High-Frequency Nanocapacitor Arrays - American Chemical Society

Sep 19, 2016 - Developments, and Outlook. Published as part of the Accounts of Chemical Research special issue “Nanoelectrochemistry”. Serge G. Le...
0 downloads 0 Views 2MB Size
Download PDF
Article pubs.acs.org/accounts

High-Frequency Nanocapacitor Arrays: Concept, Recent Developments, and Outlook Published as part of the Accounts of Chemical Research special issue “Nanoelectrochemistry”. Serge G. Lemay,*,† Cecilia Laborde,† Christophe Renault,† Andrea Cossettini,‡ Luca Selmi,‡ and Frans P. Widdershoven§ †

MESA+ Institute for Nanotechnology, University of Twente, PO Box 217, 7500 AE Enschede, The Netherlands DPIA, University of Udine, Via delle Scienze 206, Udine 33100, Italy § NXP Semiconductors, Global Technology Innovation, High Tech Campus 46, 5656 AE Eindhoven, The Netherlands ‡

CONSPECTUS: We have developed a measurement platform for performing high-frequency AC detection at nanoelectrodes. The system consists of 65 536 electrodes (diameter 180 nm) arranged in a sub-micrometer rectangular array. The electrodes are actuated at frequencies up to 50 MHz, and the resulting AC current response at each separately addressable electrode is measured in real time. These capabilities are made possible by fabricating the electrodes on a complementary metal−oxide−semiconductor (CMOS) chip together with the associated control and readout electronics, thus minimizing parasitic capacitance and maximizing the signal-to-noise ratio. This combination of features offers several advantages for a broad range of experiments. First, in contrast to alternative CMOS-based electrical systems based on field-effect detection, high-frequency operation is sensitive beyond the electrical double layer and can probe entities at a range of micrometers in electrolytes with high ionic strength such as water at physiological salt concentrations. Far from being limited to single- or few-channel recordings like conventional electrochemical impedance spectroscopy, the massively parallel design of the array permits electrically imaging micrometer-scale entities with each electrode serving as a separate pixel. This allows observation of complex kinetics in heterogeneous environments, for example, the motion of living cells on the surface of the array. This imaging aspect is further strengthened by the ability to distinguish between analyte species based on the sign and magnitude of their AC response. Finally, we show here that sensitivity down to the attofarad level combined with the small electrode size permits detection of individual 28 nm diameter particles as they land on the sensor surface. Interestingly, using finite-element methods, it is also possible to calculate accurately the full three-dimensional electric field and current distributions during operation at the level of the Poisson−Nernst−Planck formalism. This makes it possible to validate the interpretation of measurements and to optimize the design of future experiments. Indeed, the complex frequency and spatial dependence of the data suggests that experiments to date have only scratched the surface of the method’s capabilities. Future iterations of the hardware will take advantage of the higher frequencies, higher electrode packing densities and smaller electrode sizes made available by continuing advances in CMOS manufacturing. Combined with targeted immobilization of targets at the electrodes, we anticipate that it will soon be possible to realize complex biosensors based on spatial- and time-resolved nanoscale impedance detection.

■

INTRODUCTION Nanoscale electrochemical devices are perfectly suited as signal transduction elements for integration with solid-state electronics so as to create complex monolithic (bio)sensing chipbased technologies. The materials requirements and fabrication methods for integrated circuits and electrodes are (mostly) compatible, electrochemical methods use relatively little power, and their sensitivity is often enhanced upon miniaturization, as is the performance of the electronics to which they are coupled.1 The variety of electrochemical methods (amperometry,2 potentiometry,3 conductimetry,4,5 impedimetry,6,7 photoelectrochemistry8 and others9) is reflected in a correspondingly © 2016 American Chemical Society

broad range of nanoscale devices that includes (i) ion-sensitive field-effect transistors (ISFETs),10 (ii) nanoelectrodes and nanoelectrode arrays for voltammetric or amperometric electrochemistry assays11 including multielectrode configurations such as interdigitated,12,13 bipolar,14 nanogap,15 and ring− disk16 electrodes, and (iii) nanopores, either biological or solid state, employed as Coulter counters.17 An alternative transduction mechanism that has so far received limited attention at the nanoscale is electrochemical Received: July 5, 2016 Published: September 19, 2016 2355

DOI: 10.1021/acs.accounts.6b00349 Acc. Chem. Res. 2016, 49, 2355−2362

Article

Accounts of Chemical Research

wires. Doing so confers the ability to probe beyond the double layer and to probe a small volume around the electrodes, at the cost of averaging the measured signals over multiple electrodes and thus giving up the ability to detect discrete events at individual electrodes. Variations on this theme include interdigitated electrodes,30 as well as nanogap electrodes, the latter consisting of pairs of microelectrodes separated by only a few tens of nanometers. Malave et al. employed this approach to monitor the binding of molecular films in 100 nm high nanogap arrays (total interfacial capacitance 1−3 pF) at high excitation frequencies (initially up to 180 MHz31 and later reaching the gigahertz range32−34). An alternative approach exploits frequency mixing to generate low-frequency, easily extractable signals that reflect the high-frequency response of a nanoscale ISFET. Using single-walled carbon nanotubes as active elements, Kulkarni and Zhong demonstrated enhanced sensitivity at high frequencies to protein binding under high salt concentrations.35,36 Their measurement relies on the nonlinearity of the transfer characteristics of the ISFET to convert the response to an amplitude-modulated actuation voltage with a frequency up to 30 MHz into a 1.43 kHz readout signal. How generally applicable this approach is and what type of analytical information can ultimately be extracted in this manner represents a fascinating question. Here we instead describe our efforts to develop, study, and validate a unique measurement platform capable of performing high-frequency AC detection at an array of individually addressable nanoelectrodes without relying on nonlinear response. This approach tackles head on the need to minimize the background capacitance by colocating the nanoelectrodes and their associated readout electronics on the same complementary metal−oxide−semiconductor (CMOS) chip. The resulting circuitry allows massively parallel high-frequency operation with a large number of densely spaced electrodes, enabling real-time imaging with an unprecedented sensitivity to capacitance changes at the attofarad level.37

