About

Christy F. Landes earned a B.S. in chemistry from George Mason University in 1998, and her Ph.D. was awarded from the Georgia Institute of Technology in 2003 under the direction of Mostafa El-Sayed. After postdoctoral positions at the University of Oregon and the University of Texas at Austin, she began her independent career at the University of Houston in 2006. In 2009 she moved to Rice University, where she rose through the ranks to become the Kenneth S. Pitzer-Schlumberger Chair of Chemistry. In 2023, she joined the University of Illinois Urbana-Champaign. Her research interests encompass physical, analytical, and materials chemistry, with a focus on predictive separations, spectro-electrochemistry, protein dynamics at interfaces, imaging and signal processing, and single-molecule spectroscopy. Her experimental physical chemistry research aims to understand complex structure-function relationships in biological processes and to inspire innovation in materials design, emphasizing minimal cost, maximum efficiency, and optimized longevity. Her work explores how biological systems often utilize redundant or degenerate channels that outperform synthetic counterparts, providing insights into nature’s molecular-scale engineering strategies. She develops new methods to increase information content in low signal-to-noise single-molecule data, characterizing biological examples of heterogeneous structure-function relationships and identifying similar relationships in synthetic systems. Her contributions have been recognized through numerous awards and honors, including fellowships in the American Chemical Society and the American Association for the Advancement of Science, as well as awards from the National Science Foundation and the Biophysical Society.

Research topics

• Materials science
• Optoelectronics
• Nanotechnology
• Physics
• Optics
• Chemistry
• Artificial Intelligence
• Molecular physics
• Computer Science
• Acoustics
• Composite material
• Computational physics
• Photochemistry
• Chemical physics
• Biological system
• Atomic physics

Selected publications

• Solvated Electron Generation from Coupled Plasmon Modes of Gold Nanoparticles Using Visible Light

  Nano Letters · 2026-04-10

  article

  Solvated electrons are strong homogeneous reducing agents, and their generation with visible light can unlock new redox chemistry. Water imposes a high photoemission energy barrier for gold, restricting the accessible spectral window for plasmon-mediated solvated electron generation to the near-ultraviolet region. Here, we first demonstrate that by using hexamethylphosphoramide, an organic solvent that supports large applied cathodic potentials without decomposition, the photoemission threshold is lowered to provide access to the entire visible spectrum. Next, we achieve solvated electron yields up to 150-fold higher with coupled plasmon modes from clustered gold nanoparticles, as compared to a smooth gold electrode. The observed quantum yield correlates with the local electric field enhancement by gap plasmon modes for these nanostructured electrodes as identified by varying the particle density. Overall, this study offers mechanistic insights into how coupled plasmon modes and threshold optimization can be used to enhance solvated electron generation with visible light.

  PublisherDOI

• Spectrometer Assembly and Python-Based Data Science Lab on the Reduction Kinetics of Methylene Blue

  Journal of Chemical Education · 2026-01-07 · 1 citations

  articleSenior authorCorresponding

  Integrating data science and Python programming into secondary chemistry education addresses gaps in preparing students for STEM (science, technology, engineering, and mathematics) careers, where computational and analytical skills are essential. Traditional laboratories often treat instruments as “black boxes,” restricting students’ ability to grasp basic principles. High instrumentation costs and limited access to advanced data analysis tools restrict hands-on learning. We present a cost-effective laboratory module combining a do-it-yourself (DIY) spectrometer kit with data analysis using Python in Google Colaboratory (Colab). Students learn to plot data, perform least-squares fitting, calculate errors, and conduct kinetic studies, thereby developing analytical chemistry skills. These skills are applied in a problem-based learning environment to bridge introductory chemistry with quantitative analysis. Student feedback indicated a perceived improvement in understanding of instrumental components, calibration, and analytical techniques such as determining limits of linearity and dynamic range of detectors. By demystifying instruments and promoting chemical literacy and computational proficiency, this curriculum offers a model for integrating data science into secondary chemistry education.

  PublisherDOI

• Enhancing Interfacial Charge Transport in Gold Nanoparticle@Polyaniline Hybrids via <i>N</i> ‐Heterocyclic Carbene Linkers

  Angewandte Chemie International Edition · 2026-05-11

  articleOpen access

  N-Heterocyclic carbenes (NHCs) have emerged as a unique class of ligands for gold nanoparticles (Au NPs), combining strong metal binding with intrinsic electronic conductivity. Yet over the past decade, studies on Au NP@NHC systems have primarily focused on their stability, while the conductivity of NHCs has remained largely unexplored due to synthesis challenges. Here, we present a synthetic strategy that addresses this gap by employing amino-functionalized NHC-Au complexes with in situ oxidative polymerization of polyaniline (PANI) to yield electronically coupled Au NP@NHC-PANI hybrids in aqueous media. This strategy enables both a controlled PANI shell growth and introduction of an electronically active NHC interlayer. Single-particle scattering spectroscopy reveals that NHCs improve the interfacial electronic coupling as evidenced by pronounced plasmonic linewidth broadening. Conductivity measurements further confirm that NHCs enhance charge transport: conductive atomic force microscopy (C-AFM) shows an increase in contact current from 14.6 to 99.4 pA under a 300-mV bias, while lateral four-probe conductance increases from 0.17 to 3.5 nS. These results provide the first direct experimental evidence of the conductive role of NHCs in hybrid NP-polymer systems, establishing a new interface-engineering strategy for the rational design of electronically delocalized nanostructures and their applications in nanoelectronics.

