This paper identifies the electrochemical properties of individual facets of anisotropic layered conductive metal-organic frameworks (MOFs) based on M3(2,3,6,7,10,11-hexahydroxytriphenylene)2 (M3(HHTP)2) (M = Co, Ni). The electroanalytical advantages of each facet are then applied toward the electrochemical detection of neurochemicals. By employing epitaxially controlled deposition of M3(HHTP)2 MOFs on electrodes, the contribution of the basal plane ({001} facets) and edge sites ({100} facets) of these MOFs can be individually determined using electrochemical characterization techniques. Despite having a lower observed heterogeneous electron transfer rate constant, the {001} facets of the M3(HHTP)2 systems prove more selective and sensitive for the detection of dopamine than the {100} facets of the same MOF, with the limit of detection (LOD) of 9.9 ± 2 nM in phosphate-buffered saline and 214 ± 48 nM in a simulated cerebrospinal fluid. Langmuir isotherm studies accompanied by all-atom MD simulations suggested that the observed improvement in performance and selectivity is related to the adsorption characteristics of analytes on the basal plane versus edge sites of the MOF interfaces. This work establishes that the distinct crystallographic facets of 2D MOFs can be used to control the fundamental interactions between analyte and electrode, leading to tunable electrochemical properties by controlling their preferential orientation through self-assembly.
This paper identifies the electrochemical properties of individual facets of anisotropic layered conductive metal-organic frameworks (MOFs) based on M3(2,3,6,7,10,11-hexahydroxytriphenylene)2 (M3(HHTP)2) (M = Co, Ni). The electroanalytical advantages of each facet are then applied toward the electrochemical detection of neurochemicals. By employing epitaxially controlled deposition of M3(HHTP)2 MOFs on electrodes, the contribution of the basal plane ({001} facets) and edge sites ({100} facets) of these MOFs can be individually determined using electrochemical characterization techniques. Despite having a lower observed heterogeneous electron transfer rate constant, the {001} facets of the M3(HHTP)2 systems prove more selective and sensitive for the detection of dopamine than the {100} facets of the same MOF, with the limit of detection (LOD) of 9.9 ± 2 nM in phosphate-buffered saline and 214 ± 48 nM in a simulated cerebrospinal fluid. Langmuir isotherm studies accompanied by all-atom MD simulations suggested that the observed improvement in performance and selectivity is related to the adsorption characteristics of analytes on the basal plane versus edge sites of the MOF interfaces. This work establishes that the distinct crystallographic facets of 2D MOFs can be used to control the fundamental interactions between analyte and electrode, leading to tunable electrochemical properties by controlling their preferential orientation through self-assembly.
Analytical electrochemistry is a powerful
method that has revolutionized
chemical detection in healthcare,[1] industry,
and research.[2−4] Electrochemical methods have enabled advances in
spatial resolution,[5] sensitivity,[6] and selectivity[7] in
chemical analysis.[8,9] Among the most powerful and commonly
used electroanalytical techniques, voltammetry (primarily cyclic voltammetry
(CV), linear sweep voltammetry (LSV), square wave voltammetry (SWV),
and differential pulse voltammetry (DPV)) has excelled due to its
ability to differentiate and quantify analytes in solution rapidly
and inexpensively.[10,11] These methods have proven to
be amenable to miniaturization, integration into wireless sensors,[12,13] remote sensing applications,[14,15] and in vivo monitoring
of biological processes.[16−18]The development of materials
for working electrodes has been a
major driving force in advancing innovations in the design of electroanalytical
devices.[19] For example, all known allotropes
of carbon have been implemented as a component in working electrode
systems for electrochemical detection of small molecules,[20] large biomolecules,[21−23] and ions in
solution.[24−26] Sensing parameters of electrochemical systems have
improved with the progression from naturally occurring graphitic materials
to synthetic materials such as boron-doped diamond[27−30] and dimensionally controlled
materials such as carbon nanotubes,[31,32] highly oriented
pyrolytic graphite (HOPG),[33,34] and graphene.[35−37] While these materials benchmark performance for chemical detection
in contemporary analyte–interferent systems, their lack of
tunability from de novo synthesis and requirement for chemical modification
to achieve competitive performance restrict directed development toward
specific analytical targets. Studies have shown that carbon surfaces
with fewer natural defects (i.e., the basal plane of HOPG) provide
suboptimal properties as electrochemical interfaces for electron transfer
kinetics and catalytic activity toward surface-sensitive probes compared
to defect-rich surfaces.[38,39] To overcome this issue,
selectivity and, in some cases, the sensitivity of these systems toward
specific analytes can be greatly improved by postsynthetic modification
using procedures that create functionalized or hybrid materials with
improved sensing performance.[40−46] When compared with the bottom-up fabrication of functional materials,
postsynthetic modification requires additional preparation steps,
lacks chemical precision and atom economy, and is limited by available
techniques.[47−49] A valuable complementary addition to working electrode
technology would be a material system that can offer access to atomically
precise electrochemical surfaces, the ability to install electrocatalytic
subunits directly into the electrode material with chemical precision,
seamless integration into devices, and a high degree of tunability
in structure and morphology, while also conforming to the requirements
of electrochemical applications (e.g., high conductivity and electrochemical
stability). Obtaining these design features via a bottom-up synthetic
procedure would produce a material with superior adaptability to a
wide range of analytical systems.Conductive 2D metal–organic
frameworks[50,51] (MOFs) are promising functional
materials for electroanalytical
applications because they are readily prepared using highly tunable
bottom-up methods, have a high surface area, and can be used to transduce
chemical interactions into electrical signals.[52−54] Additionally,
MOFs based on 2,3,6,7,10,11-hexahydroxytriphenyelene (HHTP) are advantageous
due to the fully conjugated nature of the HHTP ligand, which installs
a rigidly extended π-framework, providing good conductivity
and driving the self-assembly of 2D sheets into nanoscale crystalline
solids.[55−60] The self-assembly of 2D sheets into layered crystallites creates
three distinct surfaces: (1) edge facets rich in sheet termination
sites within the crystallographic family of planes {100} (Figure A), (2) a basal plane
that is rich in sp2 carbons, axially exposed metal ions,
and cofacially aligned pores belonging to the crystallographic family
of planes {001} (Figure B), and (3) interior pore volume with surfaces consisting of heteroatom
lone-pairs and aromatic protons projected inwardly into the pore volume.
Figure 1
M3(HHTP)2 in the form of (a-i) hydrothermally
grown and drop-casted MOF and (b-i) MOFs obtained by epitaxial growth
and Langmuir–Blodgett deposition with their anticipated orientation
on the electrode surface. Scanning electron micrographs of (a-ii)
nanorods and (b-ii) nanosheets. Idealized models of exposed crystal
facets belonging to the Bragg family of planes (a-iii) {100} or (b-iii)
{001} were generated from reported crystal structures (blue: metal
(Ni or Co), gray: carbon, red: oxygen, and white: hydrogen). (c) A
representative hexagonal nanocrystal with the overlaid families of
planes.
