About

Kathleen J. Stebe is the Richer and Elizabeth Goodwin Professor of Engineering and Applied Science at the School of Engineering and Applied Sciences, University of Pennsylvania. She is a faculty member in the Department of Chemical and Biomolecular Engineering. Her research group focuses on areas including directed assembly, patterning, evaporation and dewetting, bacteria at interfaces, and interfacial flows. The group webpage highlights her role as principal investigator and her leadership in these research areas, which involve understanding and manipulating complex fluid interfaces and their applications in engineering and science.

Research topics

• Materials science
• Nanotechnology
• Mechanics
• Chemistry
• Thermodynamics
• Physics
• Computer Science
• Biology
• Mathematics
• Organic chemistry
• Geometry
• Chemical physics
• Classical mechanics
• Composite material
• Chemical engineering
• Biological system

Selected publications

• pH-Tunable, Ligand-Free Selective Separation of Rare Earth Elements Using Silica Nanoparticles

  ACS Applied Materials & Interfaces · 2026-02-12

  articleSenior authorCorresponding

  Rare earth elements (REEs) are essential for clean energy technologies, yet their separation remains difficult due to their similar ionic radii and oxidation states. Conventional liquid–liquid extraction is energy-intensive and environmentally harmful, which motivates the development of more sustainable alternatives. Silica nanoparticles (SiO2 NPs), widely used as supports in solid-phase extraction, offer high surface area and tunable surface chemistry. However, the direct use of unmodified SiO2 NPs as selective REE adsorbents has been largely overlooked. In this study, we investigate the interactions between REEs and unmodified SiO2 NPs over a range of pH conditions to uncover the underlying mechanisms governing REE adsorption and desorption and explore their use to selectively separate REEs. We identify three distinct pH-dependent interaction regimes: the negligible interaction (near the SiO2 NPs isoelectric point), electrostatic, and hydrolysis-mediated regimes. In the negligible interaction regime, near the SiO2 NPs’ isoelectric point, electrostatic interactions are absent, and the REE cations are stable in the bulk phase, resulting in minimal REE uptake. In the electrostatic interaction regime, at intermediate pH, negatively charged SiO2 NPs interact electrostatically with REE cations, resulting in the REE capture. Finally, in the hydrolysis-mediated regime, at high pH, neutral REE hydroxides deposit on the surfaces of the SiO2 NP, which serve as nuclei for hydroxide deposition. These interaction modes are reversible, enabling REE capture and release from the SiO2 NP via pH swing. Within the electrostatic regime, SiO2 NPs exhibit clear size-dependent selectivity, favoring the adsorption of smaller, more charge-dense REEs over larger REEs. This selectivity persists under competitive conditions in both binary and ternary mixtures. Selectivity is also observed in REE desorption: lowering the pH selectively releases smaller REEs while retaining larger REEs. This work provides fundamental insight into REE–SiO2 NP interactions and demonstrates a ligand-free, pH-responsive strategy for selective REE capture and separation using silica-based materials.

  PublisherDOI

• Coarse‐grained simulation methodology for biomacromolecule behavior in multiphase systems

  AIChE Journal · 2026-05-15

  article

  Abstract Herein the components of the nanoscale structure of a bicontinuous interfacially jammed emulsion gel (bijel) were modeled using coarse‐graining (Dissipative Particle Dynamics, DPD). The details of the computational approach are described and validated. The behavior of a macromolecule was then investigated in both continuous phases of the bijel, with emphasis on the computational protocol for obtaining physically sound and verified properties at the macroscale. Sensitivity analysis was performed and a regression model was developed that predicts the macromolecule structure given the DPD model parameters. The case study of messenger ribonucleic acid biopolymer in the system followed, allowing the investigation of its interactions with each of the bijel solvents and comparisons to experiments and theory. Finally, the diffusivity of the mRNA in each phase was computed, providing insights for designing reaction‐separation bijel systems.

  PublisherDOI

• Reconfigurable Metasurfaces Based On Multistable Elastic Pixels (MEPs)

  2025-01-01

  articleSenior author

  Multistable Elastic Pixels (MEPs) are liquid crystal-based unit cells designed to enable nonvolatile reconfiguration of scattering inclusions. We experimentally demonstrate MEPs and build metasurfaces composed of MEP arrays to achieve tunable diffraction of visible wavelengths.