impedance spectroscopy (EIS), in which a DC potential perturbed with a small alternating (AC) potential is applied to an electrode in contact with a target solution and the corresponding current response is measured as a function of frequency.18 A major strength of EIS is that it interrogates different sample properties in different frequency ranges. In the absence of faradaic contribution and at low frequencies, it probes the region within the electrical double layer (EDL), which typically extends only a few nanometers from the surface of an electrode. This renders EIS a very sensitive probe of chemical processes taking place at the surface of the electrode. Probing beyond the EDL is however desirable in a variety of applications, and a limited ability to do so has proven a major hurdle for transducers based on field-effect detection.19−23 Approaches to mitigate this problem include optimizing surface modifications so as to immobilize target analytes within the EDL24,25 or, more commonly, decreasing the ionic strength below physiological conditions so as to extend the range of the EDL.26 An alternative elegant solution is to increase the frequency of the AC excitation. At high enough frequencies, ions in solution no longer migrate sufficiently fast to allow the EDL to adjust to AC bias perturbations. In this case, the electric field penetrates further from the electrode and probes optimally at a distance comparable to the smallest electrode dimension. Simultaneously, sensitivity to small adsorbates within the EDL is diminished compared to low-frequency detection. Both of these properties suggest that high sensitivity and selectivity to, for example, supra- or macromolecular entities can be achieved using nanoelectrodes with a size comparable to that of the target. Performing EIS measurements at nanoelectrodes, however, presents serious technical challenges beyond the difficulty of creating high-quality miniaturized electrodes. This is because the crossover frequency above which probing beyond the EDL occurs, which we refer to as f1, is heuristically given by 1/f1 = 2πR sol(C EDL + Csol)

■

(1)

Here CEDL is the capacitance of the EDL, Rsol is the solution resistance between the working electrode and its counter or reference electrode, and Csol is the solution capacitance representing the displacement current associated with the time-dependent electric field in the solution. For a disk electrode with radius a, f1 is approximately proportional to a−1 and thus increases as the electrode is downsized: under physiological conditions, f1 ≈ 260 Hz for a macroscopic a = 1 mm electrode but increases to ∼3 MHz for a = 90 nm! Taking advantage of the enhanced sensitivity of nanoelectrodes for comparably sized targets therefore also requires operating at much higher frequencies, which poses an enormous experimental challenge. This is because the admittance of a typical nanoelectrode is completely dwarfed by that of the wires needed to contact it (CEDL is on the order of 1 fF for the a = 90 nm electrode discussed above, which is 3 orders of magnitude smaller than the capacitance of 1 cm of coaxial cable). Stray capacitance typically limits conventional EIS measurements to frequencies in the kilohertz range, and frequencies rarely exceed 1 MHz.27−29 Consequently, only a handful of groups to date have developed approaches for performing EIS using nanoscale electrodes. One possible work-around is to connect a large number of nanoelectrodes in parallel, such that the total admittance exceeds that associated with the capacitance of the connecting

CMOS NANOCAPACITOR ARRAYS Because of its small dimensions, the event rate of a single nanoelectrode interacting with analyte nanoparticles can be very low. Employing a large number of individually addressable nanoelectrodes in a dense two-dimensional array addresses this issue. Furthermore, in order to minimize stray capacitances, the required selection and detection electronics should be placed as close as possible to the nanoelectrodes. Advanced CMOS technology is ideally suited for both these purposes since it provides a comprehensive toolbox of sub-micrometer components (transistors, capacitors, interconnection wires, etc.) for designing and reproducibly manufacturing complex highperformance low-power circuits with record integration density and nearly 100% yield. Our basic sensor cell (Figure 1a) consists of two n-MOS transistors actuated by two nonoverlapping clock signals, ΦD and ΦT, to alternately switch the voltage VN on the left nanoelectrode plate of nanocapacitor C between a discharge voltage VD (t = t1) and a transfer (i.e., charge) voltage VT (t = t2). The right capacitor plate, constituted by the electrolyte, is at the solution potential VL. The total charge transferred by a sensor cell in N discharge/charge cycles is Q = N (VT − VD)(C + C P) 2356

(2) DOI: 10.1021/acs.accounts.6b00349 Acc. Chem. Res. 2016, 49, 2355−2362

Article

Accounts of Chemical Research

where kB is Boltzmann’s constant and T is the absolute temperature. Consequently, the intrinsic signal-to-noise ratio is ⎛ ΔQ ⎞2 N (VT − VD)2 (ΔC)2 ⎜⎜ ⎟⎟ = 2kBT (C + C P) ⎝ σQ ⎠

