Pith. sign in

REVIEW 4 major objections 5 minor 64 references

Domain Structure and Interface Control of Mechanical Stiffness in Sustainable Cellulose Bio-nanocomposites

T0 review · 4 major / 5 minor · reviewed 2026-08-11 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗ Review JSON

Pith's one-line read This paper shows that the extra stiffness from polyDOPA-coated cellulose nanocrystals in soy-protein films comes from two mechanisms—improved dispersion and stronger interfacial bonding—and gives concrete targets (matrix above 100 MPa…

desk verdict Good application of a standard agglomeration model to a new material, but the fitted parameters violate the model's own packing constraint and the interphase mechanism rests on unmeasured hand-set parameters; the design maps and mechanistic conclusions need rework before they can be trusted. read the letter →

arxiv 2412.13210 v1 pith:BAKL7TIR submitted 2024-12-09 physics.bio-ph cond-mat.mtrl-sci

Hanxun Jin , William Goldberg , Zhenqin Wang , Huiyong Li , Yuxuan Huang , Marcus Foston , Guy M. Genin This is my paper · ORCID
classification physics.bio-phcond-mat.mtrl-sci
keywords CelluloseNanocrystalNanocompositesMicromechanicsSoyProteinIsolatePolyDOPAcoatingDomainAgglomerationNanoscaleSurfaceModificationMori-TanakahomogenizationHashin-Shtrikmanbounds
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper asks why CNC-reinforced SPI-glycerol films remain far below the theoretical stiffness of a well-dispersed, high-aspect-ratio fiber composite, and traces the deficit to two microstructural causes: CNC agglomeration and imperfect interfaces. It argues—on the basis of a two-step Mori-Tanaka model fitted to tensile and TEM data—that polyDOPA surface coating stiffens the composite by acting on both causes at once: better dispersion and stronger interfacial interactions. A sympathetic reader would care because the same model turns these mechanisms into quantitative design targets: matrix stiffness above 100 MPa and CNC stiffness above 100 GPa could produce order-of-magnitude improvements, potentially making biodegradable soy-based films competitive with petroleum-based film plastics.

What carries the argument

The central object is a two-step Mori-Tanaka homogenization of a representative volume element in which CNCs are partitioned into agglomerated bundles and dispersed fibers, using two dimensionless parameters: $\xi$, the volume fraction occupied by agglomerates, and $\zeta$, the fraction of CNC material inside them. A second step adds a homogeneous isotropic interphase around the agglomerates, parameterized by its volume ratio $\rho_{\mathrm{inter}}$ and a strengthening factor $q_s$ that scales the interphase stiffness as $K_{\mathrm{inter}} = q_s V_c \zeta K_m$ and $G_{\mathrm{inter}} = q_s V_c \zeta G_m$. This machinery explains the gap between experimental data and the Hashin–Shtrikman upper/lower bounds, and separates the dispersion lever from the interface lever for design.

What would settle it

Measure the elastic modulus profile across the CNC/SPI interphase with AFM nanoindentation or equivalent nanoscale testing and compare the measured interphase modulus with the prediction $K_{\mathrm{inter}} = q_s V_c \zeta K_m$ at the fitted $q_s \approx 2000$; a large disagreement would remove the support for the interfacial lever. Alternatively, quantify the fraction of CNCs in agglomerates at 5 and 10 wt% by TEM to test whether the fitted values $\zeta = 0.98$ and $\zeta = 0.88$ correspond to real dispersion states or are compensating for other unmodeled effects.

Watch

Extended reading notes

Core claim

The paper's central claim is that the experimentally observed stiffening of SPI–glycerol films by polyDOPA-modified CNCs is produced by two coexisting mechanisms: improved dispersion and stronger interfacial interactions. In the model this is captured by the agglomeration fraction $\zeta$ (the share of CNCs sitting in bundles) falling from 0.98 for unmodified CNCs to 0.88 after coating, combined with an interphase of volume ratio $\rho_{\mathrm{inter}} = 0.8$ and a strengthening factor $q_s = 2000$ enhancing the surrounding matrix modulus. The same framework explains why data sit near the Hashin–Shtrikman lower bound despite a nominal modulus contrast exceeding 10,000:1: agglomeration, not weak CNCs, is the dominant stiffening bottleneck. With agglomeration and interfaces controlled, the paper argues, composite stiffness can approach the upper bound, and matrix stiffness above 100 MPa together with CNC stiffness above 100 GPa would yield order-of-magnitude improvements.

Load-bearing premise

The claim that interfacial bonding is a controllable stiffness lever rests entirely on an assumed scaling law, $K_{\mathrm{inter}} = q_s V_c \zeta K_m$, in which the strengthening factor $q_s$ is chosen to fit the data rather than measured independently.

