rational design of advanced oxidation processes using ... · (1st order reaction) 1. plug flow...

Daisuke Minakata1,

Ke Li2,

John C. Crittenden1,

1 Brook Byers Institute for Sustainable Systems and School of Civil and Environmental EngineeringGeorgia Institute of Technology2 Faculty of Engineering, University of Georgia

GCOE Symposium, July 21, 2011 Kyoto Univ. Kyoto, Japan.

Rational Design of Advanced Oxidation Processes using Computational Chemistry

1

Emerging contaminants: detection of trace organic contaminants and uncertain human health and ecological effects

Concern about emerging contaminants necessitate a task to assess their removal efficiency during water treatment

Advanced Oxidation Processes (AOPs) are attractive and promising water treatment technologies because of the capability of mineralization of organic compounds.

AOPs may be used to control the emerging contaminants.

Non-selectivity of HO• and radical chain reactions make AOPs complex processes as well as diversity and complexity of structure of a large number of emerging contaminants.

Introduction to Advanced Oxidation Processes

2

Modeling AOPs

1. Simplified Pseudo-Steady-State Model

2. AdoxTM – AOP simulation software

3. Conventional Approach for Kinetic Model

4. Computer-based Kinetic Model

3

3. H2O2 is added to a water containing O3, i.e. [O3]0 is known.

4

2. H2O2 and O3 are added simultaneously

3 3O O

ss, 09 2 10 2 2 11 3 12 130 0 00 0

HOHO H O HCO R NOM

LK a P H

k k k k k

UV/H2O2 H2O2/O3 Simplified pseudo-steady-state model

R 12 ss, 0HOk k

H O2 2pH p

1 2 2 30 resss, 0

11 3 12 130 00

2 H O 10 OHO

HCO R NOM

Kk

k k k

2 2 2 2

-A

H O U-V H O

ss,0 -

10 2 2 0 11 3 0 12 0 13 0

2 P f (1- e )[HO ] =

k [H O ] + k [HCO ] + k [R] + k [NOM]

g

1. UV/H2O2

R R Rr k

5

Flow Models: Ideal flow at steady state (1st order reaction)

1. Plug Flow Reactor (PFR)

k

0C C e

2. Completely Mixed Flow Reactor (CMFR)

0CC

(1 k)

3. Tank-in-series (TIS)

0

n

CC

1 kn

1/ n

0C nQV 1

C k

0Q C CV

r

0CQV ln

k C

6

Flow Models: Non-ideal flow

4. Dispersed flow model closed system

A

2 2Ao

1 vL4a exp

2 EC

a vL a vLC (1 a exp (1 a exp) )2 E 2 E

a 1 4k (E / vL)

7

Group Contribution Method -Hypothesis-

Essence is same as the GCM for the gaseous phase Observed experimental reaction rate constant for a

given organic compound is the combined rate of all elementary reactions involving HO•, which can be estimated using Arrhenius kinetic expression.

The Ea consists of two parts: (1) Base part from main reaction mechanisms (i.e.,

H-atom abstraction, HO• addition to alkenes and aromatic compounds and HO• interaction with S, N, or P-atom-containing compounds).

(2) Functional group contribution partially from neighboring and/or next nearest neighboring functional group.

= aE

RTk Ae

Minakata, Li, Westerhoff, and Crittenden. ES&T 2009, 43, 6220-6227

8

1.0E+05

1.0E+06

1.0E+07

1.0E+08

1.0E+09

1.0E+10

1.0E+11

1.0E+05 1.0E+06 1.0E+07 1.0E+08 1.0E+09 1.0E+10 1.0E+11

kca

l (M

-1s-1

)

k exp (M-1s-1)

Ideal fit

kexp/kcal = 0.5 and 2.0

H-atom abstraction (Calibrated)

HO addition to alkene (Calibrated)

HO interaction with N,S,P (Calibrated)

HO addition to aromatic compounds

(Calibrated)

H-atom abstraction (Prediction)

HO interaction with N, S, P (Prediction)

HO addition to aromatic compounds

(Prediction)

• 257 rate constants (83% of 310 data) from calibration were within 0.5 ≤ kcalc/kexp ≤ 2.0.