  PublisherDOI

• Enhancing Interfacial Charge Transport in Gold Nanoparticle@Polyaniline Hybrids via <i>N</i> ‐Heterocyclic Carbene Linkers

  Angewandte Chemie · 2026-05-12

  articleOpen access

  ABSTRACT N ‐Heterocyclic carbenes (NHCs) have emerged as a unique class of ligands for gold nanoparticles (Au NPs), combining strong metal binding with intrinsic electronic conductivity. Yet over the past decade, studies on Au NP@NHC systems have primarily focused on their stability, while the conductivity of NHCs has remained largely unexplored due to synthesis challenges. Here, we present a synthetic strategy that addresses this gap by employing amino‐functionalized NHC‐Au complexes with in situ oxidative polymerization of polyaniline (PANI) to yield electronically coupled Au NP@NHC‐PANI hybrids in aqueous media. This strategy enables both a controlled PANI shell growth and introduction of an electronically active NHC interlayer. Single‐particle scattering spectroscopy reveals that NHCs improve the interfacial electronic coupling as evidenced by pronounced plasmonic linewidth broadening. Conductivity measurements further confirm that NHCs enhance charge transport: conductive atomic force microscopy (C‐AFM) shows an increase in contact current from 14.6 to 99.4 pA under a 300‐mV bias, while lateral four‐probe conductance increases from 0.17 to 3.5 nS. These results provide the first direct experimental evidence of the conductive role of NHCs in hybrid NP‐polymer systems, establishing a new interface‐engineering strategy for the rational design of electronically delocalized nanostructures and their applications in nanoelectronics.

  PublisherDOI

• Plasmon-Induced Resonance Energy Transfer in Hybrid Nanomaterials

  ACS Energy Letters · 2026-02-18 · 2 citations

  articleSenior authorCorresponding

  Plasmon-induced resonance energy transfer (PIRET) has emerged as a powerful mechanism for harnessing and redirecting plasmon energy before it dissipates into hot carriers or heat. By matching plasmon resonance frequencies with acceptor absorption bands, PIRET extends plasmon-driven processes beyond the charge transfer pathway, enabling selective energy flow into excitonic transitions. This review highlights important progress in elucidating the fundamental plasmon decay processes and transitioning them into hybrid nanomaterials under PIRET. Employing specialized single-particle spectroscopic techniques based on scattering, extinction, and emission enables demonstration of PIRET in the face of competing mechanisms, such as interfacial charge transfer and thermalization. Finally, we complete this review by addressing strategies for active modulation of PIRET and present applications, ranging from plasmon photocatalysis to intracellular biochemical sensing.

  PublisherDOI

• Competition between Hot Carriers and Surface Electrochemistry in Gold Nanorod Dissolution

  The Journal of Physical Chemistry C · 2025-05-22 · 1 citations

  articleSenior authorCorresponding

  Plasmonic nanostructures have the potential to revolutionize photocatalysis by harnessing hot carriers to drive novel chemical reactions. Precise control of reaction sites on nanoparticles remains crucial for advancing catalyst design. The influence of hot carriers, particularly in the interplay with surface electrochemistry, needs further exploration. Employing single-particle spectroelectrochemical methods, we identify the conditions that lead to tip-preferred versus isotropic dissolution. We investigate how the applied potential, excitation laser power density, and wavelength of illumination directly direct gold nanorod dissolution. There is a competition between hot carrier localization and electrochemistry in determining the dissolution anisotropy. We observe that higher potentials favor isotropic dissolution, whereas higher laser power densities drive tip-specific dissolution. The results provide new insights into the control of tuning the gold nanoparticle dissolution anisotropy.

  PublisherDOI

• Plasmonic pathway to hybrid nanomaterials through energy transfer

  Science Advances · 2025-10-10 · 8 citations

  articleOpen accessSenior authorCorresponding

  Plasmon-induced resonance energy transfer (PIRET) is a promising approach for plasmonic photocatalysis and energy conversion, but challenges include elucidating the mechanism and maximizing its efficiency, both of which are hampered by competing processes. Another challenge is demonstrating that PIRET can photoinitiate reactions that follow efficient pathways compared to bulk processes. We report a plasmon-induced route to plasmonic-polymer hybrid nanomaterials using in operando single-particle spectroelectrochemistry. An energy transfer efficiency of 40% is achievable when the spectral overlap between gold nanorod scattering and polymer absorption is maximized. We also show that PIRET-initiated polymerization proceeds through a different mechanism than bulk polymerization, supported by spectroscopic evidence and density functional theory calculations, highlighting efficient energy cascading from photon to plasmon to exciton and, lastly, to unconventional light-initiated chemistry.

