Tuning Controlled Release Behaviour of Starch Granules using

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Tuning Controlled Release Behaviour of Starch Granules using Nanofibrillated Cellulose Derived from Waste Sugarcane Bagasse Mayur Patil, Vishal Patil, Aditya Sapre, Tushar Ambone, Arun Torris A. T., Parshuram Shukla, and Kadhiravan Shanmuganathan ACS Sustainable Chem. Eng., Just Accepted Manuscript • DOI: 10.1021/ acssuschemeng.8b01545 • Publication Date (Web): 06 May 2018 Downloaded from http://pubs.acs.org on May 6, 2018

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ACS Sustainable Chemistry & Engineering

1

Tuning

Controlled

Release

Behaviour

of

Starch

2

Granules using Nanofibrillated Cellulose Derived from

3

Waste Sugarcane Bagasse

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Mayur D. Patila, Vishal D. Patila, Aditya A. Saprea, Tushar S. Ambonea, Arun Torris A.

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T.a, Parshuram G. Shuklaa and Kadhiravan Shanmuganathana,b,*.

6 7

a

8 9

b

Polymer Science and Engineering Division, CSIR-National Chemical Laboratory, Dr.Homi Bhabha Road, Pashan, Pune 411008, India Academy of Scientific and Innovative Research, (AcSIR), Postal Staff College Area, Sector 19, Kamla Nehru Nagar,Ghaziabad, Uttar Pradesh- 201 002, India

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E-mail: [email protected]

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Synopsis: A nanocomposite controlled release system comprising two ubiquitous biopolymers suitable for

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applications in agriculture.

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Abstract

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Controlled release formulations help to encapsulate agrochemicals and deliver at a sustained rate. Growing

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environmental challenges have increased the need for controlled release systems based on sustainable feed-stocks. To

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this end, we report here the preparation and properties of a monolith type controlled release granular formulation

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based on two ubiquitous biopolymers, starch and cellulose. Cellulose nanofibres (CNF) derived from waste sugarcane

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bagasse were mixed with gelatinized maize starch and urea formaldehyde to yield nanocomposite granular

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formulation. Dimethyl phthalate (DMP) was used as model encapsulant. Morphology of CNF and CNF-reinforced

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starch granules was characterized by transmission electron microscopy, scanning electron microscopy, BET

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porosimetry and X-ray tomography. Incorporation of only 2- 4wt % CNF led to a significant reduction in porosity as

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compared to neat starch granules, while the water uptake was enhanced by 20-30%. Reinforcing starch with CNF led

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to a significant reduction in initial release rate and yet higher overall release of DMP, thereby allowing effective

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utilization of entrapped chemicals. This interesting release behaviour could be attributed to two competing factors,

25

water uptake–induced diffusion and barrier effects rendered by nanocellulose network.

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Keywords: Microencapsulation, nanocomposites, starch, nanocellulose, controlled release

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1 ACS Paragon Plus Environment

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INTRODUCTION

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Loss of crop yield due to severe insect attack is a critical problem faced by farmers across the globe. To

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protect the crops from pest attack, farmers resort to excessive application of pesticides. However, it is observed that

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only minute quantity of agrochemicals are retained at target sites1. Most of the sprayed agrochemicals move either

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into surface water streams or soil-layers. This affects the soil/water quality and leads to overall environmental

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pollution. Excess application of agrochemicals also have harmful effects on the health of farmers leading to deaths2.

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To protect the environment and yet achieve desired agricultural yield, agrochemicals can be entrapped and

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delivered at a sustained rate so that the bare minimum amount of agrochemicals reach the target site for healthy plant

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growth. Controlled release formulations (CRFs) have gained tremendous attention in recent years in diverse industries

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such as agrochemicals3-6, pharmaceuticals7-9, food products10, personal care11,12, advanced materials

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typically employed to realize triggered release of an active ingredient or to prolong the release over a desired time.

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CRFs of fertilizers and pesticides can enhance the yield of products while reducing environmental pollution.

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Application of CRFs not only helps to cut down excessive use of agrochemicals but also to protect them against

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degradation due to moisture, light, heat etc. 14. Various natural polymers including starch, gelatine, natural rubber, and

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synthetic polymers such as polyurea, polyurethane, polyvinyl alcohol, epoxy resins etc. have been employed to

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prepare CRFs15. They are produced in various morphologies including monoliths, core-shell microcapsules, hollow

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fibres and laminates16-19. Starch is one of the extensively used polymer matrix to prepare CR fertilizer17 and pesticide

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formulations20. It is a naturally available, biodegradable, and relatively cheap biopolymer. Numerous derivatives of

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starch as namely, starch xanthate21, starch calcium adduct22, starch borate23, starch-urea formaldehyde24-26, starch-g-

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poly(vinyl alcohol)27, starch-g-poly(butyl acrylate)28, starch-g-poly(vinyl acetate)17, starch-g-poly(L-Lactide)17,29 have

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been extensively studied as encapsulating matrices.