• The sample deviation was 0.92. Degree of Freedom was 164• 76 rate constants (62% of 124) from prediction were within 0.5 ≤

kcalc/kexp ≤ 2.0.

Minakata, Li, Westerhoff, and Crittenden. ES&T 2009, 43, 6220-6227

Modeling AOPs





9

• Reactor Options

– Completely mixed reactor (CMBR)

– Completely flow type reactor (CMFR) w/o TIS

– Plug flow reactor

– Non-ideal Mixing

• Main Process Operational Variables :

– Initial hydrogen peroxide concentration

– Incident UV-light intensity

• Water quality parameters:

– TOC concentration

– pH

– Concentrations of target compounds

– Byproducts can be included if they are known

Features of Current Version AdOxTM 1.0

10Crittenden et al., 1999. Wat. Res. 33, 2315-2328

Features of Current Version AdOxTM 1.0 for UV/H2O2

H2O2 + hν → 2HO•

H2O2 = quantum yield of H2O2 (=0.5) I0 = incident light intensity, einstein cm-2 sec-1 A=2.303b(εH2O2CH2O2+εRCR + εSCS + εHO2-CHO2-) b=pathlength, cm fH2O2= 2.303 b (εH2O2CH2O2 + εHO2-CHO2-)/A

H2O2/HO2- + HO H2O/OH- + HO2 2.7×107, 7.5×109

H2O2 + HO2/O2- HO + H2O/OH- + O2 3.0, 0.13

HO + HO H2O2 5.5×109

HO + HO2/O2- H2O/OH- + O2 6.6×109, 7.0×109

HO2 + HO2/O2- H2O2/HO2

- + O2 8.3×105, 9.7×107

R + hv Products

R + HO Products kMtBE=1.6×109, ktBA=6.0×108

HO + CO32-/HCO3

- CO3- + OH-/H2O 3.9×108, 8.5×106

HO + NOM Products 2.4×104 (mgC/L)-1s-1

NOM + hv Products 11

Concerns about UV/H2O2

• H2O2 has low UV light absorption

• Need to increase H2O2 concentration to lower EE/O

• High residual H2O2 will require treatment to reduce H2O2 such as chlorine

12

EE O

log i f

P t

V C C

Simulation Results (LPUV/H2O2) – NAIX + Dealkalization -

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

5 10 15 20

EE

O (k

Wh

/kg

al-

ord

er)

H2O

2re

sid

ua

l co

nc.

(m

g/L

)

H2O2 Dosage (mg/L)

Residual of H2O2 MtBE tBA

• 10 mg/L of H2O2 dosage would be the better choice although the optimum dosage of H2O2 is over 20 mg/L. This is because the cost required for over 20 mg/L of H2O2 dose overweigh the energy cost. • At 10 mg/L of H2O2 dosage, UV dose was calculated as 2,100 mJ/cm2. 13Li; Hokanson; Crittenden; Trussell; Minakata. Wat. Res. 2008, 43, 5045-5053

O3/H2O2 processfor MtBE removal and bromate mitigation

• Advanced oxidation process: O3/H2O2 process:

– HO2- + O3 → HO• + O2•- + O2 k = 2.2×106 M-1s-1

– H2O2 + O3 → O2 + H2O k = 0.0065 M-1s-1

– produce more HO• at higher pH due to pKa = 11.6 of H2O2

– H2O2 also scavenges HO•

• H2O2 + HO• → HO2• + H2O k = 2.7×107 M-1s

• optimum ratio: [H2O2]/[O3] = 0.5 mole/mole

• H2O2 addition keeps the O3 concentration low.