Editorial extensions

If this is right

  • If polyDOPA stiffens through both dispersion and interface, then processing that improves dispersion without introducing defects—such as high-pressure homogenization—should push stiffness closer to the Hashin–Shtrikman upper bound.
  • Raising matrix stiffness past 100 MPa, via crosslinking or reduced plasticizer, together with CNC modulus above 100 GPa is predicted to give order-of-magnitude composite stiffening.
  • The fitted model implies that a modest change in agglomeration ($\zeta$ from 0.98 to 0.88) can account for the observed more-than-1.5-fold stiffness increase, so dispersion quality is a primary design lever.
  • Interphase volume and quality ($\rho_{\mathrm{inter}}$ and $q_s$) act synergistically with dispersion; optimizing one without the other yields limited gains.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • Beyond the paper, the same dispersion-plus-interphase decomposition could be tested on other surface-modified bio-nanofiller systems, such as chitin or lignin nanoparticles, to see whether the fitted parameter values transfer.
  • Beyond the paper, because the fitted $\zeta = 0.98$ for unmodified CNCs exceeds the TEM-measured $0.909 \pm 0.033$, some of the dispersion lever likely absorbs sonication-induced defects and matrix heterogeneity; independent measurement of $\zeta$ at each loading would separate real dispersion from this compensation.
  • Beyond the paper, a direct route to validate the interfacial lever is to measure the interphase modulus by AFM nanoindentation or molecular simulation, converting $q_s$ from a fitted parameter into a measurable material property.
  • Beyond the paper, if the 100 MPa and 100 GPa targets are met, SPI-based films could plausibly approach stiffness parity with commodity film plastics, which is the paper's motivating application but not a demonstrated outcome.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 5 minor

Summary. The manuscript proposes a two-step Mori-Tanaka homogenization model for CNC-reinforced SPI-glycerol composites, with separate treatments of CNC agglomeration and an interphase region, to interpret experimental stiffness data and to identify design pathways. The authors fit agglomeration parameters to published stiffness data, introduce an interphase stiffening factor and interphase volume ratio, and use the resulting model to claim that polyDOPA surface modification improves stiffness through both better dispersion and stronger interfacial interactions. The paper also derives quantitative design targets for matrix and CNC stiffness and for dispersion/interface optimization.

Significance. If the model and its conclusions were supported, the paper would provide a useful mechanistic framework and quantitative design guidance for sustainable bio-nanocomposites. The comparison against Hashin-Shtrikman bounds, the explicit treatment of agglomeration, and the open listing of limitations in Section 3.5 are strengths. However, the central mechanistic claims are not currently established: the interphase law is introduced without derivation or validation, the main design maps use a geometrically inadmissible parameter region, and the dispersion conclusion is based on a fitted parameter that is not independently confirmed. These issues affect the paper's main conclusions.

major comments (4)
  1. [Section 2.3, Eqs. (20)-(21)] The interphase scaling K_inter = q_s Vc ζ K_m and G_inter = q_s Vc ζ G_m is introduced without derivation or independent measurement. The text states that interphase stiffening is proportional to the volume fraction of CNCs within the agglomerated phase, but that local quantity is W_aggl_c/W_aggl = Vc ζ / ξ, not Vc ζ; omitting the 1/ξ factor makes the interphase modulus insensitive to how tightly CNCs are packed inside the agglomerate. Combined with hand-set values q_s = 2000 and ρ_inter = 0.8, the sweeps in Figure 6 and the design guidance in Figures 7 and Section 3.4 demonstrate sensitivity to free parameters rather than establish an interface-control mechanism. The authors must either derive and validate this scaling, calibrate q_s and ρ_inter independently, or explicitly reframe the interphase results as a hypothetical scenario.
  2. [Section 2.2 and Section 3.4, Eq. (11)] The definitions in Eq. (11) imply the geometric admissibility condition ζ Vc ≤ ξ, because the volume of agglomerated CNCs cannot exceed the volume of the agglomerated phase. This condition is violated by the fitted parameter sets used in Figure 7 at Vc = 0.1: for unmodified CNCs ζ Vc = 0.098 > ξ = 0.081, and for polyDOPA-CNCs ζ Vc = 0.088 > ξ = 0.068. Consequently the matrix volume fraction inside the agglomerated phase, ξ − Vcζ, is negative in Eqs. (12)-(13), and portions of Figures 5-7 are computed in an unphysical regime. The analysis must be redone with parameters that satisfy ζ Vc ≤ ξ, for example by re-fitting ζ subject to this constraint, and all affected results and conclusions must be updated.
  3. [Section 3.2] The conclusion that polyDOPA improves dispersion is based on fitting ζ to the experimental stiffness data. The fitted value ζ = 0.98 for unmodified CNCs exceeds the experimentally reported ζ_exp = 0.909 ± 0.033 at 10 wt% CNCs, and the paper attributes the discrepancy to unspecified CNC degradation or matrix inhomogeneity. The lower fitted ζ for polyDOPA-CNCs is therefore not an independent confirmation of improved dispersion; it may instead be absorbing deficiencies of the model. The claim about improved dispersion needs independent microstructural validation, such as TEM-based dispersion statistics at the same loadings used in the fit.
  4. [Section 3.4 and Conclusions] The load-bearing conclusions that surface modification works through two mechanisms and that matrix stiffness above 100 MPa and CNC stiffness above 100 GPa are quantitative targets rest on the unvalidated interphase model and the inadmissible parameter region described above. As written, these conclusions are not supported by the evidence in the manuscript. The authors should provide independent calibration of the interphase parameters or clearly reduce Sections 3.3-3.5 to a hypothetical sensitivity analysis, with the design targets presented as model hypotheses rather than validated recommendations.
minor comments (5)
  1. [Abstract] The abstract contains a typo: 'Consistent wih' should be 'Consistent with'.
  2. [Section 2.1] The text 'was writen' should be 'was written'.
  3. [Section 2.1] The notation Vpoly is confusing: it is defined as the volume fraction of the polyDOPA coating in the coated CNC, but the symbol could be misread as a property of the polymer. Please clarify the definition and the basis for the value 0.8.
  4. [Section 3.5] The limitations paragraph does not explicitly state that Eqs. (20)-(21) are an unvalidated assumption and that q_s and ρ_inter have no independent measurement. Adding this caveat would make the limitations section more complete.
  5. [References] The experimental data used for model fitting are from reference [30], which is listed as 'In Submission'. Please provide a published version or a publicly available dataset to allow readers to reproduce the calibration.