M3(HHTP)2 in the form of (a-i) hydrothermally
grown and drop-casted MOF and (b-i) MOFs obtained by epitaxial growth
and Langmuir–Blodgett deposition with their anticipated orientation
on the electrode surface. Scanning electron micrographs of (a-ii)
nanorods and (b-ii) nanosheets. Idealized models of exposed crystal
facets belonging to the Bragg family of planes (a-iii) {100} or (b-iii)
{001} were generated from reported crystal structures (blue: metal
(Ni or Co), gray: carbon, red: oxygen, and white: hydrogen). (c) A
representative hexagonal nanocrystal with the overlaid families of
planes.Each of the three chemically distinct surfaces
of 2D layered conductive
MOFs can provide a distinct set of interactions with their chemical
environment, potentially allowing tailored degrees of control over
electrochemical properties. While we[53] and
others[61−64] have demonstrated that this general class of framework materials
are capable of electrochemical detection and differentiation of biologically
relevant organic analytes (BRO) such as dopamine (DA), uric acid (UA),
ascorbic acid (AA), glucose, and serotonin (5-HT) at nM−μM
concentrations, little is known about how morphology, dimensionality,
and orientation of MOF nanocrystals impact the liquid-phase electroanalytical
capabilities of these materials and how tuning these structural properties
can be utilized to improve electroanalytical performance in multianalyte
biologically relevant systems. This limitation restricts progress
in the molecular design of conductive MOFs for targeted electroanalytical
applications and prevents a fundamental understanding of emergent
structure–property relationships at the nanoscale.Herein,
we demonstrate that specific crystalline facets of stacked
2D MOFs can be employed to impart advantageous properties toward liquid-phase
electrochemical detection and enable the differentiation of biologically
relevant organic analytes in complex multianalyte systems. We characterize
the surface of preferentially oriented MOF nanocrystals by a combination
of spectroscopy and microscopy techniques (e.g., XPS, SEM, PXRD),
to determine structural properties, and electrochemical and computational
methods to elucidate functional properties. We utilize well-known
electrochemical probes that exhibit surface-sensitive and surface-insensitive
properties to demonstrate that electrochemically relevant interfaces
of epitaxially oriented MOF nanocrystals are dominated by three main
morphologically tunable aspects arising from the anisotropy inherent
in the structure of these framework materials: (1) hierarchical surface
area as a geometrically complex diffusion interface; (2) Coulombic
interactions between the surface charges on the MOF and charged analyte
species in solution; and (3) intermolecular interactions between probes
and the basal plane versus edge sites. We demonstrate how these three
aspects of the MOF materials determine their range of function, sensitivity
toward targeted analytes, and selective response.To investigate
these aspects and their resulting properties, we
examine the electroanalytical and electrocatalytic capabilities of
M3(HHTP)2 (M = Co, Ni) under three degrees of
structural control. First, we demonstrate that MOFs provide advantages
compared to a glassy carbon electrode (GCE), such as increased sensitivity
toward select neurochemical BROs (i.e., DA, 5-HT, and UA). Second,
preferentially orienting the MOFs to expose either their basal plane
having {001} facets or edge sites having {100} facets allows control
over their exposed surface chemistry and characteristics of electron
transfer to analytes in solution. For diffusion-controlled inorganic
probes, we show that electrochemically active surfaces of M3(HHTP)2 can be preferentially organized through self-assembly
into interfaces that promote or inhibit heterogeneous electron transfer
rates (HETRs) (k0{100} of K3Fe(CN)6: ∼4.8 × 10–5 cm/s, k0{001}: not observed).
Third, this morphological tunability proved a successful method of
enhancing the detection of desired analytes and diminishing the influence
of unwanted interferents in electroanalytical systems. Specifically,
we show that epitaxially grown interfaces of {001} Ni3(HHTP)2 can enhance sensing characteristics compared with bulk synthesized
material toward biologically relevant organic analytes, such as DA
(LOD = 9.9 nM), in the presence of challenging interferents such as
3,4-dihydroxyphenylacetic acid (DOPAC) (LOD of DA = 381 nM in 50 μM
DOPAC, 48 nM in 5 μM DOPAC) and in simulated cerebrospinal fluid
containing elevated levels of soluble protein, uric acid, and glucose.
The LOD for DA under these conditions was 214 ± 48 nM. Finally,
we used Langmuir isotherm studies in conjunction with all-atom molecular
dynamics (MD) simulations to demonstrate that the analytical differences
stemming from structural–chemical tunability come from the
specific adsorption motifs analytes experience on each electrode interface
described by parameters, such as adsorption strength (ΔG°) and surface coverage (ΓS). The
identification of interfaces that dominate electrocatalytic activity,
the demonstration of rationally designed surfaces for the enhancement
of chemical and electrochemical transformations, and the detailed
investigation into the origins of the enhancement provide valuable
contributions to the study and design of anisotropic stacked 2D nanomaterials
for electrochemical applications.
Experimental Design
Choice of MOFs
In this study, we chose two isostructural
MOFs as representative materials for conductive 2D stacked framework
systems. The two MOFs, Co3(HHTP)2 and Ni3(HHTP)2, were desirable as materials of inquiry
because Ni3(HHTP)2 has been previously reported
for its electrochemical sensing capabilities,[53] while also being isostructural with Co3(HHTP)2, which has a reported crystal structure.[55,57] Together, these materials allow molecular contributions to be studied
alongside epitaxially controlled properties. Both MOFs possess at
least three important attributes as model systems for 2D conductive
materials applied to electrochemical sensing. First, they exhibit
limited redox activity in aqueous biologically relevant buffer systems,
such as phosphate-buffered saline (PBS) and KCl, and therefore show
promise for detecting electroactive analytes in the −0.7–0.7
V (vs Ag/AgCl) potential range.[53] Second,
they have demonstrated abilities to detect a broad range of analytes
in aqueous solutions [Ni3(HHTP)2][53,64] and the gas phase [Ni3(HHTP)2 and Co3(HHTP)2][65,66] using voltammetric and amperometric
techniques, respectively. Third, they are readily accessible as nanocrystals
with tunable (e.g., sheet- or rod-like) morphologies and are amenable
to epitaxially controlled device-integration strategies.[57,60,67]Despite these reported
properties, little is known about how the anisotropy of common morphologies
of 2D MOFs (nanorods) influences their electrocatalytic and electroanalytical
properties. We hypothesized that the two distinct surfaces of stacked
2D materials could have dramatically different properties in electroanalysis
and decided to investigate their individual properties through morphological
control. In addition to a thorough examination of all MOF materials
using a range of electrochemical methods, we also singled out Ni3(HHTP)2 {001} and Ni3(HHTP)2 {100} for detailed investigations using differential pulse voltammetry
and Langmuir adsorption isotherm studies because they showed the most
promising analytical properties. To aid in these studies we also subjected
the two Ni-based MOF morphologies to additional characterization techniques.
Area density of thin films is an important feature underpinning their
electrochemical sensitivity. In this work, we chose the thickness
of MOF films having exposed {001} planes because they were the thinnest
cohesive films we could obtain by our interfacial synthesis method
without compromising structural integrity or quality (i.e., fidelity
of crystallite orientation, continuity of the film, and long-range
coverage). Additionally, when investigating individual facets, we
chose to use the thinnest possible film to promote a strongly leveraged
ratio of exposed {100} or {001} facets. Thicker films (larger crystallites
along the c-axis) would lead to a greater portion
of {100} character in the films, which was undesirable for this study
of specific families of planes.
Choice of Electrochemical Probes
The electrochemical
activity of distinct interfaces was determined by quantifying the
redox properties of inorganic and biologically relevant organic analyte
probes. The redox activity of probes at interfaces can be characterized
as surface-sensitive, surface-insensitive, or adsorption-controlled
depending on their alacrity for uncatalyzed redox transformations.[68,69] Surface-insensitive probes typically display fast redox kinetics
independent of the interface involved in the electron transfer process.
Surface-sensitive probes display fast kinetics at interfaces that
are conducive to electron transfer while displaying slow kinetics
at interfaces that hinder electron transfer.[70] Adsorption-controlled probes require the formation of intermolecular
interactions (e.g., hydrogen bonding, dispersion) with a surface in
order to facilitate redox transformations.
Inorganic Probes
In this study, we chose the following
three inorganic probes: K3Fe(CN)6, Ru(NH3)6Cl3, and K4IrCl6 (all inorganic probes were used in CV experiments at 1 mM). This
set of probes is widely used in the electrochemical literature and
provides a strong foundation with which to investigate the electrochemical
properties of electrode materials.[24] In
contrast to BRO probes, they can be selected to represent a range
of surface sensitivities and are less prone to side reactions and
fouling of electrode surfaces. Fast redox kinetics observed for K3Fe(CN)6 indicate that a surface possesses functionalities
and a density of states that are beneficial for facilitating electrochemical
processes. The inorganic probes Ru(NH3)6Cl3 and K4IrCl6 are well-known surface-insensitive
redox probes at carbon-rich surfaces such as graphene[36,71] and carbon nanotubes.[72] Their insensitivity
to surface functionalization can be used as a control to confirm that
surfaces with slow electron transfer kinetics observed for K3Fe(CN)6 exhibit reduced reactivity based on interactions
between the probe and electrode, not reduced conductivity of the functionalizing
MOF layer compared to GCE or limitations in function imposed by integration
or deposition of materials on an electrode. Initially we were concerned
that the small amount of {100} facet still present at the edges of
{001} oriented films could contribute to the electrochemical response
and obscure deconvolution of the electrochemical characteristics of
each interface ({100} versus {001}) separately. Using a combination
of surface-insensitive and surface-sensitive probes allowed us to
distinguish between surface chemistries at each interface and determine
the role, if any, of the {100} edges present in the {001} films.
