Optimization of Biomass Conversion to Levulinic Acid in AcidicIonic Liquid and Upgrading of Levulinic Acid to Ethyl Levulinate

Nur Aainaa Syahirah Ramli1 & Nor Aishah Saidina Amin1

Published online: 21 July 2016# Springer Science+Business Media New York 2016

Abstract Levulinic acid (LA) is a versatile platform chemicalthat can be derived from biomass as an alternative to fossil fuelresources. Herein, the optimization of LA production from glu-cose and oil palm fronds (OPF) catalyzed by an acidic ionicliquid; 1-sulfonic acid-3-methyl imidazolium tetrachloroferrate([SMIM][FeCl4]) have been investigated. Response surfacemethodology based on Box-Behnken design was employedto optimize the LAyield and to examine the effect and interac-tion of reaction parameters on the LA production. The reactionparameters include reaction temperature, reaction time, feed-stock loading, and catalyst loading. From the optimizationstudy, the predicted mathematical models for LA productionfrom glucose and OPF covered more than 90 % of the variabil-ity in the experimental data. At optimum conditions, 69.2 % ofLAyield was obtained from glucose, while 24.8 % of LAyieldwas attained from OPF and registered 77.3 % of process effi-ciency. The recycled [SMIM][FeCl4] gave sufficient perfor-mance for five successive cycles. Furthermore, the optimumLA produced from glucose and OPF can be directly convertedto ethyl levulinate through esterification over the[SMIM][FeCl4] catalyst. This study highlights the potential of[SMIM][FeCl4] for biorefinery processing of renewable feed-stocks at mild process conditions.

Keywords Levulinic acid . Acidic ionic liquid . Responsesurface methodology . Optimization . Oil palm fronds . Ethyllevulinate

Introduction

The depletion of fossil fuel resources is forcing a shift fromfossil fuels to renewable sources for the production of energy,fuels, and chemicals [1]. One of the alternatives for fossil fuelsis biomass, with bio-refineries which can be presented as thefuture replacement for the present-day petroleum refineries.Biomass is an abundant renewable carbon source that can helpmitigate the emission of greenhouse gases. Among the varioustypes of biomass, lignocellulosic biomass is attractive for en-ergy production because it is a low-cost, abundantly availablefeedstock that does not compete with the food chain. Biomasshas received significant attention for its potential as a startingmaterial for bio-based chemical productions [2–4]. A diversityof process selections are available for the conversion of bio-mass to high added value products including acid hydrolysis,pyrolysis, and gasification [5].

Glucose is the monomer of cellulose, the main constituentsof lignocellulosic biomass which can be further converteddownstream to building block chemicals. One of the promis-ing building block chemicals that can be derived from bio-mass is levulinic acid (LA) [6, 7]. From energy to manufactur-ing, LA can be used for the production of fuel additives, foodflavoring agents, fragrances, pharmaceutical compounds, andresins [8, 9]. In Malaysia, oil palm fronds (OPF) are the mostabundant oil palm waste generated by mills [10]. The produc-tion of value-added products such as LA from OPF may offera better way to manage the biomass waste and could offerwealth creation from the biomass industry. Thus, the develop-ment of the oil palm industry for energy fuel and chemicalproduction can be sustained.

Mineral acid has been applied as catalyst for the productionof LA from various feedstocks [11–13]. The use of mineralacid is effective, but it is not recyclable and caused adverseenvironmental effects. Metal salts have also been used in the

* Nor Aishah Saidina Aminnoraishah@cheme.utm.my

1 Chemical Reaction Engineering Group (CREG), Faculty ofChemical and Energy Engineering, Universiti Teknologi Malaysia,UTM, 81310 Johor Bahru, Malaysia

Bioenerg. Res. (2017) 10:50–63DOI 10.1007/s12155-016-9778-3

catalytic production of LA with mainly chromium chlorideexhibiting good catalytic performance [14–18]. The highprice, toxicity, and environmental pollution derived fromchromium-based catalyst have necessitated the search for anontoxic and low-cost catalyst such as the extensively avail-able iron chloride [19]. Thus, iron chloride is envisaged as aneffective and eco-friendly catalyst for LA production [20, 21].

Ionic liquids are extensively used in biomass dissolution andin the dehydration of carbohydrates to produce variouschemicals including LA [15, 22]. Catalytic process involvingionic liquid is regarded as being more environmentally friendlycompared to mineral acids. Besides, the capability to reuseionic liquid is a good step towards reducing the overall costand reducing the amounts of waste produced. In the LA pro-duction process, ionic liquid can act as both solvent and catalystin converting cellulosic materials by disrupting the hydrogenbonds between the molecules [23]. An acidic ionic liquid isgenerally synthesized through the inclusion of different func-tional groups on the cation and anion. One of the tailor-madeacidic ionic liquid is sulfonic acid functionalized ionic liquid,with strong Brønsted acidic sites [24]. To date, ionic liquids andacidic ionic liquids have exhibited good performance as cata-lyst in conversion of renewable feedstocks to LA [22, 25, 26].

Both Brønsted and Lewis acid sites played important rolesin LA production from glucose and biomass conversions. Theconversion of cellulose to glucose is based on the Brønsted acidsites [27]. Meanwhile, the isomerization of glucose to fructoseis catalyzed by the Lewis acid sites [28], and Brønsted acid sitesare required for 5-HMF rehydration to LA [28]. In our earlierwork, three different acidic ionic liquids with Brønsted and/orLewis acidic sites have been synthesized and tested as catalystfor glucose conversion to LA as the main product [29]. Fromthe analysis, 1-sulfonic acid-3-methyl imidazoliumtetrachloroferrate ([SMIM][FeCl4]) which contained bothBrønsted and Lewis acidic sites offered the highest catalyticperformance and was further applied here.

