Electrochemical Processes in Biological Systems E-Book

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Veröffentlichungsjahr: 2015

Beschreibung

The first book to provdie a comprehensive look at bioenergetics, the energy flow in living systems, by studying ion exchange and electron transfer processes in biological membranes and artificial bio-films, and how these processes contribute to developing modern biosensor and ion-sensor technology, as well as biofuel cells.

The book:

• Discusses the ion fluxes and electron transfer processes in biological membranes and artificial bio-films
• Provides an in-depth description of the processes at the interface between the membrane/film and substrate electrode
• Is the first of its kind to provide a comprehensive look at how these processes are understood in biology of living cells
• Addresses how these processes contribute to developing modern biosensor and ion-sensor technology, as well as biofuel cells

Leseprobe

CONTENTS

COVER

TITLE PAGE

CONTRIBUTORS

PREFACE

1 MODELING OF RELATIONS BETWEEN IONIC FLUXES AND MEMBRANE POTENTIAL IN ARTIFICIAL MEMBRANES

1.1 INTRODUCTORY CONSIDERATIONS

1.2 GENERAL CONSIDERATIONS CONCERNING MEMBRANE POTENTIALS AND TRANSFER OF IONIC SPECIES

1.3 POTENTIALS AND ION TRANSPORT IN ION-SELECTIVE ELECTRODES MEMBRANES

1.4 SUMMARY

REFERENCES

2 TRANSMEMBRANE ION FLUXES FOR LOWERING DETECTION LIMIT OF ION-SELECTIVE ELECTRODES

2.1 INTRODUCTION

2.2 DEFINITION OF THE DL

2.3 SIGNIFICANT REDUCTION OF THE DL

2.4 THEORETICAL DESCRIPTION OF DL

2.5 MODEL COMPARISON

2.6 INVERSE PROBLEM

2.7 IONS OF DIFFERENT CHARGES

2.8 SUMMARY

REFERENCES

3 ION TRANSPORT AND (SELECTED) ION CHANNELS IN BIOLOGICAL MEMBRANES IN HEALTH AND PATHOLOGY

3.1 ION CHANNELS: STRUCTURE, FUNCTION, AND METHODS OF STUDY

3.2 ION CHANNELS IN HEALTH AND PATHOLOGY

ACKNOWLEDGMENTS

REFERENCES

4 ELECTRICAL COUPLING THROUGH GAP JUNCTIONS BETWEEN ELECTRICALLY EXCITABLE CELLS

4.1 MOLECULAR CHARACTERISTICS OF GAP JUNCTIONS

4.2 DISTRIBUTION OF GJS IN THE BRAIN

4.3 ELECTRICAL SIGNALING THROUGH GJS

4.4 ROLES OF GJ-MEDIATED ELECTRICAL SIGNALING IN BRAIN FUNCTION

4.5 PLASTICITY AND MODULATION OF GAP JUNCTIONAL COUPLING

4.6 CLINICAL RELEVANCE

4.7 CONCLUDING REMARKS

ACKNOWLEDGMENTS

REFERENCES

5 ENZYME FILM ELECTROCHEMISTRY

5.1 INTRODUCTION

5.2 THE FILM ELECTROCHEMISTRY EXPERIMENT

5.3 ENZYME FILM ELECTROCHEMISTRY: THE BASICS

5.4 MOLECULAR DETERMINANTS OF ENZYME ACTIVITY

5.5 NONTURNOVER SIGNALS

5.6 CONCLUSION

ACKNOWLEDGMENTS

REFERENCES

6 PLANT PHOTOSYSTEM II AS AN EXAMPLE OF A NATURAL PHOTOVOLTAIC DEVICE

6.1 INTRODUCTORY REMARKS ON PHOTOSYNTHESIS

6.2 PHOTOSYNTHETIC EXCITATION ENERGY TRANSFER

6.3 PHOTOSYNTHETIC ELECTRON AND PROTON TRANSPORT

6.4 PERSPECTIVES OF BIOMIMETIC APPLICATIONS

ACKNOWLEDGMENTS

REFERENCES

7 ELECTROCHEMICAL ACTIVATION OF CYTOCHROME P450

7.1 INTRODUCTION

7.2 HOMOGENEOUS SYSTEMS: SMALL-MOLECULE ELECTROCHEMICAL MEDIATORS

7.3 HETEROGENEOUS SYSTEMS: SURFACE-CONFINED P450 FILMS

7.4 THOUGHTS ABOUT THE FUTURE OF P450 ELECTROCHEMISTRY

ACKNOWLEDGMENTS

REFERENCES

8 MOLECULAR PROPERTIES AND REACTION MECHANISM OF MULTICOPPER OXIDASES RELATED TO THEIR USE IN BIOFUEL CELLS

8.1 INTRODUCTION

8.2 MCOs IN SOLUTION: STRUCTURE AND MECHANISM

8.3 MCOs IN ELECTROCHEMISTRY

8.4 FUNCTIONALITY OF IMMOBILIZED AND SOLUBILIZED MCOs

8.5 CONCLUDING COMMENTS

ACKNOWLEDGMENTS

REFERENCES

9 ELECTROCHEMICAL MONITORING OF THE WELL-BEING OF CELLS

9.1 ELECTROCHEMICAL MONITORING

9.2 CELL DEATH: ELECTROCHEMICAL CYTOTOXICITY MEASUREMENTS

9.3 CURVATURE/SIZE EFFECT ON DENATURATION OF PROTEINS

9.4 COVALENT ANCHORING: CHEMISTRY ON GOLD

9.5 COOPERATIVITY ON GOLD: MEASURING WF

9.6 COOPERATIVE CELL IMPRINTS

REFERENCES

10 ELECTROCHEMICAL SYSTEMS CONTROLLED BY ENZYME-BASED LOGIC NETWORKS

ACKNOWLEDGMENT

REFERENCES

INDEX

END USER LICENSE AGREEMENT

List of Tables

Chapter 03

TABLE 3.1 Solute composition of extracellular fluid, cytoplasm and mitochondria.

Chapter 07

TABLE 7.1 Electrochemical mediators for HTP catalysis.

TABLE 7.2 Rates and total turnovers for the electrochemical biocatalytic reactions.

TABLE 7.3 Thermodynamic parameters for reduction of selected heme proteins.

Chapter 08

TABLE 8.1 Members of the MCO family separated into two substrate classes: organic oxidases and metalloxidases.

TABLE 8.2 Comparison of the redox potential of T1 copper sites with and without an axial methionine ligand. Entries in bold are T1 sites in MCOs.

TABLE 8.3 Immobilization method and performance of MCO-modified electrodes (in DET contact) described in Section 8.3.2.

List of Illustrations

Chapter 01

FIGURE 1.1 Dependence of M

+

and A

−

ions concentrations in the membrane (top figure) and Donnan potential (bottom figure) on concentration of salt MA in solution, for cation-exchanging membrane with ion-exchange site concentration

X

=10

−3

M.

FIGURE 1.2 Comparison of (a) boundary potential profile and (b) approached steady-state Nernst–Planck–Poisson potential profile [77].

FIGURE 1.3 Contribution (in %) to boundary potential (black and horizontal lines) and inner membrane potential (grey and vertical lines) calculated according to the Nernst–Planck–Poisson model, for [M

+

]=10

−4

and [M

+

]=10

−10

M, in the presence of interfering ion ([N

+

]=10

−3

M) and in the presence of R

−

anions in the membrane [77], for diffusion coefficients: (a)

D

M

D

R

=1·10

−7

,

D

N

=1·10

−6

cm

2

·s

−1

; (b)

D

M

=1·10

−6

,

D

R

D

N

=1·10

−7

cm

2

·s

−1

; =10

−1

, =10

−2

, =10

−1

, for X

−

anions =X=0,

k

N

/

k

M

=0.1.

