About

Dr. Russell J. Composto is a Professor of Materials Science and Engineering, Bioengineering, and Chemical and Biomolecular Engineering at the University of Pennsylvania. He holds a PhD in Materials Science and Engineering from Cornell University, earned in 1987, following an MS in Materials Science from the same institution and a BA in Physics from Gettysburg College. Dr. Composto is a member of several interdisciplinary research centers at Penn, including the Nano/Bio Interface Center (NBIC), the Laboratory for Research on the Structure of Matter (LRSM), the Institute for Medicine and Engineering (IME), and the Penn Center for Energy Innovation. His research group explores the possibilities of polymer science, focusing on polymer physics, biomaterials, and environmental sustainability. Through his leadership, the group investigates fundamental and applied aspects of polymer materials, including their interactions at the nanoscale and their applications in energy, medicine, and materials engineering.

Research topics

• Nanotechnology
• Materials science
• Artificial Intelligence
• Chemistry
• Chemical engineering
• Chemical physics
• Computer Science
• Physics
• Organic chemistry
• Polymer chemistry
• Optics
• Composite material
• Physical chemistry
• Thermodynamics
• Engineering
• Computational chemistry

Selected publications

• Using Flory-Huggins-Informed Human-in-the-Loop Bayesian Optimization to Map the Phase Diagram of Polymer Blends

  Open MIND · 2026-02-27

  otherSenior author

  This record contains the code, data, and hardware design files associated with the manuscript: "Using Flory-Huggins-Informed Human-in-the-Loop Bayesian Optimization to Map the Phase Diagram of Polymer Blends" The repository contains the implementation of a Flory-Huggins-informed human-in-the-loop Bayesian optimization workflow used to construct and analyze polymer blend phase diagrams. Included in this repository are: Jupyter notebooks implementing experimental control flow, validation simulations, and an example of instantiating a Gaussian process optimizer Python source files for Gaussian process surrogate modeling and optimization Excel spreadsheets with grayscale pixel intensity measurements extracted from sample images, as well as calibration data Example image files CAD (STEP) file for the imaging system used to collect sample images J.C.H. acknowledges support from the Vagelos Institute for Energy Science and Technology (VIEST) at the University of Pennsylvania.

  DOI

• Using Flory-Huggins-Informed Human-in-the-Loop Bayesian Optimization to Map the Phase Diagram of Polymer Blends

  Zenodo (CERN European Organization for Nuclear Research) · 2026-02-27

  otherOpen accessSenior author

  This record contains the code, data, and hardware design files associated with the manuscript: "Using Flory-Huggins-Informed Human-in-the-Loop Bayesian Optimization to Map the Phase Diagram of Polymer Blends" The repository contains the implementation of a Flory-Huggins-informed human-in-the-loop Bayesian optimization workflow used to construct and analyze polymer blend phase diagrams. Included in this repository are: Jupyter notebooks implementing experimental control flow, validation simulations, and an example of instantiating a Gaussian process optimizer Python source files for Gaussian process surrogate modeling and optimization Excel spreadsheets with grayscale pixel intensity measurements extracted from sample images, as well as calibration data Example image files CAD (STEP) file for the imaging system used to collect sample images J.C.H. acknowledges support from the Vagelos Institute for Energy Science and Technology (VIEST) at the University of Pennsylvania.

  PublisherDOI

• Using Flory–Huggins-informed human-in-the-loop Bayesian optimization to map the phase diagram of polymer blends

  Digital Discovery · 2026-01-01

  articleOpen accessSenior author

  Integrating Flory–Huggins theory into a Bayesian optimization workflow enhances the objectivity of mapping phase behavior in polymer blends.

  PublisherOA PDFDOI

• The Effect of Nanoparticle Shape, Orientation, and Heterogeneity on the Optical Birefringence of Polymer Nanocomposites

  The Journal of Physical Chemistry C · 2026-02-16

  articleOpen access

  Embedding plasmonic nanoparticles (NPs) into polymer nanocomposites (PNCs) is a facile method for integrating them into functional devices, whose properties are tunable through varying NP size, shape, and loading. Using anisotropic NPs adds an additional degree of tunability to their orientation order in the PNC, as properties such as conductivity and charge transport can be enhanced in specific directions. In thin films, the film thickness and block copolymer self-assembly can affect the degree of NP orientation, which can be used as a method of control over these properties. However, large-scale control of orientation order in randomly distributed NPs, with both anisotropic NP shapes and heterogeneous shape distributions, remains a challenge. This is partly due to the lack of cost-effective, ensemble-level characterization methods that can independently determine the orientation order and degree of aggregation of anisotropic NPs. Here, we model the complex index of refraction of PNCs with plasmonic NP inclusions in the optical frequency domain by using an effective medium approximation. We quantitatively relate the simulated optical birefringence of the medium to the orientation order parameter of plasmonic nanorods and nanodisks in a robust manner insensitive to heterogeneity in simulated NP size and shape. Experimentally, we measure this orientation order parameter through the birefringent index of refraction using variable-angle spectroscopic ellipsometry (VASE). We demonstrate that we can independently determine the orientation order and degree of aggregation for various PNCs with gold nanorods and nanosphere inclusions. This facile technique provides a powerful method to broadly measure the average orientation order of anisotropic particles in PNCs, which can be correlated to their functional properties.