Circularity Check

2 steps flagged · score 6.0 of 10

Central stiffening mechanisms are model inputs: ζ is chosen to fit the stiffness data and q_s/ρ_inter are hand-set, so the dispersion and interface conclusions restate the model's assumptions.

  1. fitted input called prediction [Section 3.2, 'Effects of CNC Agglomeration'; Fig. 5 caption]
    "We then asked what values of ζ would be required to fit experimental data for the two CNC types. ζ = 0.98 was required for unmodified CNCs, while ζ = 0.88 was required for modified CNCs. This difference aligned with the expected effect of surface modification, with improved CNC-matrix affinity leading to better dispersion."

    The agglomeration parameter ζ is the model's direct measure of dispersion (Eq. 11). The paper selects ζ to reproduce the measured stiffness curves and then presents the resulting lower ζ for polyDOPA-CNCs as evidence that polyDOPA improves dispersion and thereby increases stiffness. That agreement is imposed by the fit rather than independently predicted. The Fig. 5 caption reinforces the same inversion by stating that the lower fitted ζ value 'indicates improved dispersion, demonstrating the beneficial effect of polyDOPA surface treatment.' Thus the 'improved dispersion' mechanism is a restatement of the fitting procedure, not a validated prediction.

  2. self definitional [Section 2.3, Eqs. (20)-(21); Section 3.3 'Role of Interphase Properties']
    "The moduli of the matrix within the interphase increases with the degree of aggregation [54, 53, 55], which was taken as proportional to the volume fraction of CNCs within the agglomerated phase ( W_aggl_c / W or Vcζ). To model this, we introduced a strengthening factor q_s, representing the stiffening of the interphase due to strong CNC aggregation, so that the bulk modulus K_inter and shear modulus G_inter were written: K_inter = q_s Vc ζ K_m, (20) G_inter = q_s Vc ζ G_m. (21). ..."

    Equations (20)-(21) define the interphase moduli as proportional to q_s, and Eqs. (18)-(19) make ρ_inter the interphase volume fraction. Consequently, the observation that larger q_s or ρ_inter increases composite stiffness is a mathematical identity of the model inputs, not an empirical finding. The strengthening factor q_s is a free, unmeasured parameter (the sweeps set q_s = 2000 in Fig. 6) and ρ_inter = 0.8 is also hand-chosen. The paper then uses this sensitivity sweep to conclude that polyDOPA stiffens the composite 'through ... stronger interfacial interactions,' and the Conclusions repeat this as a demonstrated mechanism. The interfacial-stiffening result is therefore the ansatz itself, restated as a conclusion.

full rationale

The paper is not entirely circular: the Mori-Tanaka homogenization framework, the comparison to Hashin-Shtrikman bounds, and the design-map extrapolations for matrix and CNC stiffness are self-contained calculations using standard external inputs, and the quantitative targets (e.g., matrix stiffness above 100 MPa, CNC stiffness above 100 GPa) are genuine model extrapolations rather than fitted outputs. However, the two mechanisms that form the central claim—improved dispersion and stronger interfacial interactions—are not independently derived. The dispersion mechanism is inferred by fitting ζ to the very stiffness data it is then said to explain, and the interfacial mechanism is built into the model by defining K_inter and G_inter as proportional to the hand-set parameter q_s, with ρ_inter also hand-chosen. Moreover, the fitted parameter region is geometrically inadmissible: Eqs. (11) require W_aggl_c ≤ W_aggl, i.e. ζ Vc ≤ ξ, yet the paper's own values (Vc = 0.1, ξ = 0.081, ζ = 0.98) give Vc ζ = 0.098 > 0.081, which makes the matrix volume fraction inside the agglomerated phase negative in Eqs. (12)-(17). This invalidates the physical interpretation of the fitted dispersion improvement. Because the central mechanistic conclusion reduces to model inputs, the circularity score is 6.