Chapter 02

FIGURE 2.1 The statistical detection limit.

FIGURE 2.2 Definition of the lower detection limit according to the IUPAC.

FIGURE 2.3 Definition of the lower detection limit according to the IUPAC and the new extended definition.

FIGURE 2.4 Schematic representation of the processes influencing the lower detection limit of ISEs based on an ionophore (

L

) forming 1:1 complexes with the monovalent primary (I

+

) and interfering ions (J

+

). Gradients are generated in the aqueous Nernstian phase boundary (thickness

δ

aq

) because of coextraction of I

+

and A

−

from the inner solution (a) or partial exchange of primary ions by interfering ones at the sample or reference side (b or c, respectively).

FIGURE 2.5 Response of two Pb

2+

ISEs with the same membrane but different internal electrolytes (22–23°C). Conventional (empty symbols): 1:1 mixture of 10

−3

M PbCl

2

and 0.1M MgCl

2

. New (full symbols): 1mL of 0.1M Pb(NO

3

)

2

in 100mL of 0.05M EDTA-Na

2

; measured pH 4.34. Calculated activities: 10

−12

M Pb

2+

, 10

−1

M Na

+

.

FIGURE 2.6 Chronopotentiometric curves (a) and calibration curves (b) obtained for a Ca ISE polarized by different cathodic currents, in solutions with different concentrations of CaCl

2

containing 0.001M KCl background. (a) Curve 1, 10

−5

M, 16.0nA/cm

2

; curve 2, 10

−6

M, 16.0nA/cm

2

; curve 3, 10

−7

M, 16.0nA/cm

2

; curve 4, 10

−8

M, 20.0nA/cm

2

; curve 5, 10

−9

M, 30.3nA/cm

2

; curve 6, 10

−10

M, 43.8nA/cm

2

. (b) Open circles refer to zero-current potential values (taken immediately before current is on). Filled circles refer to potential values taken immediately after the positive ohmic drop.

FIGURE 2.7 Analytical procedure of lead determination in synthetic sample. (a) Three chronopotentiometric curves recorded with the two arbitrarily chosen current densities corresponding to pPb=7.2 and 8.5, and the third one corresponding to the estimated actual lead activity. (b) Calibration curve recorded using tuned polarization in solutions from 10

−7

to 10

−9

mol/dm

3

of Pb

2+

and current-off potentials recorded in a sample of 1.07×10

−8

mol/dm

3

Pb

2+

with ISE polarized with the three respective currents (labeled in the figure), all with 10

−3

mol/dm

3

KNO

3

background.

FIGURE 2.8 Methodology used in models of potentiometric ion sensors response.

FIGURE 2.9 Calibration curves at low concentrations for electrode 1. The points correspond to experimental values recorded in 0.1M NaNO

3

media. (a) Potential reading after 30min at 25°C, (b) after 15min with 4% ascorbic acid added at 20°C, (c) after 30min with 4% ascorbic acid added at 20°C, and (d) after 24h with 4% ascorbic acid. The lines shown are calculated for the following parameters:

K

so

=9·10

−16

; (a)

β–α

=−8·10

−8

,

γ

=0; (b)

β–α

=0,

γ

=0; (c)

β–α

=0,

γ

>0; (d)

β–α

=0,

γ

=1.5·10

−7

.

FIGURE 2.10 Response pattern of bromide liquid membrane electrode, Aliquat 336S-Br, and PVC: (a) unstirred solution and (b) maximal stirring rate (

v

3

). Experimental points, O-Cl

−

, x–Br

−

, O-SCN

−

; solid lines, theoretical curves calculated from Equation (2.22); dashed lines, theoretical curves calculated from the Jyo and Ishibashi equation. Set of parameters: (a)

x

Δ

(0)=0.14,

C

=5.3×10

−4

; (b)

x

Δ

(0)=0.32,

C

=9.0×10

−5

.

FIGURE 2.11 Scheme of a 2-layer system between two solutions.

c

i

L

and

c

i

R

are the concentrations of the

i

th component in the solution on the left and right side, respectively.

FIGURE 2.12 The influence of the concentration of preferred ion in the inner solution. Calibration curves obtained using the (a) SDM1, (b) TDM-E, (c) TDM-EC, and (d) NPP models.

FIGURE 2.13 Influence of measuring time for the ISE with preferred ion inner solution concentration 10–10 obtained using the TDM-EC (left) and the NPP (right) model. (a) Equal diffusion coefficients (above), (b) different diffusion coefficients

D

I

=10·

D

J

(below). Steady-state curves marked with empty circles.

FIGURE 2.14 The time–concentration–detection limit maps obtained using the TDM-EC (left) and the NPP (right) model. (a) Equal diffusion coefficients (above), (b) different diffusion coefficients

D

I

=10·

D

J

(below).

FIGURE 2.15 Time concentration map with all the individuals (points) of HGS. The symbols , , and denote the individuals of the first, second, and third populations, respectively.

FIGURE 2.16 The individuals (points) of HGS in (D1, c1R, time) space. The symbols , , and denote the individuals of the first, second, and third populations, respectively.

FIGURE 2.17 Calcium electrode with a primary ion concentration in the inner solution equal to (a) 10

−2

M, (b) 3×10

−8

M, (c) 1.3×10

−10

M, and (d) 3×10

−12

M. Experimental calibration curves (top) and theoretical curves obtained using the NPP model (bottom).

Chapter 03

FIGURE 3.1 Black lipid membrane formation. Lipids dissolved in hydrocarbon are painted over the septum separating two electrode compartments. The lipids spontaneously form a lipid bilayer. If a proteoliposome is added to one side of the bilayer, it will incorporate into the bilayer and thereby allow the electrophysiological properties of the incorporated channel molecule to be measured.

FIGURE 3.2 Purification of integral membrane proteins. To obtain an active channel molecule, one must dissolve the bilayer while not exposing the hydrophobic portion of the molecule to the aqueous environment. This is done by dissolving membrane proteins in long hydrophobic chain detergents that substitute for lipid molecules. Then, the dissolved proteins are separated by chromatography. When pure protein is obtained, detergent molecules are slowly replaced by lipids during dialysis. At the end of the purification, proteoliposomes are obtained.

FIGURE 3.3 Four patch-clamp configurations. A micropipette supplied with a silver chloride electrode is brought near the surface of a cell on an inverted microscope. Mild suction is then applied. A piece of membrane is aspirated into the pipette, often forming a gigaseal (i.e., a seal with gigaohm resistance). This configuration is called “cell attached,” and it allows channels in the small area beneath the pipette to be studied. If a short electric impulse of high amplitude is then applied, the membrane under the pipette perforates and the “whole-cell” configuration is obtained. The “whole-cell” configuration allows simultaneous measurements of ions flowing through the whole-cell membrane, while internal solution is replaced with the pipette filling solution. By applying mild suction to the “whole-cell” configuration, it is possible to achieve the “outside-out” configuration. By taking the pipette with the cell in the “cell-attached” configuration out from the solution to the air and back to the solution, the “inside-out” configuration is achieved.

FIGURE 3.4 Amplitude as a function of opening time for different types of molecules transporting ions across the cell membrane. The two lines represent the detection limits of the BLM and patch-clamp methods for single-channel events. Below the limit, other methods allowing simultaneous measurements of multiple microchannels, transporters, or ion pumps must be used.

