Why Shear History During Mixing Changes Conductivity at the Same Loading in graphene nanoplatelet systems

Introduction

Graphene nanoplatelet conductivity changes with mixing shear history because shear alters dispersion state, platelet lateral size/aspect ratio (via breakage), and local platelet orientation, and those three factors together control the electrical percolation network. Under the same bulk loading, improved dispersion and preserved high aspect ratio increase inter-platelet contact area and lower contact resistance, while agglomeration, excessive fragmentation, or unfavorable orientation increase inter-platelet gaps and raise composite resistivity. Mechanistically, shear energy concentrates at platelet contacts causing (1) breakage that reduces lateral size, (2) deagglomeration or reorientation that changes connectivity, and (3) changes in contact resistance via altered tunneling distances. Boundary: this explanation assumes the same polymer matrix, no chemical modification during mixing, and equivalent thermal history; in-situ chemistry or cure reactions add additional mechanisms. The literature reports correlations between morphology (layer count, lateral size, SSA) and electrical properties in graphene-filled composites. As a result, mixing protocol (intensity, duration, sequence) is a process variable that can change network topology and therefore macroscopic conductivity.

Read more on the material page: https://www.greatkela.com/en/product/Carbon_Allotropes/242.html

Common Failure Modes

Primary Failure Modes

• Failure observed: High resistivity despite target loading. Mechanism mismatch: persistent agglomerates leave large insulating gaps between conductive domains because van der Waals restacking is not overcome by the applied shear; the local network remains sub-percolation even though bulk wt% meets nominal threshold. See also: Why particulate conductive fillers (e.g., carbon black) rapidly increase viscosity in conductive coatings in graphene nanoplatelet systems.
• Failure observed: Conductivity drops after high-shear processing. Mechanism mismatch: excessive shear energy fragments platelets, reducing lateral size and aspect ratio, which lowers contact area and tunneling probability and therefore reduces connectivity. See also: Why Carbon Black Eliminates Transparency or Clean Color in Anti-Static Coatings in graphene nanoplatelet systems.
• Failure observed: Strong anisotropy or inconsistent conductivity directionally. Mechanism mismatch: shear aligns platelets preferentially (parallel to flow) so in-plane connectivity improves while through-thickness connections weaken, making measured bulk conductivity sensitive to probe geometry and sampling direction.

Secondary Failure Modes

• Failure observed: Time-dependent increases in resistivity after mixing (aging). Mechanism mismatch: kinetically trapped dispersions relax and re-stack over hours to days because van der Waals attraction drives restacking unless particle mobility is arrested by matrix viscosity or surface modification.
• Failure observed: Processing-to-processing variability at same machine settings. Mechanism mismatch: small differences in sequence (dry-blend then melt vs. masterbatch dilution), local temperature transients, or residence time shift the balance between deagglomeration and fragmentation, producing different network topologies at identical nominal shear rates.

Conditions That Change the Outcome

Primary Drivers

• Variable: Shear intensity and duration. Why it matters: higher cumulative shear energy both breaks agglomerates (improving dispersion) and can fragment platelets (reducing aspect ratio); the net effect on conductivity is the result of competing deagglomeration vs. fragmentation because percolation depends strongly on lateral size and contact area. (Boundary: effect depends on matrix viscosity and temperature which set stress on platelets.)
• Variable: Mixing sequence (order of addition, pre-wetting, masterbatching). Why it matters: pre-wetting or creating a concentrated masterbatch can distribute shear energy across different steps so that deagglomeration is prioritized over fragmentation; sequence changes local concentration and hence probability of restacking because aggregation kinetics are concentration-dependent.
• Variable: Polymer matrix viscosity and temperature. Why it matters: a higher-viscosity melt transmits higher shear forces to platelets for the same rotor speed, increasing fragmentation risk; elevated temperature lowers viscosity and may favor platelet sliding and reorientation rather than breakage, therefore changing network connectivity.

Secondary Drivers

• Variable: Platelet grade (lateral size, layer count, defect density, SSA). Why it matters: larger lateral size and higher aspect ratio increase the chance of forming extended conductive paths; defected or smaller platelets require higher contact density to percolate because contact resistance and tunneling distances become limiting. (Evidence: SSA and layer count correlate with electrochemical and conductive behavior .)
• Variable: Presence of surfactants, compatibilizers, or functional groups. Why it matters: surface chemistry changes inter-particle attraction and matrix wetting so shear can either more effectively disperse sheets (if compatibilized) or cause re-aggregation (if incompatible), therefore altering long-term network stability.

How This Differs From Other Approaches

• Mechanical fragmentation vs. deagglomeration: one mechanism reduces lateral size and contact area (fragmentation) while the other breaks inter-sheet van der Waals bonds to create more, smaller domains that can connect; both act under shear but have opposite effects on network topology.
• Orientation-driven anisotropic connectivity vs. isotropic random network formation: shear can align platelets producing directionally biased percolation pathways, whereas low-shear or tumble mixing tends to preserve random orientations that produce more isotropic but possibly higher percolation thresholds.
• Kinetic stabilization by matrix vitrification vs. kinetic relaxation and restacking: rapid matrix solidification (or high viscosity) freezes a shear-created topology in place because particle mobility is arrested, whereas low-viscosity or solvent systems allow thermodynamically favored restacking after mixing.
• Surface-chemistry-controlled steric/electrostatic stabilization vs. purely mechanical dispersion: chemical compatibilizers change interparticle potential energy landscapes so that the same shear leads to different final microstructures because the post-shear thermodynamic sink (restacked state) can be energetically inaccessible.