13

,etc. CRFs are

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In recent years, nanoparticulates such as nanoclay30,31 and nanosilica32 have been employed to enhance the

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barrier properties and attain further reduction in release of active ingredient from CRFs. These investigations have

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mainly focused on core shell nanocomposite microcapsules having polymer wall made of polyurea or polyurethane.

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For soil broadcast application in agricultural fields, it is ideal to have CRFs composed of bio-derived and

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biodegradable polymers. In this work, we made an attempt to prepare starch granules reinforced with cellulose

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nanofibrils to provide an extra barrier and further strengthen the sustained release of active ingredient. Cellulose is the

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most abundant biopolymer on earth, obtained readily from many natural sources such as wood, cotton, and vegetable

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biomass. It is the main structural component of plant cell wall and has been extensively used in the paper and textile

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industries. Recently nanocellulose has attracted considerable research interest in the industry and academia, due to

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their ultrafine dimension, high specific surface area, unique structural properties, low density, renewability,


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biodegradability, high reinforcing capability, lower production cost as compared to glass and carbon nanofibres, and

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their vast applicability33,34. Nanocellulose refers to two different types of nanomaterials: short, low aspect ratio

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cellulose nanocrystals or cellulose nanowhiskers (CNC or CNW) and long, high aspect ratio cellulose nanofibrils

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(CNF) which is also referred as microfibrillated cellulose in literature. CNC or CNW is typically produced by a

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sequence of chemical treatments including acid hydrolysis. This removes most of the hemicellulose, lignin and

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amorphous portions of cellulose leaving behind short nanocellulose crystals (CNC) (5-20 nm diameter, 50-200 nm

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length) with a surface charge depending on the chemical processing. CNCs are attractive as mechanical

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reinforcements and rheology modifiers. While chemical processing helps to obtain functionalized CNCs (suitable for

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many unique applications), the yield is low. Cellulose nanofibrils (CNF) can be obtained from bleached cellulose pulp

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by mechanical methods such as homogenizing, ball milling, grinding etc. This is a relatively high yield process

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resulting in thin nanofibrils of 5-50 nm diameters and several microns in length. When nanocellulose is blended with

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starch to form a nanocomposite, it enhances the barrier properties of starch based polymers33-35. Starch/cellulose

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nanofiber composites with defined pore size, porosity, mechanical strength, and biodegradability have been prepared

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by film casting, salt leaching, and freeze drying methods36. Starch/cellulose composites have also been explored for

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cartilage tissue engineering applications37. However, to the best of our knowledge there is no report on

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starch/nanocellulose based CR formulation. With rising environmental concerns and new regulatory standards,

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encapsulation using sustainable feedstocks could become a mandate in the near future. To this end, we made an

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attempt to develop a nanocomposite CR system combining two biopolymers and dimethyl phthalate (DMP) as active

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ingredient. DMP is a colorless liquid that is soluble in organic solvents. It is an insect repellent and ectoparasiticide. It

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is a well- known mosquito repellent. Hence we used it as a model active ingredient in this investigation. Herein, we

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report on the preparation and properties of starch/CNF CR formulation and the interesting effect of nanocellulose on

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release behaviour of starch granules.

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MATERIALS AND METHODS

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Materials

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Dimethyl phthalate (DMP) was purchased from Sigma-Aldrich, USA. Maize starch powder was purchased from West

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Coast Laboratories, India. Urea (99.5%) and spectral grade methanol (99.8%) were purchased from Loba-Chemie Pvt.

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Ltd., India. Formaldehyde as formalin solution (37-41% w/v) was procured from Thomas Baker Chemicals Pvt. Ltd.,

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India. Triethanolamine (≥ 97%) and sodium hydroxide were purchased from Merck Limited, India. Formic acid was

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purchased from Ranbaxy Laboratories Ltd., India. For the preparation of nanocellulose, sugarcane bagasse was

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collected from local markets. Glacial acetic acid and sodium hypochlorite were procured from Leonid Chemicals Pvt.

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Ltd., India. All chemicals were used as received.



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Isolation of nanocellulose from sugarcane bagasse

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50 g of dry sugarcane bagasse was cut into small pieces and washed with distilled water. Then they were

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treated with 4% (w/v) aqueous NaOH solution at 1:30 (w/v) fibre to liquor ratio at 50-60 °C for 2 h under mechanical

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stirring. This procedure was repeated three times. In between each treatment stage, the fibres were filtered and rinsed

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with distilled water. Subsequently the fibres were bleached at 70-80 °C for 3 h. The bleaching solution containing

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equal parts (v/v) of aqueous sodium hypochlorite (1.5 wt % NaClO in water) and acetate buffer (27 g NaOH and 75

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mL glacial acetic acid, diluted to 1000 mL using distilled water) was employed. 1:30 (w/v) fibre to liquor ratio was

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also used for the bleaching experiment. Bleaching procedure was repeated until the fibres became white in colour. The

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bleached pulp was filtered and rinsed with distilled water and then subjected to high shear in an ultra-friction micro

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grinder (Supermass Collider®, Masuko, Japan). In this process, the cellulose slurry was repeatedly passed through a

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static grinding stone and a rotating grinding stone revolving at 1500 rpm until the microfiber cellulose was reduced in

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diameter to 20-100 nm. The reduction in size was ascertained by transmission electron microscopy. The aqueous

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nanocellulose suspension was lyophilized and stored for further use.