BRO Probes
Accurate electrochemical detection and monitoring
of electroactive BRO probes, such as DA, DOPAC, UA, and AA, have become
crucial for the diagnosis and treatment of many diseases (Figure S21).[73,74] For example,
DA and DOPAC play important roles in the molecular pathogenesis of
stress reactions, cardiovascular diseases, hypertension, Parkinson’s
disease, depression, schizophrenia, and more.[74−77] Metabolites, such as UA,[78] and cofactors, such as AA,[79] both impact physiological function and act as interferents
to the detection of other BROs.[80] Neurological
pathologies can be especially difficult to diagnose chemically, and
the direct, continuous, and minimally invasive detection of chemical
biomarkers implicated in neurological disorders would provide better
defined diagnostic protocols as well as the potential for improved
understanding of the mechanisms of these diseases.[81,82] We chose to characterize our MOF electrode materials against the
probes DA (10 μM), DOPAC (100 μM), 5-HT (10 μM),
UA (100 μM), and AA (100 μM).The electrochemical
properties of these probes have been well studied on a wide array
of surfaces such as graphene,[83] MOFs,[53] gold,[84] and multicomponent
coatings.[40,85] Their interaction with electrodes is highly
dependent on their ionicity, the charge of the electrode, and surface
functionality capable of facilitating their electrochemical transformation.[84,86,87] The oxidation and reduction of
DA, DOPAC, and 5-HT involve two-electron, two-proton processes (Figure S21).[27,84,88−90] Exploring these probes can allow
for an improved understanding of structure–property relationships
and elucidate the importance of controlled epitaxial orientation on
the kinetic capabilities of these MOF-based electrodes.
Choice of Electrochemical Methods
For this work a three-electrode
configuration consisting of a working, a reference, and a counter
electrode was used to allow accurate measurements of current and minimize
the influence of capacitive double-layer effects in voltammetric measurement
regimes.
Choice of Electrodes
Glassy carbon was chosen for the
working electrode for its moderate kinetics and chemical inertness.
MOF materials were mounted on the GCE to provide a low-resistance,
water-stable, chemically inert method of applying a working potential
from the potentiostat to the materials of interest. The counter electrode
was chosen to be platinum for its ability to enable high current density
and inertness over a wide potential range. An AgCl-coated Ag wire
in 1 M KCl was chosen as the reference electrode because of its well-known
stability, reproducibility, compatibility with aqueous chemistry,
and convenient reduction potential versus the standard hydrogen electrode
(Ag/AgCl: +0.235 V vs SHE).
Choice of Electrolyte
The supporting electrolytes chosen
for this study were either 0.1 M KCl or 0.1 M PBS (pH = 7.4). The
unbuffered saline solution, 0.1 M KCl, was chosen for its sufficient
conductivity (reducing the series resistance of the electrochemical
cell) as well as the inert nature of the K+ and Cl– components. KCl electrolyte was primarily used in
experiments having no biologically relevant components. The electrolyte
composed of PBS (0.1 M, pH = 7.4) was chosen to replicate conditions
typically associated with electrochemical sensing of BROs. The drawback
of PBS is that the phosphate anions have low solubility with divalent
transition metals (Ksp ∼ 10–32–10–37).[91,92] This low Ksp indicates that PO42– could be capable of leaching metals from MOFs
or capping exposed metal sites on MOF surfaces. To provide context
for in vivo sensing applications, we also examined the ability of
the nanomaterial Ni3(HHTP)2 to detect DA in
a mimic of cerebrospinal fluid containing the following: 42 μM
UA, 4 mM glucose, and 0.5% bovine serum albumin (BSA) in PBS. The
judicious usage of the three electrolyte solutions, having distinct
properties, ensured accurate characterization under various conditions
such as biological relevance and the fidelity of pristine MOF surfaces.
Choice of Electrochemical Techniques
Cyclic voltammetry
was the primary method of investigating materials mounted on GCE.
Cyclic voltammetry was used because it allows a wealth of information
to be gathered about electrode materials, electrode–electrolyte
interfaces, and the kinetics and thermodynamics of electrochemical
transformations of probe analytes at electrode surfaces. Voltammetric
data were collected over scan rates starting at 1000 mV/s down to
5 mV/s. For inorganic probes, the peak separation between oxidation
and reduction waves was used to determine the HETR constant as k0 for electrode–probe systems. Because
reaction systems at electrodes can be reversible, quasi-reversible,
or irreversible, for a variety of chemical, kinetic, and thermodynamic
reasons, only reactions exhibiting reversible or quasi-reversible
voltammograms were characterized to determine k0. Practical application of the Nicholson–Shain[93] and Klinger–Kochi[94] methods was accomplished by applying the equation describing
an extended working curve developed by Magno and co-workers (eq ).[95]For systems that exhibited irreversible
electron transfer characteristics or irreversible chemical transformations
(identified by peak separations > 300 mV, or where kinetic parameters
were no longer applicable, or irreversible CVs), HETR constants were
not calculated. We typically encountered these cases for the BROs.
Similarly, in electrochemical systems where the probe was under an
adsorption regime rather than diffusion control, the HETR constants
were not calculated. An experimental determination of the diffusion
coefficient for analytes with each electrode system was needed to
determine k0. This value was obtained
by plotting the peak potential versus the square root of the scan
rate to generate Randles–Ševčík plots
(R–Š plots) for the fully reversible case.To
examine electron transfer rates, redox probes were studied across
a potential window of −0.7 to 0.7 V vs Ag/AgCl. This potential
window was chosen as it encompasses the oxidation and reduction potentials
of the analytes examined. Oxidation and reduction of target analytes
occur at specific potentials determined by factors related to the
working electrode (electrode geometry, overpotential, electron transfer
rate, scan rate, and diffusion coefficient) and the electrochemical
system (nature of target probe). For investigations using inorganic
probes, 0.1 M KCl was used as the electrolyte. When examining BROs,
0.1 M PBS (pH = 7.4) was used as the electrolyte.Since the
materials used in this study were both nanostructured
and highly porous, the addition of material deposited on the GCE was
anticipated to enhance the electrochemical surface area (ECSA) of
the working electrode compared to unmodified GCE. The ECSA was determined
by monitoring current density in non-Faradaic regions. Current densities
monitored over multiple scan rates provided the double-layer capacitance
(Cdl), which could then be compared to
unmodified GCE. The roughness factor obtained was then used to scale
the surface area of the working electrode to account for the increased
surface area when functionalized with MOF nanomaterials.Electrochemically
derived Langmuir isotherm studies can be used
to investigate how analytes adsorb to electrode surfaces. For analytes
such as DA that adsorb to electrode surfaces during oxidation/reduction,
these isotherms provide information such as the density of host sites
on the electrode material and the thermodynamics of adsorption.[45] We used Langmuir adsorption isotherms to quantify
MOF–analyte interactions to gain deeper insight into the material
properties governing analytical sensitivity and selectivity. The Langmuir
model provides information about the ensemble-level interactions occurring
at the morphologically tuned surfaces of Ni3(HHTP)2 {100} and Ni3(HHTP)2 {001} (Supporting Information Section XVII).