This relation motivates the need for advanced CMOS in order to maximize the signal-to-noise ratio. First, ΔC increases with decreasing nanoelectrode dimensions, calling for electrodes with a size as small as possible. Second, decreasing C + CP gives less noise; while nanoelectrodes with a small capacitance C still can be made with non-CMOS methods such as electronbeam lithography, small CP really requires the unique submicrometer dense integration capabilities of modern CMOS technology. The basic sensor cell is repeated in a dense 256 × 256 array with row and column pitches of 720 and 600 nm, respectively, as sketched in Figure 1b. Figure 1c shows a transmission electron microscope image of the cross-section of a cell, which consists of a single nanoelectrode connected with a 2.5 μm-high vertical pillar to the two control n-MOS transistors located directly below the electrode. This pillar consists of a stack of four copper islands and so-called vias (M1/V1−M4/V4) fabricated at different stages during the standard CMOS manufacturing process. To form the nanoelectrodes, a gold layer is deposited on the chip surface and alloyed with the copper in the V4 vias to form a gold-rich AuCu alloy. Excess Au and AuCu on the chip surface is removed with a polishing step, leaving well-separated AuCu nanoelectrodes exposed at the original chip surface (Figure 1d). The same Au alloying and polishing steps are used to make AuCu bond pads for electrical connections to the chip. The sensor cells are measured one row at a time. All cells in a selected row are operated in parallel by applying the clock signals of Figure 1a to their ΦD and ΦT row terminals. VD and VT are applied row- and column-wise, respectively. All nonselected nanoelectrodes are isolated from the column lines (by applying a low voltage on their ΦT row terminals) and merged into one large on-chip counter electrode by connecting them to AC-grounded discharge lines (using a high voltage on their ΦD row terminals). This “reconfigurable on-chip counter electrode” concept provides the shortest possible lowimpedance AC return path from the electrolyte to the chip.

Figure 1. (a) Schematic of a basic sensor cell with actuation clock signals. (b) Schematic of a 4 × 4 section of the array with a single sensor cell highlighted in red. (c) Transmission electron microscope cross section through a column of sensor cells, showing the nanoelectrodes and vertical interconnection pillars. The M and V labels correspond to distinct metal layers created at different steps in the CMOS fabrication process. (d) Scanning electron microscope topview image of 44 × 24 nanoelectrodes (∼1.6% of an array). Inset: optical image of the complete chip (2.1 mm × 3.2 mm) with a white arrow indicating the location of the array.

where CP is the parasitic capacitance of the nanoelectrode. A capacitance change ΔC, induced, for example, by the binding of an analyte to the nanoelectrode, causes a change ΔQ = N (VT − VD)ΔC

(3)

The variance of the statistical fluctuations in Q, consisting of the accumulated transistor reset noise of the 2N switching steps, is σQ 2 = 2NkBT (C + C P)

(5)

(4)

Figure 2. (a) Measured capacitance as a function of time, Cexp(t), for three neighboring electrodes in response to the sedimentation of a 4.4 μm radius polystyrene particle on the array. (b) Spatial map of the change in capacitance, ΔCexp, measured at 50 MHz upon microparticle sedimentation. Each pixel represents a single electrode, and the blue spots correspond to microparticles covering multiple electrodes. (c) Spatial map obtained simultaneously with that in panel b but at a frequency of 1.6 MHz. Here microparticles only incite a response in a single electrode when located directly above the electrode (red circle). (d) Measured capacitance, Cexp(t), upon binding a 28 nm diameter particle. Panels a−c are adapted with permission from ref 38. 2357

DOI: 10.1021/acs.accounts.6b00349 Acc. Chem. Res. 2016, 49, 2355−2362

Article

Accounts of Chemical Research The charges transferred by the selected sensor cells are detected by measuring the column currents and digitized with eight on-chip analog-to-digital converters. To further reduce noise, multiple digital samples of each sensor cell can be accumulated on the chip before being exported over a serial bus.

■

PROOF-OF-CONCEPT EXPERIMENTS The basic functioning of the nanocapacitor array during measurements is illustrated in Figure 2. Here insulating polystyrene microparticles suspended in water were allowed to sediment on the array while the response of each of the 65 536 electrodes was monitored in real time. When a particle approaches an electrode, it causes the ionic current to that electrode to decrease and leads to a drop in the measured capacitance Cexp = C + CP. This is shown in Figure 2a for the case of a large (4.4 μm radius) particle, which causes a decrease of a few hundred attofarads in the measured capacitance. Interestingly, this decrease is observed at several electrodes simultaneously, a consequence of the microparticle being sufficiently large to span multiple electrodes. This spatial dependence is shown in more detail in Figure 2b. Here the response of (a portion of) the array is represented as a twodimensional map in which each pixel represents a single electrode and the change of capacitance after sedimentation of particles (that is, the size of the steps in Figures 2a) is represented via a color scale. Each landing particle incites a response in a cluster of electrodes, electrodes immediately below the particle exhibiting the largest signal and the response of other electrodes decreasing with distance from its center. The size of the “footprint” of a particle in the response is comparable to its diameter, in agreement with predictions from numerical simulations.38 These detection experiments are made possible by the use of high frequencies as they allow probing beyond the EDL. This is illustrated explicitly in Figure 2c, which was obtained simultaneously with Figure 2b but with a frequency of 1.6 MHz instead of 50 MHz. At this frequency, the particles are essentially invisible apart from a few cases where a single electrode yields a measurable signal at the position of a particle. This can be understood by noting that the cutoff frequency, f1, as defined in eq 1, has a value of 2.6 MHz under the conditions measured here. As expected, below this frequency only particles in direct contact with an electrode, and thus within the range of the EDL, yield a significant signal. What about analytes with dimensions comparable to or smaller than the electrode radius? In this case, only a single electrode exhibits a response, an example of which is shown in Figure 2d for the binding of a single 28 nm diameter polystyrene nanoparticle under similar conditions as Figure 2a (137 mM ionic strength, pH 7). While a clear step can be discerned, its magnitude is a mere 2 aF, far below the sensitivity of conventional EIS instrumentation. The step is also much more abrupt in time compared to the larger microparticles, reflecting faster diffusion dynamics and a shorter-range interaction with the electrode. An additional advantage of long-range, high-frequency detection is that the response depends on the electrical properties of the entity being detected. This is illustrated in Figure 3a, which shows the response of the array to a mixture of dielectric (polystyrene) and conducting (gold-coated polystyrene) microparticles. The response to the conducting particles is an increase in Cexp, opposite in polarity to that of the dielectric