Assumptions & free parameters 5 free parameters · 5 assumptions · 0 invented entities

The central quantitative claims rest on two fitted parameters (ζ for each composite type), two hand-chosen interphase parameters (q_s, ρ_inter), and an estimated coating volume fraction, plus several domain assumptions that the paper itself flags as simplifications.

free parameters (5)
  • Agglomeration fraction ζ (unmodified CNCs) = 0.98
    Fitted to match experimental Young's modulus data for SPI/CNC composites in Fig. 5; exceeds the experimentally measured value of 0.909±0.033 at 10 wt%.
  • Agglomeration fraction ζ (polyDOPA-CNCs) = 0.88
    Fitted to match experimental data for SPI/polyDOPA-CNC composites in Fig. 5; lower value interpreted as improved dispersion.
  • Interphase strengthening factor q_s = 2000 (used in Figs. 6 and 7)
    Chosen by hand to show that interphase stiffening can raise predicted stiffness; no independent measurement.
  • Interphase volume ratio ρ_inter = 0.8 (used in Fig. 6b and 7b)
    Chosen by hand for the interphase parameter sweeps; not fitted or measured here.
  • Volume fraction of polyDOPA coating V_poly = 0.8
    Estimated from TEM images in companion paper [30]; affects the effective modulus of polyDOPA-coated CNCs via the Voigt model.
assumptions (5)
  • domain assumption Mori-Tanaka mean-field homogenization is valid for sub-percolation CNC volume fractions and randomly oriented inclusions.
    Invoked in Section 2.1, citing references [38-40]; the representative volume element approach treats the matrix strain as the far-field strain.
  • domain assumption The SPI-glycerol matrix is homogeneous, isotropic, linear elastic, with Em=14.7 MPa and νm=0.45.
    Section 2.1, based on [30]; the paper acknowledges in Section 3.5 that matrix heterogeneity is neglected.
  • domain assumption CNC agglomerates can be represented as randomly oriented ellipsoidal inclusions with aspect ratio approximately 2, and the two-step Shi et al. homogenization applies.
    Section 2.2 and Eqs. (11)-(17), following [49].
  • ad hoc to paper The interphase is homogeneous and isotropic, and its moduli scale linearly with the CNC volume fraction inside the agglomerate via K_inter = q_s Vc ζ K_m.
    Section 2.3, Eqs. (20)-(21); this scaling is introduced without independent experimental support and is used to generate the main design conclusions.
  • domain assumption The experimental Young's modulus measurements in the companion paper [30] are accurate and representative.
    All fitting and comparisons rely on these data; [30] is in submission and not publicly available.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Domain Structure and Interface Control of Mechanical Stiffness in Sustainable Cellulose Bio-nanocomposites." pith.science (2026). https://pith.science/paper/BAKL7TIR

@misc{pith2026241213210,
  author       = {Pith},
  title        = {Pith review of: Domain Structure and Interface Control of Mechanical Stiffness in Sustainable Cellulose Bio-nanocomposites},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/BAKL7TIR}},
  note         = {Machine review of arXiv:2412.13210}
}
read the original abstract

Renewable and biodegradable plastics derived from soy protein isolate (SPI) offer a promising alternative to conventional petroleum-based plastics, particularly for film-grade bioplastics applications such as plastic bags. However, even with reinforcement from cellulose nanocrystals (CNCs), their mechanical properties including stiffness lag behind those of petroleum-based plastics. To identify pathways for improving CNC-reinforced SPI composites, we studied stiffening mechanisms by interpreting experimental data using homogenization models that accounted for CNC agglomeration and the formation of CNC/SPI interphases. To model effects of surface modification of CNCs with polydopamine (polyDOPA), we incorporated two key mechanisms: enhanced CNC dispersion and modified CNC-SPI interfacial interactions. Models accounted for interphases surrounding CNCs, arising from physicochemical interactions with the polyDOPA-modified CNC surfaces. Consistent wih experimental observations of polyDOPA modification enhancing mechanical properties through both increased spatial distribution of CNCs and matrix-filler interactions, results demonstrated that improved dispersion and interfacial bonding contribute to increased composite stiffness. Results highlight the potential of biodegradable CNC/SPI bio-nanocomposites as sustainable plastic alternatives, and suggest pathways for further enhancing their mechanical properties.

Figures

Figures reproduced from arXiv: 2412.13210 by the authors.