• In the presence of Br-, H2O2/HO2- reacts with HOBr/OBr- to produce Br- resulting in BrO3- formation. In addition, there is significant contribution of the reaction of O3 with Br• in regard with BrO3- formation (von Gunten and Oliveras, 1998).

14

Simulation – O3 with H2O2 process–

Simulation parameters

• MtBE = 300 ug/L

• pH = 7.6

• NOM = 1.4 mg/L

• Alkalinity = 318 mg/L as CaCO3

• initial O3 = 3 mg/L

• molar ratio: [H2O2]/[O3] = 0.5 (optimum), 0.75, 1.0

• H2O2 = 1.06, 1.59, 2.12 mg/L

• Br- = 300 ug/L

• Completely Mixed Batch Reactor (CMBR)

15

Simulation results – O3 with H2O2 process–

0.0

0.5

1.0

1.5

2.0

2.5

3.0

[O3]

(mg

/L)

[H2O2]/[O3]=0.5

[H2O2]/[O3]=0.75

[H2O2]/[O3]=1.0

0.0

0.5

1.0

1.5

2.0

0 20 40 60 80 100 120

[H2O

2]

(mg

/L)

Time (sec)

0

5

10

15

20

25

30

0

50

100

150

200

250

300

[tB

A]

(ug/

L)

[MtB

E]

(ug

/L)

MtBE tBA

0

1

2

3

4

5

6

7

0 20 40 60 80 100 120

[BrO

3-]

(u

g/L

)

Time (sec)16

17

Comparison of Adox (UV/H2O2) to Simplified-pseudo steady state model

The impact of H2O2 dosage on EE/O for trichloroethylene (TCE) destruction using H2O2/UV process (operating conditions: [TCE]0 = 100 g/L, Alkalinity = 100 mg/L CaCO3, [NOM] = 0 mg/L, UV Light Intensity = 1.04x10-6 einstein L-1 s-1 at 254 nm, reactor size = 70 L with 15.8 cm of the effective path length and the total lamp power is 160 W (assuming 20 % efficiency)

Modeling AOPs





18

Conventional Approach for Kinetic Model in AOP

1.One “hot” parent organic chemical contaminant

2.Conduct batch experiments to measure byproducts using GC/MS etc.

3.Obtain rate constant/Measure rate constant (e.g., pulse radiolysis)

4.Build kinetic model based on both experimental findings and literature-reported rate constants. Unknown rate constants are usually obtained by fitting with experimental data.

19

• UV irradiation ranging from 200 nm to 300 nm inan interval of 1 nm

• Molar extinction coefficients of TCE, H2O2 and 4types of main byproducts are measured andsimulated in an interval of 1 nm from 200 to 300nm

• pH change of the system

• Dissociation of 8 organic/inorganic acids

• 22 literature reported rate constants are used in the model

The model is a kinetic model and considers:

TCE UV/H2O2 Modeling

20

Li, Stefan, and Crittenden, 2004, ES&T 38, 6685-6693Li, Stefan, and Crittenden, 2007, ES&T 41, 1696-1703

0.E+00

2.E-03

4.E-03

6.E-03

8.E-03

1.E-02

1.E-02

0 5 10 15 20 25 30 35

Time (min)

Co

nc

en

tra

tio

n (

mo

l/L

)

exp

mod

0.E+00

2.E-04

4.E-04

6.E-04

8.E-04

1.E-03

1.E-03

0 10 20 30 40

Time (min)

Co

nc

en

tra

tio

n (

mo

l/L

)

mod

exp

0.E+00

1.E-06

2.E-06

3.E-06

4.E-06

5.E-06

6.E-06

7.E-06

8.E-06

9.E-06

0 10 20 30 40

Time (min)

Co

nc

en

tra

tio

n (

mo

l/L

)

exp

mod

0.E+00

2.E-06

4.E-06

6.E-06

8.E-06

1.E-05

1.E-05

0 10 20 30 40

Time (min)