103 104

Entrapment of active ingredient

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Starch granular formulations with DMP as entrapped active were prepared using established procedure24. The degree

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of cross-linking (w/w ratio of urea to starch (U/S) i.e., X) for all formulations was kept constant at 0.4. Urea to

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formaldehyde molar ratio in all the formulations was maintained as 2:3 and starch to water ratio was also kept

108

constant (1:3). Granules were prepared with 2 and 4 wt% of CNF with respect to total weight of starch-urea

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formaldehyde (St-UF) matrix. Blank granules were also prepared for comparative analysis i.e. granules without DMP.

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A typical procedure for entrapment with X= 0.4 and 6 wt % of active loading (DMP) is as follows; Initially, UF

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prepolymer was prepared by taking 39-41g formalin solution in a 250 mL round bottom flask and neutralizing with

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0.6 % (v/v) aqueous NaOH solution. pH was increased to 8-8.5 by adding triethanol amine followed by the addition of

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20 g of urea. The mixture was refluxed for 10-15 min and then allowed to cool to room temperature. In a separate

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container, 50 g of starch was dispersed in 150 mL distilled water and gelatinized in a boiling water bath. Gelatinized

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starch was then transferred to a Hobart planetary mixer with an overhead paddle. 3.89 gm of DMP was gradually

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added to gelatinized starch and stirred for about 10-15 min to achieve uniform dispersion. Separately prepared UF

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prepolymer was then added gradually to this mixture. After 10-15 min, 3-4 mL of 20% (v/v) formic acid was added

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dropwise (5-8 min) to adjust pH to 3.0- 3.5 with continued stirring for 5 min. After 30 min, the reaction mixture

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turned into a rubbery mass. This mass was shredded into small pieces through stainless steel sieve (mesh size: 12 -

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ASTM) and dried in an airdraft oven at 50 °C for 4 h. The dried granules were primarily sieved by 12-mesh size. The

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material remained over the sieve, is denoted as set-1 while the sample that passed through is designated as set-2.


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Further, the set-2 was sieved using 25-mesh sieve and fractions were collected. The middle fraction, i.e. set-2, is a

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major part of the sample (~70-80 wt %) with size ranging between 0.7 to 1.8 mm. This was used for further

124

investigation. In case of CNF-reinforced granules, 1.5 and 3.1 g of nanocellulose was taken in 90 mL of distilled

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water separately for 2 wt% and 4 wt% respectively. It was stirred for 15 h with an overhead stirrer followed by

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sonication for 30 minutes to make a homogeneous dispersion. To maintain similar starch to water ratio in all

127

formulations, 50 g of starch was dissolved in 60 mL of water and then combined with CNF dispersion prior to

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gelatinization. Further protocol was similar to the preparation of neat starch-UF granules. The samples prepared with

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0 wt%, 2 wt%, and 4 wt% CNF are hereafter referred as GR-0, GR-2 and GR-4 respectively.

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CHARACTERIZATION

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Transmission electron microscopy of nanocellulose

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Nanocellulose samples were dispersed in distilled water (concentration of 0.05 wt%) by mechanical stirring, followed

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by sonication. One drop of this dispersion was deposited on carbon coated copper grid. The grid was subjected to

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drying at ambient conditions for 24 h. Images of the samples were obtained using Transmission Electron Microscope

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(Technai T-20) at an accelerating voltage of 200 kV.

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Determination of DMP content in the sample

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Approximately 1 g of sample was taken and transferred to 100 mL round bottom flask. 50-60 mL of 50% (v/v)

138

aqueous methanol was added to this flask and refluxed for 8 h. The mixture was cooled to room temperature and

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filtered through Grade-3 sintered crucible. The residue was washed with 20-30 mL of 50% (v/v) aqueous methanol.

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After that, filtrate was transferred to 100 mL volumetric flask and diluted with distilled water up to the mark. For

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further dilution, 1.0 mL of this solution was transferred to 25 mL volumetric flask and diluted with distilled water.

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The absorbance of the diluted solution was noted at 276 nm (λmax of DMP) on UV spectrophotometer (Hitachi-Model

143

220).

144

The concentration of DMP was obtained using previously determined calibration slope by the following formula:

(1)

145

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Water uptake of granules

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A series of 25 mL volumetric flasks were taken (one flask for each time interval), and approximately 1.0 g of oven

148

dried sample was placed in each flask with 20 mL of distilled water at room temperature (~25 oC). The contents were



Page 6 of 22

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gently stirred 2-3 times during first 1-2 h to avoid agglomeration. At different time intervals (up to 172 h), swollen

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granules were recovered from the designated flasks by filtration and weighed meticulously. Water uptake was

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calculated using following formula:

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(2) 153 154 155

Each measurement was carried out in duplicate to obtain average value of percent water uptake. Similar procedure

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was repeated for all samples.

