapeutic and diagnostic applications. However, broad application of RNA-based technologies in clinical settings will require focused research efforts in key areas: increasing target specificity and delivery efficiencies, improving stability and functional retention at ambient temperatures, ensuring precise patient-specific regulation of toxicities, and decreasing production and handling costs. Addressing these critical factors will be essential in realizing the full potential of RNA technologies for widespread clinical use.

  PublisherOA PDFDOI

• Empirical evidence that glucan-interacting amino acid side chains within the transmembrane channel collectively facilitate cellulose synthase function

  Plant Molecular Biology · 2025-07-09 · 1 citations

  articleOpen access

  The fundamental mechanism of cellulose synthesis is widely conserved across Kingdoms and depends on cellulose synthases, which are processive, dual-function, family 2 glycosyltransferases (GT-2). These enzymes polymerize glucose on the cytoplasmic side of the plasma membrane and export the glucan chain to the cell surface through an integral transmembrane (TM) channel. Structural studies of active plant cellulose synthases (CESAs) have revealed interactions between the nascent glucan chain and the side chains of polar, charged, and aromatic amino acid residues that line the TM channel. However, the functional consequences of modifying these side chains have not been tested in vivo in CESAs or other processive GT-2s. To test this, we used an established in vivo assay based on genetic complementation of CESA5 in the moss, Physcomitrium patens. For accurate prediction of glucan-interacting amino acid residues, we generated a complete homotrimeric molecular model of PpCESA5 using a combination of homology and de novo modeling. All-atom molecular dynamics-based analyses of contact metrics and interaction energy identified 23 amino acid residues with high propensity to interact with the nascent glucan chain within the TM channel or on the apoplastic surface of PpCESA5. Mutating any one of 18 of these amino acid residues to alanine, thereby removing their side chains, abolished or impaired CESA function, with the strongest effects observed upon the loss of charged amino acid side chains. This provides direct evidence to support the hypothesis that multiple amino acid residues collectively maintain a smooth energy landscape within the TM channel to facilitate glucan translocation.

  PublisherDOI

• RL-CURATE-KG: Multi-Agent Reinforcement Learning for Scalable Knowledge Graph Curation

  2025-12-08

  article
  PublisherDOI

Recent grants

• Collaborative Research: Processing Films from Multi-Functional Polymer Dispersion Blends

  NSF · $285k · 2017–2021

• Collaborative Research: Supramolecular Materials by Nucleic Acid Block Copolymer Self-Assembly

  NSF · $180k · 2014–2018

• CAREER: Integrating DNA and Inorganic Surfaces for Functional Materials Design

  NSF · $445k · 2012–2018

• Collaborative Research: Probing Coordination Specificity of Metalloprotein Domains with Peptide-Polymer Amphiphile Self Assembly

  NSF · $315k · 2021–2025

• Collaborative Research: Exploring self-organization of functional nucleic acid supramolecular assemblies with stimuli responsive properties

  NSF · $263k · 2022–2025

Frequent coauthors

• Soichiro Tsuda

  252 shared

• Melissa A. Pasquinelli

  North Carolina State University

  134 shared

• Murat Okandan

  134 shared

• Maarten P. Boer

  Carnegie Mellon University

  133 shared

• Rita E. Serda

  University of New Mexico

  133 shared

• Gabriela Juárez-Martı́nez

  133 shared

• Jit Muthuswamy

  Arizona State University

  133 shared

• Mitsumasa Iwamoto

  Tokyo Institute of Technology

  133 shared

Labs

• Yaroslava YinglingPI

Education

• PhD, Materials

  Pennsylvania State University

  2002

• B.S., Computer Science and Engineering

  Saint Petersburg State Polytechnical University

  1996