  PublisherDOI

• Investigating CoolSeal as an Urban Heat Solution in Philadelphia

  Scholarly Commons (University of Pennsylvania) · 2025-08-26

  otherOpen accessSenior author

  Extreme heat plagues Philadelphia, driving high energy consumption, increased public health risk, and exacerbated temperature inequities. The Composto Lab has partnered with the Philadelphia Office of Sustainability to pilot CoolSeal, a reflective asphalt street coating with potential to mitigate heat risk. Through qualitative interviews, competitor analysis, and pilot site measurements, our team outlines CoolSeal's feasibility and performance. CoolSeal shows significant surface temperature reductions, but its high cost may limit widespread adoption. CoolSeal lies within a broader set of extreme heat solutions. For detailed quantitative findings on surface temperature and mean radiant temperature, please reference "Evaluation of Asphalt Coatings’ Impact on Urban Heat in Philadelphia" by Nafisa Bangura and Angelica Dadda.

  Publisher

• Cross-Linking Density Controls the Interstitial Pore Size and Elasticity in Polyacrylamide Microgel Packings

  Macromolecules · 2025-04-08 · 8 citations

  articleSenior authorCorresponding

  Concentrated packings of microgel particles behave like soft elastic solids, in which the macroscopic elastic properties arise from the interactions of the underlying particles. In order to utilize these microgel packings as scaffolds for three-dimensional biological assays, the macroscopic elastic behavior and the size of the interstitial pores that form between particles must be controlled. Here, we explore the effect of cross-linking density on the rheological behavior of packed polyacrylamide microgel particles. At low polymer concentrations, just above the onset of solid-like behavior, the elastic properties of the microgel packings emanate from the interactions of brush-like polymer chains on the corona of the microgels. This behavior depends on the size of the polymer brush relative to the size of the microgel, where increasing the cross-linking density of the microgel particle decreases the brush length, resulting in high shear moduli of the packed microgels. At high polymer concentrations, well above the onset of elastic behavior, we observe a transition in the rheological behavior, in which the loss factor becomes independent of the polymer concentration. In this regime, the elastic shear moduli of microgels with low cross-linking (x-linking) densities follow distinct polymer physics scaling laws for bulk hydrogel networks. Additionally, we explore how these changes in the x-linking density alter the structure of interstitial pores between microgel particles through a combination of cryo-SEM and single nanoparticle tracking. We find that stiffer microgel particles with shorter brush-like coronas not only have larger pore sizes but also nanoparticles exploring the pores are able to escape and enter neighboring pores. Further, we find that the viscosity within the interstitial pores of the microgels with high x-linking density is less than that of the lower x-linked systems having comparable pore sizes. These findings show that the stiffness and pore size of microgel packings can be tuned independently and will guide the development of packed microgels as sacrificial scaffolds for three-dimensional biological applications.

  PublisherDOI

• Gold Nanoparticle Adsorption in Covalently Bonded Weak Polyelectrolyte Brushes

  Macromolecules · 2025-02-28 · 2 citations

  articleCorresponding

  The adsorption of spherical citrate-coated gold nanoparticles (AuNPs) into poly(2-vinylpyridine) (P2VP) brushes was investigated using a quartz crystal microbalance with dissipation (QCM-D). This study examined the impacts of environmental pH and brush molecular weight (10 and 53 kg/mol) on AuNP adsorption kinetics and areal number densities. We synthesized and characterized the P2VP brushes, grafted onto a poly(glycidyl methacrylate) (PGMA) priming layer, on both silicon wafers and QCM-D sensors. Adsorption experiments explored the pH-dependent adsorption behavior of 10- and 20-nm diameter AuNPs. The QCM-D data show that higher molecular weight brushes enhanced AuNP uptake. At pH = 4.0, the swollen brushes promote greater adsorption compared with the collapsed brush state at pH = 6.2. This study highlights the advantages of the homopolymer brush architecture compared with the block copolymer brush architecture from our previous work. Additionally, it reaffirms the pH-mediated size selectivity observed in our prior study, where the smaller 10 nm AuNPs show preferential adsorption at higher pH. These findings provide insights into the impacts of brush molecular weight and environmental conditions on nanoparticle adsorption, with implications for designing smart surfaces for sensing and filtration applications.