Figure 1
Figure 1. Mechanical characterization of cellulose nanocrystal (CNC) reinforced soy protein isolate (SPI)-glycerol composites. (a) Chemical structure and transmission electron microscope (TEM) images showing how CNCs change with surface modification: (i) unmodified CNC regions appear as long, needle-like structures, while (ii) after coating with polydopamine (polyDOPA), CNC regions appear shorter and thicker. Dotted lines rep… view at source ↗
Figure 2
Figure 2. Schematic of an idealized model for CNC reinforcement in a SPI-glycerol matrix. The model for the idealized case assumes perfectly dispersed CNCs (unmodified or polyDOPA-modified) within a continuous matrix phase. This idealized case serves as a theoreti￾cal baseline for understanding the effects of CNC surface modification and evaluating the impact of agglomeration and interface quality on composite mechanics. Poly… view at source ↗
Figure 3
Figure 3. Two-step micromechanical modeling approach for CNC-reinforced SPI￾glycerol composites with agglomeration. (a) Schematic of composite microstructure, show￾ing CNCs partitioned into two states: agglomerated bundles and individually dispersed CNCs within the SPI/glycerol matrix. The interphase region between CNCs and matrix is highlighted, representing the zone of modified matrix properties due to CNC-matrix interactio… view at source ↗
Figures from the paper (4 more)
Figure 4
Figure 4. Figure 4: Comparison between experimental measurements and theoretical predic￾tions for the elastic modulus of CNC-reinforced SPI-glycerol composites. Results shown for (a) unmodified CNCs and (b) polyDOPA-modified CNCs. The Hashin-Shtrikman (H-S) bounds represent theoretical up…
Figure 5
Figure 5. Figure 5: Effect of CNC agglomeration on composite stiffness for (a) unmodified CNCs and (b) polyDOPA-modified CNCs. Curves represent Mori-Tanaka (M-T) pre￾dictions for different values of the agglomeration parameter ζ, which represents the fraction of CNCs in agglomerated versu…
Figure 6
Figure 6. Figure 6: Mori-Tanaka micromechanical modeling predictions incorporating both agglomeration and interphase effects. (a) Impact of interphase volume ratio (ρinter) on composite stiffness for (ai) unmodified CNCs and (aii) modified polyDOPA-CNCs, with fixed strengthening factor qs…
Figure 7
Figure 7. Figure 7: Design maps for optimizing CNC-reinforced SPI nanocomposites. (a) Col￾ormaps showing the ratio of actual to theoretical maximum stiffness (E aggl M-T/EUpper H-S ) as a function of matrix modulus (Em) and CNC modulus (ECNC) for (ai) unmodified CNCs and (aii) modified CN…

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

64 extracted references · 64 canonical work pages

  1. [1]

    Gowthaman, H

    N. Gowthaman, H. Lim, T. Sreeraj, A. Amalraj, S. Gopi, Advantages of biopolymers over synthetic polymers: social, economic, and environmental aspects, Elsevier, 2021, pp. 351–372

    work page 2021

  2. [2]

    H. Jin, T. Jiao, R. J. Clifton, K.-S. Kim, Dynamic fracture of a bicontinuously nanostructured copolymer: A deep-learning analysis of big-data-generating experi- ment, Journal of the Mechanics and Physics of Solids 164 (2022) 104898

    work page 2022

  3. [3]

    T. H. Epps, L. T. Korley, T. Yan, K. L. Beers, T. M. Burt, Sustainability of synthetic plastics: Considerations in materials life-cycle management, JACS Au 2 (2021) 3–11

    work page 2021

  4. [4]

    H. Jin, A. K. Landauer, K.-S. Kim, Ruga mechanics of soft-orifice closure under external pressure, Proceedings of the Royal Society A 477 (2021) 20210238

    work page 2021

  5. [5]

    X. Zhao, Y. Wang, X. Chen, X. Yu, W. Li, S. Zhang, X. Meng, Z.-M. Zhao, T. Dong, A. Anderson, Sustainable bioplastics derived from renewable natural resources for food packaging, Matter 6 (2023) 97–127. 20

    work page 2023

  6. [6]

    L. K. Ncube, A. U. Ude, E. N. Ogunmuyiwa, R. Zulkifli, I. N. Beas, Environmental impact of food packaging materials: A review of contemporary development from conventional plastics to polylactic acid based materials, Materials 13 (2020) 4994

    work page 2020

  7. [7]

    Mukherjee, D

    C. Mukherjee, D. Varghese, J. Krishna, T. Boominathan, R. Rakeshkumar, S. Di- neshkumar, C. B. Rao, A. Sivaramakrishna, Recent advances in biodegradable poly- mers–properties, applications and future prospects, European Polymer Journal 192 (2023) 112068

    work page 2023

  8. [8]

    A. K. Mohanty, F. Wu, R. Mincheva, M. Hakkarainen, J.-M. Raquez, D. F. Mielewski, R. Narayan, A. N. Netravali, M. Misra, Sustainable polymers, Nature Reviews Methods Primers 2 (2022) 46

    work page 2022

Show all 64 references
  1. [9]

    Samir, F

    A. Samir, F. H. Ashour, A. A. Hakim, M. Bassyouni, Recent advances in biodegrad- able polymers for sustainable applications, npj Materials Degradation 6 (2022) 68

    2022

  2. [10]

