About

John C. Crocker is an Associate Professor of Chemical & Biomolecular Engineering at the University of Pennsylvania's Perelman School of Medicine. His professional focus is on research within the Department of Chemical & Biomolecular Engineering. His contact information includes an email address: jcrocker@seas.upenn.edu. The webpage indicates his role as part of the faculty at the university, emphasizing his academic and research contributions in the field of chemical and biomolecular engineering.

Research topics

• Computer Science
• Materials science
• Physics
• Artificial Intelligence
• Thermodynamics
• Nanotechnology
• Political Science
• Chemistry
• Psychology
• Nursing
• Classical mechanics
• Medicine
• Applied psychology
• Physical chemistry
• Mechanics
• Statistical physics
• Engineering
• Psychiatry
• Mathematics
• Optics
• Medical education
• Crystallography
• Chemical physics

Selected publications

• Mechanosensitive Remodeling Sustains Rigidity Homeostasis in Actin Cortex Models

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-10-06 · 2 citations

  preprintOpen access

  The actin cortex is a dynamic biopolymer network whose mechanical rigidity, while relying critically on tensioned filaments, is robustly sustained amid constant architectural changes through the assembly and disassembly of filaments and crosslinkers. Yet the role of such remodeling processes in rigidity homeostasis remains essentially unexplored in computational models. As a result, we still lack proper understanding of the biological rationale for remodeling, which is energetically expensive, or of the microscopic mechanisms through which collective rigidity is maintained. To address this, we develop two complementary elastic network models in which rigidity homeostasis with complete turnover emerges as a result of mechanosensitive dynamics of filaments (edges) and crosslinkers (nodes), respectively. Both models require the following minimal ingredients: (1) preferential disassembly of edges or nodes under small tension or force, (2) a small but nonzero rate of random disassembly, and (3) energy injection upon assembly. Our models are robust to variations in random disassembly rates and can recover from drastic structural disruption. Remarkably, nodes and edges undergo diffusion even while elastic moduli and structural correlations reach steady states, showing that the models display representational drift similar to that found in neuronal activities and physical learning circuits. We propose that the cortex is an example of “tunable matter,” i.e ., its mechanosensitive remodeling dynamics tune its edges and nodes so that the cortex as a whole can maintain robust but flexible rigidity in fluctuating mechanical environments, creating survival advantages that justify its energy consumption.

  PublisherOA PDFDOI

• Slow relaxation and landscape-driven dynamics in viscous ripening foams

  Proceedings of the National Academy of Sciences · 2025-11-20

  articleOpen accessSenior authorCorresponding

  Foams and dense emulsions display complex mechanical behavior, including intermittent rearrangement dynamics, power-law rheology, and slow recovery after perturbation. These effects have long been considered evidence for glassy physics in these and other materials having similar mechanics, such as the cytoskeleton. Here, we study such anomalous mechanics in a simulated wet foam driven by ripening and find behavior that has a different physical origin than that in glasses. Rather, the dynamics is due to a balance of forces from the system's self-similar potential energy landscape and viscous stress. At the lowest viscosities, bubbles move intermittently, with the system shifting abruptly between shallow potential energy minima. For higher viscosities, in contrast, the bubbles move continuously and the system follows a tortuous, fractal path through high-dimensional configuration space, at higher mean energy than the lower viscosity case. The long-time dynamics and power-law rheology are the direct consequence of the potential energy landscape's self-similar geometry. Last, we find that the slow recovery of perturbed foams is due to the foam being kinetically rather than energetically trapped in high-energy portions of the energy landscape. Overall, viscous ripening foams follow a biased energy minimization pathway that explores regions of the energy landscape that are qualitatively different (flatter and smoother) than those corresponding to well-annealed glasses.

  PublisherDOI

• Building rigid networks with prestress and selective pruning

  Physical Review Research · 2024-10-22 · 5 citations

  articleOpen access

  Biopolymer networks from the intracellular to tissue scale display high rigidity and tensile stress while having coordinations well below the normal threshold for mechanical rigidity. The elastic filaments in these networks are often severed by enzymes in a tension-inhibited manner. The effects of such pruning on the mechanics of prestressed networks have not been studied. We show that networks pruned by a tension-inhibited method remain rigid at much lower coordinations than randomly pruned ones. These findings suggest a possible reason for the repeated evolution of tension-inhibited filament-severing proteins. Published by the American Physical Society 2024