The common reaction parameters which varied for LA pro-duction are reaction temperature, reaction time, feedstockloading, and catalyst loading [8, 30–33]. The determinationof optimum process variables is important for an optimum LAproduction. Besides, a more technically feasible process andbetter utilization of resources can be achieved. The conven-tional method used in process optimization can be costly andtime consuming since one variable is evaluated at a time. Byapplying the design of experiment, multiple parameters can beevaluated in the same factorial experiment. As such, responsesurface methodology (RSM) can be used for optimizing theLA production process. RSM is a statistical technique used toanalyze the relationship between a set of experimental factorswith some measureable response and at the same time opti-mize the desired output [3, 34]. Previously, RSM has beenemployed to optimize many processes including LA produc-tion from various feedstocks [8, 12, 32, 35].

Currently, extensive study on the conversion of LA intochemicals is being carried out. Among these explorations,one attractive approach is the production of alkyl levulinatethrough esterification of LAwith alkyl alcohol [36, 37]. Alkyllevulinate such as ethyl levulinate is a short-chain fatty esterwith similar properties to biodiesel fatty acidmethyl esters [38].Ethyl levulinate can be applied as fragrance and flavoringagents and functions as diesel fuel additives. Studies have re-ported a high conversion of LA to ethyl levulinate which can beachieved in the presence of acid catalyst such as zeolites andheteropolyacid-based catalysts [39, 40].

Herein, the optimization of LA production from catalyticconversions of glucose and OPF using [SMIM][FeCl4] as cat-alyst have been carried out using RSM. A Box-Behnken de-sign was employed for the design of experiment to elucidatethe effect of the process parameters: reaction temperature, re-action time, feedstock loading, and [SMIM][FeCl4] loading,on the LA yield. The interactions between the parameters onLA production were also examined using RSM. The reusabil-ity of [SMIM][FeCl4] on LA production from glucose andOPF was also addressed. Besides, the direct upgrading ofthe generated LA into ethyl levulinate at the optimum condi-tions was investigated as well.

Materials and Methods

Materials

All chemicals were obtained from Merck (Germany) andSigma-Aldrich (USA) and used as received without any fur-ther purification. The chemicals used for the preparation of[SMIM][FeCl4] were 1-methylimidazole, chlorosulfonic acid(HSO3Cl), dichloromethane (CH2Cl2), and iron (III) chloridehexahydrate (FeCl3·6H2O). Glucose, LA (99 %), H2SO4 (96–98 %), 5-HMF (99 %), formic acid (98 %), furfural (99 %),ethanol (99 %), and ethyl levulinate (99 %) were used in thecatalytic tests and product analysis. OPF were provided by theMalaysian Palm Oil Board (MPOB), Kuala Lumpur. The pet-iole part of OPF was dried and grinded to small size particles(<5 mm).

[SMIM][FeCl4] Preparation and Characterization

The preparation of [SMIM][FeCl4] involved the mixing of theprepared 1-sulfonic acid-3-methyl imidazolium chloride[SMIM][Cl] and FeCl3·6H2O. Detailed procedure for the syn-thesis of [SMIM][Cl] is described elsewhere [29]. For thepreparation of [SMIM][FeCl4], a mixture of equimolar[SMIM][Cl] and FeCl3·6H2O was stirred for 24 h, then driedovernight at 80 °C. The prepared [SMIM][FeCl4] was charac-terized using CHNS elemental analysis and 1H and 13C NMR.

Bioenerg. Res. (2017) 10:50–63 51

The acidity of [SMIM][FeCl4] was inspected using pyridine-FTIR, Hammett, and acid-base titration methods [29].

Determination of OPF Compositions

The OPF compositions were determined using thermal gravi-metric analysis (TGA) and standard procedure of acid hydro-lysis process from the National Renewable Energy Laboratory(NREL) [41]. For TGA analysis, 10 mg of OPF sample wasplaced in a platinum pan and heated from 30 to 700 °C underN2 flow (100 mL/min) at a heating rate of 10 °C/min using aNETZSCH STA 449F3 instrument. Meanwhile, the determi-nation of cellulose and hemicellulose content in OPF followedthe NREL procedure LAP 002 determination of carbohydratesin biomass by high-performance liquid chromatography.

Catalytic Tests

All experiments were carried out in a closed 100-mL Schottbottle, reacted as batch reactor, and equipped with a thermo-couple and magnetic stirrer. The reactor was loaded with apredetermined amount of feedstock (glucose or OPF) and[SMIM][FeCl4] catalyst and dissolved in 10 mL of water.The solution was heated up to the specified temperature. Inall experiments, the stirring speed was fixed at 200 rpm andthe temperature was controlled within ±1 °C of the set value.The reaction time was started once the reaction mixturereached the set temperature. After the reaction was completed,the reaction mixture was cooled down to room temperature.The analysis of product from glucose and OPF conversionswas carried out using HPLC.

The following procedure was used for [SMIM][FeCl4] recov-ery and separation of the reaction product. After every run, dis-tilled water (5 mL) was added to the reaction mixture. For OPFconversion reaction, the remaining OPF samples were filteredafter the addition of water. Then, ethyl acetate (5 mL) was addedseveral times, which resulted in the formation of a two-layersolution: organic phase (upper layer) and aqueous phase (bottomlayer). The [SMIM][FeCl4] in the bottom layer was then driedovernight at 105 °C to completely removewater and ethyl acetateresidual. The dried [SMIM][FeCl4] was used directly in the nextrun by adding fresh feedstock to study the reusability of[SMIM][FeCl4]. Meanwhile, the reaction product was obtainedfrom the upper layer after ethyl acetate was evaporated.