Scope and Limitations

• Applies to: polymer composites and coatings processed via melt mixing, solvent blending, extrusion, or high-shear mixing where Graphene nanoplatelets (GNPs) are introduced to create conductive networks in ESD and anti-static plastics; explanation assumes identical nominal bulk loading and unchanged chemical composition of GNPs during processing.
• Does not apply to: systems where graphene is chemically converted in situ during mixing (e.g., in‑situ reduction of graphene oxide to conductive graphene under reactive conditions), electroless plating that deposits metal on GNPs, or architectures where a continuous metal filler network provides primary conduction because those add new mechanisms beyond physical percolation.
• When results may not transfer: to thermosetting cure systems where curing chemistry changes during shear (chemical grafting to platelets), to composites with ionic conductive fillers where ionic conduction dominates, or to situations with extreme thermal oxidation or chemical degradation during mixing because oxidation changes intrinsic platelet conductivity. Therefore, transfer fails when chemical state or intrinsic conductivity of platelets is changed.
• Physical/chemical pathway (separated): Absorption (how shear energy couples): shear provides mechanical work that concentrates at contacts and edges because stress transmits through the viscous matrix to platelets; Energy conversion (what happens to that work): part of the mechanical work breaks van der Waals junctions (deagglomeration), part creates fracture energy that severs platelets (fragmentation), and part reorients platelets along streamlines; Material response (why conductivity changes): because electrical percolation relies on geometric connectivity and low contact resistance, any process that reduces lateral size, increases inter-particle gaps, or reduces contact area increases bulk resistivity, whereas processes that improve contact density and lower tunneling distances decrease resistivity. As a result, identical wt% loading can produce a large spread in conductivity depending on shear history and post-mix relaxation.

Related Links

Application page: Conductive & Anti-Static Coatings

Failure Modes

• Why particulate conductive fillers (e.g., carbon black) rapidly increase viscosity in conductive coatings in graphene nanoplatelet systems
• Why Carbon Black Eliminates Transparency or Clean Color in Anti-Static Coatings in graphene nanoplatelet systems
• Why graphitic particulate fillers sediment and cause conductivity drift in coatings in graphene nanoplatelet systems

Mechanism

• Mechanisms for surface-dominant conductive pathways in thin films in graphene nanoplatelet systems

Key Takeaways

• Graphene nanoplatelet conductivity changes with mixing shear history.
• Failure observed: High resistivity despite target loading.
• Variable: Shear intensity and duration.

Engineer Questions

Q: At the same 3 wt% GNP loading, why does a primer mixed on a three-roll mill show lower bulk resistivity than the same mix made by a high-shear rotor?

A: Because three-roll milling applies compressive and extensional stresses that can delaminate agglomerates and align platelets with less net fragmentation, improving lateral connectivity, whereas high-shear rotor mixing can generate higher local shear rates that fragment platelets and reduce aspect ratio; the resulting network topology from roll shear favors continuous contacts and lower contact resistance.

Q: How can I test whether my mixing step caused platelet fragmentation vs. improved dispersion?

A: Compare lateral size distributions (optical/SEM/AFM) and BET/SSA before and after mixing to detect size reduction or increased surface area, and map local conductivity (four-point probe or impedance mapping) correlated with microscopy; Raman D/G changes can indicate defect/edge introduction consistent with fragmentation.

Q: What processing levers reduce the chance of fragmentation while still dispersing agglomerates?

A: Use staged dilution (masterbatch then low-shear dilution), reduce instantaneous shear rate, increase processing temperature to lower melt viscosity (reducing stress on platelets), or add compatibilizers to lower inter-sheet attraction so less mechanical energy is required for deagglomeration.

Q: Why does conductivity measured in-plane differ from through-thickness after the same mixing process?

A: Shear commonly aligns platelets parallel to flow, increasing in-plane contacts and lowering in-plane resistivity while reducing vertical contacts; percolation becomes anisotropic as orientation-dependent contact probabilities change.

Q: If I observe conductivity loss over days after mixing, what is the likely cause and mitigation?

A: Likely thermodynamically driven restacking as kinetically trapped dispersion relaxes; mitigate by increasing matrix viscosity before relaxation (faster cure/cooling), using surface functionalization or compatibilizers to stabilize separated platelets, or removing solvent that enables platelet mobility.

Q: Is there a simple process metric that correlates with final conductivity?

A: Cumulative specific work (integral of shear power per mass) is a practical metric because it captures intensity and duration, but its predictive use requires knowledge of matrix viscosity and platelet grade since identical specific work can produce different deagglomeration/fragmentation outcomes.