    Calvino, N

    C. Calvino, N. Macke, R. Kato, S. J. Rowan, Development, processing and applica- tions of bio-sourced cellulose nanocrystal composites, Progress in Polymer Science 103 (2020) 101221

    2020

  3. [11]

    Song, D.-L

    F. Song, D.-L. Tang, X.-L. Wang, Y.-Z. Wang, Biodegradable soy protein isolate- based materials: a review, Biomacromolecules 12 (2011) 3369–3380

    2011

  4. [12]

    Trache, M

    D. Trache, M. H. Hussin, M. M. Haafiz, V. K. Thakur, Recent progress in cellulose nanocrystals: sources and production, Nanoscale 9 (2017) 1763–1786

    2017

  5. [13]

    Shojaeiarani, D

    J. Shojaeiarani, D. Bajwa, A. Shirzadifar, A review on cellulose nanocrystals as promising biocompounds for the synthesis of nanocomposite hydrogels, Carbohydrate Polymers 216 (2019) 247–259

    2019

  6. [14]

    A. B. Rashid, M. E. Hoque, N. Kabir, F. F. Rifat, H. Ishrak, A. Alqahtani, M. E. 21 Chowdhury, Synthesis, properties, applications, and future prospective of cellulose nanocrystals, Polymers 15 (2023) 4070

    2023

  7. [15]

    S. Cao, P. Rathi, X. Wu, D. Ghim, Y.-S. Jun, S. Singamaneni, Cellulose nano- materials in interfacial evaporators for desalination: a “natural” choice, Advanced Materials 33 (2021) 2000922

    2021

  8. [16]

    Habibi, L

    Y. Habibi, L. A. Lucia, O. J. Rojas, Cellulose nanocrystals: chemistry, self-assembly, and applications, Chemical Reviews 110 (2010) 3479–3500

    2010

  9. [17]

    R. J. Moon, A. Martini, J. Nairn, J. Simonsen, J. Youngblood, Cellulose nanoma- terials review: structure, properties and nanocomposites, Chemical Society Reviews 40 (2011) 3941–3994

    2011

  10. [18]

    Channab, A

    B.-E. Channab, A. E. Idrissi, Y. Essamlali, M. Zahouily, Nanocellulose: Struc- ture, modification, biodegradation and applications in agriculture as slow/controlled release fertilizer, superabsorbent, and crop protection: A review, Journal of Envi- ronmental Management 352 (20...

    2024

  11. [19]

    Zhang, M

    S. Zhang, M. L. Minus, L. Zhu, C.-P. Wong, S. Kumar, Polymer transcrystallinity induced by carbon nanotubes, Polymer 49 (2008) 1356–1364

    2008

  12. [20]

    H. Zhu, H. Yang, Y. Ma, T. J. Lu, F. Xu, G. M. Genin, M. Lin, Spatiotemporally con- trolled photoresponsive hydrogels: design and predictive modeling from processing through application, Advanced Functional Materials 30 (2020) 2000639

    2020

  13. [21]

    Gomri, M

    C. Gomri, M. Cretin, M. Semsarilar, Recent progress on chemical modification of cel- lulose nanocrystal (cnc) and its application in nanocomposite films and membranes-a comprehensive review, Carbohydrate Polymers 294 (2022) 119790

    2022

  14. [22]

    Habibi, Key advances in the chemical modification of nanocelluloses, Chemical Society Reviews 43 (2014) 1519–1542

    Y. Habibi, Key advances in the chemical modification of nanocelluloses, Chemical Society Reviews 43 (2014) 1519–1542. 22

    2014

  15. [23]

    Abraham, D

    E. Abraham, D. Kam, Y. Nevo, R. Slattegard, A. Rivkin, S. Lapidot, O. Shoseyov, Highly modified cellulose nanocrystals and formation of epoxy-nanocrystalline cel- lulose (cnc) nanocomposites, ACS Applied Materials & Interfaces 8 (2016) 28086– 28095

    2016

  16. [24]

    Y. Chu, Y. Sun, W. Wu, H. Xiao, Dispersion properties of nanocellulose: a review, Carbohydrate Polymers 250 (2020) 116892

    2020

  17. [25]

    Zhang, Y

    C. Zhang, Y. Ou, W. X. Lei, L. S. Wan, J. Ji, Z. K. Xu, Cuso4/h2o2-induced rapid deposition of polydopamine coatings with high uniformity and enhanced stability, Angewandte Chemie International Edition 55 (2016) 3054–3057

    2016

  18. [26]

    J. F. Rocha, L. H. Hasimoto, M. Santhiago, Recent progress and future perspectives of polydopamine nanofilms toward functional electrochemical sensors, Analytical and Bioanalytical Chemistry 415 (2023) 3799–3816

    2023

  19. [27]

    Y. Xu, J. Hu, J. Hu, Y. Cheng, X. Chen, Z. Gu, Y. Li, Bioinspired polydopamine hydrogels: Strategies and applications, Progress in Polymer Science (2023) 101740

    2023

  20. [28]