  PublisherDOI

• Interpretation of CPTu data using machine learning techniques to develop the ground model of a dam

  2024-01-01 · 2 citations

  articleOpen access

  Building a ground model through manual processes can be time consuming, as large amounts of data need to be classified to define the extent and spatial distribution of the different soil materials. This paper delves into the application of machine learning (ML) methodologies, in conjunction with in-situ geotechnical testing data, to develop the ground model for a downstream dam founded on both weak and liquefiable soils. The dam covers a linear extent of approximately 800 m and was extensively characterized by means of in-situ tests, including 206 cone penetration tests (CPTu), 37 boreholes and 35 test pits. The performance of two unsupervised ML clustering algorithms are compared: Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and an extended version with a hierarchical component (HDBSCAN). The clustering uses CPTu data, which consists of the normalized cone tip resistance (Qtn) and the normalized sleeve friction (Fr) varying with elevation. Nearby borehole logs are used to evaluate the results of both clustering methods for a single single CPTu sounding using different clustering parameters. Then, a global clustering including several CPTu soundings is done and results are compared with the ground model that was manually made using Leapfrog software. Both methods show very good performance, with HDBSCAN being better and more robust.

  PublisherOA PDFDOI

• Linking local microstructure to fracture location in a two-dimensional amorphous solid under isotropic strain

  Soft Matter · 2024-01-01 · 1 citations

  articleOpen access

  . An analysis of the microstructural features that most contribute to increased Weakness values suggests that local density is more important than orientational order. Our methodology and results provide a basis for further research on microscopic processes during the fracturing process.

  PublisherOA PDFDOI

• Computational analysis of the effect of interaction heterogeneity on fluid–crystal coexistence in micron-scale colloidal systems

  The Journal of Chemical Physics · 2024-12-23

  article

  Micron-scale colloidal particles with short-ranged attractions, e.g., colloids functionalized with single-stranded DNA oligomers, have emerged as a powerful platform for studying colloidal self-assembly phenomena with the long-term goal of identifying routes for metamaterial fabrication. Although these systems have been investigated extensively both experimentally and computationally, the role of "real world" features that may impact self-assembly in unexpected ways has been largely ignored. One such example of an important, yet underappreciated, feature is interaction heterogeneity (IH), i.e., variations in interparticle interaction strengths, which can arise from variability in the DNA strand areal density on particle surfaces during fabrication. A previous study demonstrated that IH can modulate nucleation and gelation kinetics under non-equilibrium conditions. Here, we investigate in detail the dependence of bulk fluid-crystal coexistence on IH. Using a multicomponent coexistence tracing approach, we compute phase diagrams for both Gaussian and bidisperse IH distributions, revealing that IH shifts the fluid-side coexistence boundaries outward, promoting crystallization at lower particle volume fractions while also resulting in crystals that are enhanced in the stronger binding species. Our results demonstrate that IH significantly influences crystallization behavior even under equilibrium conditions and provide a new perspective on tuning IH as a controllable parameter for optimizing colloidal self-assembly.

  PublisherDOI

• Microstructural features governing fracture of a two-dimensional amorphous solid identified by machine learning

  arXiv (Cornell University) · 2024-04-24

  preprintOpen access

  Brittle fracturing of materials is common in natural and industrial processes over a variety of length scales. Knowledge of individual particle dynamics is vital to obtain deeper insight into the atomistic processes governing crack propagation in such materials, yet it is challenging to obtain these details in experiments. We propose an experimental approach where isotropic dilational strain is applied to a densely packed monolayer of attractive colloidal microspheres, resulting in fracture. Using brightfield microscopy and particle tracking, we examine the microstructural evolution of the monolayer during fracturing. Furthermore, using a quantified representation of the microstructure in combination with a machine learning algorithm, we calculate the likelihood of regions of the monolayer to be on a crack line, which we term Weakness. From this analysis, we identify the most important contributions to crack propagation and find that local density is more important than orientational order. Our methodology and results provide a basis for further research on microscopic processes during the fracturing process.