  PublisherDOI

• Machine Learning to Adaptively Predict Gold Nanorod Sizes on Different Substrates

  The Journal of Physical Chemistry C · 2025-03-18 · 4 citations

  article

  Correlating a nanoparticle’s morphology with its optical properties is essential and is achieved by a combination of electron microscopy and optical spectroscopy. Machine learning has gained attention for enhancing in situ measurements and enabling inverse nanoparticle design. However, new training data for each specific condition are often required when testing data differ from training data. We propose a method to adapt existing training data for predicting the size of gold nanorods (AuNRs) on different substrates. This method is based on simulated spectra of AuNRs on glass and indium tin oxide-coated glass (ITO), adapting the resonance energy between substrates. Using the adapted data, we train a decision tree regressor to predict AuNR sizes on ITO and test it with experimental data on ITO. This correction achieves comparable accuracy in predicting AuNR length to a decision tree trained directly on ITO. In addition, we apply the correction method to predict AuNR sizes on Al2O3, despite the lack of extensive training data, leading to an improvement in length prediction as well. Our analysis reveals that length prediction is more sensitive to the change in the resonance energy, suggesting that substrate differences mostly affect the length prediction. Overall, adapting training data enables real-time size determination across various environments without additional training data.

  PublisherDOI

• In operando single-particle spectroelectrochemistry of hybrid nanomaterials

  2025-09-17

  article1st authorCorresponding

  We report in-operando single-particle spectroelectrochemistry to induce and quantify plasmon-induced resonance energy transfer (PIRET)-assisted electropolymerization of methylene blue (MB) on individual gold nanorods (AuNRs). PIRET is a promising approach for plasmonic photocatalysis and energy conversion, but challenges that must be overcome include elucidating the mechanism and maximizing its efficiency, both of which are hampered by competing processes. Another challenge is demonstrating that PIRET can initiate useful photocatalytic reactions that follow efficient reaction pathways compared to thermally or electrochemically activated processes. Here, we quantify polymerization and demonstrate a PIRET efficiency of 40% in plasmonic-polymer nanohybrids when the spectral overlap between AuNR scattering and MB absorption is maximized. We propose a mechanism, supported by spectroscopic evidence and density functional theory calculations. Our findings demonstrate the efficient conversion from photon to plasmon to exciton and finally, to novel plasmon-induced chemistry.

  PublisherDOI

• D-Blur: A Deep Learning Approach for Mapping Subdiffraction Diffusion with Motion-Blurred Images

  Chemical & Biomedical Imaging · 2025-07-25

  articleOpen accessSenior authorCorresponding

  Image-based single-particle tracking (SPT) provides insight into complex transport within diverse biological and porous material structures, but its performance is constrained by motion blur and a low signal-to-noise ratio (SNR). Traditional SPT methods are sensitive to localization errors and often struggle with short trajectories and fast-moving emitters. In this work, we develop D-Blur, a U-Net-based convolutional neural network (CNN) algorithm designed to localize single particles and predict their diffusion coefficients (D) from motion-blurred point spread functions (PSFs). The obtained D values of emitters enable the reconstruction of diffusion maps on confined transport in porous materials. We validate the algorithm with simulated emitters in a heterogeneous environment, as well as the experimental data of free diffusers in a controlled diffusion environment. By directly extracting molecular dynamics from microscopy images without requiring trajectory linking, D-Blur overcomes key limitations of conventional SPT, providing a solution for subdiffraction diffusion maps within the native imaging flow of fluorescence microscopy. This work enhances diffusion analysis in complex systems and lays the foundation for future applications.

  PublisherDOI

Recent grants

• NIH Grant F32GM073534

  NIH · $68k · 2006

• CCI Phase I: NSF Center for Adapting Flaws into Features

  NSF · $1.8M · 2021–2024

• CAREER: Transport in Supported Polyelectrolyte Membranes

  NSF · $623k · 2011–2016

• Collaborative Research: Ion-exchange adsorption of proteins: a single-molecule investigation

  NSF · $204k · 2011–2014

• Instrument Development: 4-D Super Time Resolved Microscopy (4-D STReM) for Understanding Dynamics in Porous Materials

  NSF · $866k · 2018–2024

Frequent coauthors

• Stephan Link

  University of Illinois Urbana-Champaign

  74 shared

• Helen Foster

  Newcastle University

  63 shared

• Claudia May

  27 shared

• T. Rapley

  Birmingham Children's Hospital

  27 shared

• Wei‐Shun Chang

  University of Massachusetts Dartmouth

  22 shared

• Lydia Kisley

  Case Western Reserve University

  20 shared

• Richard C. Willson

  University of Houston

  19 shared

• M. W. Beresford

  University College London

  18 shared

Awards & honors

• Distinguished Alumnus, George Mason University College of Sc…
• Fellow, American Association for the Advancement of Science…
• Langmuir Lectureship, ACS Division of Colloids and Surfaces…
• Kinosita Award in Single Molecule Biophysics, Biophysical So…
• Fellow, American Chemical Society (2022)