The reaction product from glucose and OPF conversions atoptimum conditions proceeded to be investigated for ethyllevulinate production. The reaction product was obtained afterthe separation of residues and catalyst. Ethyl levulinate produc-tion process was conducted by mixing the reaction product with5 g [SMIM][FeCl4] and 30 mL ethanol into the reactor flask andheated at ethanol reflux temperature (78.4 °C) for 7 h. For com-parison, direct conversion of glucose and OPF to ethyl levulinatewas also performed. The solution was heated at a constant

stirring speed of 200 rpm and left to cool to room temperatureafter the reaction was completed. The analysis of product fromthe esterification reaction was carried out using GC-FID.

Product Analysis

All samples were filtered using a 0.45-μm nylon membranefilter to ensure particle-free sample before being analyzed usingHPLC and GC-FID. The concentration of LA in the liquidproduct was determined using HPLC (Waters 2690) under thefollowing conditions: column = Hi-Plex H, flow rate = 0.6 mL/min, mobile phase = 5 mM H2SO4, detector = UV 250 nm,retention time = 45 min, column temperature = 60 °C. The LAyield, theoretical LAyield, and efficiency of OPF conversion toLA were calculated according to the following equations(Eqs. (1)–(3)):

LA yield %ð Þ ¼ LA amount gð ÞInitial feedstock amount gð Þ � 100% ð1Þ

Theoretical LA yield %ð Þ ¼ Cellulose content� 0:71 ð2Þ

where the value of 0.71 is equal to the molecular weight of LAdivided by the molecular weight of cellulose (MW of LA,C5H8O3 = 116, MWof cellulose, C6H10O5 = 162).

Efficiency %ð Þ ¼ LA yield

Theoretical LA yield� 100% ð3Þ

where efficiency refers to the efficiency of OPF conversion toLA based on the cellulose content.

Other water-soluble products from glucose and OPF con-versions were detected using HPLC under the same conditionas LA determination. Meanwhile, the concentration of ethyllevulinate in the product mixture was determined using GC-FID (Agilent 7820A) equipped with a capillary column (HP-5; 30 m × 0.32 mm × 0.25 μm) under the following condi-tions: carrier gas, N2 at 1.0 mL/min, and retention time10 min. The oven temperature of GC was held at initial tem-perature of 80 °C then ramped to 170 °C (13 °C/min) andfinally reached 300 °C (40 °C/min). The product yields werecalculated according to Eq. (4):

Product yield %ð Þ ¼ Product amount gð ÞInitial feedstock amount gð Þ � 100% ð4Þ

Experimental Design

Herein, Box-Behnken design was used to design the experi-ments with four variables, namely, reaction temperature (x1),reaction time (x2), feedstock loading (x3), and [SMIM][FeCl4]loading (x4). The level and range of process variables are

52 Bioenerg. Res. (2017) 10:50–63

summarized in Table 1. The range of process variables wasselected based on the preliminary experiments. The statisticalanalysis was carried out using StatSoft Statistica software ver-sion 8.0.

Results and Discussions

[SMIM][FeCl4] Characterization and OPF Compositions

The prepared [SMIM][FeCl4] is a stiff solid at room temper-ature, and it melts at higher temperature (~70 °C). The prop-erties of [SMIM][FeCl4] have been examined using severalmethods [29]. The elemental CHNS analysis result revealedsimilar calculated and found values, which confirmed the pre-pared [SMIM][FeCl4]. The NMR data for [SMIM][FeCl4] are1H NMR (DMSO-d6, 300MHz) 3.854 (3H, s), 7.622 (1H, m),7.666 (1H, m), 9.028 (1H, s), and 13.210 (1H, s) and 13CNMR (DMSO-d6, 75 MHz) (ppm) 35.8, 120.41, 123.48, and136.24 [29]. From the determination of [SMIM][FeCl4] acid-ity, [SMIM][FeCl4] comprised both Brønsted and Lewis acidsites. The Brønsted acid sites in the [SMIM][FeCl4] couldcome from the sulfonic acid group in the imidazolium cation,while the Lewis acid sites could emerge from the FeCl4

− in theanion. Meanwhile, the Hammett value of [SMIM][FeCl4] was3.36 and the amount of acidity from acid-base titration methodwas 0.94 (g NaOH/g [SMIM][FeCl4]).

The compositions of OPF have been inspected using TGAand acid hydrolysis step procedures. The thermal degradationof OPF from TGA gives few distinct stages of weight losses.The weight losses are due to the evaporation of residual water,volatilization of holocellulose, and degradation of lignin [41].The TGA and acid hydrolysis procedure revealed that OPFcontains 12.8 % moisture, 11.2 % lignin, 10.5 % ash, 45.2 %cellulose, and 20.3 % hemicellulose [41].

RSM Study of LA Production from Glucose and OPF

Model Analysis

The optimization process was investigated according to BBDwith 27 batch experiments. Table 2 lists the design of the

experiment matrix and the experimental results of LA yieldfrom glucose and OPF. The mathematical model for LAyieldwas fitted to second-order polynomial model as in Eq. (5) byconsidering linear term coefficient interaction of the variables.

Y i ¼ βo þ β1x1 þ β2x2 þ β3x3 þ β4x4 þ β11x12

þ β22x22 þ β33x3

2 þ β44x42 þ β12x1x2 þ β13x1x3

þ β14x1x4 þ β23x2x3 þ β24x2x4 þ β34x3x4 ð5Þ

where Yi is the dependent variable, LA yield; x1, x2, x3, andx4 are the independent variables; βo is the regression coef-ficient at the central point; β1, β2, β3, and β4 are the linearcoefficients; β11, β22, β33, and β44 are the quadratic coef-ficients; and β12, β13, β23, β34, β24, and β14 are the second-order interaction coefficients.