Figure 3. Impedance imaging. (a) Dielectric and conducting microparticles yield negative and positive changes in capacitance, respectively, due to the difference in their conductivity. (b) Response of the array to suspended K562 (left), adsorbed MCF7 (middle), and dead BEAS (right) cancer cells. (c, d) Response to emulsions of orthodichlorobenzene (c) and [BmPyrr]+[NTf2]− (d) in water. Panels a and b are adapted with permission from ref 38.

particles. Similarly, Figure 3b shows the capacitance response to the presence of three types of cancer cells with different characteristics. K562 cells in suspension (left) induced a decrease in the response qualitatively comparable to the signature of dielectric beads as a result of their insulating outer membrane. MCF7 cells also led to a negative response but exhibited strong attachment and migration over the chip surface, which could be monitored with the sub-micrometer spatial resolution inherent to the array.38 In contrast, dead BEAS cells presented a positive change in capacitance induced by the formation of a layer of highly charged macromolecules after the cellular membrane was destroyed. Finally, Figure 3c,d shows the change in capacitance induced by emulsions consisting of inhomogeneous droplets of 1% v/v orthodichlorobenzene and 5% v/v 1-butyl-1-methylpyrrolidinium bis(trifluoromethyl-sulfonyl)imide ([BmPyrr]+[NTf2]−), respectively, suspended in water after 1 min of sonication. While both solvents have a dielectric constant lower than that of water (9.939 and 14.7,40 respectively), the high conductivity of the [BmPyrr]+[NTf2]− ionic liquid yields an increase in Cexp similar to that for conducting microparticles, enabling clear differentiation between the two emulsions. These images demonstrate the flexibility of the array to image a broad variety 2358

DOI: 10.1021/acs.accounts.6b00349 Acc. Chem. Res. 2016, 49, 2355−2362

Article

Accounts of Chemical Research

corresponding equilibrium Poisson−Boltzmann (PB) equation. 42,43 Coupled to site-binding models to describe immobilized charges,44 possibly enriched by specific models for the compact layer permittivity,45 the PB equation is well accepted for describing and optimizing ISFETs and BioFETs.46−49 For impedance spectroscopy analysis with nanocapacitor arrays, a natural and convenient extension of the PB and PNP models is to consider the corresponding AC smallsignal equations. Following this strategy, we coded a general purpose, custom full 3D control-volume finite-elements method (CVFEM) solver of the DC and AC small signal PB and PNP equations,50 respectively, onto tetrahedral unstructured grids. The results of a typical calculation are illustrated in Figure 4a, which shows a

of systems and to discern different materials not only due to their shape but also due to their differing electrical properties. While the combination of sensitivity, high frequencies, and spatiotemporal resolution outlined above is unsurpassed, a fully integrated, chip-based approach introduces experimental considerations that depart from common practice in electrochemical measurements. Once designed and fabricated within the constraints allowed by the CMOS fabrication process, modifying the chip represents a major investment. As a result, experimental parameters such as the electrode material cannot be replaced as readily as in conventional macroscopic measurements. Even relatively minor changes such as modifying the sequence in which the electrodes are read out require low-level programming that lies outside the realm of experience of most electrochemists. On the other hand, because of the small physical size of the chips and the fact that all of the readout electronics are embedded on it, the method is quite insensitive to electromagnetic and vibrational interference. In stark contrast with other nanoscale electrochemical measurements in our laboratories, which typically require Faraday cages and protection from vibrational and acoustic noise, the experiments outlined above were all performed on a regular table top without any form of shielding.