Co

nc

en

tra

tio

n (

mo

l/L

)

mod

exp

Comparison of Modeled and Experimental Concentration Profiles 1/2

TCE

MCADCA

H2O2


21

Comparison of Modeled and Experimental Concentration Profiles 2/2

0.E+00

1.E-05

2.E-05

3.E-05

4.E-05

5.E-05

6.E-05

7.E-05

8.E-05

9.E-05

1.E-04

0 5 10 15 20 25 30 35

Time (min)

Co

nc

en

tra

tio

n (

mo

l/L

)

exp

mod

Oxalic acid

0.E+00

5.E-05

1.E-04

2.E-04

2.E-04

3.E-04

3.E-04

4.E-04

4.E-04

5.E-04

0 10 20 30

Time (min)

Co

nc

en

tra

tio

n (

mo

l/L

)

exp

mod

Formic acid

0

1

2

3

4

5

6

7

0 10 20 30 40

Time (min)

pH

exp

mod

pH


22

23

Parent compoundMajor byproducts

(yield 10-30 mole%)

Minor byproducts

(yield 2-5 mole%)

Acetone

*Stefan and Bolton, 1999

acetic, pyruvic, and oxalic acids

pyruvaldehyde

formic and glyoxylic acids

hydroxyacetone, formaldehyde

MtBE

* Stefan et al., 2000

acetone, acetic acid, formaldehyde,

tert-butyl formate (TBF), pyruvic acid,

tert-butyl alcohol (TBA), 2-methoxy-2-

methyl propionaldehyde (MMP), formic,

methyl acetate

hydroxy-iso-butylaldehyde,

hydroxyacetone,

pyruvaldehyde and hydroxy-

iso-butyric, oxalic acid

Dioxane

*Stefan and Bolton, 1998

1,2-ethanediol diformate, formic acid,

oxalic acid, glycolic acid, formaldehyde,

1,2-ethanediol monoformate

methoxyacetic acid glyoxal

TCE

* Stefan and Bolton, 2002formic acid, oxalic acid

dichloroacetic acid,

mono-chloroacetic acid

A few studies examined entire reaction mechanisms

24

Parent compound

H-atom abstraction by HO•or HO• addition

O2 addition

Uni/Bi molecular decay

HydrolysisHO• reactions

Β-scission, 1,2-H shift

Peroxyl radical mechanisms

Carbon centered radical

PeroxylRadical

Oxy radical

Intermediates (aldehydes, alcohols etc.)

Carbon centered radical

Carboxyl acid

CO2/Minerals

*Bolton, J.R.; Carter, S.R. (1994) in Aquatic and Surface Photochemistry, Lewis Publishers, Boca Raton, USA., 467-490.

General Reaction Mechanisms in AOP

The most significant observed by-products are the carboxylic acids, due to

the fact that the second order rate constants for these compounds are

much lower than those for most organics. However, if adequate reaction

time is provided, all by-products (>99% as measured by a TOC mass

balance) are destroyed.

Modeling AOPs





25

Computer based kinetic model Establish a computer-based first-principle kinetic model

of reactions that are initiated by HO• in aqueous AOPs.

Reaction Pathway Generator (Graph theory)

Reaction Rate Constant Predictor(QSARs, Quantum mechanical calculations)

Ordinary Differential Equations (ODEs) Solver

26

Reaction Pathway Generator

Reaction Rate Constant Predictor

ODE Generator and Solver

ToxicityProfiles

Toxicity Estimator

ConcentrationProfiles

A Computer-Based Kinetic Model in AOPs

Why so important?

We now know the general reaction mechanisms that HO• initiates in the aqueous phase AOPs based on a number of experimental studies.

We have a large number of datasets for reaction rate constants in the aqueous phase AOPs.

Concern about emerging contaminants

Greater than 50 million chemical compounds registered in CAS and more than 40 million chemicals are available

Is it feasible?

We now have robust tool (e.g., computational chemistry) and computational resources

We can make it feasible

27

Reaction Pathway Generator – HO• with CH3CH2OH

Pathway

Running...