Results and Discussion
Morphological Control of Oriented Electrochemically Accessible
Crystal Facets
Ni3(HHTP)2 and Co3(HHTP)2 are isostructural frameworks. They possess
similar packing structures of alternating layers and honeycomb lattices.[55,57] In this study, we achieved epitaxially oriented surfaces of MOF
nanocrystals through morphological control of MOF crystallites under
hydrothermal synthetic conditions.[55] Previously,
both step-by-step epitaxial methods and solid–liquid interface
methods have been applied to achieve enhanced c-axis
orientation of nanocrystalline MOFs.[57,96] Preceding
studies have indicated that the thickness of the films in addition
to the composition of the films is an important tunable feature.[67] Herein, we synthesized rod-like and sheet-like
assemblies of nanocrystals under hydrothermal and interfacial reaction
conditions and achieved deposition on GCE either through drop-casting
or Langmuir–Blodgett techniques (Supporting Information Section II). Rod-shaped crystallites were produced
using previously reported hydrothermal conditions and drop-cast directly
from the reaction solution either onto GCE for the fabrication of
working electrodes or onto the surface of a glassy carbon substrate
(Figures S5, S17, S18) or SI wafers for
physical analysis (Supporting Information Sections II–VI). Sheet-like crystallites were grown at the interface
between an anoxic aqueous solution and ambient air (Figure S5) and were transferred onto surfaces (GCE or Si)
using the Langmuir–Blodgett technique.[55] The similar manner in which samples were prepared across physical
characterization procedures and electrochemical experiments allowed
the morphology determined by SEM to be compared with observations
of crystallinity and epitaxial orientation obtained by PXRD and implicated
in results of electrochemical experiments.SEM imaging of the
silicon-mounted samples revealed that the materials prepared by the
Langmuir–Blodgett method consisted of highly aligned bundles
of crystallites with their hexagonal faces parallel to the silicon
plate (Figure b, Figures S2, S4, S5). Hydrothermally obtained
materials revealed a rod-like crystalline habit with a random distribution
of orientations relative to the plane of the silicon plate (Figures b, S1, S3). SEM also revealed that the nanorod materials were
distributed evenly across the surface as a film when deposited from
a suspension.
Figure 2
(a) PXRD diffractograms of the {100} and {001} preferential
orientations
of Ni3(HHTP)2 and Co3(HHTP)2. The residuals from the Rietveld refinement process are shown below
each PXRD trace. Characteristic diffraction lines and their corresponding
(hkl) planes depicted in gray and red correspond
to the basal plane and edge plane crystallographic planes, respectively.
Corresponding SEM images of the materials characterized by PXRD (b)
showing the orientation of materials on the substrate. (c) The crystallographic
planes corresponding to the strongest diffractions observed in the
{001} (top) and {100} (bottom) materials. The diffraction plane is
shown in either gray or red, and the unit cell is shown in green.
Atoms are depicted as gray, carbon; red, oxygen; blue, metal (Ni or
Co); white, hydrogen.
(a) PXRD diffractograms of the {100} and {001} preferential
orientations
of Ni3(HHTP)2 and Co3(HHTP)2. The residuals from the Rietveld refinement process are shown below
each PXRD trace. Characteristic diffraction lines and their corresponding
(hkl) planes depicted in gray and red correspond
to the basal plane and edge plane crystallographic planes, respectively.
Corresponding SEM images of the materials characterized by PXRD (b)
showing the orientation of materials on the substrate. (c) The crystallographic
planes corresponding to the strongest diffractions observed in the
{001} (top) and {100} (bottom) materials. The diffraction plane is
shown in either gray or red, and the unit cell is shown in green.
Atoms are depicted as gray, carbon; red, oxygen; blue, metal (Ni or
Co); white, hydrogen.We anticipated that the large sheet-like plane
of the Ni3(HHTP)2 and Co3(HHTP)2 MOFs observed
by SEM would be coplanar with the molecular basal plane corresponding
to the Miller indices defined by the family of planes {001}, meaning
the dominant exposed interface would be the basal plane (Figure ). Similarly, we
anticipated that the majority surface area of the hydrothermal synthesis
was described by the set of Miller indices defined by the family of
planes {100}, meaning that the majority of exposed surface area was
terminal edge sites.To confirm these premises, the crystallinity
and preferential orientation
of both morphologies were assessed by PXRD with Rietveld refinement.
The highly oriented interfacially grown materials, characterized by
powder X-ray diffraction (PXRD), exhibited a single strong diffraction
peak at 27.5° 2θ that was calculated to arise from an intermolecular
distance of 3.34 Å (Figure a). By comparison with computational models and single-crystal
structures of previously reported isostructural Co3(HHTP)2, we determined the Miller index of the corresponding diffraction
plane to be (004) (Figure a,c).[55]Rietveld refinement
was used to confirm that the interfacially
grown sheet-like films of both Co3(HHTP)2 and
Ni3(HHTP)2 had a nearly quantitative alignment
of the c-axis of the crystalline domains within the
polycrystalline film aligned perpendicular to the PXRD substrate (Figure a, Supporting Information Section V). The orientation observed
for the sheet-like film confirmed that interfaces observed by SEM
were indeed the basal plane of the MOF (Figure b).PXRD analysis of the rod-like hydrothermal
nanomaterials of Co3(HHTP)2 and Ni3(HHTP)2 exhibited
a prominent diffraction peak at 4.6° 2θ corresponding to
an interatomic distance of 18.0 Å commensurate with the anticipated
prominence of the (100) diffraction plane (Figure a,c). Rietveld refinement identified a slight
preferential orientation of the nanorods having their c-axis parallel to the substrate. This result matched the observed
orientation of nanocrystallites observed by SEM (Figure b, Supporting Information Section V).[55] In the
future, additional studies with wide-angle X-ray scattering could
aid in the determination of crystallite orientation in thin-film systems
such as these. Having confirmed that the synthesized materials had
interfaces with the anticipated orientations, we then examined the
chemical composition of the crystalline facets by XPS analysis. Survey
spectra of the four distinct materials showed similar features including
elemental emission lines corresponding to O 1s and C 1s transitions
as well as the corresponding metal for each MOF (Co or Ni) (Figures S15, S16). Additional characterization
using energy dispersive X-ray spectroscopy confirmed the presence
of the expected elements as well as their even distribution throughout
the materials (Figures S17, S18).After confirming that the synthetic methods we developed and the
material integration methods we used provided access to specific crystalline
facets with good fidelity, we assessed the response of these two distinct
orientations using electrochemical methods. Because we wanted to determine
how the analytical properties of the materials changed on each facet,
we chose to first study the electrochemical properties of these materials
with redox-active inorganic probes.
The Electrochemical Response of the {100} Facet and the {001}
Facet of MOFs toward Inorganic Probes
Analysis with inorganic
probes served two primary purposes. First, we used these probes to
identify electrochemically distinct properties specific to the {001}
or {100} interfaces of M3(HHTP)2. Second, although
the orientation of the materials appeared quantitative by SEM and
PXRD, we were cognizant of the inextricable nature of the individual
facets. That is, even in the sheet-like materials dominated by the
surface chemistry of the {001} interface, edge sites were still present
at the exposed columnar edges of the tightly packed and aligned rods.
Additionally, preferred orientation of particles does not guarantee
that electrolytes and analytes will access a particular facet over
others. We investigated the electrochemical properties of each of
the four distinct materials toward two types of inorganic redox-active
agents, surface-sensitive (K3Fe(CN)6) and surface-insensitive
probes (Ru(NH3)Cl3 and K4IrCl6).Our initial experiments with surface-insensitive
probes served as a control experiment for both morphologies. All four
of the materials we examined using CV, including sheet-like ({001})
and rod-like ({100}) Co3(HHTP)2 and Ni3(HHTP)2, showed similar kinetics and peak currents for
the surface-insensitive inorganic probes Ru(NH3)Cl3 (Figures a, S24, S32) and K4IrCl6 (Figures a, S26, S34). From these similar
results, we were confident that both the {001} and {100} interfaces
exhibited good contact with the underlying GCE, were conductive enough
to allow electrochemical characterization and use in analytical applications,
and that any differences we observed in further experimentation were
indeed originating from differences within the materials rather than
extrinsic experimental properties.