FIGURE 3.5 Single-channel recordings. (a) The effect of complex ATP/Mg (blocker) and BMS 191096 (opener) on the mito-KATP channel from a bovine heart. (b) The effect of paxilline (blocker) on the mito-BKCa channel from astrocytoma cells (Piotr Bednarczyk unpublished results).

FIGURE 3.6 The events leading to insulin secretion from pancreatic β-cells. 1. The ATP concentration in β-cells is low. Plasma membrane K

ATP

channels are open. K

+

ions flow out from the cytoplasm leading to the formation of a high negative membrane potential Δ

ψ

. 2. Glucose concentration outside the cell rises. 3. Glucose is transported into the cell. 4. Glucose reaches mitochondria where it is used to produce ATP. 5. The concentration of ATP inside the cell rises and blocks the K

ATP

channel. 6. K

+

ions no longer flow out from the cell and the membrane potential becomes less negative. 7. The rising membrane potential opens Ca

v

channels and Ca

2+

ions flow into the cell. The increased calcium concentration in the cytoplasm opens calcium-dependent calcium channels, which release more calcium ions from internal cellular stores (not shown). 8. Via a complex series of events (not shown), calcium ions lead to the secretion of insulin stored in intracellular vesicles. 9. Calcium ions open BK channels (and/or voltage-dependent potassium channels K

v

). K

+

ions flow out from the cell, restoring the high negative membrane potential and terminating the insulin secretion.

FIGURE 3.7 Mitochondria produce ATP on the expense of energy stored in protons. The oxidative chain expels protons that return via ATP synthase.

FIGURE 3.8 As the ATP concentration in the cytoplasm is not high, mito-K

ATP

channels are partly open. Potassium influx into the mitochondrial matrix increases ΔpH. If the calcium concentration in the cytoplasm becomes high, mito-BK

Ca

channels open leading to the production of ΔpH. Calcium ion influx via mito-Ca channels also increases ΔpH (calcium preconditioning). It is likely that hydroxyapatite is formed from apatite, calcium, and hydroxyl ions. Formation of hydroxyapatite produces large pH buffering capacity of the mitochondrial matrix.

FIGURE 3.9 During ischemia, the oxidative chain is stopped, but ATP synthase is still working to produce ATP at the beginning due transformation of hydroxyapatite to apatite and then at the expense of ΔpH. The electroneutrality of the later process is maintained by an outward flux of calcium ions via mito-Ca channels. The higher the amount of hydroxyapatite and ΔpH, the longer mitochondria produces ATP during ischemia.

FIGURE 3.10 Reperfusion (i.e., resumption of the oxygen supply) restarts the oxidative chain, which expels protons from the matrix. As both potassium channels and the calcium channel are open, the expulsion of protons increases ΔpH rather than Δ

ψ

.

FIGURE 3.11 (a) The sealed tissue layer is placed between the two compartments, and ions moving across can be measured by radioisotopes or by means of voltage clamp or current clamp techniques [62]. (b) The isolated sweat gland impaled on microcapillary is used to measure ion transport during sweat production [77].

FIGURE 3.12 Ion transporters involved in cell pH homeostasis. (a) pH too high. (b) pH too low. (CAII—carbonic anhydrase).

FIGURE 3.13 Ion channels and transporters involved in cell volume homeostasis. (a) Volume too small. (b) Volume too large.

FIGURE 3.14 Electrochemical considerations. (a) Chloride and bicarbonate currents flowing via CFTR channels for different potential difference between apical fluid and cytoplasm. (b) Chloride and bicarbonate currents flowing via CaCC secretion phase of human bronchial apical membrane (four chloride anions are accompanied by one bicarbonate anion). (c) During the absorptive phase, chloride anions flowing into the cell are exchanged for bicarbonate anions flowing out from the cell via CFTR channel. For calculations, cytoplasm chloride and bicarbonate concentrations [Cl]

cyt

 = 20 mM and [HCO

3

]

cyt

 = 15 mM were accepted and [Cl]

asl

 = 116 mM and [HCO

3

]

asl

 = 25 mM for apical surface liquid. Selectivity ratio Cl

−

/HCO

3

−

 = 4 for CFTR and Cl

−

/HCO

3

−

 = 2 for CaCC were adopted. The potential difference is between apical fluid and cytoplasm.

FIGURE 3.15 The mechanism of water secretion in human bronchial epithelium. Fluid transported to the apical face is rich in chloride ions flowing via CaCC.

FIGURE 3.16 The mechanism of water absorption in human bronchial epithelium involves both ENaC and CFTR channels. During the absorptive phase, there is an exchange of chloride ions moving into the cell and bicarbonate ions moving out via CFTR channel. The defective CFTR channel in cystic fibrosis (CF) leads to low bicarbonate concentration in bronchial fluid causing condensation of mucus in the lungs—striking agreement with Quinton’s [59] “bicarbonate” hypothesis of mucus condensation in CF.

Chapter 04

FIGURE 4.1 (a) A schematic representation of the general gap junction (GJ) structure. The GJ plaque connecting two closely apposed cells (left panels) allows bidirectional flux of ions and small biomolecules through up to thousands of individual GJ channels arranged in the plaque. Each GJ channel is composed of two GJ hemichannels or connexons, each one crossing the plasma membrane of one connected cell (right); the membranes are separated from each other by a 2–4 nm gap of extracellular space. The channels are, in turn, composed of six connexin proteins, arranged in a circular formation with a pore in the middle. (b) Empirical determination of GJ conductance between two coupled neurons, where a GJ is present at a distal dendritic location. Voltage changes (ΔV) in two coupled cells are compared during injection of a negative command current (I

cmd

) step into cell 1, and the steady-state coupling coefficient (CC) is defined as the ratio of voltage changes in cell 2 and cell 1. (c) Equivalent circuit roughly approximating the electrical elements contributing to the measured steady-state CC. In addition to the somatic (input) resistances (R

soma

), the anatomical location of the GJ on dendrites and the dendritic cable properties (axial resistivity (R

ax

) and leak conductances (G

leak

)) are a major determinant of the coupling efficacy. Notably, if a GJ is residing on a tip of a long dendrite, the leak conductance through dendritic channels will be a major factor. The differences in relative positions of GJs on dendrites will result in coupling asymmetry, due to the mismatches in total resistances in the coupled cells; in general, the coupling will be stronger from a lower- to higher-resistance cell. (d) The neuronal capacitance (C

cell

in panel B) together with the resistances determines the time constant of the coupled neurons and results in the GJ communication acting as first-order low-pass filter for signals. As a result, neuronal electric signals are differentially transmitted based on their temporal features; a strongly depolarizing and fast action potential in prejunctional cell (left) may result in a slow hyperpolarization in the postjunctional cell (right). (e) A schematic drawing depicting the mechanism recently shown to modulate the GJ coupling among inferior olivary neurons. The sites of GJ connections are targeted by axonal terminals, which, upon activation, release neurotransmitters that activate shunting conductances on both sides of the GJ, thereby greatly decreasing intersomatic signal transmission.

Chapter 05

FIGURE 5.1 Enzyme film electrochemistry. (a) Schematic illustration of the nonturnover scenario for an enzyme with two redox cofactors, namely, the relay (open circle) and active site (closed circle) as indicated (left). The cyclic voltammetric response of current (

i

) versus potential (

E

) anticipated for a single redox cofactor undergoing reversible electron transfer where

E

p

indicates the peak potential for the oxidative (ox) and reductive (red) peaks and

hhw

indicates the half-height width of the oxidative peak (right). (b) Schematic illustration of the catalytic scenario for the enzyme in (a) (left). The catalytic current profiles that would be observed during cyclic voltammetry (right) for oxidative (continuous), reductive (dashed), and bidirectional (dotted) catalysis. The oxidative and reductive catalytic currents (

i

cat

) for each response are indicated. See text for details.