157 158

Release Measurements

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Release rate study of formulations was carried out under perfect sink conditions24,25. The experiments were carried out

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in duplicate. Calculated amount of granules were taken in hand-stitched muslin cloth bag. The bag was dipped in a

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500 mL beaker, filled with 400 mL of distilled water. The system was kept under stirring at 30 °C (±1) and 310 rpm

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over a magnetic stirrer in a temperature controlled system. 10 mL aliquots were taken out at specific time intervals

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from the system and replenished by same quantity of distilled water to maintain concentration gradient. The aliquots

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were analysed by UV spectrophotometry at 276 nm. Average value of percent cumulative release was plotted as a

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function of time.

166 167

Morphological Analysis

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Surface morphology of GR-0, GR-2 and GR-4 samples was examined using Scanning Electron Microscope (E-SEM,

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Quanta 200-3D) at 15 kV. The samples were directly mounted on carbon tape and sputter coated with gold to avoid

170

charging. Porosity of these granules was analysed with autosorb-iQ2 Quantachrome BET-porosimetry instrument.

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Further, pore characteristics of the granules were studied by a non-invasive X-ray microtomography imaging using

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Xradia Versa 510 X-ray Microscope (Zeiss X-ray Microscopy, Pleasanton, CA, USA). Granules were loaded on to 2

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mL plastic vial and the vial was placed on the sample holder which is in between the X-ray source and detector

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assembly. Detector assembly consists of a scintillator, objective lens and a CCD camera. X-ray source was ramped up

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to 120 kV and 10 W and 0.4x lens was employed in the detector assembly which provides a field of view of about 7

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mm x 7 mm. Source was placed at a distance of 17 mm from the center of sample and the detector assembly was kept

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at 150 mm distance from the sample. The tomographic image acquisitions were completed by acquiring 3201

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projections over 360° of rotation with a pixel size of 7 microns and 0.5 sec exposure per projection. In addition,

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projections without the samples in the beam (reference images) were also collected and averaged. Filtered back-


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projection algorithm is used for the reconstruction of the projections to generate two-dimensional (2D) virtual cross-

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sections of the capsules. 2D images were segmented using image processing software, Dragonfly Pro (Version 3.0), to

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generate three-dimensional (3D) image of the capsules. Porosity and pore-size distribution was deduced from the

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segmented 3D volume by differentiating the voxels pertaining to air and granules.

184 185

Statistical Interpretations

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To understand the release behaviour, the experimental data was evaluated using a mathematical model. This model is

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based on Ritger-Peppas and Peppas-Sahalin equations. Simple iterative methodologies were employed to attain a

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proper fit of theoretical dataset with experimental values38,39. The algorithm for the same is elaborated in the last

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section of the article. Based on Peppas-Sahalin equation, we attempted to employ two release frequencies to model the

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release trends which enabled us to have an improved fit and hence better physical understanding of the system.

191 192

RESULTS AND DISCUSSIONS

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Morphology of Nanocellulose Fibres

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Bleached pulp of waste sugarcane bagasse was subjected to multiple steps of grinding using ultrafriction micro

195

grinder, wherein shear forces during the grinding process led to defibrillation of cellulose pulp yielding cellulose

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nanofibres. The grinding process and number of steps of grinding need to be optimized for every source of cellulose.

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For sugarcane bagasse, the original pulp fibres before grinding were 20-60 µm in diameter. Grinding the pulp for

198

about 1 h, by passing the pulp repeatedly between the grinding stones 12-15 times ensured that more fibres were

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mechanically fibrillated and reduced to smaller fibrils. The number of fibres retaining original pulp dimensions

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substantially reduced and within 2 h of grinding, the pulp became smooth, homogenous and fine resulting in CNF

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having diameter in the range of 20 -50 nm and length ranging several microns as confirmed by transmission electron

202

microscopy (Figure 1). Similar process has been reported for producing CNF from wood pulp elsewhere40.

203



204

205

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Figure 1: Transmission electron micrographs of CNF derived from sugarcane bagasse.

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Morphology and DMP Content of Starch/CNF Granules

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Scanning electron micrographs (SEM) of crosslinked starch granules and starch/CNF nanocomposite is shown in

209

Figure 2. Neat starch granules (GR-0) exhibited a smooth surface structure, while CNF - reinforced starch granules

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had a compact structure and relatively rough surface morphology. The surface roughness was found to increase with

211

increasing concentration of CNF. Yoo, Y. et.al. have reported on reinforced polymer microspheres containing cellulose

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nanocrystals (CNC), where they found that the surface compactness and roughness of the polymer increases due to the

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presence of CNC41. This implies that the addition of nanoparticles not only makes the microcapsules chemically

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heterogeneous but also physically heterogeneous. For agricultural applications, surface roughness may not have direct

215

implications, but the increase in surface roughness of capsules could enhance their adhesion to substrates and is a

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desired property in many applications such as textiles. Several methodologies have been reported in the literature to

217

estimate the overall core content in CRFs. In this work, we have followed the process reported by us earlier24.

218

Extraction of DMP was carried out in 50% (v/v) aqueous methanol against the theoretical 6 wt % DMP loading in this

219

starch based CRF. We found that DMP content obtained by extraction was between 5.49-5.57 wt% for all the samples

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and very close to theoretical loading (Table 1). This indicates a better entrapment efficiency of starch granules with

221

least interference of CNF.