Figure 4
Summary of electrochemical properties of Co3(HHTP)2 and Ni3(HHTP)2 electrodes
having {100}
and {001} preferential orientation. For inorganic probes (a) the figure
of merit is the heterogeneous electron transfer rate constant (HETR k0) for surface-insensitive (i.e., Ru(NH3)6Cl6 and K4IrCl8) and surface-sensitive (i.e., K3Fe(CN)6) probes.
For biologically relevant organics (BRO) (b) the figure of merit in
analytical applications is the observed peak current. This value is
obtained from the oxidative wave of cyclic voltammograms. The data
for inorganic probes were collected from solutions of 0.1 M KCl and
an analyte concentration of 1 mM. For BROs, CVs were collected in
a solution of 0.1 M PBS at a pH of 7.4. The analyte concentrations
were 10 μM for DA and 5-HT and 100 μM for DOPAC, AA, and
UA.
Cyclic voltammograms of (a–d) Ni3(HHTP)2 {100} and {001} interfaces with DA, DOPAC,
5-HT, and UA. (e–h)
Cyclic voltammograms of Co3(HHTP)2 {100} and
{001} interfaces with 10 μM DA, 100 μM DOPAC, 10 μM
5-HT, and 100 μM UA. All voltammograms were recorded in 0.1
M PBS at a pH of 7.4. A scan rate of 50 mV/s was used to obtain all
traces across a scan window of −0.7–0.7 V (vs Ag/AgCl).
Traces have been offset vertically for clarity.Summary of electrochemical properties of Co3(HHTP)2 and Ni3(HHTP)2 electrodes
having {100}
and {001} preferential orientation. For inorganic probes (a) the figure
of merit is the heterogeneous electron transfer rate constant (HETR k0) for surface-insensitive (i.e., Ru(NH3)6Cl6 and K4IrCl8) and surface-sensitive (i.e., K3Fe(CN)6) probes.
For biologically relevant organics (BRO) (b) the figure of merit in
analytical applications is the observed peak current. This value is
obtained from the oxidative wave of cyclic voltammograms. The data
for inorganic probes were collected from solutions of 0.1 M KCl and
an analyte concentration of 1 mM. For BROs, CVs were collected in
a solution of 0.1 M PBS at a pH of 7.4. The analyte concentrations
were 10 μM for DA and 5-HT and 100 μM for DOPAC, AA, and
UA.Next, we examined the MOFs using CV and the surface-sensitive
K3Fe(CN)6. Here we observed dramatic differences
in HETR k0 between materials having predominantly
{001} orientations (sheet-like morphologies) and {100} orientations
(rod-like morphologies). While the {100} M3(HHTP)2 materials provided observable HETR k0 values, albeit significantly slower than bare GCE, the {001} interface
of M3(HHTP)2 showed no discernible ability to
engage in redox transformations of the [Fe(CN)6]4–/3– probe (Figures a, S25, S33). The dramatic differences in activity
we observed for surface-sensitive probes but not for surface-insensitive
probes confirmed that the morphologically obtained interfaces defined
which facets were predominantly performing electrochemical transformations,
specifically that the {100} surface area present in the oriented {001}
films did not play a significant role in electrochemical experiments.Our observations demonstrated that the reactivity of electrochemical
surfaces can be tuned by controlling the morphology of the active
material. We also demonstrated that self-assembly of preferentially
oriented surfaces provides control over the electron transfer processes
across the electrode–electrolyte interface. We hypothesize
that this tunability is a function of two primary factors. First,
like HOPG and graphene, the basal plane of the MOFs is inherently
slower in electron transfer processes compared to edge sites. This
is a phenomenon commonly observed in 2D materials where defect sites,
such as growing edges, vacancies, and dislocations in the crystalline
lattice, are the locations that harbor the highest density of states
(DOS).[97] Second, surface chemistry of the
edge sites is more advantageous for catalyzing the surface-sensitive
transformation of specific probes like [Fe(CN)6]4–/3–.[98] Features such as DOS and surface chemistry
together provide a means of affecting the electroanalytic properties
for inorganic analytes. Having characterized the intrinsic features
of the materials and their electrochemical properties toward inorganic
analytes, we next looked to examine BROs.
Application of Morphological Control for the Detection of Biologically
Relevant Organic Analytes
To expand our understanding of
morphologically controlled properties to BROs, we examined the electrochemical
response of the {100} and {001} facets of M3(HHTP)2 to DA, DOPAC, 5-HT, UA, and AA. This selection of analytes
was chosen because they present a range of oxidation potentials, surface
sensitivities, and cationic and anionic species in solution. DA and
5-HT possess a positive charge when dissolved at pH 7.4, while DOPAC,
UA, and AA are negatively charged at pH 7.4.
The Response of BROs at GCE
To benchmark analytical
performance, we first measured the CVs of BROs on bare GCE. We generally
observed weak peak currents (ip) for all
the BROs at GCE (Figures b, S23). We also observed lower
overpotentials of analytes on GCE compared to the MOFs (Figures , S23). We anticipated that these differences could be explained by two
phenomena. First, the strong peak currents observed for BROs at MOFs
compared to the GCE are a product of the enhanced host–guest
interactions (e.g., hydrogen bonding) and surface area provided by
the MOF. Second, the higher overpotentials observed for BROs on MOFs
compared to GCE could result from increased double-layer effects arising
from created interfaces (GCE–MOF and MOF–electrolyte)
in the electrochemical system. Another possibility is that the conductance
of the polycrystalline MOFs is less than that of GCE, causing some
uncompensated resistance to play a role.
Figure 3
Cyclic voltammograms of (a–d) Ni3(HHTP)2 {100} and {001} interfaces with DA, DOPAC,
5-HT, and UA. (e–h)
Cyclic voltammograms of Co3(HHTP)2 {100} and
{001} interfaces with 10 μM DA, 100 μM DOPAC, 10 μM
5-HT, and 100 μM UA. All voltammograms were recorded in 0.1
M PBS at a pH of 7.4. A scan rate of 50 mV/s was used to obtain all
traces across a scan window of −0.7–0.7 V (vs Ag/AgCl).
Traces have been offset vertically for clarity.
Discussion of Epitaxially Controlled Facets of MOFs for Electroanalysis
of BROs
The electrochemical response of analytes at MOF surfaces
was measured for two MOFs (i.e., Co3(HHTP)2 and
Ni3(HHTP)2) and five BROs (i.e., DA, DOPAC,
5-HT, AA, and UA, Figure , Supporting Information Section X, Section XII). Epitaxially controlling
the integration of nanomaterials provided three broad levels of control.
First, all MOFs in this study showed improved ip over bare GCE for the BROs carrying a positive charge in
solution (i.e., DA, 5-HT) and a worse response for probes carrying
a negative charge (i.e., DOPAC, AA) despite these analytes being evaluated
using a 10× concentration (Figure b). The improvement most likely stemmed from a combination
of properties such as complementary Coulombic interactions and differences
in adsorption sites between GCE and MOF interfaces. Second, the {001}
interface of both M3(HHTP)2 MOFs showed dramatically
higher ip for DA compared to the {100}
interface (Figures , 4b). This difference between the ip measured on the {001} versus {100} was not
as pronounced for 5-HT and not observed for other BROs. Finally, Co3(HHTP)2 and Ni3(HHTP)2 (Figure b) showed similar
electrochemical properties as one another for all the analytes, which
suggested that metal identity (Co vs Ni) played a diminished role
compared to morphology and exposed interface.DOPAC is an important
metabolite of l-DOPA and DA in physiological systems.[99] DA and DOPAC are often co-occurring but have
significantly different physiological roles, necessitating their independent
quantification. Our CV experiments showed that the MOFs had increased
sensitivity toward DA and decreased sensitivity toward DOPAC compared
to GCE, with DOPAC requiring 10× the concentration of DA to produce
an equivalent observable response (Figures , 4b). We noted that
the {001} facet of Ni3(HHTP)2 was more sensitive
to DA, producing a 6× greater ip compared
to the {100} facet, while also shifting the oxidation peak of DOPAC
toward higher potentials (Figure ). We hypothesized that the electrochemical properties
of the {001} facet of Ni3(HHTP)2 could be used
to produce a selective electrochemical interface for the detection
of DA.