  PublisherDOI

• Nanoparticle Percolation Improves the Mechanical Properties of Polymer Nanocomposite Films

  ACS Macro Letters · 2025-07-08 · 2 citations

  articleSenior authorCorresponding

  Nanoparticle (NP) percolation governs the mechanical reinforcement of polymer nanocomposite (PNC) films. In this study, we demonstrate that both internal network morphology and near-surface morphology of NPs influence the mechanical properties of PNC films composed of poly(methyl methacrylate)-grafted silica nanoparticles (PMMA-NPs) in a poly(styrene-ran-acrylonitrile) (SAN) matrix. By systematically varying film thickness and annealing conditions, we achieve distinct NP morphologies, including continuous pillars, discrete pillars, clusters, and interconnected networks, each exhibiting different levels of NP percolation. Atomic force microscopy nanoindentation reveals that films with interconnected networks exhibit the highest reduced modulus (7.6 GPa), nearly quadrupling that of as-cast films with uniform NP dispersion (1.8 GPa), along with a substantial increase in hardness (624 MPa compared to 298 MPa). Notably, surface NP structures formed during annealing contribute to an enhanced modulus at low loads. These findings establish a direct structure–property relationship, providing insights into designing mechanically robust PNCs for applications in coatings, electronics, and energy storage.

  PublisherDOI

• Polymer–Wall Interactions Slow Infiltration Dynamics in Bicontinuous, Nanoporous Structures

  Macromolecules · 2025-04-15 · 1 citations

  articleSenior authorCorresponding

  Polymer infiltration is studied in a bicontinuous nanoporous gold (NPG) scaffold. For poly(2-vinylpyridine) (P2VP) with molecular weights (Mw) ranging from 51k to 940k Da, infiltration is investigated in an NPG with a fixed pore radius (Rp = 34 nm) under moderate confinement (Γ = Rg/Rp) 0.18 to 0.78. The time for 80% infiltration (τ80%) scales as Mw1.43, similar to PS, but weaker than the bulk behavior. Infiltration of P2VP is slower than PS due to stronger P2VP–wall interactions resulting in a physisorbed P2VP layer. This interpretation is supported by the similar scaling of τ80% for P2VP and PS, as well as molecular dynamics (MD) simulations. Simulations show that infiltration time scales as Mw1.4 and that infiltration slows as the polymer–wall attraction increases. As Mw increases, the effective viscosity transitions from greater than to less than the bulk viscosity due to pore narrowing and a reduction in entanglement density. These studies provide new insight into polymer behavior under confinement and a new route for preparing nanocomposites at high filler loadings.

  PublisherDOI

• Investigating polymer infiltration kinetics in nanoporous metal scaffolds using UV-vis spectroscopy

  Soft Matter · 2025-01-01

  articleOpen accessSenior author

  spectroscopic ellipsometer results. AFM and XPS support the strong attraction of P2VP for the Au surface and pores as demonstrated by wetting of P2VP over surface ligaments and a shift of the 4f orbital from the N on P2VP to higher binding energy, respectively. Using nanorods configured as a "T" to model ligament geometry, discrete dipole approximation (DDA) simulations capture the optical properties of the P2VP/NPG nanocomposite during infiltration and confirm experimental results. The evolution of the P2VP/NPG optical properties is attributed mainly to an increase in the effective refractive index within the pores. This study presents UV-vis spectroscopy as an alternative method for studying polymer infiltration into nanoporous metal scaffold films.

  PublisherOA PDFDOI

Recent grants

• Thermodynamic and Dynamic Control of Nanoparticles in Polymer Matrices

  NSF · $620k · 2019–2024

• PIRE: Research and Education in Active Coatings Technologies (REACT) for the Human Habitat

  NSF · $3.7M · 2015–2022

• Phase-Separating Polymer Blend Films Containing Nanoparticles

  NSF · $373k · 2002–2007

• Polymer Nanocomposites using Discrete Nanoparticles and Bicontinuous Scaffolds: New Strategies for Connective Morphologies and Property Control

  NSF · $510k · 2024–2027

• Vertically Oriented Anisotropic Nanoparticles in Polymer Matrices

  NSF · $580k · 2015–2020

Frequent coauthors

• Karen I. Winey

  University of Pennsylvania

  110 shared

• Kohji Ohno

  Metropolitan University

  73 shared

• Nigel Clarke

  University of Sheffield

  60 shared

• David M. Eckmann

  The Ohio State University

  51 shared

• Hyun‐Joong Chung

  University of Alberta

  38 shared

• Michael J. A. Hore

  Case Western Reserve University

  30 shared

• Matthew A. Caporizzo

  University of Vermont

  27 shared

• Jeffrey S. Meth

  Wilmington University

  25 shared

Labs

• Composto Research GroupPI

Education

• Ph.D., Materials Science and Engineering

  University of California, Berkeley

  1991

• B.S., Chemical Engineering

  University of California, Berkeley

  1986