222 223


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224 225

Figure 2: Scanning Electron Micrographs of (a) GR-0, (b) GR-2, (c) GR-4

226 DMP (wt %) Sample No. Theoretical Loading

Obtained Loading

GR-0

6.00

5.50

GR-2

6.00

5.57

GR-4

6.00

5.49

227 228

Table 1: Extraction of DMP content

229 230

Water Uptake Behaviour of Starch/CNF Granules

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The release behaviour of CRFs applied as soil broadcast in agricultural fields is significantly influenced by water

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induced swelling of the encapsulating matrix. Hence, we investigated the kinetics of water uptake in neat starch and

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starch/CNF nanocomposites. The plot of percentage water uptake (wt %) vs. time for starch granules (with and without

234

CNF) is shown in Figure 3. Nanocomposite starch granules revealed a higher water uptake than neat starch granules. It

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was observed that in the case of GR-0 and GR-2 initial water uptake up to 25 h is almost similar (30 ± 5%). However,

236

GR-4 showed significantly higher water uptake which could be attributed to the increased hydrophilicity of



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nanocomposite in the presence of CNF. The numerous hydroxyl groups on the surface of CNF facilitate water

238

penetration and swelling of nanocomposites (Figure 3). When the study was continued for 1 week, GR-0 had an

239

equilibrium water uptake of 70-75 wt %, while GR-2 and GR-4 samples showed 90-95 wt % and 97-98 wt % water

240

uptake respectively (Table 2). The higher water uptake observed in starch/CNF granules is consistent with earlier

241

reports on CNC reinforced polymer nanocomposites, where incorporation of CNC has been found to significantly

242

enhance the water uptake of both polar and non-polar polymers42-44. The kinetics of water transport in these granular

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formulations was investigated using Ritger and Peppas equation (3)39,

244 245

(3)

246 247

Where ‘(Mt/M∞)’ is the fractional water uptake at time t, ‘k’ is a constant characteristic for water uptake and exponent

248

‘n’ is a transport mechanism of the penetrant water.

(a)

(b)

249 251

250 Figure 3: Water uptake (wt %) vs. time - (a) Up to 25 h, (b) Up to 168 h

252 253

The k values for samples GR-0, GR-2 and GR-4 were 0.0573 min-n, 0.0415 min-n and 0.1412 min-n respectively (Table

254

2). The increase in rate constant value from GR-0 to GR-4 indicates that CNC facilitates faster water transport into the

255

granules.

256 257


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Degree of Equilibrium Sample

crosslinking, X

DMP

k

Name.

U/S

(wt %)

(min)-n

Correlation n

Water Uptake (wt coefficient %)

(w/w ratio) GR-0

0.4

5.50

0.0573

0.2509

0.9586

72.13

GR-2

0.4

5.57

0.0415

0.3195

0.9637

94.22

GR-4

0.4

5.49

0.1412

0.2211

0.9886

98.18

258 259

Table 1: Water uptake rate constant ‘k’ and exponent of transport mechanism of penetrant ‘n’ of granules

260 261

The ‘n’ values for samples were in the range of 0.22 to 0.32, suggesting that the water transport mechanism remains

262

unchanged in the presence of CNC. A value of n = 0.5 indicates a Fickian mechanism, while n = 1.0 shows Case II

263

transport (polymer relaxation) for slab type of geometry, and values in between are considered as non-Fickian

264

(anomalous) transport. These limiting values of n are relatively lower for different geometry, (0.45 and 0.89 for a

265

cylinder, 0.43 and 0.85 for a sphere) as computed by Ritger and Peppas for solute release or solvent (water)

266

penetration. In the case of a polydisperse system of spherical microcapsules these values could be even lower. Ritger

267

and Peppas computed values of n as low as 0.3 and 0.45 for Fickian and Case II transport, respectively for a certain

268

specific distribution of spherical particles38,39,45. Further reduction in these values could be expected when dealing with

269

a polydisperse system of irregular shaped particles, such as St-UF granules described in this study22. Therefore, n

270

values (0.22-0.32) in this system indicate that the transport mechanism could be either Fickian or anomalous as

271

reported earlier.

272 273

Effect of Nanocellulose on Release Behaviour

274

The release plots of dimethyl phthalate (DMP) entrapped in GR-0 and CNF-reinforced St-UF granules GR-2 and GR-

275

4 are shown in Figure 4. GR-2 exhibited slower initial burst release (6-8%) as compared to GR-4 (18-20%) and GR-0

276

(22-25%)(Figure 4a). Release study was extended up to one week to observe the behaviour at steady state. Starch-UF

277

granules (GR-0) led to an overall release level of about 60% DMP and exhibited a plateau thereafter. However,

278

overall release percentage of GR-2 and GR-4 ranged between 90-95% and 75-80% respectively (Figure 4b). While

279

the addition of nanocellulose mitigated the initial burst release of starch granules, overall release of active ingredient

280

was higher than neat granules. In neat starch granules, the release of DMP was saturated at 60% and about 40 % of

281

DMP remained entrapped within the crosslinked starch matrix. There is no significant increase in release of active

282

ingredient with further increase in time. However, about 80-95% of DMP was released within a week in starch/CNF



283

granules due to water induced swelling. Entrapped actives are typically expensive, hence maximizing their utilization

284

can prove to be cost effective. Reinforcing starch with 2 wt % CNF (GR-2) helps to lower the initial burst release and

285

yet attain higher overall release of active ingredient. This lab evaluation method is a first step illustrating proof of

286

concept. Actual release in the field would also depend on factors like soil pH, moisture content, irrigation pattern etc.