The Sensing Performance of {100} and {001} Facets of Ni3(HHTP)2
To test this hypothesis, we used
differential pulse adsorption stripping voltammetry (DPASV) to determine
the LOD of DA in three different electrolyte formulations, including
a 0.1 PBS electrolyte, a 0.1 M PBS solution containing high concentrations
of the interferent DOPAC, and a simulated cerebral spinal fluid (CSF)
containing 0.1 M PBS, 0.5% bovine serum albumin (BSA), 1 mM glucose,
and 7 μM UA. In the simplest electrolyte solution, 0.1 M PBS,
we found an LOD for DA of 9.9 ± 2 nM (Figure a, Figure S43).
Next, we repeated the DPASV experiment with comparatively high concentrations
of DOPAC. The first test measured a limit of detection of 381 nM for
DA in a solution containing 50 μM DOPAC (Figures b, S44). When
the concentration of DOPAC was reduced to 5 μM, the LOD of DA
was measured to be 48 nM (Figures b, S44). Finally, in simulated
CSF we measured a LOD for DA of 241 ± 48 nM with good separation
between the oxidative waves of UA and DA and no observed interference
from glucose (Figures c, S45).
Figure 5
Sensitivity of Ni3(HHTP)2 {001} for the detection
of DA using differential pulse adsorption stripping voltammetry (DPASV)
in each distinct analytical solution. (a) DPASV traces of increasing
[DA] in 0.1 M PBS. (b) DPASV of increasing [DA] in 0.1 PBS with overwhelming
concentrations of 3,4-dihydroxyphenylacetic acid (DOPAC) including
5 μM DOPAC (blue traces) and 50 μM DOPAC (brown trace).
(c) DPASV of DA in a solution of simulated cerebrospinal fluid (CSF)
containing UA, glucose, and 0.5% bovine serum albumin. For all linear
fits, R2 > 0.97.
Sensitivity of Ni3(HHTP)2 {001} for the detection
of DA using differential pulse adsorption stripping voltammetry (DPASV)
in each distinct analytical solution. (a) DPASV traces of increasing
[DA] in 0.1 M PBS. (b) DPASV of increasing [DA] in 0.1 PBS with overwhelming
concentrations of 3,4-dihydroxyphenylacetic acid (DOPAC) including
5 μM DOPAC (blue traces) and 50 μM DOPAC (brown trace).
(c) DPASV of DA in a solution of simulated cerebrospinal fluid (CSF)
containing UA, glucose, and 0.5% bovine serum albumin. For all linear
fits, R2 > 0.97.This series of analytical experiments demonstrated
three features
of the MOFs. First, the inherent sensitivity of the {001} interface
to DA allowed nM detection limits in biologically relevant PBS solutions.
Second, we showed that the interface of 2D MOFs could be used to strategically
modulate the response to analytes and interferents in analytical systems
to select against interferents such as DOPAC, UA, and glucose. Third,
the electrode system was able to perform in complex analytical environments
such as those containing high concentrations of soluble protein (BSA).
Full experimental data sets and concentration ranges can be found
in the Supporting Information (Sections XIV–XVI).
Adsorption of DA and DOPAC on Ni3(HHTP)2
Electrochemical oxidation of DA and DOPAC requires adsorption
of the analytes to electrode substrates. In our experiments, we observed
that the oxidation of DA was largely irreversible at the scan rates
(<1 V/s) and concentrations (10–100 μM) we investigated
(Figure ). We were
therefore interested in determining how adsorption properties differed
at each interface of the MOFs and if those adsorption parameters were
underpinning the observed differences in analytical sensitivity and
selectivity between the {001} and {100} interfaces of M3(HHTP)2. Because Ni3(HHTP)2 was
the material we chose to advance toward analytical experiments and
showed exceptional sensing characteristics, it was also the material
we decided to examine in our Langmuir isotherm studies. To characterize
the interactions between DA and DOPAC with the two interfaces of Ni3(HHTP)2, we used both experimentally obtained adsorption
parameters from Langmuir adsorption isotherms as well as MD simulations
to elucidate adsorption motifs in MOF–analyte interactions.The Langmuir model assumes that a fixed number of heterogeneous
host sites are available for adsorption, adsorption sites are energetically
equivalent, and that exactly one analyte adsorbs at each host site.[100] While these assumptions limit the ability to
differentiate between multiple distinct adsorption interactions that
may be occurring on the anisotropic MOF surface, the Langmuir model
can still provide information on the ensemble of interactions occurring
at the morphologically tuned surfaces of Ni3(HHTP)2 {001} and Ni3(HHTP)2 {100} (Supporting Information Section XVII). We used
the oxidative peak current maxima derived from cyclic voltammograms
to calculate the electrode surface coverage (ΓA)
at concentrations spanning the range [DA] = 10 μM–3 mM
using eq S1.[101] Plotting ΓA for each analyte concentration provided
a curve that was fit with Langmuir’s isotherm equation (eq S2), which allowed us to extract the saturation
surface coverage, ΓS, and the thermodynamic equilibrium
constant, β, that describe the ensemble of adsorption interactions.[101] These values were then used to calculate the
Gibbs free energy of adsorption, ΔG°,
using eq S3.[101]The isotherms for Ni3(HHTP)2 {100},
Ni3(HHTP)2 {001}, and GCE adsorbing the analyte
DA
or DOPAC are shown in Figure ; 3–6 replicates of each experiment were conducted.
The curves were fit using a weighted least-squares regression model,
meaning that the points with the least uncertainty had the greatest
impact on the fitted curve (Supporting Information Section XVII).
Figure 6
Langmuir isotherms presented as surface coverage (ΓA) versus concentration [analyte] for dopamine (DA, top) and
3,4-dihydroxyphenylacetic
acid (DOPAC, bottom), for electrodes composed of (a) Ni3(HHTP)2 {100}, (b) Ni3(HHTP)2 {001},
and (c) glassy carbon. Insets are included for each plot corresponding
to surface coverages at low concentrations of analyte. Surface coverage
at each concentration was calculated from peak current from the oxidative
wave of a cyclic voltammogram (CV). CVs were performed at 50 mV/s
in a solution of 0.1 M phosphate-buffered solution at a pH of 7.4.
Langmuir isotherms presented as surface coverage (ΓA) versus concentration [analyte] for dopamine (DA, top) and
3,4-dihydroxyphenylacetic
acid (DOPAC, bottom), for electrodes composed of (a) Ni3(HHTP)2 {100}, (b) Ni3(HHTP)2 {001},
and (c) glassy carbon. Insets are included for each plot corresponding
to surface coverages at low concentrations of analyte. Surface coverage
at each concentration was calculated from peak current from the oxidative
wave of a cyclic voltammogram (CV). CVs were performed at 50 mV/s
in a solution of 0.1 M phosphate-buffered solution at a pH of 7.4.By qualitatively comparing the isotherms based
on the shape of
the curve and magnitude of ΓA values, we identified
that Ni3(HHTP)2 materials behave differently
than GCE in adsorbing DA versus DOPAC, indicated by their measured
ΓS, β, and ΔG°
values. The ΓS, β, and ΔG° derived from the isotherm plots are compared in the Supporting Information Table S2.
Interpretation of Langmuir Isotherm Studies
The isotherm
studies involving the adsorption of DA and DOPAC to electrode surfaces
composed of Ni3(HHTP)2 {100}, {001}, and GCE
yielded the parameters ΓS, β, and ΔG° visualized in Figure a–c, respectively. We found key trends for all
three of these adsorption metrics that held true for both DA and DOPAC.