Table 1 Experimental range and levels for the independent variables ofglucose and OPF conversions

Variables Symbol Range and level

−1 0 +1

Reaction temperature (°C) x1 130 150 170

Reaction time (h) x2 3 4 5

Feedstock loading (g) x3 0.1 0.2 0.3

[SMIM][FeCl4] loading (g) x4 2 6 10

Table 2 Experimental data set for glucose and OPF conversions to LA

Run Variables Responsea

x1 (°C) x2 (h) x3 (g) x4 (g) Y1 (%) Y2 (%)

1 130 3 0.2 6 41.3 15.7

2 130 5 0.2 6 60.7 21.3

3 170 3 0.2 6 71.7 23.2

4 170 5 0.2 6 60.8 19.6

5 150 4 0.1 2 56.7 18.7

6 150 4 0.1 10 60.2 23.6

7 150 4 0.3 2 64.3 19.2

8 150 4 0.3 10 68.3 23.7

9 130 4 0.2 2 38.4 17.2

10 130 4 0.2 10 59.6 22.3

11 170 4 0.2 2 69.9 21.8

12 170 4 0.2 10 61.6 20.1

13 150 3 0.1 6 60.9 23.7

14 150 3 0.3 6 66.2 21.3

15 150 5 0.1 6 57.5 21.8

16 150 5 0.2 6 65.2 23.7

17 130 4 0.1 6 42.7 16.8

18 130 4 0.3 6 60.7 21.7

19 170 4 0.1 6 64.3 23.2

20 170 4 0.3 6 61.5 18.6

21 150 3 0.2 2 52.2 20.4

22 150 3 0.2 10 71.2 23.3

23 150 5 0.2 2 69.2 22.9

24 150 5 0.2 10 58.3 22.3

25 150 4 0.2 6 69.7 25.7

26 150 4 0.2 6 68.4 25.2

27 150 4 0.2 6 70.1 25.3

a Y1: LA yield from glucose, Y2: LA yield from OPF

Bioenerg. Res. (2017) 10:50–63 53

The polynomial regression models for LA yield from glu-cose and OPF conversions are in Eqs. (6) and (7), where Y1and Y2 are the dependent variables, LAyield from glucose andOPF, respectively.

Y 1 ¼ −938:155þ 9:062x1 þ 85:627x2 þ 480:532x3

þ 24:525x4−0:02x121−2:569x22−313:182x32−0:224x42

−0:378x1x2−2:603x1x3−0:092x1x4

þ 18:44x2x3−1:87x2x4 þ 0:35xxx4 ð6Þ

Y 2 ¼ −338:984þ 3:528x1 þ 28:177x2 þ 209:852x3

þ 5:769x4−0:009x121−1:42x22−176:067x32−0:112x42

−0:115x1x2−1:188x1x3−0:021x1x4

þ 10:077x2x3−0:219x2x4−0:25xxx4 ð7Þ

The validity of the empirical models was performed byanalysis of variance (ANOVA). Both models successfully ex-plained the variability of the data for LA yields from glucoseand OPF conversions where the R2 values were 0.981 and0.929, respectively, at the 95 % significance level. The ade-quacy of the fitted model was also examined using F test. Thecalculated F value was compared with the tabulated F value ata high confidence level in order to obtain a good predictionmodel. The calculated F value should be greater than the tab-ulated F value to reject the null hypothesis. For both models,the calculated F values were higher than the tabulated F valuesby rejecting the null hypotheses at the 95 % significance level(Table 3). Therefore, the models are suitable to predict the LAproduction from glucose and OPF conversions.

The Parity plots in Fig. 1a, b compare the predicted andobserved LA yields from experiments for glucose and OPFconversions, respectively. The results specify that the ob-served LA yields were scattered relatively near to the straightline, and the sufficient correlation between these values wasobserved. The significance of process variables—linear,

quadratic, and interaction terms—are revealed in the Paretocharts (Fig. 2a, b). The coefficient with smaller p value indi-cates that the coefficient is more significant towards the re-sponse [12]. For both models, with small p values, the qua-dratic term of all variables—x1

2, x22, x3

2, and x42—gave a

remarkable effect on the LAyield. This implies that increasingeach individual parameter will increase the LA yield until itreached its optimum value. The Pareto charts revealed thatreaction temperature was the most significant factor that influ-enced the LAyields from both glucose and OPF conversions.With p value higher than 0.05, it is confirmed that there areless interactions between reaction time and feedstock loading(x2x3) and glucose loading and [SMIM][FeCl4] loading (x3x4)for LAyield from glucose. Meanwhile for LAyield fromOPF,there are less interactions between reaction time and glucoseloading (x2x3), glucose loading and [SMIM][FeCl4] loading(x3x4), and reaction time and [SMIM][FeCl4] loading (x2x4).

Effect and Interaction of Variables on LA Production

The relationship between response and variables is visualizedby the 3D response surface plot and contour plot. These plotswere drawn by varying two variables while the other variableswere maintained at zero level. Figures 3 and 4 illustrate theinteractions between reaction variables on LA yield for glu-cose and OPF conversions, respectively. The interaction ef-fects were considered within the range of variables.

The interaction between reaction temperature and otherparameters can be observed from Figs. 3a–c and 4a–c. Fromthese figures, reaction temperature exhibited a quadratic be-havior on LA yield. When reaction temperature exceeds theoptimum point, the formation of insoluble humins is enhancedand decreases the LA yield. The quadratic effect of reactiontemperature on LA yield was more profound on OPF conver-sion compared to glucose conversion. This behavior was re-lated to the possible reactions that could have occurred andformation of by-products from OPF at high temperature. OPFcontains cellulose and hemicellulose polysaccharides, wherecellulose are the polymers of glucose while hemicellulose arethe polymers of several sugar monomers including xylose,

Table 3 Analysis of variance(ANOVA) for quadratic modelsof LA yield from glucose andOPF conversions

Sources Sums of square Degree of freedom Mean square F value F0.05,14,12

LA from glucose (R2 = 0.981)

Regression 2007.70 14 143.41 40.65 2.64

Residual 39.09 12 3.26

Total 2046.80 26

LA from OPF (R2 = 0.929)

Regression 166.19 14 11.92 11.20 2.64

Residual 12.77 12 1.06

Total 179.68 26

54 Bioenerg. Res. (2017) 10:50–63

mannose, galactose, and arabinose. Subsequently, the sugarmonomers of hemicellulose could enhance the formation ofby-products at temperatures exceeding the optimum.Figures 3a and 4a exhibit a significant interaction betweenreaction temperature and time, as revealed in the Pareto chartsand the elliptical nature of the contour plots. At low reactiontemperature, the LA yield increased linearly with reactiontime. Higher LA yield could be attained at higher reactiontemperature and prolonged time implying the acceleration ofreaction rate at higher temperature, where atoms donate orreceive electrons more easily [12, 42].

