Hong Lin1,Wesley Thompson2, Brian Marquardt2, Richard Gustafson1, Renata Bura1, Shannon Ewanick1

Membrane Separations in Biorefinery Streams: Application of Raman Spectroscopy to Enhance Process Optimization

1School of Forest Resources, 2Applied Physics Laboratory; University of Washington, Seattle WA

INTRODUCTION + OBJECTIVES RESULTS

MATERIALS + METHODS

CONCLUSIONS

Acknowledgements: CPAC and Consortium for Plant Biotechnology Research

Raw Raman Spectra and Spectra Principle Components

Change in component concentrations during filtration (by HPLC, UV, and Raman)

Apparatus

Experimental

Analytical methods

BBLBiofuels andBioproducts LaboratoryUniversity of Washington School of Forest Resources

Background Separations in biorefinery will require use of membranes to improve energy efficiency and because many of the components are non-volatile. Optimization of membrane performance requires continuous monitoring of permeate flux and composition to assess selectivity. One of the obstacles to developing and commercializing biorefinery membrane systems is a lack of instrumentation to assess membrane performance in real time. Raman spectroscopy offers the potential to make rapid and accurate measurements of both carbohydrate and lignin content in biorefinery streams. This work demonstrates application of Raman spectroscopy to enhance membrane separation research and its potential for commercial application.

Objectives: Assess potential for membranes to separate sugars from lignin in a

biorefinery process streams Apply Raman Spectroscopy to assess lignin and carbohydrate

content of membrane permeate streams

Pressure GaugeNeSSI Block

Membrane Cassette

Peristaltic Pump

Manually measure flow rate and collect samples very 15 minutes

Collected samples were analyzed by UV and HPLC to determine lignin and sugar concentrations

Raman Probe

Feed Flow

Permeate Flow

RamanRetentate Flow

Feed Reservoir

UV-VIS spectrophotometer (lignin content) Sample diluted 500 fold with deionized water, and absorbance measured at 280

nm Ion Chromatography System (ICS- 3000) (monomer sugar content)

50 μl of sample mixed with 950 μl epure water and 50 μl fucose was injected to HPLC for sugar concentration analysis

Volumetric method (flux rate) Record the permeate volume per minute in every 15 minutes interval Flux rate J=V/t· area ( L / h· m2)

500 mL synthetic biorefinery solution; 1% concentration each of lignosulfonate, glucose, and xylose

Polysulfone membrane with 5,000 and 10,000 Dalton molecular weight cut off (from Pall)

Membrane pressure was ~2 bar with 40 mL/min feed flow rate, ambient temperature. Retentate returned to feed reservoir

Raman data collected on membrane permeate with Kaiser HoloPro Instrument 5 second exposure, 10 accumulations

400 600 800 1000 1200 1400 1600 1800

-0.03

-0.02

-0.01

0

0.01

0.02

0.03

0.04

0.05

0.06

Variable

Load

ings

on

PC

2 (

0.03

%)

Variables/Loadings Plot for Multiple SPC files

400 600 800 1000 1200 1400 1600 1800

0

0.005

0.01

0.015

0.02

0.025

Variable

Load

ings

on

PC 1

(99

.97%

)

Variables/Loadings Plot for Multiple SPC files

Loading plots

PC 1 Fluorescence

PC 2Lignosulfonate and sugar peaks

20 40 60 80 100 120 140-1

-0.5

0

0.5

1

1.5

2

x 106

Raman Spectrum Number

Scor

es o

n PC

1

2 3 4 5 6 7 82

3

4

5

6

7

8

Measured Lignosulfonate by UV (g/L)

Pred

icte

d Li

gnos

ulfo

nate

by

Ram

an (g

/L)

A-1 A-2 A-3 A-4 A-5 A-6 A-7 A-8 A-90.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

GlucoseXyloseLignosulfonate

Sample

Conc

entr

ation

(g/L

)

Averaged 5 spectra centered on the median of the sample spectra

R2 = 0.9952 Latent VariablesRMSEC = 0.097962

5000 Dalton membranes provides good separation of sugars from lignin 10,000 Dalton membrane gave similar performance Lignin data shows there is an optimal point to concentrate process stream

Raman spectroscopy promising method for biorefinery process stream measurements Lignin concentration determined by Raman correlates well with determination

using UV spectroscopy Sugar analysis not yet to be completed but previous work shows feasibility

FUTURE WORK

Optimize membrane separation of sugars and lignin Optimal pore size and operating conditions Expand research to real process streams, with greater potential for

fouling Develop fundamental model of membrane separation

Apply data from Raman measurements to develop model Optimize membrane separation of lignin and hemicellulose polymers

Hong Lin