Date Approved

5-28-2021

Embargo Period

6-7-2021

Document Type

Dissertation

Degree Name

PhD Chemical Engineering

Department

Chemical Engineering

College

Henry M. Rowan College of Engineering

Advisor

C. Stewart Slater, PhD

Committee Member 1

Mariano J. Savelski, PhD

Committee Member 2

Kirti M. Yenkie, PhD

Committee Member 3

Robert P. Hesketh, PhD

Committee Member 4

Ramon Christian P. Eusebio, PhD

Keywords

Dynamic membrane systems, Mathematical modeling, Membrane separation, Nanofiltration, Sustainable processing, Water recovery

Subject(s)

Nanofiltration; Coffee industry

Disciplines

Chemical Engineering

Abstract

A vibratory nanofiltration (NF) system was investigated for the preconcentration of coffee extracts for soluble coffee production. The simulated coffee extracts studied contained mostly suspended and colloidal organic components that, although were effectively rejected by the NF membrane (>99% turbidity rejection), affected the vibratory NF performance. The vibratory NF operation improved permeate flux, rejection efficiencies, and reduced flux decline from those observed in crossflow (CF) operation. Further, the effects of applied transmembrane pressure (TMP) and vibrational frequency (F) at corresponding displacement (d) were investigated and modeled. A semi-empirical resistance-in-series model was employed to characterize the mass transfer mechanism, osmotic pressure effects, and fouling resistances that affected the vibratory NF performance. Response surface methodology (RSM), in conjunction with a Box-Behnken experimental design, was also employed to develop statistical models and determine optimal operating conditions (TMP = 3.79 MPa, F = 54.7 Hz, d = 3.18 cm). Lastly, scale-up design, economic, and environmental assessment for a 3% feed coffee extract corresponded to a 7-module i84 VSEP filtration system recovering 379,500 L of reusable water per day, a capital cost of $2,100,000 with estimated annual savings of $481,900 per year, a payback period of 10 years, and a potential to reduce the environmental emissions of the process by approximately 40%.

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