■

A NONEMPIRICAL THEORETICAL DESCRIPTION EIS experiments are most often interpreted by fitting the impedance of compact lumped-element circuit models to the measurements. While providing a useful characterization tool, these empirical models have limited predictive value, in no small part because the circuit elements and nodes have no unique and clear correspondence to the geometry and physics of the system under consideration.18 An alternative theoretical approach is to establish a system of model equations capturing the essential physics and to discretize and solve them numerically with dedicated or general-purpose codes such as Comsol Multiphysics. This method is well established for computer-assisted design of nanoelectronic devices in the semiconductor industry41 and has led to highly dependable transistor simulations in all bias regimes and up to very high frequency. Once the model equation parameters (e.g., mobility, diffusivity, etc.) and the system geometry are known, or calibrated on a limited set of experiments, the system response can be predictively calculated for a variety of physical conditions. Extending this methodology to the realm of impedancebased sensors, which include the semiconductor device, the electrode−electrolyte interface, and the analyte, is not a straightforward task. This is mainly because of the multiscale/ multiphysics nature of the physicochemical processes occurring in the first few nanometers from an electrode. In this respect, high-frequency EIS provides an especially favorable case study. At high frequency, the AC field at the surface is small and the response is only weakly sensitive to the surface potential and charges. Thus, the details of molecular and atomic scale charge distributions can be approximated (e.g., with dielectric layers and charge sheets) without major loss of accuracy, while meanfield theory and partial differential equation models become adequate to represent the electrode and the analyte interactions via the electrolyte. An appropriate theoretical framework to describe analytes in electrolytes is given by the Poisson−Nernst−Planck (PNP) model, also known as the Poisson-drift-diffusion (PDD) equation in the semiconductor literature, as well as the

Figure 4. (a) Color map of the AC potential on the surface of the nanocapacitor array and of a spherical dielectric micrometer-scale particle in water at 50 MHz and 10 mM salt. Note the small signal (1 mV) excitation of a row of electrodes and the corresponding penetration of the high-frequency electric field to the particle’s bottom surface. (b) Three-dimensional simulations of nanoelectrode capacitance spectra (solid lines) without particles (green) and with rp = 2.5 μm particles suspended 10 and 40 nm above the center of the electrodes (red and yellow, respectively) or in between electrodes in the diagonal direction (blue). The corresponding dashed lines show the change in capacitance with respect to the case without particles.

spatial map of the AC component of the electric potential in the presence of a microparticle. Values for the predicted frequency-dependent capacitance response of individual electrodes can be extracted from these simulations, as illustrated in Figure 4b. The spectra exhibit a plateau at low frequencies that extends up to the cutoff frequency, f1, defined by eq 1. The observed change in capacitance upon the introduction of the microparticle, ΔC, exhibits a maximum above f1, thus suggesting the existence of an optimum (salt-concentration dependent) detection frequency. An advantage of full 3D simulations is the possibility to explore a configuration space where the position and orientation of analytes can be arbitrarily set, as illustrated in Figure 4b for different microparticle positions. The impact of particle position, shape, volume, height, and permittivity, as well 2359

DOI: 10.1021/acs.accounts.6b00349 Acc. Chem. Res. 2016, 49, 2355−2362

Article

Accounts of Chemical Research

quantitative information is embedded in the frequency dependence of the impedance signal. It will be interesting to see what new recognition and fingerprinting capabilities emerge when we fully embrace the challenge of interpreting the frequency response of complex biological entities.

as electrode shape, can be assessed quantitatively. Another advantage that cannot be matched by analytical or lumpedelement models is to account for experimental details such as the actual pattern of excitation electrodes in the array. This can be clearly seen in Figure 4a, where an entire row of the array being excited at once is reflected in an anisotropic electric potential on the microsphere surface. Numerical simulations can thus provide a solid ground also to the derivation of simpler lumped element circuits, and assist a clear identification of the physical equivalent of each circuit element.

■

AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Phone: +31-53 489 2306.

■

Author Contributions

OUTLOOK The chip designs, as well as the theoretical and experimental results summarized above, represent only early steps in exploring the potential of nanoscale, high-frequency AC detection. Indeed, very substantial boosts in performance and capabilities can be achieved beyond what we have presented here. First, it is crucial that our nanocapacitor array is based on standard CMOS technology. This signifies that, as further advances take place as anticipated by the International Technology Roadmap for Semiconductors (ITRS),51 it will become possible to attain higher frequencies, smaller electrode sizes, and higher array densities. Anticipated developments include characteristic feature sizes comparable to the size of macromolecules such as antibodies (Figure 5), potentially

The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. Funding

S.G.L., C. L., and C. R. acknowledge financial support from the European Research Council (ERC) under Project Number 278801. Notes

The authors declare the following competing financial interest(s): F.P.W. is the co-inventor of multiple patents on which the CMOS nanocapacitor platform is based and is employed by NXP, where it was developed. The other authors declare no competing interests. Biographies Serge G. Lemay was born in Rimouski, Canada, in 1970. He received a B.A.Sc. in Electrical Engineering with minor in Physics from the University of Waterloo, Canada, in 1993 and a Ph.D. in Physics from Cornell University, NY, USA, in 1999. He was faculty at the Kavli Institute of Nanoscience, Delft University of Technology, The Netherlands, from 2001 to 2009. In 2009, he founded the Nanoionics group at the MESA+ Institute for Nanotechnology, University of Twente, The Netherlands. His main research interests at present include electrostatics in liquids, electroosmosis, and electrochemical nanofluidics. Cecilia Laborde was born in Bahiá Blanca, Argentina, in 1986. She studied Physics at the University of Buenos Aires, Argentina, and received her Ph.D. degree from the University of Twente, The Netherlands, in 2016. Her main research interests include impedance spectroscopy, biosensing mechanisms, and nanoscale phenomena.

Figure 5. CMOS intermediate wiring half pitch roadmap as predicted by ITRS in 2009 compared to typical biomolecular dimensions. Metal 1 half pitch stands for half the minimum center-to-center distance spacing between metal 1 lines as shown in Figure 1c. Adapted with permission from ref 37. Copyright 2010 IEEE.