The significant interactions between reaction temperatureand feedstock loading at 4 h and 6 g [SMIM][FeCl4] are illus-trated by the elliptical contour plots in Figs. 3b and 4b. LAyield increased until the optimum with the increase of feed-stock loading and reaction temperature, suggesting that thereare still available active sites from [SMIM][FeCl4] in the re-action system. Meanwhile, Figs. 3c and 4c illustrate the con-tour plots for the interaction between reaction temperature and[SMIM][FeCl4] loading. The elliptical nature of both contour

plots indicated the significant interactions between reactiontemperature and [SMIM][FeCl4] on LA production from glu-cose and OPF conversions. It is demonstrated that LA yieldincreased with increasing [SMIM][FeCl4] loading at low tem-perature, as the number of active sites available in the reactionsystem is increased. After the [SMIM][FeCl4] loading met theoptimum requirement, increasing the catalyst loading and re-action temperature resulted in lower LA yield, as side reac-tions were promoted and enhanced the formation of unwantedby-products.

The saddle nature of the contour plot for LA yield fromglucose conversion, observed in Fig. 3d, indicates significantinteractions of reaction time and [SMIM][FeCl4] loading. Incontrast, there is less significant interaction between reactiontime and [SMIM][FeCl4] loading on OPF conversion to LA,which can be observed from the circular nature of the contourplot in Fig. 4d. For glucose conversion, either high[SMIM][FeCl4] loading and at short time or low[SMIM][FeCl4] loading and at prolonged reaction time willgive high LA yield. On the other hand, low [SMIM][FeCl4]loading at reaction time exceeding the optimum will result in

35 40 45 50 55 60 65 70 75 80

Observed LA yield (%)

35

40

45

50

55

60

65

70

75

80P

re

dic

ted

LA

yie

ld (

%)

R2 = 0.981

(a)

14 16 18 20 22 24 26 28

Observed LA yield (%)

14

16

18

20

22

24

26

28

Pre

dic

ted

LA

yie

ld (

%)

R2= 0.929

(b)

Fig. 1 Parity plots of LA yield model from glucose (a) and OPF (b)conversions

(a)

x 1

x1x

3

x3x

4

x2x

3

x1x

2

x1

x4

x 3

x2

x4

x1

2

x4

2

x2

x2

2

x3

2

x4

13.809

-8.367

-8.289

-5.769

7.779

4.673

1.631

1.673

4.556

3.875

3.167

-8.173

10.630

0.155

p value = 0.05

(b)

x1

2

x4

x4

2

x3

x1

x3

2

x2

2

x1x

3

x1x

2

x1x

4

x2x

3

x 2

x3x

4

x2x

4

-4.605

-4.460

4.081

3.813

3.351

-3.296

3.219

3.063

-1.697

1.559

0.878

-0.134

4.226

8.072

p-value = 0.05

Fig. 2 Pareto charts of LA yield model from glucose (a) and OPF (b)conversions

Bioenerg. Res. (2017) 10:50–63 55

x2 (h

)

LA

yie

ld (

%)

x 1

(o C

)

130

5.0

50

80

40

30

70

60

4.6

4.2

3.8

3.4

3.0

140

150

160

170

(a)

x 1

(o C

)x3 (g

)

160

130

140

150

170

0.10

0.14

0.18

0.30

0.26

0.22

LA

yie

ld (

%)

80

60

40

20

70

50

30

(b)

x 1

(o C

)x4 (g

)

LA

yie

ld (

%)

130

170

160

150

140

2

4

20

60

70

80

50

40

30

10

8

6

(c)

x 2

(h)

x4 (g

)

LA

yie

ld (

%)

75

45

40

23.0

3.8

5.0

4.6

4.2

3.4

10

8

6

4

50

55

70

60

65

(d)

(e)

LA

yie

ld (

%)

40

45

75

60

65

70

55

50

x 2

(h)

x3 (g)

3.0

4.2

5.0

4.6

3.8

3.4

0.10

0.14

0.18

0.22

0.26

0.30

(f)

LA

yie

ld (

%)

x 3(g

)

x4

(g)

2

10

9

76

5

4

3

8

0.10

0.14

0.18

0.22

0.26

0.30

75

70

65

60

55

50

45

40

Fig. 3 Response surface plots of LA yield versus different variables for glucose conversion

56 Bioenerg. Res. (2017) 10:50–63

x 1

(o C

)

x2 (h

)

LA

yie

ld (

%)

(a)

28

3.0 130

140

150

160

170

3.8

4.2

4.6

5.0

8

3.4

12

16

20

24

x 1

(o C

)

x3 (g

)

LA

yie

ld (

%)

(b)

130

28

24

16

12

8

0.10

0.14

0.18

0.22

0.26

0.30

20

140

150

160

170

x 1

(o C

)

x4 (g

)

LA

yie

ld (

%)

(c)

1302

6

10

28

24

20

16

12

8

8

4140

150

160

170

(d)

LA

yie

ld (

%)

x 2

(h)

x4

(g)

28

26

24

22

20

18

16

2

4

6

8

10

3.0

3.4

3.8

4.2

4.6

5.0

(e)

x 2

(h)

x3

(g)

LA

yie

ld (

%)

0.10

0.14

0.22

0.26

0.30

0.18

3.0

3.4

3.8

4.2

4.6

5.0

28

26

20

22

18

16

24

(f)

LA

yie

ld (

%)

x 3

(g)

x4 (g

)

28

26

16

18

20

22

24

20.10

0.14

0.18

0.22

0.26

0.30

6

8

10

4

Fig. 4 Response surface plots of LA yield versus different variables for OPF conversion

Bioenerg. Res. (2017) 10:50–63 57

low LA yield from OPF conversion. At limited amount of[SMIM][FeCl4], prolonged reaction time was needed forOPF dissolution prior to LA formation. However, huminsoriginated from sugars (glucose, fructose, xylose) and 5-HMF will form when the reaction was continued for too long.Besides, lower LAyield at higher [SMIM][FeCl4] loading wasdue to the excess Lewis acid sites as Lewis acid sites areknown to catalyze the formation of humins [29].