First, we found that Ni3(HHTP)2 {001} had the
lowest saturation surface coverage (ΓS) and GCE had
the highest saturation surface coverage for both analytes (Figure a, Table S2). Second, the equilibrium constant of adsorption
(β) for DA and DOPAC was dramatically higher for Ni3(HHTP)2 {001} compared to Ni3(HHTP)2 {100} and was lowest for GCE. Third, we found that the adsorption
strength (ΔG°) of the analytes was greater
(more negative) on Ni3(HHTP)2 interfaces compared
to GCE and was largest on the Ni3(HHTP)2 {001}
interface (Figure c, Table S2). These three trends were
then compared to the ip values of DA at
10 μM measured by CV (Figure d, Table S2). We found that
greater values of β and more favorable values of ΔG° (more negative ΔG°)
followed the trend of ip for DA ({001}
> {100} > GCE).
Figure 7
Summary of data obtained from Langmuir isotherm studies
for the
adsorption of the analytes DA and DOPAC to electrodes composed of
Ni3(HHTP)2 {100} and {001}. (a) Surface coverage
ΓS, (b) thermodynamic equilibrium constant β,
(c) Gibb’s free energy of adsorption ΔG°, and (d) comparison of the trends in the adsorption of DA
compared to the electrochemical response for DA (peak current and
ΓA reported for [DA]: 10 μM) for the three
electrode materials.
Summary of data obtained from Langmuir isotherm studies
for the
adsorption of the analytes DA and DOPAC to electrodes composed of
Ni3(HHTP)2 {100} and {001}. (a) Surface coverage
ΓS, (b) thermodynamic equilibrium constant β,
(c) Gibb’s free energy of adsorption ΔG°, and (d) comparison of the trends in the adsorption of DA
compared to the electrochemical response for DA (peak current and
ΓA reported for [DA]: 10 μM) for the three
electrode materials.ΓA (pmol cm–2) indicates the
density of occupied host sites at a particular concentration, while
ΓS (pmol cm–2) indicates the maximum
density of available host sites for an electrode material. Higher
ΓA values contribute directly to higher peak currents
in voltammetric analysis.[45] For trends
in saturation surface coverage (ΓS) we observed separate
regimes at high and low concentrations of DA. At low concentrations
([DA] < 100 μM, Figure S47), we
observed that ΓS trended against ΓA. This relationship indicated that at low concentrations the Ni3(HHTP)2 {001} was a more sensitive electrode interface
for detecting DA. At concentrations above this regime ([DA] > 100
μM, Figure S47) we observed a correlation
between ΓS and ΓA for DA, which
suggested that the higher saturation coverage was dominating the response.
The relationship between β (cm3 pmol–1) and ip was useful in understanding
the difference observed between ΓS and ΓA. At subsaturating concentrations the magnitude of β
describes the portion of active sites occupied by analyte. For voltammetric
analyte detection in the nM range, β becomes an important descriptor
of how many DA are adsorbed (i.e., what fraction of adsorption sites
are occupied) and can be oxidized as a function of solution-phase
concentration. The magnitude of β stems from the favorability
of analyte–material interactions (ΔG°), meaning that the exergonicity of the adsorption governs
the surface coverage at subsaturating concentrations.[101] In summary, we found that at low concentrations
([DA] < 100 μM, Figure S47) the
greater β exhibited by the {001} interface produced a higher
surface coverage, ΓA, and thus a stronger electrochemical
response. At high concentrations ([DA] > 100 μM) the greater
number of host sites, ΓS, on the {100} surface was
the most important factor for designing a sensitive electrode interface.
To understand why the {001} interface of Ni3(HHTP)2 had a more favorable β and ΔG° compared to the {100} interface, we conducted all-atom MD
simulations to understand material features important to favorable
analyte adsorption.
MD Simulations of Interactions between M3(HHTP)2 MOFs and Neurochemicals
The electrochemical methods
used in this study were limited in their ability to determine specific
features of adsorption between analytes and the MOF interfaces. To
inform our isotherm findings, we aimed to identify chemical features
responsible for the differences in surface coverage and adsorption
strength. To probe these aspects of analyte adsorption, we conducted
MD simulations of systems comprising DA or DOPAC with each MOF. Each
system was created by placing one type of MOF (Co3(HHTP)2 or Ni3(HHTP)2) at the center of the
simulation domain (Figure S48), then adding
27 molecules of a given analyte of interest (DA or DOPAC) around the
MOF (Figure S49). Each system was then
solvated with TIP3P water molecules and equilibrated for 100 ps at
293 K and 1 atm. Following equilibration, MD simulations were performed
in the NPT ensemble on each system for 20 ns with a time step of 2
fs using the DL_POLY_4 package.[102]The results from all-atom MD simulations (Figures , S51) provided
a set of visualized interactions between DOPAC and DA at each MOF
interface (Tables S3–S6). The sampling
of adsorbed structures we obtained provided a molecular-scale understanding
of analyte interactions at each interface. As expected, interactions
between the catecholate-based analytes and the {100} facet of M3(HHTP)2 were dominated by hydrogen-bonding interactions
with terminal aqua ligands, as well as heteroatoms of the HHTP ligands.
In contrast, the {001} facet of M3(HHTP)2 was
able to host hydrogen-bonding interactions as well as hydrophobic
π–π interactions. These two observations, increased
areal density of host sites at the {100} interface and mixed bonding
(H-bonding and π-bonding) types at the {001} interface, were
then used to further interpret the results from our Langmuir isotherm
adsorption studies.
Figure 8
Interactions between analytes and Ni3(HHTP)2 observed during MD simulations. Structures of the MOFs are
represented
by spheres (blue = Ni, gold = Co, red = O, gray = C, protons and aqua
ligands were removed for clarity), and analytes are represented by
stick structures. Interactions of DA with Ni3(HHTP)2 at the (a) {100} and (b) {001} interfaces. The adsorption
of DOPAC at the (c) {100} and (d) {001} interface of Ni3(HHTP)2.
Interactions between analytes and Ni3(HHTP)2 observed during MD simulations. Structures of the MOFs are
represented
by spheres (blue = Ni, gold = Co, red = O, gray = C, protons and aqua
ligands were removed for clarity), and analytes are represented by
stick structures. Interactions of DA with Ni3(HHTP)2 at the (a) {100} and (b) {001} interfaces. The adsorption
of DOPAC at the (c) {100} and (d) {001} interface of Ni3(HHTP)2.
Insight into Electrochemical Properties from Electrochemical
Experimentation and MD Simulations
Adsorption parameters
obtained from Langmuir isotherm studies and results obtained from
MD simulations pointed to the role of surface coverage and adsorption
strength in determining the analytical performance of Ni3(HHTP)2 electrodes. Surface coverage (ΓS), which we experimentally identified as trending inversely with
electroanalytical sensitivity, was higher for DA on {100} than {001}
and appeared to originate from the dense hydrogen-bonding sites at
the edge sites of the MOF. In MD simulations the basal plane appeared
to have fewer adsorption sites due to both void space from the pores
and fewer hydrogen-bonding sites compared to the edge plane. We propose
that higher ΓS leads to a greater fouling of the
electrode surface by polymerization reactions and other fouling mechanisms.
The adsorption parameter ΔG° for DA on
electrode interfaces was identified as the cause of enhanced sensitivity
of the {001} interface over the {100} interface as well as the sensitivity
enhancement of MOF-based electrodes over GCE. The more exergonic adsorption
of DA to the {001} of the MOF manifested as a higher value for the
equilibrium adsorption constant β, which determines electrode
coverage at subsaturating concentrations. MD simulations suggested
that the {001} interface of the MOF provided more exergonic adsorption
sites because of its ability to host both hydrophobic (π–π
bonding) and hydrophilic (H-bonding) interactions.