Christophe Renault was born in l’Isle-Adam, France, in 1985. He received a M.S. in physico-chemistry and a Ph.D. in biomolecular electrochemistry from the University Paris 7 Denis-Diderot. He undertook postdoctoral research in the University of Texas at Austin (USA) in successively the groups of R. M. Crooks (2012−2014) and A. J. Bard (2015−2016). He is currently a postdoctoral researcher in the Nanoionics group at the University of Twente. His main research interests are biomolecular electrochemistry, nanoelectrochemistry, and sensors.

allowing direct measurements at the single-molecule level, higher electrode packing densities leading to arrays with spatial resolutions superior to optical imaging, and faster measurements, including both higher readout temporal resolutions and modulation frequencies. Reaching frequencies greater than the so-called electrolyte dielectric relaxation cutoff frequency, f 2 = 1/(2πRsolCsol), approximately 500 MHz at physiological salt conditions, is particularly interesting because the capacitance signal then becomes independent of the ionic conductivity of the electrolyte. We anticipate that measurements in this regime will be particularly robust and amenable to quantitative interpretation. In addition to improvements in raw performance, realizing concrete biosensing applications will require targeted modification of the electrode surfaces to introduce specific recognition. More generally, the measurements presented here have focused mainly on simple detection at a single frequency. As in conventional EIS, however, a wealth of

Andrea Cossettini was born in Udine, Italy, in 1989. He received a M.Sc. in Electronic Engineering from the University of Udine, Italy, in 2015. During Spring 2014, he was at Acreo Swedish ICT AB (Kista, Sweden), designing waveguide-to-chip transitions at millimeter or submillimeter waves. He developed his master’s thesis at Infineon Technologies (Villach, Austria), working on signal integrity for highspeed serial interfaces. He is currently pursuing his Ph.D. working on electronic nano-biosensors. His main research interests include bioelectronics and biosensing techniques, high-frequency electronics, and electromagnetic phenomena. 2360

DOI: 10.1021/acs.accounts.6b00349 Acc. Chem. Res. 2016, 49, 2355−2362

Article

Accounts of Chemical Research

(13) Varshney, M.; Li, Y. Interdigitated array microelectrodes based impedance biosensors for detection of bacterial cells. Biosens. Bioelectron. 2009, 24, 2951−2960. (14) Fosdick, S. E.; Knust, K. N.; Scida, K.; Crooks, R. M. Bipolar electrochemistry. Angew. Chem., Int. Ed. 2013, 52, 10438−10456. (15) Zevenbergen, M. A. G.; Wolfrum, B. L.; Goluch, E. D.; Singh, P. S.; Lemay, S. G. Fast electron-transfer kinetics probed in nanofluidic channels. J. Am. Chem. Soc. 2009, 131, 11471−11477. (16) Ma, C.; Contento, N. M.; Gibson, L. R.; Bohn, P. W. Redox cycling in nanoscale-recessed ring-disk electrode arrays for enhanced electrochemical sensitivity. ACS Nano 2013, 7, 5483−5490. (17) Howorka, S.; Siwy, Z. Nanopore analytics: Sensing of single molecules. Chem. Soc. Rev. 2009, 38, 2360−2384. (18) Barsoukov, E.; Macdonald, J. R. Impedance Spectroscopy: Theory, Experiment, and Applications: John Wiley & Sons, Inc.: Hoboken, NJ, 2005. (19) Matsumoto, A.; Miyahara, Y. Current and emerging challenges of field effect transistor based bio-sensing. Nanoscale 2013, 5, 10702− 10718. (20) Nair, P. R.; Alam, M. A. Screening-limited response of NanoBiosensors. Nano Lett. 2008, 8, 1281−1285. (21) Stern, E.; Wagner, R.; Sigworth, F. J.; Breaker, R.; Fahmy, T. M.; Reed, M. A. Importance of the debye screening length on nanowire field effect transistor sensors. Nano Lett. 2007, 7, 3405−3409. (22) Walcarius, A.; Minteer, S. D.; Wang, J.; Lin, Y.; Merkoçi, A. Nanomaterials for bio-functionalized electrodes: Recent trends. J. Mater. Chem. B 2013, 1, 4878−4908. (23) Ingebrandt, S. Bioelectronics: Sensing beyond the limit. Nat. Nanotechnol. 2015, 10, 734−735. (24) Lerner, M. B.; D’Souza, J.; Pazina, T.; Dailey, J.; Goldsmith, B. R.; Robinson, M. K.; Johnson, A. T. C. Hybrids of a genetically engineered antibody and a carbon nanotube transistor for detection of prostate cancer biomarkers. ACS Nano 2012, 6, 5143−5149. (25) Eteshola, E.; Keener, M. T.; Elias, M.; Shapiro, J.; Brillson, L. J.; Bhushan, B.; Lee, S. C. Engineering functional protein interfaces for immunologically modified field effect transistor (ImmunoFET) by molecular genetic means. J. R. Soc., Interface 2008, 5, 123−127. (26) Yang, L. Electrical impedance spectroscopy for detection of bacterial cells in suspensions using interdigitated microelectrodes. Talanta 2008, 74, 1621−1629. (27) Susloparova, A.; Koppenhöfer, D.; Vu, X. T.; Weil, M.; Ingebrandt, S. Impedance spectroscopy with field-effect transistor arrays for the analysis of anti-cancer drug action on individual cells. Biosens. Bioelectron. 2013, 40, 50−56. (28) Couniot, N.; Afzalian, A.; Van Overstraeten-Schlögel, N.; Francis, L. A.; Flandre, D. Capacitive biosensing of bacterial cells: Analytical model and numerical simulations. Sens. Actuators, B 2015, 211, 428−438. (29) Ionescu-Zanetti, C.; Nevill, J. T.; Di Carlo, D.; Jeong, K. H.; Lee, L. P. Nanogap capacitors: Sensitivity to sample permittivity changes. J. Appl. Phys. 2006, 99, 024305. (30) Van Gerwen, P.; Laureys, W.; Huyberechts, G.; Op De Beeck, M.; Baert, K.; Suls, J.; Varlan, A.; Sansen, W.; Hermans, L.; Mertens, R. Nanoscaled interdigitated electrode arrays for biochemical sensors. International Conference on Solid-State Sensors and Actuators, Proceedings; IEEE: Chicago, 1997; Vol. 2, pp 907−910. (31) Malavé, A.; Tewes, M.; Gronewold, T.; Lö hndorf, M. Development of impedance biosensors with nanometer gaps for marker-free analytical measurements. Microelectron. Eng. 2005, 78−79, 587−592. (32) Löhndorf, M.; Schlecht, U.; Gronewold, T. M. A.; Malavé, A.; Tewes, M. Microfabricated high-performance microwave impedance biosensors for detection of aptamer-protein interactions. Appl. Phys. Lett. 2005, 87, 243902. (33) Schlecht, U.; Malavé, A.; Gronewold, T.; Tewes, M.; Löhndorf, M. Comparison of antibody and aptamer receptors for the specific detection of thrombin with a nanometer gap-sized impedance biosensor. Anal. Chim. Acta 2006, 573−574, 65−68.