FIGURE 5.2 The three-electrode cell configuration typically used for protein film electrochemistry experiments with a PGE working electrode surface. The electrode–potentiostat interface is denoted by asterisks.

FIGURE 5.3 Nitrate dependence of the catalytic PFE response for

P. pantotrophus

NarGH. (a) Variation of catalytic current magnitude with nitrate concentration at the potentials as indicated. (b) Cyclic voltammograms recorded at 20 mV s

−1

in the presence of nitrate for experiments performed in 25 mM Mes and 50 mM Na

2

SO

4

, pH 6, 20°C, with electrode rotation at 3000 rpm. Nitrate concentrations are 5, 10, 20, 40, 80, 150, 30, and 760 μM. (c) Dependence of

K

M

and

i

max

on electrochemical potential.

FIGURE 5.4 Inhibition of the nitrite reductase activity of

E. coli

NrfA by cyanide as revealed by PFE. (a) Cyclic voltammogram at 30 mV s

−1

in the presence of 20 μM nitrite and consecutive voltammograms after the addition of 3 μM KCN as indicated. (b) Chronoamperometry in 20 μM nitrite with and without KCN as indicated. Both experiments performed in 50 mM Hepes and 2 mM CaCl

2

, pH 7, 20°C, with electrode rotation at 3000 rpm.

FIGURE 5.5 Nonturnover peaks displayed by the soluble domain of NapC during cyclic voltammetry of a protein film at the indicated pH values (gray area). Fit (continuous lines) of the peaks to the response from the sum of four independent centers acting as single-electron (

n

 = 1) sites (broken lines). Reduction potentials of the four hemes taken as the average values from the oxidative and reductive fits are −35, −91, −146, and −222 (all ±10) mV at pH 7 and −56, −119, −160, and −239 (all ±10) mV at pH 8. Cyclic voltammetry performed at 50 mV s

−1

, 20 °C.

Chapter 06

FIGURE 6.1 Model of the structure of the light-harvesting pigment–protein complex of photosystem II based on crystallographic data deposited in PDB (ID: 1RWT). The basic constituents of the complex are marked. See the text for more explanations.

FIGURE 6.2 A comparative Jablonski diagram of the energy levels of chlorophyll

a

and of a carotenoid with indicated basic photophysical processes, including the singlet–singlet excitation energy transfer from carotenoid to chlorophyll (considered as antenna function) and the triplet–triplet excitation energy transfer from chlorophyll to carotenoid (considered as photoprotection). A stands for light absorption, D thermal energy dissipation, and ISC intersystem crossing. For simplicity, the bands B and Q of chlorophyll are represented by single energy levels. See the text for more explanations.

FIGURE 6.3 The schematic representation, on the redox potential scale, of the electron transport in photosystem II. Typical time-scale parameters of individual electron transfer steps are also presented. See the text for further explanations.

FIGURE 6.4 Schematic model of the photosynthetic electric charge transport within the thylakoid membrane. See the text for explanations.

FIGURE 6.5 Flash-induced oxygen yield pattern in photosystem II particles isolated from tobacco, expressed as amplitudes of the polarographic signal. See Ref. [16].

FIGURE 6.6 Simplified scheme of the thylakoid membrane with indicated proton flows. PSII, photosystem II; OEC, oxygen-evolving complex; PQ, plastoquinone pool.

FIGURE 6.7 Simplified scheme of the dye-sensitized solar cell based on the photosynthetic antenna complexes.

Chapter 07

FIGURE 7.1 Chemical reactions catalyzed by P450.

FIGURE 7.2 Canonical mechanism for cyt P450.

FIGURE 7.3 Cyclic voltammogram of hBM3–DDAPSS film at a basal plane graphite (BPG) electrode. Recorded in 0.05 M KPi/20 mM KCl, pH 7, at a scan rate of 0.5 mV s

−1

.

FIGURE 7.4 Levich plots for wt (a) and 1-12G (b) hBM3 in DDAPSS on BPG. Straight lines represent the theoretical dependence of

i

L

on angular velocity assuming a two- and four-electron process. Dashed lines represent best fits to Equation (7.4), assuming respective values of

n

and

k

obs

of 2.7 and 1.4 × 10

6

 M

–1

 s

–1

(wt) and 4.7 and 1 × 10

5

 M

–1

 s

–1

(1-12G).

FIGURE 7.5 Koutecky–Levich plots for wt (a) and 1-12G (b) hBM3 in DDAPSS on BPG. Solid lines correspond to response calculated for

n

 = 2 and

n

 = 4.

FIGURE 7.6 Absorption spectra of hBM3 in solution and in DDAB on glass.

FIGURE 7.7 Temperature dependence of the FeIII/II redox couple of hBM3 in DDAB films on BPG. Voltammograms were recorded in 50 mM KP

i

/50 mM KCl, pH 7 buffer.

FIGURE 7.8 Difference spectrum of the ferrous hBM3—CO complex in DDAB two minutes after incorporating hBM3—CO into the film.

FIGURE 7.9 IR spectra of the ferrous hBM3 complex in the absence and presence of DDAB (2.5 mM in 50 mM KP

i

, pH 7).

FIGURE 7.10 Hydrogen bonding to the proximal cysteine sulfur reduces the electron density around the iron center. As the CO stretching frequency in ferrous hBM3—CO depends on π-backbonding from the metal center, it is a convenient reporter for changes in the relative push effect of the thiolate ligand.

FIGURE 7.11 Direct electrochemical oxidation pathways and the resulting heme species.

FIGURE 7.12 Cyclic voltammogram of P450 CAM in DDAB at a BPG electrode in 50 mM KP

i

, pH 8.

FIGURE 7.13 Rebound mechanism for metal–oxo C—H bond activation. The key O—H bond is highlighted.

FIGURE 7.14 Thermodynamic cycle for calculating D(O—H) for Fe(III)—OH

2

.

FIGURE 7.15 Schematic representation (top) and cyclic voltammogram (bottom) of pyrene-wired hBM3 to BPG electrode. Integration of the CV trace yields a surface coverage of 1.2 pmol cm

−2

or approximately 40% monolayer coverage based on the heme-protein dimensions.

FIGURE 7.16 Crystal structure of the cytochrome P450 BM3 heme domain. The heme and the position of the amino acid (aa) substitutions to surface cysteines are shown.

FIGURE 7.17 (a) Distance dependence of

k

° for the FeIII/II couple of hBM3 mutants as a function of surface cysteine/heme spacing. The data suggest that systems in which

k

° is greater than ~10 s

–1

exhibit 4e

–

dioxygen reduction, while those with slower rates result primarily in 2e

–

reduction to peroxide. (b) Calculated activationless (–Δ

G

° = 

λ

) ET tunneling times for hBM3 mutants based on a heme reorganizational energy,

λ

, of 0.8 eV. The straight lines correspond to theoretical activationless tunneling times assuming

β

 = 1 Å

–1

(top) and 1.3 Å

–1

(bottom).

FIGURE 7.18 Levich plots for hBM3 387 (diamonds, Ref. [14]), 62 (triangles), and 383 (squares). Dashed lines corresponding to current densities predicted for

n

 = 2 and

n

 = 4 are shown for comparison.

Chapter 08

FIGURE 8.1 The structure of the MCO active site with arrows marking the flow of substrate, electrons (e

−

), and O

2

.