Conclusion
The experimental evidence we presented demonstrates
that the confluence
of epitaxial self-assembly and anisotropic crystallinity can yield
tunable interfaces for electroanalytical applications. This work provides
a significant advancement in understanding the electroactive interfaces
of anisotropic stacked 2D conductive MOFs for different classes of
analytes. We build on previous demonstrations of MOFs for electroanalysis
by elucidating fundamental factors that are important in designing
effective MOF-based electrodes for analytical applications.Synthetic access to oriented nanocrystalline facets ({001} and
{100}) of two isostructural MOF analogs (Ni3(HHTP)2 and Co3(HHTP)2) and their subsequent
electrochemical characterization using a series of inorganic and organic
redox probes allowed us to identify three key characteristics of the
MOFs in electrochemical applications. First, we identified a distinct
advantage of the MOFs over bare GCE for enhancing the detection of
positively charged analytes, such as DA, while suppressing the interference
from negatively charged analytes, such as DOPAC and AA. Second, we
discovered electrochemical attributes of the electrolyte–MOF
interface at the {100} and {001} family of planes of M3(HHTP)2. The basal planes belonging to the {001} family
of planes of both Co3(HHTP)2 and Ni3(HHTP)2 showed slower HETR k0 for surface-sensitive inorganic probes compared to edge facets belonging
to the {100} family of planes. Electrochemical investigations with
BROs revealed that the {001} planes were advantageous in adsorption-driven
electrochemical processes, such as the oxidation of DA. The herein
reported method of integrating {001} oriented Ni3(HHTP)2 onto GCE allowed the detection of concentrations of DA as
low as 9.9 ± 2 nM in PBS. The electrodes also displayed promising
sensitivity and selectivity for DA in simulated CSF containing BSA,
UA, and glucose at physiologically representative concentrations.
Third, we used Langmuir isotherm studies to obtain thermodynamic adsorption
parameters of the analytes DA and DOPAC with the {001} and {100} interfaces
of Ni3(HHTP)2, which, when informed by our MD
simulations, identified important molecular design criteria for anisotropic
MOF systems for the detection of adsorbing analytes.While this
work identifies chemical and structural aspects of MOFs
important to their electroanalytical properties, several features
and processes remain for further investigation. The limitations of
this study are primarily twofold. First, we did not investigate the
electron transfer rate or mechanism for BRO detection at MOF electrodes.
Oxidative detection of BROs, especially those containing catechol
redox centers, commonly relies on proton-coupled electron transfer
(PCET) processes.[103,104] Identifying the role of hydrogen
bonding, proton transfer, and analyte adsorption in the oxidation
of BROs would provide additional insight into the observed benefits
of the {001} interface in chemical sensing. Second, we did not examine
differences
in impedance between the {001} and {100} interfaces for the MOF–GCE
heterostructure. Further investigations using electrochemical impedance
spectroscopy could provide more insight into the role of each interface
and the heterojunction of MOF–GCE. While these limitations
span a range of fundamental to applied aspects, the current work focuses
on the experimentally observable differences in 2D conductive MOF
orientation in liquid-phase electroanalysis.In summary, this
work provides a crucial experimental and computational
methodology for characterizing 2D materials in electrochemical systems.
As 2D materials gain prominence in electrochemical applications (i.e.,
sensing, energy storage, and catalysis), it becomes important to understand
how their anisotropy can be controlled and leveraged into advantageous
properties. Our demonstration herein, that chemically distinct facets
of anisotropic nanocrystalline 2D MOFs can direct electrochemical
properties of electrodes by controlling their ensemble orientation
through self-assembly, is poised to inform growing areas of electrochemistry
and the investigation of important properties of this class of materials.
Experimental Methods
A complete account of methods,
supporting characterization, and
experimental results can be found in the Supporting Information.
Synthesis of MOF Nanocrystalline Interfaces
M3(HHTP)2 Hydrothermal Method to Obtain
Rods
To prepare MOFs, 0.037 mmol of hexahydroxytriphenylene
(12 mg) and 0.074 mmol of metal(II) acetate tetrahydrate (18.4 mg,
metal = Co or Ni) were added to a 20 mL scintillation vial. Deionized
water (15 mL, 0.005 M [HHTP]) was added, and the vial was loosely
capped to allow the exchange of air in the headspace. The reaction
mixture was subjected to sonication (5 min) and then heated without
stirring (85 °C) overnight (18–24 h). The resulting suspension
was characterized by drop-casting onto silicon plates and imaging
by SEM and PXRD. Suspensions were stored at 7 °C for up to 2
weeks. Rods were not isolated from the initial reaction mixture but
were used as a suspension.
Interfacial Synthesis of M3(HHTP)2 Films
Into a recrystallizing dish (⦶ = 8 cm) were added metal(II)
acetate tetrahydrate (56.5 mg, 0.227 mmol, 2 equiv, metal = Co or
Ni) and 100 mL of DI water. Into a vial were added fully reduced HHTP
(36.8 mg, 0.113 mmol, 1 equiv) and 20 mL of DI water. The vial was
then sonicated for 10 min until a pink/gray suspension was formed.
This suspension was poured into the recrystallizing dish containing
the M(OAc)2 solution. The reaction was left exposed to
air but gently covered to prevent contamination from airborne particles.
After 2 h, a thin film visually similar to an oil slick was observed
on the surface of the reaction. After an additional 4 h, the film
was uncovered and used. Finished films were mounted onto GCE using
the Langmuir–Blodgett method.
Electrochemical Experimental Parameters
Cyclic Voltammetry
Inorganic Probes
Electrochemical experiments were performed
in 0.1 M KCl that had been degassed with N2. Cyclic voltammograms
were collected at nine scan rates starting from the fastest rate and
proceeding to the slowest in the following order: 1000, 750, 500,
250, 100, 50, 25, 10, and 5 mV/s. The potential range applied in these
experiments was −0.7–0.7 V. Four scans were collected
at each scan rate, and the fourth scan from each experiment was plotted
on the same plot to characterize the reduction and oxidation events.
Biologically Relevant Organic Probes
Probes in this
category were used to determine the performance of these materials
in physiologically relevant conditions. Therefore, the electrolyte
solution was chosen to be 0.1 M 1× PBS at a pH of 7.4. Cyclic
voltammograms were collected at nine scan rates starting from the
fastest rate and proceeding to the slowest in the following order:
1000, 750, 500, 250, 100, 50, 25, 10, and 5 mV/s. The potential range
applied in these experiments was −0.7–0.7 V, except
for the case of K4IrCl6, where a potential range
of −0.7–1.2 V was used to accommodate the higher oxidation
potential of the iridium-based probe. Four scans were collected at
each scan rate, and the fourth scan from each experiment was plotted
on the same plot to characterize the reduction and oxidation events.
Authors: Jessica E Koehne; Michael Marsh; Adwoa Boakye; Brandon Douglas; In Yong Kim; Su-Youne Chang; Dong-Pyo Jang; Kevin E Bennet; Christopher Kimble; Russell Andrews; M Meyyappan; Kendall H Lee Journal: Analyst Date: 2011-03-08 Impact factor: 4.616
Authors: Sam Emaminejad; Wei Gao; Eric Wu; Zoe A Davies; Hnin Yin Yin Nyein; Samyuktha Challa; Sean P Ryan; Hossain M Fahad; Kevin Chen; Ziba Shahpar; Salmonn Talebi; Carlos Milla; Ali Javey; Ronald W Davis Journal: Proc Natl Acad Sci U S A Date: 2017-04-17 Impact factor: 11.205
Authors: Raymond C S Seet; Chung-Yung J Lee; Erle C H Lim; June J H Tan; Amy M L Quek; Wan-Ling Chong; Woan-Foon Looi; Shan-Hong Huang; Huansong Wang; Yiong-Huak Chan; Barry Halliwell Journal: Free Radic Biol Med Date: 2009-12-04 Impact factor: 7.376
Authors: You Seung Rim; Sang-Hoon Bae; Huajun Chen; Jonathan L Yang; Jaemyung Kim; Anne M Andrews; Paul S Weiss; Yang Yang; Hsian-Rong Tseng Journal: ACS Nano Date: 2015-10-29 Impact factor: 15.881
Authors: Robert W Day; D Kwabena Bediako; Mehdi Rezaee; Lucas R Parent; Grigorii Skorupskii; Maxx Q Arguilla; Christopher H Hendon; Ivo Stassen; Nathan C Gianneschi; Philip Kim; Mircea Dincă Journal: ACS Cent Sci Date: 2019-12-10 Impact factor: 14.553