The less significant interaction between reaction time andfeedstock loading on LA yield from glucose and OPF can bedistinguished from the circular contour plots in Figs. 4e and5e, respectively. With limited amount of [SMIM][FeCl4],prolonged reaction time was needed for a complete conver-sion of glucose to LA, and for dissolution of OPF beforefurther conversion to LA. The same trend has also been re-ported for homogeneous acid catalysts [8, 43]. With the surgeof feedstock loading, LA yield decreased as the available ac-tive sites from [SMIM][FeCl4] were limited [14]. At constantreaction temperature and [SMIM][FeCl4] loading, the qua-dratic behavior of feedstock loading on LA yield was moresubstantial to OPF conversion compared to glucose conver-sion, as exhibited in the Pareto charts and 3D plots. It is sug-gested that OPF required more active sites from[SMIM][FeCl4], as [SMIM][FeCl4] was needed throughoutdissolution, hydrolysis, and dehydration processes for LA pro-duction from OPF. Meanwhile, [SMIM][FeCl4] was requiredduring dehydration reaction for LA production from glucose.

The circular nature of contour plots in Figs. 4f and 5fdemonstrates the interaction between feedstock and[SMIM][FeCl4] loading on LA yields from glucose andOPF, respectively. Increment of LA yields with incrementof [SMIM][FeCl4] amounting up to the critical loadingcan be observed from the plots. At low [SMIM][FeCl4]loading, the increase in glucose loading did not result inconsiderable decrease in LA yield. It is suggested thatthere are sufficient active sites in the reaction system forglucose conversion to LA even at high feedstock loading.Besides, the decrease in LA yield with increasing feed-stock—glucose and OPF—and [SMIM][FeCl4] loadingis probably due to the mixing effect. Too much amountof feedstock and catalyst will increase the viscosity of thereaction mixture, thus affecting the mixing effect. Thesignificance of feedstock and catalyst amount on mixinghas been considered and discussed before [32, 44, 45].

High temperature, prolonged time, and high catalyst load-ing could boost dissolution of biomass and increase the acces-sibility of dissolved cellulose from biomass to catalyst activesites [8, 46]. Nonetheless, unwanted side reactions might alsoincrease at these conditions. At higher catalyst loading, excessactive sites could boost the dehydration process and at thesame time promote the undesired side reactions. Meanwhile,higher feedstock loading might boost the probability of thereactive compounds such as glucose, fructose, and 5-HMF

to collide with each other and cause cross-polymerization forundesired humin formation.

From the observations of glucose and OPF conversions, thefinal color of the solution turned darker as the reaction wasconducted at higher temperature, prolonged reaction time,using higher feedstock loading, and higher [SMIM][FeCl4]loading. The change in color might be the evidence of thepresence of insoluble humins, and inferred unwanted side re-actions also increased at the same time. The same trend hasalso been observed previously [14, 32]. From the discussionson the variables and interaction effect on LA yield from glu-cose and OPF conversions, the optimal reaction temperature,reaction time, feedstock loading, and [SMIM][FeCl4] loadingfor maximum LA yield have to be scrutinized to design aneconomic biomass conversion process in the future.

Optimization of LA Production from Glucose and OPFConversions

The response surface analyses predicted that optimum LAyields from glucose and OPF conversions were 70.8 and25.6 %, respectively. The optimum conditions for LA yieldsfrom glucose and OPF are presented in Table 4. Further testswere conducted at the optimum conditions to validate thepredicted yields. The LA yields obtained from experimentsconducted at optimum conditions are in good agreement withthe predicted values at the 95 % confidence level. This behav-ior shows the competency of the models to the experimentalresults, which confirms the validity and adequacy of themodels. From the optimization study, the same optimum re-action temperature was obtained for both glucose and OPFconversion. Even though shorter reaction time was requiredto give an optimum LAyield from OPF compared to glucose,lower OPF loading and higher [SMIM][FeCl4] loading wereneeded instead. This could be explained by the need of OPFdissolution using [SMIM][FeCl4] before it can be further con-verted to LA.

In this work, LA is the final desired product from glucoseand OPF conversions using [SMIM][FeCl4] as catalyst. Yet,other water-soluble compounds were also detected such as 5-HMF, formic acid, and furfural. At the optimum conditions,complete conversion of glucose was achieved, with 69.2 and3.4 % of LA and 5-HMF yields, respectively, and traces offormic acid and furfural. Meanwhile, 24.8, 2.3, 6.8, and 3.1 %of LA, 5-HMF, formic acid, and furfural yields, respectively,were obtained from OPF conversion at the optimum condi-tions. Besides, insoluble black solid residues regarded ashumins were also observed in all reactions. In glucose conver-sion to LA, 5-HMF is formed as the intermediate, whileformic acid is regarded as the co-product. In acidic and high-temperature reaction media, formic acid has high chance todecompose to CO2, H2, CO, and H2O [47], which resulted inits trace amount. The insignificant amount of furfural was

58 Bioenerg. Res. (2017) 10:50–63

likely to be initiated by the loss of formaldehyde from 5-HMF[48, 49]. In addition, furfural was originated from xylose, thesugar monomer of hemicellulose presented in the biomassfeedstock [50–52].