    S. X. Peng, S. Shrestha, Y. Yoo, J. P. Youngblood, Enhanced dispersion and prop- erties of a two-component epoxy nanocomposite using surface modified cellulose nanocrystals, Polymer 112 (2017) 359–368

    2017

  21. [29]

    Babaei-Ghazvini, B

    A. Babaei-Ghazvini, B. Vafakish, R. Patel, K. J. Falua, M. J. Dunlop, B. Acharya, Cellulose nanocrystals in the development of biodegradable materials: A review on cnc resources, modification, and their hybridization, International Journal of Biolog- ical Macromolecules (2023) 128834

    2023

  22. [30]

    Z. Wang, H. Li, H. Jin, M. Senanayake, S. V. Pingali, W. Goldberg, D. Kobayashi, G. Genin, M. Foston, Structure-property optimization of sustainable nanocomposites through surface-modified cellulose nanocrystals, 2024. In Submission. 23

    2024

  23. [31]

    C. Miao, W. Y. Hamad, Critical insights into the reinforcement potential of cellu- lose nanocrystals in polymer nanocomposites, Current Opinion in Solid State and Materials Science 23 (2019) 100761

    2019

  24. [32]

    J. R. Capadona, K. Shanmuganathan, D. J. Tyler, S. J. Rowan, C. Weder, Stimuli- responsive polymer nanocomposites inspired by the sea cucumber dermis, Science 319 (2008) 1370–1374

    2008

  25. [33]

    Favier, H

    V. Favier, H. Chanzy, J. Cavaill´ e, Polymer nanocomposites reinforced by cellulose whiskers, Macromolecules 28 (1995) 6365–6367

    1995

  26. [34]

    E. C. Demir, A. Benkaddour, D. R. Aldrich, M. T. McDermott, C. I. Kim, C. Ayranci, A predictive model towards understanding the effect of reinforcement agglomeration on the stiffness of nanocomposites, Journal of Composite Materials 56 (2022) 1591– 1604

    2022

  27. [35]

    Josefsson, F

    G. Josefsson, F. Berthold, E. K. Gamstedt, Stiffness contribution of cellulose nanofib- rils to composite materials, International Journal of Solids and Structures 51 (2014) 945–953

    2014

  28. [36]

    G. Weng, Some elastic properties of reinforced solids, with special reference to isotropic ones containing spherical inclusions, International Journal of Engineering Science 22 (1984) 845–856

    1984

  29. [37]

    Y. Qiu, G. Weng, On the application of mori-tanaka’s theory involving transversely isotropic spheroidal inclusions, International Journal of Engineering Science 28 (1990) 1121–1137

    1990

  30. [38]

    T. Mori, K. Tanaka, Average stress in matrix and average elastic energy of materials with misfitting inclusions, Acta Metallurgica 21 (1973) 571–574. 24

    1973

  31. [39]

    Saadat, V

    F. Saadat, V. Birman, S. Thomopoulos, G. M. Genin, Effective elastic properties of a composite containing multiple types of anisotropic ellipsoidal inclusions, with application to the attachment of tendon to bone, Journal of the Mechanics and Physics of Solids 82 (2015) 367–377

    2015

  32. [40]

    G. M. Genin, V. Birman, Micromechanics and structural response of function- ally graded, particulate-matrix, fiber-reinforced composites, International journal of solids and structures 46 (2009) 2136–2150

    2009

  33. [41]

    J. D. Eshelby, The determination of the elastic field of an ellipsoidal inclusion, and re- lated problems, Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences 241 (1957) 376–396

    1957

  34. [42]

    G. M. Genin, J. W. Hutchinson, Composite laminates in plane stress: constitutive modeling and stress redistribution due to matrix cracking, Journal of the American Ceramic Society 80 (1997) 1245–1255

    1997

  35. [43]

    Maurin, P

    R. Maurin, P. Davies, N. Baral, C. Baley, Transverse properties of carbon fibres by nano-indentation and micro-mechanics, Applied Composite Materials 15 (2008) 61–73

    2008

  36. [44]

    Hill, Theory of mechanical properties of fibre-strengthened materials: I

    R. Hill, Theory of mechanical properties of fibre-strengthened materials: I. elastic behaviour, Journal of the Mechanics and Physics of Solids 12 (1964) 199–212

    1964

  37. [45]

    Hill, Theory of mechanical properties of fibre-strengthened materials: Ii

    R. Hill, Theory of mechanical properties of fibre-strengthened materials: Ii. inelastic behaviour, Journal of the Mechanics and Physics of Solids 12 (1964) 213–218

    1964

  38. [46]

    Hill, A self-consistent mechanics of composite materials, Journal of the Mechanics and Physics of Solids 13 (1965) 213–222

    R. Hill, A self-consistent mechanics of composite materials, Journal of the Mechanics and Physics of Solids 13 (1965) 213–222

    1965

  39. [47]

    H. Li, J. Xi, Y. Zhao, F. Ren, Mechanical properties of polydopamine (pda) thin films, MRS Advances 4 (2019) 405–412. 25

    2019

  40. [48]