CCO

----->

C0(O0(H0)C0(H0H0H0)H0H0)

9 done

initial size is : 2

Generation started, be patient pls.

below is the species list

C(O(H)C(HHH)HH)

|

O*(H)

|

C*(O(H)C(HHH)H)

|

O(HH)

|

O*(C(C(HHH)HH))

|

C*(C(O(H)HH)HH)

|

O*(O(C(O(H)C(HHH)H)))

|

the following is the reaction list

C(O(H)C(HHH)HH) + O*(H) = C*(O(H)C(HHH)H) + O(HH) [HA]

|

C(O(H)C(HHH)HH) + O*(H) = O*(C(C(HHH)HH)) + O(HH) [HA]

|

C(O(H)C(HHH)HH) + O*(H) = C*(C(O(H)HH)HH) + O(HH) [HA]

|

C*(O(H)C(HHH)H) + O(//O) = O*(O(C(O(H)C(HHH)H))) [OA]

|

O*(C(C(HHH)HH)) = C*(O(H)C(HHH)H) [OT]

|

O*(C(C(HHH)HH)) = C(//OHH) + C*(HHH) [BS]

|

C*(C(O(H)HH)HH) + O(//O) = O*(O(C(C(O(H)HH)HH))) [OA]

|

O*(O(C(O(H)C(HHH)H))) = C(//OHC(HHH))+ *OOH [PH]

|

C(//OHH) + H2O = C(O(H)O(H)HH) [HC]

|

C*(HHH) + O(//O) = O*(O(C(HHH))) [OA]

|

2*O*(O(C(C(O(H)HH)HH))) = O*(C(C(O(H)HH)HH)) *2 + O2 [PB3]

|

2*O*(O(C(C(O(H)HH)HH))) = O(C(C(O(H)HH)HH)O(C(C(O(H)HH)HH))) + O2 [PB4]

|

2*O*(O(C(C(O(H)HH)HH))) = C(C(//OH)O(H)HH) *2 + H2O2 [PB2]

|

2*O*(O(C(C(O(H)HH)HH))) = C(C(//OH)O(H)HH) + C(O(H)HHC(O(H)HH)) + O2 [PB1]

|

C(//OHC(HHH)) + H2O = C(O(H)O(H)C(HHH)H) [HC]

Total number of reactions is: 2921

Total number of species is: 243

Species lists

Reaction lists

28

Li and Crittenden, 2009 ES&T 43, 2931-2837

29

6

7

8

9

10

11

6 7 8 9 10 11

log

kH

O•in

aq

eou

s p

hase

(M

-1s-1

)

log k HO• in gaseous phase (M-1 s-1)

alkane

alcohol

ether

ester

aldehyde

Ketone

carboxylic

Nitrile

Alkylhalide

y=x

y = 0.57x + 4.39R² = 0.97

y = 0.61x + 3.54R² = 0.58

y = 0.55x + 4.1R² = 0.89

y = 0.97x + 0.026R² = 0.82

y = 4.56-36.7R² = 0.83

y = 0.98x + 0.077R² = 0.77

y = 1.88x - 8.25R² = 0.66

y = 0.65x + 2.69R² = 0.99

y = 0.96x - 0.53R² = 0.70

Rate Constant Prediction for the Aqueous Phase

Significant mechanistic differences between the gaseous and aqueous phases (e.g., effect of hydrogen bond to the oxygenated compounds, cage effect, solvation, etc.)

GCM is limited because:1. Many datasets are required to calibrate parameters2. Only deal with molecules for which all required group rate

constants and group contribution factors have been calibrated before.

3. Limited number of literature-reported experimental rate constants for other reaction mechanisms than HO•

4. Assumed that a functional group has approximately the same interaction properties under a given molecule, so that the GCM disregards the changes of the functional properties that can arise from the intramolecular environment by electronic push-pull effects, hydrogen bond formation, or by steric effects.