LA Production from Different Biomass Feedstocks

The po t e n t i a l o f OPF t o p r o du c e LA u s i n g[SMIM][FeCl4] has been examined in this study. The de-termination of OPF cellulose content can be used to de-termine the theoretical LA yield and to calculate the pro-cess efficiency. The theoretical LA yield from OPF with45.2 % of cellulose content is 32.1 %. With 24.8 % of LAyield, the efficiency of OPF conversion to LA catalyzedby [SMIM][FeCl4] has been accounted as 77.3 %. Thehigh percentage of process efficiency revealed that morethan three quarters of the cellulose content in the OPF wassuccessfully converted into LA.

Some related works on LA production from different lig-nocellulosic biomass are listed in Table 5. It can be observedthat LAyields varied with different types of biomass feedstockand the cellulose content. Biomass with higher cellulose con-tent theoretically will produce higher LA. Besides, the LAproduction from biomass conversion also depends on the re-action conditions and catalysts applied in the reaction. LA

yield could be enhanced for reaction conducted at higher re-action temperature, prolonged reaction time, and stronger acidcatalyst. As summarized in Table 5, most of the process effi-ciency based on the theoretical yield was lower than 70 %.Basically, 100 % efficiency of biomass conversion to LA isnot achievable due to recalcitrance of biomass and other pos-sible parallel reactions that could have occurred [53].

Biomass conversion to LA involving mineral acids of-fered substantial process efficiency [12, 13, 42, 54]; how-ever, mineral acids cannot be recycled and thus can causeproblems to the environment. In addition, pretreatment ofbiomass [55–57] and initial hydrolysis of biomass to pro-duce sugar [8, 58] which were applied prior to LA pro-duction have improved the process efficiency withinsho r t e r r e a c t i on t ime . Fo r r e a c t i on app l y i ng[SMIM][FeCl4] as catalyst, the efficiency of OPF conver-sion to LA reached up to 77 % under the optimum con-ditions, which was higher and comparable with those pre-viously reported in Table 5. The relatively high efficiencyof LA production from OPF using [SMIM][FeCl4] couldbe well explained by the feature of [SMIM][FeCl4]. Theproperties of ionic liquid are compatible for biomass dis-solution, and its high acidity could serve to catalyze theoverall reaction. It is suggested that [SMIM][FeCl4] canbe used as a potential catalyst for the production of LA by

Table 5 LA production from various biomass feedstocks and catalysts

Feedstock Cellulosecontent (%)

Catalyst Reaction Condition LAyield (%) Efficiency(%)

Reference

Temperature(°C)

Time(min)

Theoretical Biomass

Cotton straw (hydrolyzed sugar) 42.6 H2SO4 180 60 30.2 12.0 39.7 [58]Red algae (hydrolyzed sugar) 64.7 H2SO4 180 48 45.9 42.9 93.5 [8]Water hyacinth 26.3 H2SO4 175 30 18.7 9.0 48.1 [54]Wheat straw 40.4 H2SO4 209 38 28.7 19.9 69.4 [12]Sorghum grain 73.8 H2SO4 200 40 52.4 32.6 62.2 [42]Pretreated giant reed 36.6 HCl 200 60 26.0 22.2 85.4 [55]Pretreated rice husks 31.0 HCl 160 70 22.0 12.0 54.5 [56]Bagasse 42.0 HCl 220 45 29.8 22.8 76.5 [13]Paddy straw 40.0 HCl 220 45 28.4 23.7 83.4 [13]Pretreated rice straw 46.1 S2O82−/ZrO2−SiO2-

Sm2O3

200 10 32.7 22.8 70.0 [57]

Empty fruit bunch 41.1 Cr/HY zeolite 145 146 29.2 15.5 53.1 [32]Kenaf 32.0 Cr/HY zeolite 145 146 22.7 15.0 66.1 [32]Oil palm fronds 45.2 Fe/HY zeolite 173 198 32.1 17.6 54.8 [45]Bamboo shoot shell 37.8 [C4MIM][HSO4] 145 104 26.8 17.9 66.7 [33]Oil palm fronds 45.2 [SMIM][FeCl4] 155 222 32.1 24.8 77.3 This study

Table 4 Optimum conditions,predicted and observed LA yieldsfrom glucose and OPFconversions

Feedstock Variables LA yield (%) Error (%)

x1 (°C) x2 (h) x3 (g) x4 (g) Predicted Observed

Glucose 154.5 4.2 0.25 5.45 70.8 69.2 2.3

OPF 154.5 3.7 0.18 7.27 25.6 24.8 3.1

Bioenerg. Res. (2017) 10:50–63 59

direct conversion of biomass in aqueous ionic liquidmedia.

[SMIM][FeCl4] Reusability for LA Production

The prospect of [SMIM][FeCl4] reusability was consideredsince the cost of ionic liquid is of high concern. The reusabilityof [SMIM][FeCl4] was inspected for glucose and OPF con-versions conducted at the optimum conditions. After a reac-tion run, water was added to decrease the viscosity of thereaction mixture, while ethyl acetate was added to facilitatethe extraction of the reaction product. The two-layer solutionformed after the addition of water and ethyl acetate—organic(upper layer) and aqueous (bottom layer)—were separatedaccordingly. It is implied that humins remained mostly in theaqueous layer as can be observed from the dark color[SMIM][FeCl4] in the aqueous layer solution. After extrac-tion, the excess water and residual ethyl acetate werecompletely removed by heating before [SMIM][FeCl4] beingused directly in the next run under the same reaction condi-tions. The catalytic activity of recycled [SMIM][FeCl4] didnot decrease significantly after five runs, demonstrating agood stability of [SMIM][FeCl4] (Fig. 5). The incompletenessof LA extraction and the residue of the unreacted feedstock in

the previous runs may have influenced the results of the reus-ability test. Besides, as humins were generated during thereaction and remained with [SMIM][FeCl4], the presence ofhumins might have partly blocked the [SMIM][FeCl4] reac-tive sites, consequently affecting the activity of recycled[SMIM][FeCl4] and decreased the LA yield.

