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oai:figshare.com:article/33835811 2026-09-16T09:05:49Z category_1 category_915 category_7 category_272 category_39 category_502 category_734 category_61 category_135 portal_63 item_type_2 month_year_09_2026

Tunable Morphologies of Dried Colloidal Deposits in Graphene Oxide-Laden Aqueous Sessile Droplets Mediated by Mesophase Characteristics Sanghamitro Chatterjee (9121277) Prayas Singh (13771703) Bibek Kumar (14082303) Ravi Kumar Shukla (21643549) Jitendra Bahadur (1352934) Rajneesh Bhardwaj (2295700) Biophysics Physical Sciences not elsewhere classified Medicine Environmental Sciences not elsewhere classified Ecology Astronomical and Space Sciences not elsewhere classified Biological Sciences not elsewhere classified Developmental Biology Computational Biology providing useful insights orientational order parameter experimentally report tunability desiccating sessile droplets continuous elastic sheets also investigated concentration mesoscale structural correlations different structural features deposit patterns ranging smectic elastic response dried colloidal deposits aqueous colloidal suspensions colloidal deposit morphologies polydisperse go suspensions characteristic mesophases driven aforementioned go suspensions radially striped morphologies observations revealed mesophase g </ b assembly subsequently leads structural morphologies deposit regime prominent striped lamellar smectic experiments revealed driven regimes characteristic self tunable morphologies morphologies span mesophase characteristics aqueous medium aqueous media </ b work elucidates weaker oxidation uniform deposits strongly oxidized spontaneous self rheological tests respectively elucidate ray scattering ordered phase mechanical strength graphene oxide go due droplet desiccation directed regimes dependent disordered We experimentally report tunability in the colloidal deposit morphologies of <b>G</b>raphene <b>O</b>xide (GO) from desiccating sessile droplets, governed by characteristic mesophases driven by spontaneous self-assembly in aqueous media. Observations revealed mesophase-directed regimes of GO-deposit patterns ranging from ring-like to uniform deposits; within the uniform-deposit regime, morphologies span from prominent striped to mosaic-like configurations. Experiments revealed that polydisperse GO suspensions of larger average lateral sheet size (∼2.2 μm) but weaker oxidation (C/O = 14.4) form orientationally ordered nematic domains in the aqueous medium; this characteristic self-assembly subsequently leads to radially striped morphologies after droplet desiccation. Alternatively, smaller in average lateral sheet size (∼0.5 μm) but strongly oxidized (C/O = 10.4) polydisperse GO colloids self-assemble in lamellar smectic-like domains as continuous elastic sheets that conform to the linear smectic elastic framework. Subsequently, this results in uniform deposits with mosaic-like fine-structural morphologies. We also investigated concentration-dependent disordered (isotropic) and ordered phase-driven regimes of ring-like and uniform deposit patterns formed by both of the aforementioned GO suspensions. The mesophase characteristics were analyzed by precision experimental tools including Small-Angle X-ray Scattering (SAXS) and rheological tests to respectively elucidate the mesoscale structural correlations and mechanical strength of the aqueous colloidal suspensions. The measurements corroborate theoretical frameworks involving the orientational order parameter and smectic elastic response. This work elucidates the general rules governing modulation in dried colloidal deposit patterns of GO due to structure–mesophase correlation, addressing variability in deposit patterns across GO samples with different structural features and providing useful insights for inkjet-printed electronic device fabrication. 2026-09-16T00:00:00Z Dataset Media 10.1021/acs.langmuir.6c04461.s003 https://figshare.com/articles/media/Tunable_Morphologies_of_Dried_Colloidal_Deposits_in_Graphene_Oxide-Laden_Aqueous_Sessile_Droplets_Mediated_by_Mesophase_Characteristics/33835811 CC BY-NC 4.0