FIGURE 8.2 EPR and absorption spectra of

Rhus vernicifera

laccase highlighting the representative spectral features of copper sites in the MCOs.

FIGURE 8.3 Comparison of the T1 Cu site in hCp (PDB: 1KCW) with an axial methionine that is redox active near the substrate binding site (a) with that of

M. albomyces

fungal laccase (PDB: 3FU8) that does not have a methionine (b).

FIGURE 8.4 Trinuclear copper cluster (TNC) active site structure with residue numbering according to the Fet3p sequence.

FIGURE 8.5 Electronic structure of the resting TNC.

FIGURE 8.6 Cu K-edge X-ray absorption spectra of deoxy-Hc (a) and T2D laccase (b) and their reactions with O

2

.

FIGURE 8.7 Energy of O

2

binding to the reduced T3 site with

S

 = 0 in closed circles and

S

 = 1 in open circles and Hc site with

S

 = 0 in closed triangles and

S

 = 1 in open triangles.

FIGURE 8.8 Potential energy surfaces for deoxy-Hc and deoxy-T3 sites as a function of Cu—Cu distance (dashed lines show electrostatic interactions between the two Cu(I) centers).

FIGURE 8.9 Comparison of the constrained structures of deoxy-Hc (PDB code 1JS8) and deoxy-T3 (PDB code 1GYC).

FIGURE 8.10 Correlation of log(kcat/Km) with Δ

E

(= 

E

T1site

 − 

E

Substrate

) at pH = 5.0.

FIGURE 8.11 Crystal structures of (a) Ma Lc with DMP bound in the substrate binding sites near the T1 Cu (PDB, 3FU8) and (b) hCp with dication bound to substrate site (PDB, 1KCW) and another view highlighting the ET pathway from substrate to T1 through the hydrogen bond of E272 and H1026 (c).

FIGURE 8.12 Single-electron transfer to the T1 from phenolic substrate in the organic oxidases (left) and for the Fe(II) the ferroxidases (right) with Fet3p sequence numbers.

FIGURE 8.13 Superexchange pathway of the blue copper site: (a) RAMO superimposed on part of the crystal structure of a MCO (b) π-to-σ hole delocalization between the T1 and the T3 site (c) superexchange pathways through a Cys—His molecular orbital.

FIGURE 8.14 The Raman spectrum of T1 Cu of T2D Lc with the T3 site in both oxidized and reduced states.

FIGURE 8.15 Schematic of the O

2

reactivity of both native and T1D/T1Hg forms of the MCOs and the cleavage of the O—O bond.

FIGURE 8.16 (a) Calculated geometric structures of PI with and without D94. The PI structure without D94 (left) has both T3 Cu’s oxidized and the T2 Cu reduced, while in the structure with D94 (right), the T3B and T2 are oxidized and the T3A is reduced. (b) Contours of the α-LUMO (based on the T2 ) and the β-LUMO (based on the T3B ) of PI + D94.

FIGURE 8.17 Peroxide to Cu(II) charge transfer absorption spectrum of oxy-Hc and PI.

FIGURE 8.18 Stopped flow absorption spectra (top) and rapid freeze quench MCD spectra (a), Cu K-edge XAS spectrum (b), variable field behavior at low T of the MCD spectra (c), low-temperature X-band EPR (d), temperature dependence of the MCD spectra at high field (e), and plot of temperature dependence of MCD intensity at 25,000 cm

−1

of NI.

FIGURE 8.19 Orientation of electron spins in the spin-frustrated ground state of NI (a) and the calculated geometric structure of NI (b).

FIGURE 8.20 Calculated structures of PI, PI+e, and NI (a). 2D potential energy surface of the reductive cleavage of the O—O bond (b). Schematic of triangular topology of the TNC and depiction of the frontier molecular orbitals relevant in O—O cleavage. Note that T2 and T3α transfer two electrons into the peroxide σ* orbital, while T3β is oxidized and acts as a Lewis acid in stabilizing the σ* orbital.

FIGURE 8.21 Schematic showing the conversion of NI to resting oxidized TNC marking the position of the oxygen atoms from dioxygen (top) and geometric structures and energies for the doubly protonated form of NI rotating the μ

3

OH from inside to outside the cluster (bottom).

FIGURE 8.22 Mechanism of dioxygen reduction to water by the multicopper oxidases. Bold arrows indicate the steps that take place in the catalytic cycle. Black arrows indicate steps that can be experimentally observed but are not a part of catalysis. The dashed arrows at the right indicate the transfer of an electron from the T1Cu to the T2 to generate PI+e and the fascicle cleavage of the O—O bond due to the FMOs of the TNC.

FIGURE 8.23 Anaerobic CV of TtBOD immobilized on an SPGE electrode. Circles represent enzymatic current obtained by subtraction of background spectrum. pH 7.0, 0.1 M phosphate, 100 mV s

−1

.

FIGURE 8.24 Ratio of peak-current dependence on scan rate for RvL under anaerobic conditions.

FIGURE 8.25 Schematic representation of liquid-induced shrinkage of CNTFs resulting in efficient entrapment of enzyme. CNTF-modified electrodes can be handled with tweezers, as illustrated in top right corner.

FIGURE 8.26 (a) Rotation rate dependence on catalytic current density for immobilized CueO. 500 (top curve), 1000, 2000, 3000, 4000, 6000, and 8000 rpm (bottom curve). (b) Current density versus square root of angular velocity (at 0 mV), fit to a four-electron transfer process.

FIGURE 8.27 Polarizations of TvL-modified redox hydrogel with Os redox complex via long (1) and short (2) linkers. Platinum electrode under similar conditions is incorporated for comparison (3).

FIGURE 8.28 (a) Effect on electrocatalytic O

2

reduction of Cl

−

addition to

T. hirsuta

laccase in DET with the electrode. Arrows indicate the addition of chloride ions with the final concentration in mM listed above. (b) Effect of Cl

−

addition to ABTS-mediated electrocatalytic O

2

reduction. Background DET current is approximately 5 μA and is seen to be inhibited by the addition of F

−

.

FIGURE 8.29 Optimized structure of fluoride binding to a fully oxidized resting TNC.

Chapter 09

FIGURE 9.1 SEM pictures of PC12 cells on PCL fibers secreting thin fibers as new components of the extracellular matrix [1].

SCHEME 9.2  Visual presentation of cell addition, adhesion, anchorage, spreading, and mitosis.

FIGURE 9.2 EIS results (measuring the resistance only): (a) blank control, (b) cell adhesion, (c) toxin added from the beginning of the experiments (no cell adhesion), and (d) toxin added after 20 h (cell adhered).

FIGURE 9.3 Open-circuit potentiometry results for addition of the medium (I), cell adhesion (II), and cells leaving the surface (III) due to the addition of the Triton X-100 toxin. The dotted line is a control without cells. Also, pH was monitored to be stable during the I–III events.

FIGURE 9.4 Redshift observed at various stages in experiment. The squares show the redshift upon protein adsorption to the nanosphere in phosphate buffer solution, the circles show the redshift (relative to room temperature) as the sample is heated from 45 to 80°C, and the triangles show the difference between room temperature measurements before and after a complete heating cycle.

FIGURE 9.5 Conformational assessment if surface-bound BSA onto hydrophilic surface. , random/extended; Δ, helix; , sheet/turn.

FIGURE 9.6 Open-circuit potential of gold surface in PBS and albumin solution. Albumin concentration: 0.1 mg mL

−1

.

FIGURE 9.7 Potential shifts of Au and Ag substrates under open-circuit situation in acetonitrile 0.1 M LiClO

2

solution after addition of decanethiol (a) or dipropyl disulfide (b).