(a)

287 289

(b)

288 Figure 4: Percentage release vs. time- (a) up to 25 h , (b) up to 168 h

290 291

To elucidate the interesting release behavior of starch nanocomposite granules, X-ray microtomography was used for

292

the first time to investigate the pore structure of these types of materials (Figure 5). Total volume of 282 and 284 mm3

293

were imaged for granules GR - 0 and GR - 2, respectively. 3D image obtained after the segmentation of the 2D cross-

294

sectional images shows a porosity of 1.64 and 1.68 % for granules GR - 0 and GR - 2, respectively. Pore-size

295

distribution is calculated by fitting spheres into the pores in the 3D volume of the granules and thereby extracting the

296

diameter of the fitted spheres. Since the spatial resolution of the images acquired with the optimum imaging

297

parameters is 0.9 microns, observation of pore-size below 0.9 microns is not possible by this method. As evident from

298

the pore-diameter distribution profile, granule GR - 0 contains more pores in the higher size range in comparison with

299

granule GR - 2.


Page 12 of 22

Page 13 of 22 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


a

b

1mm

1mm 300

301 Figure 5: X-Ray tomography micro-images a) GR – 0; b) GR – 2 and c) pore-diameter distribution of GR – 0 and GR – 2. 302

We also performed porosity measurements using BET nitrogen adsorption method (Table 3). The overall pore

303

diameter was found to decline with increase in CNF content. Total pore volume of starch granules was reduced by six

304

fold with the inclusion of only 2 wt % CNFs. Further increase in nanocellulose concentration to 4 wt% did not change

305

the pore characteristics significantly. This serves to explain the marginal effect of CNF on release when concentration

306

is increased from 2 wt% to 4 wt%. It is plausible that the high surface area nanocellulose fibres are effectively filling

307

the voids in starch granules and reducing their porosity. The sharp decline in burst release in CNF-reinforced starch

308

granules could be ascribed to this reduced porosity, where CNF network within starch matrix lead to tortuous

309

diffusion pathway for active ingredients thereby slowing down their release into the surrounding medium. We

310

estimated the surface area and porosity by BJH (Barrett-Joyner-Halenda) desorption method. Interestingly the surface

311

area of neat granules were 3.5 times higher than the CNF reinforced granules (GR-4), which also serves to explain the

312

influence of CNF on release behaviour of starch granules.

Sample Name

Surface Area (m2 g-1)

Total Pore Volume ( cm3 g-1)

Pore Diameter (Ao)

GR-0

63.74

0.09121

35.070

GR-2

25.35

0.01498

33.031

GR-4

18.30

0.01519

31.288

313 314

Table 3: Porosity analysis of granules performed using BJH desorption method.

315

However, as the starch granules start to swell in water, the higher water uptake of GR-2 and GR-4 starch granules

316

enhances the overall release of entrapped active. Thus, the release behaviour of CNF-reinforced starch granules is

317

mediated by a competition between water uptake–induced diffusion and tortuosity rendered by nanocellulose network.

318

In the initial stages, barrier effects of nanocellulose dominate the release behaviour, and as water diffuses into the



Page 14 of 22

319

granules, water uptake of granules dominates the release characteristics. Analysis of release profile carried out with

320

equation (4) reported by Ritger and Peppas39 gave the values of ‘k’ and ‘n’ as reported in Table 4.

321

(4)

322 323 324

Where ‘Mt/M∞’ is fractional solute release at time ‘t’, ‘k’ is a constant characteristic of solute release and values of

325

exponent ‘n’ suggests the type of release mechanism. For a slab type geometry, n = 0.5 indicates Fickian release (i.e.

326

by diffusion), n = 1.0 indicates Case II or zero order (by polymer relaxation) and 0.5 < n < 1.0 indicates non-Fickian

327

where diffusion and polymer relaxation both mechanisms are operative. According to prior results given by Ritger and

328

Peppas, the exact release mechanism is difficult to ascertain by simple population of poly-dispersed particles. Yet, any

329

change in release mechanism due to change in morphologies of particles can be predicted. In this study, ‘n’ values for

330

GR-0 and GR-4 were 0.1313 and 0.2012 respectively indicating Fickian release but ‘n’ values for GR-2 was 0.4020

331

implying Case-II39. ‘k’ values for GR-0, GR-2 and GR-4 were 0.2094 min-n, 0.0303 min-n, 0.1515 min-n respectively.

332 Degree of Sample

crosslinking, X

DMP

Correlation

k n

Name.