Luca Selmi was born in Roma, Italy, in 1961. He received a Ph.D. from the University of Bologna in 1992. Since 2000, he is Professor of Electronics at University of Udine, Italy. In 2015, he was elected to the IEEE Fellow grade. He served as TPC member of various conferences, including IEEE IEDM and IEEE VLSI Tech. Symposium, and as Editor of IEEE EDL. His research interests include simulation, modeling, and characterization of nanoscale CMOS transistors and NVM, with emphasis on hot-carrier effects, quasi-ballistic transport, Monte Carlo simulation techniques, and with a recent twist toward nanoelectronic (bio)sensors. Frans Widdershoven was born in Sittard, The Netherlands, in 1959. He received a M.S. in Electrical Engineering from the Technical University of Eindhoven in 1984. From 1984 to 2006, he was a researcher and group leader at Philips N.V. In 1991, he obtained a Ph.D. degree from the University of Twente. In 2006, he joined NXP Semiconductors when it was split off from Philips. At NXP, he worked on embedded flash memories, embedded phase change memories, CMOS biosensors, hardware security, gas sensing, and technology scouting. In 2010, Frans was promoted to the degree of Fellow.

■

REFERENCES

(1) Zhu, C.; Yang, G.; Li, H.; Du, D.; Lin, Y. Electrochemical Sensors and Biosensors Based on Nanomaterials and Nanostructures. Anal. Chem. 2015, 87, 230−249. (2) Bartlett, P. N. Bioelectrochemistry: Fundamentals, Experimental Techniques and Applications; John Wiley & Sons, Ltd.: Southampton, U.K., 2008. (3) Yin, T.; Qin, W. Applications of nanomaterials in potentiometric sensors. TrAC, Trends Anal. Chem. 2013, 51, 79−86. (4) El Ichi, S.; Leon, F.; Vossier, L.; Marchandin, H.; Errachid, A.; Coste, J.; Jaffrezic-Renault, N.; Fournier-Wirth, C. Microconductometric immunosensor for label-free and sensitive detection of Gramnegative bacteria. Biosens. Bioelectron. 2014, 54, 378−384. (5) Spera, R.; Festa, F.; Bragazzi, N. L.; Pechkova, E.; LaBaer, J.; Nicolini, C. Conductometric monitoring of protein-protein interactions. J. Proteome Res. 2013, 12, 5535−5547. (6) Bryan, T.; Luo, X.; Bueno, P. R.; Davis, J. J. An optimized electrochemical biosensor for the label-free detection of C-reactive protein in blood. Biosens. Bioelectron. 2013, 39, 94−98. (7) Lisdat, F.; Schäfer, D. The use of electrochemical impedance spectroscopy for biosensing. Anal. Bioanal. Chem. 2008, 391, 1555− 1567. (8) Tu, W.; Dong, Y.; Lei, J.; Ju, H. Low-potential photoelectrochemical biosensing using porphyrin- functionalized TiO2 nanoparticles. Anal. Chem. 2010, 82, 8711−8716. (9) Ronkainen, N. J.; Halsall, H. B.; Heineman, W. R. Electrochemical biosensors. Chem. Soc. Rev. 2010, 39, 1747−1763. (10) Rothberg, J. M.; Hinz, W.; Rearick, T. M.; Schultz, J.; Mileski, W.; Davey, M.; Leamon, J. H.; Johnson, K.; Milgrew, M. J.; Edwards, M.; Hoon, J.; Simons, J. F.; Marran, D.; Myers, J. W.; Davidson, J. F.; Branting, A.; Nobile, J. R.; Puc, B. P.; Light, D.; Clark, T. A.; Huber, M.; Branciforte, J. T.; Stoner, I. B.; Cawley, S. E.; Lyons, M.; Fu, Y.; Homer, N.; Sedova, M.; Miao, X.; Reed, B.; Sabina, J.; Feierstein, E.; Schorn, M.; Alanjary, M.; Dimalanta, E.; Dressman, D.; Kasinskas, R.; Sokolsky, T.; Fidanza, J. A.; Namsaraev, E.; McKernan, K. J.; Williams, A.; Roth, G. T.; Bustillo, J. An integrated semiconductor device enabling non-optical genome sequencing. Nature 2011, 475, 348−352. (11) LaFratta, C. N.; Walt, D. R. Very high density sensing arrays. Chem. Rev. 2008, 108, 614−637. (12) Choi, J. W.; Oh, K. W.; Thomas, J. H.; Heineman, W. R.; Halsall, H. B.; Nevin, J. H.; Helmicki, A. J.; Henderson, H. T.; Ahn, C. H. An integrated microfluidic biochemical detection system for protein analysis with magnetic bead-based sampling capabilities. Lab Chip 2002, 2, 27−30. 2361