FIGURE 9.8 Cooperative effect through a mixed organic layer. (a) Small dipoles pointing away from the surface and (b) large dipoles pointing toward the surface.

FIGURE 9.9 Measured contact potential differences (plotted as electron affinity) versus the dipole moments of the free molecules. The end groups of the monolayer compounds indicated in the figure.

FIGURE 9.10 Surface imprinting process and detection of the analytes. (a–c) Formation of the layer, (d) wash, and (e–f) binding of the BSA analyte and nonbinding of the Hg control.

FIGURE 9.11 Potential response of myoglobin sensor to (a) the mixture of myoglobin, hemoglobin, and ovalbumin and (b) to hemoglobin and ovalbumin as a function of concentration of single component in the solution.

Chapter 10

FIGURE 10.1 Scheme showing the general concept of interfacing enzyme-based logic systems with signal-responsive polymers operating as “smart” chemical actuators controlled by the gate output signals.

FIGURE 10.2 The biochemical logic gates with the enzymes used as input signals to activate the gate operation: the absence of the enzyme is considered as “

0

” and the presence as “

1

” input signals. The

Reset

function was catalyzed by urease. (a) The

AND

gate based on GOx- and Inv-catalyzed reactions. (b) pH changes generated

in situ

by the

AND

gate upon different combinations of the input signals: (a) “

0

,

0

”; (b) “

0

,

1

”; (b) “

1

,

0

”; and (c) “

1

,

1

.” Inset: bar diagram showing the pH changes as the output signals of the

AND

gate. (c) The truth table of the

AND

gate showing the output signals in the form of pH changes generated upon different combinations of the input signals. (d) Equivalent electronic circuit for the biochemical

AND/Reset

logic operations. (e) The

OR

gate based on GOx- and Est-catalyzed reactions. (f–h) The same as (b–d) for the

OR

gate.

FIGURE 10.3 The signal-responsive membrane coupled with the enzyme-based logic gates. (A) The schematic representations of a single pore of the polyelectrolyte membrane switched between the closed (a) and open (b) states. (c) The structure of the alginate hydrogel constituted of D-mannuronic acid and L-guluronic acid residues cross-linked with divalent ions (Ca

2+

) in (d) an egg box-like conformation. The swelling and shrinking of the hydrogel are attributed to the ionization (a) and protonation (b) of the unbound carboxyl groups at pH > 5 and pH < 4, respectively. (B) SPM topography images (10 × 10 µm

2

) of the swollen (a) and shrunken (b) membrane. (C) The electron transfer resistance,

R

et

, of the membrane deposited on the electrode surface derived from the impedance spectroscopy measurements obtained upon different combinations of input signals. (D) The permeability (ratio of the membrane permeability deposited on the supporting filter to the permeability of the filter with no membrane) for rhodamine B obtained upon different combinations of the input signals. The left and right bars in each pair correspond to the

AND

and

OR

gates, respectively.

FIGURE 10.4 The electronic scheme (a) of the signal-transducing device based on the Si chip modified with Au nanoparticles coated with a pH-sensitive organic shell (FRA, frequency response analyzer; RE, reference electrode). The bar diagrams showing the output signals generated by

OR

(b)/

AND

(c) enzyme logic gates and transduced by the Si chip in the form of capacitance changes. The dash lines correspond to the threshold values: the output signals located below the first threshold were considered as “

0

,” while the signals higher than the second threshold were treated as “

1

.”

FIGURE 10.5 (a) The multigate/multisignal processing enzyme logic system producing

in situ

pH changes as the output signal. (b) The equivalent logic circuitry for the biocatalytic cascade.

FIGURE 10.6 (a) Cyclic voltammograms obtained for the ITO electrode modified with the P4VP polymer brush in (a) the initial OFF state, pH ca. 6.7; (b) the ON state enabled by the input combinations resulting in acidifying of the solution to pH ca. 4.3; and (c)

in situ

reset to the OFF state, pH ca. 8.8. Inset: reversible current changes upon switching the electrode ON–OFF. Deoxygenated unbuffered solution of 0.1 M Na

2

SO

4

, 10 mM K

3

Fe(CN)

6

, and 10 mM K

4

Fe(CN)

6

also contained ADH, GDH, and GOx, 10 units·mL

−1

each. Input A was 0.5 mM NADH, input B was 5 mM acetaldehyde, and input C was 12.5 mM glucose. Potential scan rate of 100 mV s

−1

. (b) Anodic peak currents, I

p

, for the 16 possible input combinations. The dotted lines show threshold values separating logic

1

, undefined, and logic

0

output signals.

FIGURE 10.7 Logic operations

AND

/

OR

performed by the enzyme-based systems resulting in the

ON

and

OFF

states of the bioelectrocatalytic interface followed by the

Reset

function to complete the reversible cycle. Schematically shown cyclic voltammograms and impedance spectra correspond to the

ON

and

OFF

states of the bioelectrocatalytic electrode applied for the NADH oxidation.

FIGURE 10.8 The biofuel cell composed of the pH-switchable logically controlled biocatalytic cathode and glucose-oxidizing anode.

FIGURE 10.9 (a) The cascade of reactions biocatalyzed by alcohol dehydrogenase (ADH), amyloglucosidase (AGS), invertase (Inv) and glucose dehydrogenase (GDH) and triggered by the chemical input signals NADH, acetaldehyde, maltose, and sucrose added in different combinations. (b) The logic network composed of three concatenated gates and equivalent to the cascade of enzymatic reactions outlined in (a).

FIGURE 10.10 (a) V–i polarization curves obtained for the biofuel cell with different load resistances: (a) in the inactive state prior to the addition of the biochemical input signals (pH value in the cathodic compartment ca. 6), (b) in the active state after the cathode was activated by changing pH to ca. 4.3 by the biochemical signals, (c) after the

Reset

function activated by the addition of 5 mM urea. Inset: switchable i

sc

upon transition of the biofuel cell from the mute state to the active state and back performed upon biochemical signals processed by the enzyme logic network. (b) The bar diagram showing the power density produced by the biofuel cell in response to different patterns of the chemical input signals. Dashed lines show thresholds separating digital

0

, undefined, and

1

output signals produced by the system.

FIGURE 10.11 (a) The immune system composed of two antigens, two primary antibodies, and two secondary antibodies labeled with horseradish peroxidise (HRP) biocatalytic tag used for the

OR

logic gate. (b) The biocatalytic reaction producing pH changes to control the biofuel cell performance. (c) The biofuel cell controlled by the immune

OR

logic gate due to the pH-switchable [Fe(CN)

6

]

3−

-reducing cathode. MB

ox

and MB

red

are oxidized and reduced states of the mediator methylene blue.

FIGURE 10.12 (a) The polarization curves of the biofuel cell with the pH-switchable cathode obtained at different pH values generated

in situ

by the immune

OR

logic gate: (a) pH 4.5, (b) pH 5.8. (b) Electrical power density generated by the biofuel cell on different load resistances at different pH values generated

in situ

by the immune

OR

logic gate: (a) pH 4.5, (b) pH 5.8. Inset: the maximum electrical power density produced by the biofuel cell upon different combinations of the immune input signals.

FIGURE 10.13 (a) Functionalization of Au-shell/CoFe

2

O

4

-magnetic core NPs with GOx. (b) Magneto-assisted concentration of the GOx NPs on the electrode surface modified with the P4VP brush to perform glucose oxidation at the interface. (c) Opening of the P4VP brush for the electrochemical reaction at acidic pH generated at the interface upon the biocatalytic reaction.