  PublisherOA PDFDOI

• Lévy-distributed fluctuations in the living cell cortex

  Physical Review Research · 2024-12-12 · 4 citations

  articleOpen access

  The actomyosin cortex is an active material that provides animal cells with a strong but flexible exterior whose mechanics, including non-Gaussian fluctuations and occasional large displacements or cytoquakes, have defied explanation. We study the active fluctuations of the cortex using nanoscale tracking of arrays of flexible microposts adhered to multiple cultured cell types. When the confounding effects of static heterogeneity and tracking error are removed, the fluctuations are found to be heavy tailed and well described by a truncated Lévy <a:math xmlns:a="http://www.w3.org/1998/Math/MathML"><a:mi>α</a:mi></a:math>-stable distribution over a wide range of timescales, in multiple cell types. The largest random displacements closely resemble the earlier-reported cytoquakes, but notably, we find these cytoquakes are not due to earthquakelike cooperative rearrangement of many cytoskeletal elements. Rather, they are indistinguishable from chance large excursions of a superdiffusive random process driven by heavy-tailed noise. The noncooperative microscopic events driving these fluctuations need not be larger than the expected elastic energy of single tensed cortical actin filaments, and the implied distribution of microscopic event energies will need to be accounted for by future models of the cytoskeleton. Published by the American Physical Society 2024

  PublisherDOI

• Lévy distributed fluctuations in the living cell cortex

  arXiv (Cornell University) · 2023-09-12

  preprintOpen access

  The actomyosin cortex is an active material that provides animal cells with a strong but flexible exterior, whose mechanics, including non-Gaussian fluctuations and occasional large displacements or cytoquakes, have defied explanation. We study the active fluctuations of the cortex using nanoscale tracking of arrays of flexible microposts adhered to multiple cultured cell types. When the confounding effects of static heterogeneity and tracking error are removed, the fluctuations are found to be heavy-tailed and well-described by a truncated Lévy alpha-stable distribution over a wide range of timescales, in multiple cell types. The largest random displacements closely resemble the earlier-reported cytoquakes, but notably, we find these cytoquakes are not due to earthquake-like cooperative rearrangement of many cytoskeletal elements. Rather, they are indistinguishable from chance large excursions of a super-diffusive random process driven by heavy-tailed noise. The non-cooperative microscopic events driving these fluctuations need not be larger than the expected elastic energy of single tensed cortical actin filaments, and the implied distribution of microscopic event energies will need to be accounted for by future models of the cytoskeleton.

  PublisherOA PDFDOI

• Slow Relaxation and Landscape-Driven Dynamics in Viscous Ripening Foams

  arXiv (Cornell University) · 2023-01-31

  preprintOpen accessSenior author

  Foams and dense emulsions display complex mechanical behavior, including intermittent rearrangement dynamics, power-law rheology, and slow recovery after perturbation. These effects have long been considered evidence for glassy physics in these and other materials having similar mechanics, such as the cytoskeleton. Here we study such anomalous mechanics in a simulated wet foam driven by ripening and find behavior that has a different physical origin than that in glasses. Rather, the dynamics is due to a balance of forces from the system's self-similar potential energy landscape and viscous stress. At the lowest viscosities, bubbles move intermittently, with the system shifting abruptly between shallow potential energy minima. For higher viscosities, in contrast, the bubbles move continuously and the system follows a tortuous, fractal path through high-dimensional configuration space, at higher mean energy than the lower viscosity case. The long-time dynamics and power-law rheology are the direct consequence of the potential energy landscape's self-similar geometry. Lastly, we find that the slow recovery of perturbed foams is due to the foam being kinetically rather than energetically trapped in high-energy portions of the energy landscape. Overall, viscous ripening foams follow a biased energy minimization pathway that explores regions of the energy landscape that are qualitatively different (flatter and smoother) than those corresponding to well-annealed glasses.

  PublisherOA PDFDOI

Recent grants

• Engineering phases and kinetics for processing DNA-linked particle materials

  NSF · $330k · 2011–2014

• Realizing non-close-packed colloidal crystals using directional-bonding superparticles

  NSF · $350k · 2014–2018

• Collaborative Research: Understanding the Fractal Physics of the Cell Cortex

  NSF · $255k · 2020–2024

Frequent coauthors

• Talid Sinno

  47 shared

• N. J. Curro

  University of California, Davis

  35 shared

• A. P. Dioguardi

  Los Alamos National Laboratory

  34 shared

• Abigail Shockley

  University of California, Davis

  28 shared

• Kent Shirer

  Max Planck Institute for Chemical Physics of Solids

  24 shared

• Ian Jenkins

  21 shared

• Arjun G. Yodh

  University of Pennsylvania

  21 shared

• C. H. Lin

  20 shared