U/S

(wt %)

(min)-n

coefficient

(w/w ratio) GR-0

0.4

5.50

0.2094

0.1313

0.9273

GR-2

0.4

5.57

0.0303

0.4020

0.9652

GR-4

0.4

5.49

0.1515

0.2012

0.9265

333 334

Table 4: Release rate constant (k) and release exponent (n) of granules.

335 336

MATHEMATICAL INTERPRETATION

337

Several mathematical models have been used to understand and predict controlled release. Basic first and second

338

order dissolution models were initially used by several researchers for understanding the CRFs46,47. Due to their

339

incapability of handling complex polymeric systems, models of Hixon/Crowell, and Higuchi were introduced in the

340

early 60’s48. However, their assumptions related to constant rate of release made them unsuitable for real life

341

systems49,50. In 1986, Ritger and Peppas had formulated a model for predicting the release behaviour of swellable


Page 15 of 22 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


342

matrix. This model is a simple power-law model as described below. In this equation ‘k’ is the rate constant and ‘n’ is

343

the release exponent38.

344

(5) 345 346

In this work, we employed the Ritger-Peppas model (RPM), and the Peppas-Sahlin model51 (PSM). Since the PSM

347

model uses dual frequency approach, better fit as well a better physical interpretation can be obtained. The model

348

follows similar assumptions as the RPM- model. The generic equation employed for modelling is as follows:

349

= k1

+ k2

(6)

350

Where ‘Mt/M∞’ is the percentage release/water uptake, ‘k1’ and ‘n1’ are the release/ water uptake rate constant and

351

exponent respectively corresponding to timespan ‘t1’, while‘k2’ and ‘n2’ are the release/ water uptake rate constant and

352

exponent respectively corresponding to timespan ‘t2’. ‘t1’ is the time span till 40 h and t2 is time span post 40 h.

353

Using the governing equation of Peppas and Sahalin51 model, the basic release exponent, ‘n’, and the rate constant, ‘k’

354

values were obtained for the mathematical model. The boundaries of these values were set after considering such

355

comparable values from our earlier studies25, and literature of Kulkarni et al.51. The respective release exponent values,

356

ranged from 0.05-0.5 with a step-size of 0.05. For this set of values, Mt/M∞ values were assumed within a range of 0.1

357

to 1.5 for water uptake and 0.1 to 0.95 for release. The time‘t’ required for the release was varied from 0.05-250 h

358

with a variable step-size. After careful consideration of experimental data and literature values, these limits were set.

359

Using basic iterative calculations, rate constant ‘k’ values were obtained (Table 5). The obtained values of ‘k1, k2’’

360

and ‘n1, n2’ for a respective case correspond to the PSM model. Experimentally obtained ‘k’ and ‘n’ values have been

361

used for the RPM model plots. The physical interpretation of the system is discussed below.

362

As discussed before, the rate of water uptake is highest for GR-4 which gives initial rate constant of 0.141 h-0.225 and

363

release exponent 0.225. Further as we move into the time zone of water uptake after 40 h, the rate constant for water

364

uptake for GR–2 and GR-4 are higher than GR-0 which in turn proves mathematically that water uptake has increased

365

due to incorporation of CNF within the system.

366 367 368 15 ACS Paragon Plus Environment


Page 16 of 22

Sr. Sample Name

Water Uptake (wt %)

No.

K1

K2

(min –n1)

369

1.

GR – 0

2.

GR – 2

3.

GR – 4

n1

(min –n2)

n2

0.032

0.325

0.002

0.624

0.033

0.329

0.009

0.492

0.141

0.225

0.389

0.098

Table 5: k and n values for water uptake

370

In the case of release of active ingredient, the rate constant values have reduced by 14 folds from GR-0 to GR-2

371

within the 40 h time frame (Table 6); which serves to explain the slower burst release of GR-2 as compared to that of

372

GR-0. For the release trend above 40 h, we found the combined effect of K2 and n2 to be higher for GR-2 and GR-4

373

which concurs with higher overall release of active ingredient in these samples. The respective fits are presented in

374

Figure 6. Sr. No.

Sample Name

Release (%) K2

K1 (min –n1) 1.

GR – 0

2.

GR – 2

3.

GR – 4

n1

(min –n2)

n2

0.209

0.128

0.421

0.043

0.015

0.541

0.255

0.141

0.086

0.301

0.759

0.004

375 Table 6: k and n values for release behaviour

376

The theoretical and practical rate constant values of ‘k’ were compared using a Chi-square test. We checked whether

377

the hypothesis lies on the appropriate side within the table of analysis or not. The basic formulae used for the Chi-

378

Squared test involves:

(7) 379 380

Where ‘χ2’ is the test statistics, ‘O’ is the calculated/theoretical value, ‘E’ is the experimental value.

381 382 383


Page 17 of 22 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


b

a

384

c

d

e

f

385

386 387

Figure 6: Experimental and modelled behaviour of granules – Water uptake: (a) GR-0, (c) GR-2, (e) GR-4; Release:

388

(b) GR-0, (d) GR-2, (f) GR-4.

ACS Paragon Plus Environment 17


Sr. No.