  PublisherDOI

• Integrative machine learning predicts activating kinase mutations for precision oncology

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-10-15

  preprintOpen access

  Abstract Kinases are enzymes that catalyze phosphorylation and play crucial roles in a myriad of cellular regulatory processes and hemostasis. Patient-specific genetic mutations that aberrantly activate kinases can profoundly influence cancer progression and alter drug efficacy. Predicting the impact of such missense mutations across the human kinome on protein function and cellular signaling is therefore a critical step toward personalized targeted therapy. Here, we present Kinome-AI, an integrative machine learning framework that classifies kinase missense mutations as activating or non-activating. Kinome-AI is trained on a rich multi-modal feature set, including residue-level biochemical changes, sequence embeddings from a protein language model, and structural descriptors of kinase–ATP–substrate complexes derived from molecular modeling. Notably, detailed structural features were available for only 21% of mutants; we leverage these as privileged information during training to impute missing structural data for the remaining ∼79. This strategy boosts performance without requiring structural inputs for new (unseen) mutations. The resulting classifier achieves an area under the receiver operating characteristic curve (AUROC) of 0.85 and a balanced accuracy (BACC) of 0.76 across 1,003 mutations spanning 110 different kinases —substantially outperforming existing bioinformatics and general-purpose variant effect predictors. This work provides a robust approach to quantify sequence–structure– function relationships of cancer-driving kinase mutations, paving the way for improved personalized cancer treatment. Significance Statement In cancer patients, numerous mutations in diverse protein kinases lead to marked differences in disease progression and drug response. Identifying which kinase mutations are activating in individual patients is therefore critical for precision oncology. Drawing inspiration from teacher– student (privileged information) learning, we developed a deep learning framework that integrates structural features from molecular simulations with sequence embeddings from protein language models. This approach enables accurate binary classification of the activation status of kinase mutations. Our study demonstrates how data-driven algorithms can leverage accumulated sequence and structural knowledge of known mutations to predict the effects of novel variants a priori . The model, termed Kinome-AI, shows significant promise for incorporation into personalized cancer therapy decision pipelines.

  PublisherOA PDFDOI

• The Role of Asparagine as a Gatekeeper Residue in the Selective Binding of Rare Earth Elements by Lanthanide‐Binding Peptides

  Chemistry - A European Journal · 2025-05-01 · 3 citations

  articleOpen access

  Abstract Lanthanide‐binding tag (LBT) peptides selectively complex lanthanide cations (Ln 3+ ) in their binding pockets and are promising for lanthanide separation. However, designing LBTs that selectively target specific Ln 3+ cations remains a challenge due to limited molecular‐level understanding and control of interactions within the lanthanide‐binding pocket. In this study, we reveal that the N5 asparagine residue acts as a gatekeeper in the binding pocket, resulting in a 100‐fold selectivity for smaller Lu 3+ over larger La 3+ cations. Nuclear magnetic resonance spectroscopy and molecular dynamics simulations show that the N5 residue weakly binds to the larger La 3+ cation, permitting H 2 O molecules inside the pocket. For the smaller Lu 3+ cations, the N5 residue forms an inter‐arm hydrogen bond with the E14 glutamic acid residue, locking the Lu 3+ cation in the pocket and preventing H 2 O infiltration. Mutating the N5 asparagine to a D5 aspartic acid prevents such a hydrogen bond, eliminating the gatekeeping mechanism and precipitously reducing selectivity. The resulting binding affinity to Ln 3+ cations is non‐monotonic but generally increases with cation size. These results suggest a molecular design paradigm: the reduced affinity for larger lanthanides is due to open pocket conformations, while the selectivity of smaller Ln 3+ cations over larger ones is due to the gatekeeping hydrogen bond.