Application of computational chemistry (quantum mechanical calculations) for predicting reaction rate constants in aqueous phase

Looking at reaction energies (transition states) 30

Challenges still remains

31

rxn,aq aq reactants,aqG G G

G≠aq is a quasithermodynamic quantity, kcal/mol, that indicates the free

energy of the transition state Greactants,aq is the molar free energy of reactants, kcal/mol

rxn,aq rxn,gas rxn,solvationG G G

,0 0

rxn,solvation solvation solvation reactants,solvation reactants,solvationG G G G G

where

rxn,aqln k a G b

Correlation between rate constant and free energy of activation

From transition state theory (TST)

H-atom abstraction from a C-H bond of Aliphatic Saturated Compound

32

based on calculated ∆G≠based on experimental ∆G≠

Minakata and Crittenden, ES&T 2011, 45, 3479-3486

Minakata, Song, and Crittenden, ES&T, 2011, 45, 6057-6065

8

9

10

11

12

15 14

1

6

4

y = -0.418x + 21.271r² = 0.681

0

5

10

15

20

25

-6 -4 -2 0 2 4 6 8 10 12

ln k

H

∆ Gactaq,calc, kcal/mol

Neutral (G3 + COSMO-RS)-ref.16

Ionized (G4 + SMD) - This study

y = -1.386x + 27.723R² = 0.849

0

5

10

15

20

25

0.0 2.0 4.0 6.0 8.0 10.0

ln k

∆GactI , kcal/mol

Neutral

Ionized

Calibration (N=26)13 out of 14 from prediction was within difference of factor of 5

33

Oxygen addition to carbon centered radical

exp Dk k

04 /1000D lk D r N From Smoluchowski’sequation

Ф (=0.25): modification parameter

5

1.14 0.589

13.26 10l

b

DV

*CH3*CH2CH3 *CH2OH

CH3C*HOH*CH2CH2OH

*CCl3

*CH(OH)2

*CH2COCH3

CH3COOC*H2

*CH2COOCH30.0E+00

2.0E+09

4.0E+09

6.0E+09

8.0E+09

1.0E+10

1.2E+10

1.4E+10

1.6E+10

1.8E+10

2.0E+10

0.0E+00 1.0E+10 2.0E+10

kca

lc, M

-1s-1

kexp, M-1s-1

perfect fit*CH3

*CH2CH3*CH2OH

CH3C*HOH*CH2CH2OH*CCl3

Radius of molecule and molar volume are quantum mechanically calculated at B3LYP/6-311++G(3df,3pd)

34

HO• addition to C=C bond of Alkenes Peroxyl Radical Bi-decay

1-Hydroxyethylperoxyl

2-Hydroxyethylperoxyl

Hydroxymethylp

eroxyl

1-Hydroxy-1-methylethylperoxyl

Carboxymethylpe

roxyl, anion

2-

Oxopropylperoxyl

Acetoxymethylpe

roxyl

y = -0.389x + 21.492R² = 0.806

0

5

10

15

20

25

0 2 4 6 8 10 12 14ln

kDelta Gact

aq

Summary • Four different approaches have been shown to model aqueous phase advanced oxidation processes.

• A simplified pseudo-steady-state model is precise enough to examine the feasibility of the process.

• AdoxTM (UV/H2O2) simulation software can be used to design AOPs not assuming constant pH, steady-state.

• Conventional approach to establish kinetic model in AOP is time consuming and does not consider all possible by-products.

• Our under-developing computer-based kinetic model is robust for rational design of AOPs but there are still some challenges remains.

35

Acknowledgement

• National Science Foundation (NSF): 0607332 and 0854416

• Georgia Tech College of Computing, Office of Information Technology and CEE IT Services for high computational resources.

• High Tower Chair and Georgia Research Alliance at Georgia Tech

• Brook Byers Institute for Sustainable Systems

• University of Notre Dame Radiation Center and Department of Energy

36

rational design of advanced oxidation processes using ... · (1st order reaction) 1. plug flow...

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