FIGURE 10.14 (a) Cyclic voltammograms obtained on the P4VP-modified electrode: (a) GOx NPs in the solution in the absence of glucose, (b) GOx NPs confined at the electrode in the absence of glucose, (c) GOx NPs confined at the electrode in the presence of glucose, (d) GOx NPs redispersed in the solution in presence of glucose. Inset: reversible ON–OFF electrode switching by adding and removing glucose, while the GOx NPs are confined at the electrode surface. (b) Impedance spectra (Nyquist plots) obtained on the P4VP-modified electrode with the GOx NPs confined at the electrode: (a) in the absence of glucose, (b) in the presence of glucose (also shown at a smaller scale). Inset: reversible switching of the

R

et

by adding and removing glucose. Solution: 0.1 mM ABTS in 0.1 M Na

2

SO

4

, pH 7; GOx NPs, 0.3 mg mL

−1

; glucose addition, 10 mM; cyclic voltammograms, 100 mV s

−1

; impedance bias potential, 0.62 V.

Guide

Cover

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WILEY SERIES ON ELECTROCATALYSIS AND ELECTROCHEMISTRY

Andrzej Wieckowski, Series Editor

Fuel Cell Catalysis: A Surface Science Approach, Edited by Marc T. M. Koper

Electrochemistry of Functional Supramolecular Systems, Margherita Venturi, Paola Ceroni, and Alberto Credi

Catalysis in Electrochemistry: From Fundamentals to Strategies for Fuel Cell Development, Elizabeth Santos and Wolfgang Schmickler

Fuel Cell Science: Theory, Fundamentals, and Biocatalysis, Andrzej Wieckowski and Jens Norskov

Vibrational Spectroscopy at Electrified Interfaces, Edited by Andrzej Wieckowski, Carol Korzeniewski and Bjorn Braunschweig

ELECTROCHEMICAL PROCESSES IN BIOLOGICAL SYSTEMS

Edited by

ANDRZEJ LEWENSTAMLO GORTON

Wiley Series on Electrocatalysis and Electrochemistry

Copyright © 2015 by John Wiley & Sons, Inc. All rights reserved

Published by John Wiley & Sons, Inc., Hoboken, New JerseyPublished simultaneously in Canada

No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, [phone], fax [phone], or on the web at www.copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, [phone], fax [phone], or online at http://www.wiley.com/go/permissions.

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Library of Congress Cataloging-in-Publication Data

Electrochemical processes in biological systems / edited by Andrzej Lewenstam, Lo Gorton.        pages    cm. – (Wiley series on electrocatalysis and electrochemistry)    Includes bibliographical references and index.

    ISBN 978-0-470-57845-2 (cloth : alk. paper)1. Bioenergetics.    2. Ion exchange.    I. Lewenstam, Andrzej.    II. Gorton, L. (Lo)    QP517.B54E44 2015    612′.01421–dc23

                            2014049433

CONTRIBUTORS

Julea N. Butt, School of Chemistry and School of Biological Sciences, University of East Anglia, Norwich, UK

Krzysztof Dołowy, Laboratory of Biophysics, Warsaw University of Life Sciences (SGGW), Warsaw, Poland

Andrew J. Gates, School of Biological Sciences, University of East Anglia, Norwich, UK

Harry B. Gray, Beckman Institute, California Institute of Technology, Pasadena, CA, USA

Wiesław I. Gruszecki, Department of Biophysics, Institute of Physics, Maria Curie-Skłodowska University, Lublin, Poland

Jan Halámek, Department of Chemistry and Biomolecular Science, and NanoBio Laboratory (NABLAB), Clarkson University, Potsdam NY, USA

David E. Heppner, Department of Chemistry, Stanford University, Stanford, CA, USA

Michael G. Hill, Department of Chemistry, Occidental College, Los Angeles, CA, USA

Evgeny Katz, Department of Chemistry, University at Albany, SUNY, Albany, NY, USA

Christian H. Kjaergaard, Department of Chemistry, Stanford University, Stanford, CA, USA

Ramya Kolli, Department of Chemical and Biomolecular Engineering, New York University Polytechnic School of Engineering, Six Metrotech Center, Brooklyn, USA

Yaara Lefler, Department of Neurobiology, The Institute of Life Sciences and Edmond and Lily Safra Center for Brain Sciences (ELSC), The Hebrew University, Jerusalem, Israel

Kalle Levon, Department of Chemical and Biomolecular Engineering, New York University Polytechnic School of Engineering, Six Metrotech Center, Brooklyn, USA

Krzysztof Maksymiuk, Faculty of Chemistry, University of Warsaw, Warsaw, Poland

Sophie J. Marritt, School of Chemistry, University of East Anglia, Norwich, UK

Aabhas Martur, Department of Chemical and Biomolecular Engineering, New York University Polytechnic School of Engineering, Six Metrotech Center, Brooklyn, USA

Agata Michalska, Faculty of Chemistry, University of Warsaw, Warsaw, Poland

David J. Richardson, School of Biological Sciences, University of East Anglia, Norwich, UK

Tomasz Sokalski, Laboratory of Analytical Chemistry, Faculty of Science and Engineering, Åbo Akademi University, Turku, Finland

Edward I. Solomon, Department of Chemistry, Stanford University, Stanford, CA, USA

Andrew K. Udit, Department of Chemistry, Occidental College, Los Angeles, CA, USA

Marylka Yoe Uusisaari, Department of Neurobiology, The Institute of Life Sciences and Edmond and Lily Safra Center for Brain Sciences (ELSC), The Hebrew University, Jerusalem, Israel

Yanyan Wang, Department of Chemical and Biomolecular Engineering, New York University Polytechnic School of Engineering, Six Metrotech Center, Brooklyn, USA

Qi Zhang, Department of Chemical and Biomolecular Engineering, New York University Polytechnic School of Engineering, Six Metrotech Center, Brooklyn, USA

PREFACE

This series covers recent advancements in electrocatalysis and electrochemistry and depicts prospects for their contribution into the present and future of the industrial world. It aims to illustrate the transition of electrochemical sciences from its beginnings as a solid chapter of physical chemistry (covering mainly electron transfer reactions, concepts of electrode potentials, and structure of electrical double layer), to the field in which electrochemical reactivity is shown as a unique chapter of heterogeneous catalysis; is supported by high-level theory; connects to other areas of science; and includes focus on electrode surface structure, reaction environment, and interfacial spectroscopy.

The scope of this series ranges from electrocatalysis (practice, theory, relevance to fuel cell science, and technology), to electrochemical charge transfer reactions, biocatalysis, and photoelectrochemistry. While individual volumes may appear quite diverse, the series promises updated and overall synergistic reports providing insights to help further our understanding of the properties of electrified solid/liquid systems. Readers of the series will also find strong reference to theoretical approaches for predicting electrocatalytic reactivity by such high-level theories as density functional theory. Beyond the theoretical perspective, further vehicles for growth are such significant topics such as energy storage, syntheses of catalytic materials via rational design, nanometer-scale technologies, prospects in electrosynthesis, new instrumentation, and surface modifications. In this context, the reader will notice that new methods being developed for one field may be readily adapted for application in another.