    Benveniste, A new approach to the application of mori-tanaka’s theory in com- posite materials, Mechanics of Materials 6 (1987) 147–157

    Y. Benveniste, A new approach to the application of mori-tanaka’s theory in com- posite materials, Mechanics of Materials 6 (1987) 147–157

    1987

  41. [49]

    Shi, X.-Q

    D.-L. Shi, X.-Q. Feng, Y. Y. Huang, K.-C. Hwang, H. Gao, The effect of nanotube waviness and agglomeration on the elastic property of carbon nanotube-reinforced composites, J. Eng. Mater. Technol. 126 (2004) 250–257

    2004

  42. [50]

    H. Tian, G. Guo, A. Xiang, W.-H. Zhong, Intermolecular interactions and microstruc- ture of glycerol-plasticized soy protein materials at molecular and nanometer levels, Polymer Testing 67 (2018) 197–204

    2018

  43. [51]

    Sharma, M

    A. Sharma, M. Thakur, M. Bhattacharya, T. Mandal, S. Goswami, Commercial application of cellulose nano-composites–a review, Biotechnology Reports 21 (2019) e00316

    2019

  44. [52]

    Pakzad, J

    A. Pakzad, J. Simonsen, R. S. Yassar, Gradient of nanomechanical properties in the interphase of cellulose nanocrystal composites, Composites Science and Technology 72 (2012) 314–319

    2012

  45. [53]

    S. K. Rahimi, J. U. Otaigbe, The effects of the interface on microstructure and rheo- mechanical properties of polyamide 6/cellulose nanocrystal nanocomposites prepared by in-situ ring-opening polymerization and subsequent melt extrusion, Polymer 127 (2017) 269–285

    2017

  46. [54]

    C. I. Idumah, C. M. Obele, Understanding interfacial influence on properties of polymer nanocomposites, Surfaces and Interfaces 22 (2021) 100879

    2021

  47. [55]

    Sinko, X

    R. Sinko, X. Qin, S. Keten, Interfacial mechanics of cellulose nanocrystals, MRS Bulletin 40 (2015) 340–348

    2015

  48. [56]

    Hashin, S

    Z. Hashin, S. Shtrikman, A variational approach to the theory of the elastic behaviour 26 of multiphase materials, Journal of the Mechanics and Physics of Solids 11 (1963) 127–140

    1963

  49. [57]

    Moln´ ar, D

    G. Moln´ ar, D. Rodney, F. Marto ¨ ıa, P. J. Dumont, Y. Nishiyama, K. Mazeau, L. Org´ eas, Cellulose crystals plastify by localized shear, Proceedings of the Na- tional Academy of Sciences 115 (2018) 7260–7265

    2018

  50. [58]

    E. C. Emenike, K. O. Iwuozor, O. D. Saliu, J. Ramontja, A. G. Adeniyi, Advances in the extraction, classification, modification, emerging and advanced applications of crystalline cellulose: a review, Carbohydrate Polymer Technologies and Applications 6 (2023) 100337

    2023

  51. [59]

    J. F. Matthews, M. Bergenstr ˚ ahle, G. T. Beckham, M. E. Himmel, M. R. Nimlos, J. W. Brady, M. F. Crowley, High-temperature behavior of cellulose i, The Journal of Physical Chemistry B 115 (2011) 2155–2166

    2011

  52. [60]

    Lee, S.-J

    S.-Y. Lee, S.-J. Chun, I.-A. Kang, J.-Y. Park, Preparation of cellulose nanofibrils by high-pressure homogenizer and cellulose-based composite films, Journal of Industrial and Engineering Chemistry 15 (2009) 50–55

    2009

  53. [61]

    Shalauddin, S

    M. Shalauddin, S. Akhter, W. J. Basirun, N. S. Anuar, O. Akbarzadeh, M. A. Mohammed, M. R. Johan, Carboxylated nanocellulose dispersed nitrogen doped graphene nanosheets and sodium dodecyl sulfate modified electrochemical sensor for the simultaneous determination of paracetamo...

    2022

  54. [62]

    X. Sui, T. Zhang, L. Jiang, Soy protein: Molecular structure revisited and recent advances in processing technologies, Annual Review of Food Science and Technology 12 (2021) 119–147

    2021

  55. [63]

    X. Liu, C. E. Athanasiou, C. L´ opez-Pern ´ ıa, T. Zhu, N. P. Padture, B. W. Sheldon, 27 H. Gao, Tailoring the toughening effects in two-dimensional nanomaterial-reinforced ceramic matrix composites, Journal of Applied Mechanics 91 (2024) 011003

    2024

  56. [64]

    G. Guo, Y. Zhu, Cohesive-shear-lag modeling of interfacial stress transfer between a monolayer graphene and a polymer substrate, Journal of Applied Mechanics 82 (2015) 031005. 28

    2015

Pith tools

Reviewed August 11, 2026 · model on record in the stance chip above.