Reaction Scheme of LA Production Using [SMIM][FeCl4]

The reaction scheme of LA production from glucose and OPFis shown in Fig. 6. The first step in biomass conversion reac-tion is the dissolution process. The reduction in cellulose crys-tallinity through dissolution process provided more accessibil-ity for the biomass to be converted into the selected product.The dissolution of the complex OPF structure takes place inthe presence of [SMIM][FeCl4], as the nature of ionic liquiditself is for biomass dissolution. Then, the dissolved cellulosewas hydrolyzed to give sugars, mainly glucose. The hydroly-sis of cellulose to glucose was mainly due to the Brønsted acidsites and the water medium [27]. Cellulose was converted bythe protonation of glycosidic oxygen in the cellulose and bythe attack of water on the anomeric carbon. The producedglucose from cellulose hydrolysis was isomerized to fructosewhich is then converted to 5-HMF. The isomerization stepwas catalyzed by the presence of Lewis acid sites.Meanwhile, the dehydration of fructose for 5-HMF formation

O

HO

OH

OH

OH

O

HO O

HO

O

O

LA

OH

O

O

OH

OH

OH

O

OH

OH

OH

O

CelluloseGlucose

[SMIM][FeCl4]OPF

O

HO OH

OH

OH OH

Fructose5-HMF

H2O

[SMIM][FeCl4]

[SMIM][FeCl4]

[SMIM][FeCl4]

H2O

H2O

[SMIM][FeCl4]

H2OH2O

H2O

+H

Fig. 6 Reaction scheme of LAproduction catalyzed by[SMIM][FeCl4]

Table 6 Ethyl levulinate production from LA, glucose, and OPF

Feedstock Reaction time (h)a Ethyl levulinate yield (%)d

Glucoseb 5 57.7

OPFb 5 20.1

Glucosec 10 27.5

OPFc 10 12.8

a Reaction time for ethyl levulinate productionb Feedstocks were converted to LA before being subjected to ethyllevulinate productionc Feedstocks were directly subjected to ethyl levulinate productiond Calculated based on feedstock

0

5

10

15

20

25

1 2 3 4 5

0

15

30

45

60

75

LA

yie

ld (

%) fr

om

OP

F c

onve

rsio

nLA

yie

ld (

%) f

rom

glu

cose c

onversio

n

Runs

Glucose

OPF

Fig. 5 Reusability of [SMIM][FeCl4] for LA production

60 Bioenerg. Res. (2017) 10:50–63

and rehydration of 5-HMF for LA production were both cat-alyzed by the Brønsted acid sites.

Ethyl Levulinate Production

The production of ethyl levulinate comes from the esterifica-tion reaction of LA with ethanol in the presence of the acidcatalyst. The reaction product mixture containing LA fromglucose and OPF conversions was further utilized for ethyllevulinate production in the presence of [SMIM][FeCl4] cata-lyst (Table 6). At mild reaction temperature, the conversion ofreaction products from glucose and OPF gives promising eth-yl levulinate production. For comparison, glucose and OPFwere directly converted to ethyl levulinate using[SMIM][FeCl4]. The ethyl levulinate yield from the directconversion of OPF was much less in contrast to the directconversion of glucose. This might be caused by the recalci-trance of lignocellulosic biomass which hindered the hydroly-sis process and subsequent esterification for ethyl levulinateproduction. In addition, the ethyl levulinate produced in a two-step reaction was higher compared to a one-step reaction. Forall reactions, traces of LA were detected from the productmixture after the esterification reaction, suggesting a completeconversion of LA to ethyl levulinate catalyzed by[SMIM][FeCl4].

Conclusion

The conversions of glucose and OPF to LA catalyzed by acid-ic ionic liquid [SMIM][FeCl4] were optimized by RSM ap-plying the Box-Behnken design. The LAyields from the pro-cesses were optimized while four parameters (reaction tem-pera ture , reac t ion t ime, feeds tock loading , and[SMIM][FeCl4] loading) were evaluated on the reaction. Itwas discovered that reaction temperature was the most influ-ential parameter for both glucose and OPF conversions to LA.The optimum LA yield from glucose was obtained at154.5 °C, 4.2 h, 0.25 g glucose, and 5.45 g [SMIM][FeCl4].Meanwhile, reaction conducted at 154.5 °C, 3.7 h, 0.18 gOPF, and 7.27 g [SMIM][FeCl4] generated an optimum LAyield from OPF. The predicted LAyields were in good agree-ment with the experimental LA yields which gave optimumLAyields of 69.2 and 24.8 % from glucose and OPF, respec-tively. The conversion of OPF to LA with 45.2 % cellulosecontent in OPF registered 77.3 % of process efficiency.Moreover, [SMIM][FeCl4] displayed stable catalytic activityfor five successive cycles for LA production from both glu-cose and OPF. After LAwas generated at the optimum condi-tions of glucose and OPF conversions, LA in the reactionproduct can be completely converted to ethyl levulinatethrough esterification with ethanol over the [SMIM][FeCl4]catalyst. This study promotes the use of lignocellulosic

biomass to generate a biobased chemical, particularly LA, asthe alternative to fossil fuels.

Acknowledgments The authors would like to acknowledge the finan-cial support from Universiti Teknologi Malaysia under the ResearchUniversity Grant (vot. number 07H14). One of the authors (NASR) is aResearcher of Universiti Teknologi Malaysia under the Post-DoctoralFellowship Scheme for the Project: Development of Nanocatalyst forChemical Conversion to Fuels (vot. number 02E54).

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