DOI: 10.1021/acs.accounts.6b00349 Acc. Chem. Res. 2016, 49, 2355−2362

Article

Accounts of Chemical Research (34) Schlecht, U.; Malavé, A.; Gronewold, T. M. A.; Tewes, M.; Löhndorf, M. Detection of Rev peptides with impedance-sensors  Comparison of device-geometries. Biosens. Bioelectron. 2007, 22, 2337−2340. (35) Kulkarni, G. S.; Zhong, Z. Detection beyond the Debye screening length in a high-frequency nanoelectronic biosensor. Nano Lett. 2012, 12, 719−723. (36) Kulkarni, G. S.; Zhong, Z. Fabrication of carbon nanotube highfrequency nanoelectronic biosensor for sensing in high ionic strength solutions. J. Visualized Exp. 2013, 77, e50438 14 pp. (37) Widdershoven, F.; Steenwinckel, D. V.; Jüberfeld, M. T.; Suy, H.; Jedema, F.; Hoofman, R.; Tak, C.; Sedzin, A.; Cobelens, B.; Sterckx, E.; Werf, R. v. d.; Verheyden, K.; Kengen, M.; Swartjes, F.; Frederix, F. CMOS biosensor platform. Electron Devices Meeting (IEDM), 2010 IEEE International; IEEE: San Francisco, CA, 2010; pp 36.1.1−36.1.4. (38) Laborde, C.; Pittino, F.; Verhoeven, H. A.; Lemay, S. G.; Selmi, L.; Jongsma, M. A.; Widdershoven, F. P. Real-time imaging of microparticles and living cells with CMOS nanocapacitor arrays. Nat. Nanotechnol. 2015, 10, 791−795. (39) Accascina, F.; Swarts, E. L.; Mercier, P. L.; Kraus, C. A. The Conductance of Solutions of Salts in Orthodichlorobenzene. Proc. Natl. Acad. Sci. U. S. A. 1953, 39, 917−924. (40) Huang, M.-M.; Jiang, Y.; Sasisanker, P.; Driver, G. W.; Weingärtner, H. Static Relative Dielectric Permittivities of Ionic Liquids at 25 °C. J. Chem. Eng. Data 2011, 56, 1494−1499. (41) Synopsys Sentaurus Device User Guide; Synopsys: Mountain View: CA, USA, 2013. (42) Fogolari, F.; Brigo, A.; Molinari, H. The Poisson-Boltzmann equation for biomolecular electrostatics: A tool for structural biology. J. Mol. Recognit. 2002, 15, 377−392. (43) APBS/PDB2PQR Home Page. http://www.poissonboltzmann. org (accessed June, 2016). (44) Yates, D. E.; Levine, S.; Healy, T. W. Site-binding model of the electrical double layer at the oxide/water interface. J. Chem. Soc., Faraday Trans. 1 1974, 70, 1807−1818. (45) Gongadze, E.; Rienen, U.; Iglič, A. Generalized stern models of the electric double layer considering the spatial variation of permittvity and finite size of ions in saturation regime. Cell. Mol. Biol. Lett. 2011, 16, 576−594. (46) Shinwari, M. W.; Deen, M. J.; Selvaganapathy, P. R. FiniteElement Modelling of Biotransistors. Nanoscale Res. Lett. 2010, 5, 494−500. (47) Baumgartner, S.; Heitzinger, C.; Vacic, A.; Reed, M. A. Predictive simulations and optimization of nanowire field-effect PSA sensors including screening. Nanotechnology 2013, 24, 225503 (9pp). (48) Wang, Y.; Li, G.: Performance investigation for a silicon nanowire FET biosensor using numerical simulation. 2010 IEEE Nanotechnology Materials and Devices Conference, NMDC2010; IEEE: Monterey, CA, 2010; pp 81−86. (49) Yang, X.; Frensley, W. R.; Zhou, D.; Hu, W. Performance analysis of Si nanowire biosensor by numerical modeling for charge sensing. IEEE Trans. Nanotechnol. 2012, 11, 501−512. (50) nanoHUB website. https://nanohub.org/resources/biolab (accessed June, 2016). (51) International Technology Roadmap for Semiconductors Home page. http://www.itrs2.net/ (accessed June, 2016).

2362

DOI: 10.1021/acs.accounts.6b00349 Acc. Chem. Res. 2016, 49, 2355−2362