Electrochemistry and electrocatalysis have both benefited from numerous monographs and review articles due to their depth, complexity, and relevance to the practical world. The Wiley Series on Electrocatalysis and Electrochemistry is dedicated to present the current activity by focusing each volume on a specific topic that is timely and promising in terms of its potential toward useful science and technology. The chapters in these volumes will also demonstrate the connection of electrochemistry to other disciplines beyond chemistry and chemical engineering, such as physics, quantum mechanics, surface science, and biology. The integral goal is to offer a broad-based analysis of the total development of the fields. The progress of the series will provide a global definition of what electrocatalysis and electrochemistry are now, and will contain projections about how these fields will further evolve in time. The purpose is twofold—to provide a modern reference for graduate instruction and for active researchers in the two disciplines, as well as to document that electrocatalysis and electrochemistry are dynamic fields that are expanding rapidly, and are likewise rapidly changing in their scientific profiles and potential.

Creation of each volume required the editor’s involvement, vision, enthusiasm, and time. The Series Editor thanks each Volume Editor who graciously accepted his invitation. Special thanks go to Ms. Anita Lekhwani, the Series Acquisitions Editor, who extended the invitation to edit this series to me and has been a wonderful help in its assembling process.

Andrzej Wieckowski              Series Editor

1MODELING OF RELATIONS BETWEEN IONIC FLUXES AND MEMBRANE POTENTIAL IN ARTIFICIAL MEMBRANES

Agata Michalska and Krzysztof Maksymiuk

Faculty of Chemistry, University of Warsaw, Warsaw, Poland

1.1 INTRODUCTORY CONSIDERATIONS

A membrane can be regarded as a phase, finite in space, which separates two other phases and exhibits individual resistances to the permeation of different species (Schlögl’s definition cited in [1]). The membranes can be of different thickness, from thin used typically for biological and artificial bilayers (in the range of a few nanometers) to relatively thick (hundreds of micrometers) used typically in ion-selective electrodes. A particular case is a membrane separating two electrolyte solutions, where ions are transferable species. In such a case, different modes of ion transport are possible: (i) Brownian motion; (ii) diffusion, resulting from concentration gradient; and (iii) migration as transport under the influence of an electrical field.

A general prerequisite related to the presence of charged species is electroneutrality condition of the membrane. However, even if electroneutrality is held on a macroscopic scale, charge separation effects appear, mainly at membrane/solution interfaces, resulting in the formation of potential difference. Taking into account possible chemical and electrical forces present in the system, assuming for simplicity one-dimensional transfer along the x-axis only, the flux of ion “i,” Ji, across the membrane can be described as

(1.1)

where k is a constant; Ui, ci, and are electrical mobility, concentration, and electrochemical potential of ion “i,” respectively; and x is the distance from the membrane/solution interface. Using a well-known definition of electrochemical potential and assuming that the activity of ion “i” is equal to the concentration, this equation can be transformed to

(1.2)

with φ as the Galvani potential of the phase.

Since mobility, Ui, is a ratio of the transfer rate, v, and potential gradient (∂φ/∂x), while the flux under influence of the electrical force is Jvc, it follows from Equation (1.2) that k=1/|zi|F. Taking then into account the Einstein relation, concerning diffusion coefficient, DiUiRT/|zi|F, Equation (1.2) can be rewritten as

(1.3)

This is the Nernst–Planck equation, relating the flux of ionic species, “i,” to gradients of potential and concentration, being generally functions of distance, x, and time, t.

The Nernst–Planck equation is a general expression describing transport phenomena in membranes. Unfortunately, as differential equations deal with functions dependent on distance and time, solving of this equation is neither easy nor straightforward. However, under some conditions, simplifications of this equation are possible.

(i) For the equilibrium case, summary fluxes of all ionic species are zero, Ji=0. In such a case,

(1.4)

After rearrangement and integration across the whole membrane (of thickness d), the well-known form is obtained:

(1.5)

where R and L refer arbitrarily to “right” and “left” hand side (membrane/solution interface) and cR and cL are solution concentrations at “right” and “left” interfaces. This equation describing a membrane potential, Δφmem, is equivalent of the typical Nernst equation.

(ii) For the case of a neutral substance, zi=0, or in the absence of electrical driving force (∂φ/∂x)=0, the Nernst–Planck equation reduces to Fick’s equation, describing diffusional transport:

(1.6)

Solutions of the Nernst–Planck equation can be more easily obtained for the steady state, when the ionic fluxes Ji=const and a time-independent version of the equation can be used. In this case, the Nernst–Planck equation can be applied to calculate potential difference in the membrane for given values of concentrations and mobilities. However, this procedure also requires integration, which can be difficult in some cases. Therefore, additional approximations are often used [2, 3]. The most known and used solutions are the Goldman and Henderson approximations.

1.1.1 Goldman Approximation and Goldman–Hodgkin–Katz Equation

This approximation assumes linearity of potential gradient across the membrane (i.e., constant electrical field in the membrane). This approximation is usually applicable to thin biological membranes, where charge prevails only in the surface areas of the membrane. In such a case, the derivative (∂φ/∂x) can be approximated by the term (φR−φL)/d leading to the simplified Nernst–Planck equation:

(1.7)

Under constant field condition, a steady state is practically obtained (Ji=const) and the Goldman flux equation can be derived:

(1.8)

In the absence of transmembrane potential, φR−φL~0, this equation simplifies to the well-known diffusion equation in a steady state.

Taking into account that the sum of individual ionic contributions to electrical current is zero (denoting the absence of applied external current),

(1.9)

further rearrangements are possible. For a simplified case of solution of ions of ±1 charge (e.g., Na+, K+, Cl−), the equation describing the potential difference across the membrane (under steady-state conditions) can be obtained:

(1.10)

It can be also assumed that ions take part in ion-exchange equilibrium, between the membrane and bathing electrolyte solution (sol) from the right or left hand side, (Eq. 1.11a) and (Eq. 1.11b), respectively:

(1.11a)

(1.11b)

with partition coefficients ki of the species “i” between the solution and membrane phases. Then, introducing the permeability coefficient, Pi, PiUiki/|zi|Fd, Equations (1.10) and (1.11a) can be transformed to the Goldman–Hodgkin–Katz equation, expressing the membrane potential as a function of ion concentrations in bathing solutions on both sides of the membrane and partition (permeability) coefficients:

(1.12)

This equation is applicable, for example, to describe resting potentials of biological membranes.

1.1.2 Henderson Approximation

This approximation assumes linear concentration gradient across the membrane, while the electrical field need not be constant [4]. This approximation is usually applied to describe diffusion (liquid junction) potentials, particularly for the case of ion-selective electrodes. This potential can be approximated by the equation

(1.13)

where ui is Ui/|zi|F.

Membrane processes related to charge separation and transport of charged species concern both biological membranes in cell biology (or artificial membranes having significant importance in separation processes) and membranes used in electroanalytical chemistry, for example, in ion-selective electrodes. However, in contrast to similarity of physicochemical phenomena occurring in all membranes containing mobile charged species, the description related to biological or separation membranes is different from that applicable to membranes of ion-selective electrodes. Therefore, the considerations in the following were divided into two sections: (i) related to more general description typical for separation and biological membranes where typically the Nernst–Planck equation is applicable and (ii) related to membranes used in ion-selective electrodes. In case (ii), practical and historical conditions result in dominance of simple empirical equations for the membrane potentials; however, in the last decade, the role of a more general theory using the Nernst–Planck equation is increasing.

1.2 GENERAL CONSIDERATIONS CONCERNING MEMBRANE POTENTIALS AND TRANSFER OF IONIC SPECIES

1.2.1 Boundary and Diffusion Potentials

Separation membranes are important both in biology and various technological areas: fuel cells, dialysis, reverse osmosis, separation of mixtures components, etc. These membranes can be generally described as neutral or charged membranes. For the former class of membranes, size exclusion and specific chemical interactions are the main factors responsible for selective permeability, while for charged membranes with incorporated ionic sites, electrostatic interactions are of substantial significance.