Page 18 of 22

Chi-Square Value

Chi-Square Value

for water uptake analysis

for release analysis

2.56

2.67

2.28

2.59

2.33

3.73

Sample Name

1.

GR – 0

2.

GR – 2

3.

GR – 4

389 Table 7: χ2 values for water uptake and release behaviour

390 391

The values obtained from Chi-square test are provided in Table 7 for both water uptake and release for comparison of

392

experimental and PSM model rate constant, i.e. ‘k’ values. The rate constant values were compared with the

393

experimental values at 95% level of significance. Hence, to accept the hypothesis the values that are calculated must

394

be lesser than the critical value, i.e. 11.07. From Table 7, we observe that the calculated values are less than 11.07

395

giving a positive support to the hypothesis.

396

CONCLUSION

397

In summary, a controlled release nanocomposite granular formulation has been successfully prepared using two

398

naturally abundant biodegradable polymers, starch and cellulose. CNF derived from waste sugarcane bagasse have

399

been used to reinforce starch-urea formaldehyde granules. Incorporation of CNF was found to have a significant

400

influence on morphology and release behaviour of crosslinked starch granules. The initial release of DMP is

401

significantly inhibited in the presence of CNF while the overall release is enhanced. This allows controlled release of

402

entrapped chemicals while ensuring their effective utilization in applications. The interesting release profile has been

403

mathematically interpreted using models of Ritger-Peppas and Peppas-Sahalin. Such controlled release granular

404

formulations based on biorenewable feedstocks could be ideal for applications in agriculture.

405

AUTHOR INFORMATION

406

*Tel./Fax:

407

Shanmuganathan: 0000-0001-8062-6684. Notes: The authors declare no competing financial interest

408

ACKNOWLEDGEMENTS

409

The authors wish to acknowledge Central Material Characterization facility at CSIR-National Chemical Laboratory

410

for helping with SEM and TEM images.

+91-20-25902173.

E-mail

address:

[email protected]


(K.S.).

ORCID

Kadhiravan

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411

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Sharma, S.; Nair, S. S.; Zhang, Z.; Ragauskas, A. J. & Deng, Y. Characterization of micro fibrillation process of cellulose and mercerized cellulose pulp. RSC Adv. 2015, 5, 6311163122. Yoo, Y.; Martinez, C.; Youngblood, J. P. Sustained dye release using poly(urea– urethane)/cellulose nanocrystal composite microcapsules. Langmuir 2017, 33(6), 1521-1532. Shanmuganathan, K.; Capadona, J. R.; Rowan, S. J.; Weder, C. Bio-inspired mechanicallyadaptive nanocomposites derived from cotton cellulose whiskers. J. Mater. Chem. 2010, 20 (1), 180-186. Hsu, L.; Weder, C.; Rowan, S. J. Stimuli-responsive, mechanically-adaptive polymer nanocomposites. J. Mater. Chem. 2011, 21 (9), 2812-2822. Dagnon, K. L.; Shanmuganathan, K.; Weder, C.; Rowan, S. J. Water-triggered modulus changes of cellulose nanofiber nanocomposites with hydrophobic polymer matrices. Macromolecules 2012, 45 (11), 4707-4715. Davidson, G. W. R.; Peppas, N. A. Solute and penetrant diffusion in swellable polymers: V. Relaxation-controlled transport in P(HEMA-co-MMA) copolymers. J.Cont. Rel. 1986, 3 (1), 243-258. Varelas, C. G.; Dixon, D. G.; Steiner, C. A. Zero-order release from biphasic polymer hydrogels. J. of Cont. Rel. 1995, 34(3), 185-192. Amy, R.-P; Jon, W. Statistical methods for population pharmacokinetic modelling. Stat. Methods in Med. Res. 1998, 7(1), 63-84. Higuchi, T. Rate of release of medicaments from ointment bases containing drugs in suspension. J. of Pharma. Sci. 1961, 50(10), 874-875. Chen, S.; Zhu, J.; Cheng, J. Preparation and in vitro evaluation of a novel combined multiparticulate delayed-onset sustained-release formulation of diltiazem hydrochloride. Pharmazie. 2007, 62(12), 907-913. Siepmann, J.; Siepmann, F. Mathematical modeling of drug dissolution. Int. Journal of Pharma. 2013, 453(1), 12-24. Peppas, N. A.; Sahlin, J. J. A simple equation for the description of solute release. III. Coupling of diffusion and relaxation. Int. Journal of Pharma. 1989, 57(2), 169-172. Kulkarni, N.V.; Rajgopalan, N.; Kale, R.P.; Khilar K.C. Starch urea formaldehyde matrix encapsulation of solid agrochemicals.ii. release mechanism and release modelling. J.Appl. Polym. Sci. 1992, 45(5), 915-922.

541 542 543 544 545 546 547 548



549

FOR TABLEOF CONTENTS ONLY

550

Synopsis: A controlled release system, comprising a biopolymer and nanomaterial derived from natural wastes,

551

having potential applications in agriculture.

552 553


Page 22 of 22

Tuning Controlled Release Behaviour of Starch Granules using

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