  PublisherOA PDFDOI

• Room-Temperature Preservation of mRNA using Deep Eutectic Solvent

  ChemRxiv · 2025-08-28

  preprintOpen access

  mRNA, a versatile vaccine and therapeutic platform of growing global importance, is notoriously unstable in aqueous environments due to various chemical degradation pathways, significantly limiting its potential. mRNA is particularly susceptible to hydrolytic degradation, often catalyzed by ubiquitous ribonucleases (RNases). Current stabilization methods rely heavily on cold-chain logistics, which are expensive and challenging to maintain, particularly in resource-limited settings. To address these challenges, ionic liquids and deep eutectic solvents have been explored as non-aqueous solvents for RNA extraction and preservation. However, most previously studied media contain toxic heavy metals or form ternary aqueous two-phase systems that do not protect against RNases. Moreover, model RNAs used in prior studies are simple and not representative of mRNAs. Here, we report the use of a simple, metal-free, hydrophobic deep eutectic solvent (hDES) composed of methyltrioctylammonium chloride and 1-decanol to extract and preserve mRNA at room temperature. Under optimized conditions, we achieve near 100% extraction efficiency into the protective hDES phase that effectively preserves mRNA integrity as assessed by capillary gel electrophoresis and an in vitro assay. We also demonstrate that this hDES system can extract complex mRNA strands of clinically relevant lengths and modifications. Importantly, the hDES phase also shields mRNA from RNase A exposure and suppresses hydrolytic degradation, enabling long-term preservation of mRNAs at room temperature for at least 227 days. Due to its ability to partition, preserve, and release mRNA, hDES composed of fatty alcohols and quaternary ammonium salts could be tailored for use as shelf-stable, non-aqueous precursors to RNA-based therapeutics such as cationic emulsions and lipid nanoparticles. This work potentially informs new strategies for the development of stable mRNA formulations, essential for next-generation vaccines and therapeutics.

  PublisherOA PDFDOI

• Correction: Interfacial rheology of lanthanide binding peptide surfactants at the air–water interface

  Soft Matter · 2025-01-01

  erratumOpen accessSenior authorCorresponding

  Correction for ‘Interfacial rheology of lanthanide binding peptide surfactants at the air–water interface’ by Stephen A. Crane et al. , Soft Matter , 2024, 20 , 9161–9173, https://doi.org/10.1039/D4SM00493K.

  PublisherOA PDFDOI

• Metal-Oxide-Decorated Mesoporous Silica Chemiresistors for Exhaled Biomarker Detection

  ACS Omega · 2025-04-11 · 1 citations

  articleOpen access

  A metal-oxide-decorated mesoporous silica (MOMS) chemiresistor platform enables the selective detection of disease-specific volatile organic compounds (VOCs) in exhaled breath. Functionalization of these mesoporous structures with metals and metal oxides facilitates the detection of a wide range of VOCs. To create a sensing architecture with a bicontinuous morphology that optimizes molecular diffusion and electron transport pathways, we employ physically confined polymerization-induced phase separation (PC-PIPS) to fabricate template-directed mesoporous structures with controlled film thicknesses ranging from 1 to 5 μm. Incorporation of metal oxides (SnO2, ZnO) and noble metals (Pt, Au) forms p–n heterojunctions, enhancing sensitivity and selectivity through modulation of electron depletion layers. The MOMS chemiresistors demonstrate distinct response patterns toward key biomarkers, including hydrogen sulfide (periodontal disease), toluene (gingivitis), formaldehyde (oral carcinoma), and acetone (diabetes mellitus). Response magnitudes range from 1.75–5.66 at 10 ppm to 5.56–12.13 at 100 ppm of H2S, with unique electronic signatures, enabling identification of complex gas mixtures. This scalable and versatile fabrication approach establishes MOMS chemiresistors as a promising platform for noninvasive, early-stage disease detection via breath analysis.

  PublisherDOI

• 3D Printing of Bicontinuous Nanoparticle‐Stabilized Emulsion Gels via Co‐Solvent Removal

  Small · 2025-11-03

  articleOpen accessCorresponding

  Bicontinuous emulsion gels are mixtures with interpenetrating arrangements of two immiscible liquids stabilized with particles. The structures of such gels are readily made into simple macroscale geometries, like sheets and fibers; however, achieving more complex macroscopic structures while maintaining control over microscopic features and morphological bicontinuity remains a challenge. In this study, the ability to fabricate complex 3D structures of bicontinuous emulsion gels using direct ink writing (DIW) is demonstrated. The emulsion precursors are formulated with a mixture of hydrophilic and hydrophobic fumed silica particles; these precursors exhibit shear-thinning and yield stress behavior necessary for DIW. The thixotropic nature of the precursor further promotes the formation of bicontinuous emulsion gels through vaporization-induced phase separation and stabilization through both interfacial jamming and bulk stabilization mechanisms. This fabrication technique enables the creation of functional bicontinuous structures with complex architectures, paving the way for application in biomedical implants, catalytic reactors, and beyond.

  PublisherOA PDFDOI

• Room-Temperature Preservation of mRNA using Deep Eutectic Solvent

  ChemRxiv · 2025-08-24

  articleOpen access

  mRNA, a versatile vaccine and therapeutic platform of growing global importance, is notoriously unstable in aqueous environments due to various chemical degradation pathways, significantly limiting its potential. mRNA is particularly susceptible to hydrolytic degradation, often catalyzed by ubiquitous ribonucleases (RNases). Current stabilization methods rely heavily on cold-chain logistics, which are expensive and challenging to maintain, particularly in resource-limited settings. To address these challenges, ionic liquids and deep eutectic solvents have been explored as non-aqueous solvents for RNA extraction and preservation. However, most previously studied media contain toxic heavy metals or form ternary aqueous two-phase systems that do not protect against RNases. Moreover, model RNAs used in prior studies are simple and not representative of mRNAs. Here, we report the use of a simple, metal-free, hydrophobic deep eutectic solvent (hDES) composed of methyltrioctylammonium chloride and 1-decanol to extract and preserve mRNA at room temperature. Under optimized conditions, we achieve near 100% extraction efficiency into the protective hDES phase that effectively preserves mRNA integrity as assessed by capillary gel electrophoresis and an in vitro assay. We also demonstrate that this hDES system can extract complex mRNA strands of clinically relevant lengths and modifications. Importantly, the hDES phase also shields mRNA from RNase A exposure and suppresses hydrolytic degradation, enabling long-term preservation of mRNAs at room temperature for at least 227 days. Due to its ability to partition, preserve, and release mRNA, hDES composed of fatty alcohols and quaternary ammonium salts could be tailored for use as shelf-stable, non-aqueous precursors to RNA-based therapeutics such as cationic emulsions and lipid nanoparticles. This work potentially informs new strategies for the development of stable mRNA formulations, essential for next-generation vaccines and therapeutics.

  PublisherOA PDFDOI

Recent grants

• Active Surface Agents: Enhanced Transport by Active Colloids at Fluid Interfaces

  NSF · $366k · 2020–2025

• Process Intensification via Bijels for Simultaneous and Continuous Catalytic Reaction and Separation

  NSF · $417k · 2020–2024

• Drop detachment modes in microfluidics devices

  NSF · $200k · 2007–2011

• Curvature gradient driven assembly of trapped and reconfigurable structures

  NSF · $428k · 2016–2020

• Directed Assembly by Capillarity

  NSF · $315k · 2011–2015

Frequent coauthors

• Daeyeon Lee

  University of Pennsylvania

  89 shared

• Nima Sharifi-Mood

  50 shared

• Randall D. Kamien

  48 shared

• Iris B. Liu

  University of Pennsylvania

  42 shared

• Daniel A. Beller

  Johns Hopkins University

  39 shared

• Robert L. Leheny

  Johns Hopkins University

  31 shared

• Liana Vaccari

  Consortium For Ocean Leadership

  25 shared

• Neha Manohar

  University of Pennsylvania

  23 shared

Labs

• KATHLEEN J. STEBE GroupPI

  Responsive Theme is free template based on Bootstrap framework.

Education

• Ph.D., Chemical Engineering

  University of California, Berkeley

  1990

• B.S., Chemical Engineering

  University of California, Berkeley

  1985

Awards & honors

• Member, National Academy of Engineering (2021)
• Member, American Academy of Arts and Sciences (2020)
• Johns Hopkins Society of Scholars (2015)
• Fellow, American Physical Society (2010)
• Fellow, Radcliffe Institute, Harvard University (2002)