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Fully Integrated On-Chip Coil in 0.13 CMOS for Wireless Power Transfer Through Biological Media Meysam Zargham and P. Glenn Gulak, Senior Member, IEEE

Abstract—Delivering milliwatts of wireless power at centimeter distances is advantageous to many existing and emerging biomedical applications. It is highly desirable to fully integrate the receiver on a single chip in standard CMOS with no additional postprocessing steps or external components. This paper presents a 2 2.18 on-chip wireless power transfer (WPT) receiver (Rx) coil fabricated in 0.13 CMOS. The WPT system utilizes a 14.5 14.5 transmitter (Tx) coil that is fabricated on a standard FR4 substrate. The on-chip power harvester demonstrates a , and peak WPT efficiency of at 10 mm of separation through air, bovine muscle and 0.2 molar NaCl, respectively. The achieved efficiency enables the delivery of milliwatts of power to application circuits while staying below safe power density and electromagnetic (EM) exposure limits. Index Terms—Energy harvesting, inductive coupling, integrated CMOS coil, near-field, power density, specific absorption rate (SAR), wireless power transfer.

I. INTRODUCTION

T

HE early 1960’s marks the beginning of implanted medical devices (IMDs). These early implants were bulky and power hungry with high failure rates due to battery complications [1]. Today IMDs are frequently powered wirelessly using an inductively coupled link [2]–[9]. However power receiving coils are traditionally fabricated on a separate substrate from the application circuits and attached to the chip through wirebonding. This segmentation of the design enlarges the volume of the implant, increases the total cost and decreases the reliability. An elegant solution is to integrate the receiver coil with the rest of the circuitry on a single die in standard CMOS. The resulting single-chip prototype would be low-cost, mass producible, compact, reliable and can potentially be used in a bare die form with minimal encapsulation. This level of integration offers significant clinical and laboratory advantages for in vivo and in vitro applications and offers new possibilities for disposable lab-on-chip (LoC) solutions. Historically, researchers have designed and optimized the Tx and Rx coils in the low MHz range to minimize the losses through conductive media [10]–[13]. Therefore, the optimization process uses a simple coupled-inductor model for a fixed

Manuscript received March 04, 2014; revised May 20, 2014; accepted May 29, 2014. This work was supported by NSERC. This paper was recommended by Associate Editor M. Sawan. The authors are with the Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON M5S 3G4, Canada (e-mail: [email protected]). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TBCAS.2014.2328318

load, ignores the media between the coils and commonly converges to coil designs with many ( ) turns. Designing CMOS integrated WPT coils under the above assumptions results in poor power transfer efficiency. Hence, it is widely acknowledged that silicon integrated coils in a standard CMOS process do not yield sufficient WPT capability, due to poor electromagnetic coupling, to support application circuits of interest. Therefore, different coil-on-chip processes have been proposed and implemented [14]–[17]. These technologies enhance the quality factor of the receiving coil by adding magnetic cores and/or using very thick metal ( ) layers. The resulting coils are then connected to the chip using through-silicon-vias (TSVs) or flip-chip connection [18], [19]. However, these post-processing steps increase the cost and fabrication complexity. The context of the discussion then raises the question of whether or not the low frequency region of operation is actually a fundamental property of optimum WPT coils. Wireless power transfer is the result of varying magnetic flux passing through the Rx coil and according to Faraday’s law of induction it is proportional to the rate of change of the magnetic flux. Therefore, as we miniaturize the Rx coil we can increase the frequency of the electromagnetic waves to compensate for the smaller coil area. On the other hand the loss of energy through conductive biological media and the silicon substrate increase with frequency [20]. Therefore, there exists an optimal frequency of operation that maximizes the WPT efficiency through biological media by balancing these two competing effects [21], [22]. In this paper, we show that by properly designing the coil geometry, appropriate frequency selection, proper layout techniques and effective substrate shielding, it is possible to achieve comparable or better WPT efficiencies than previously published approaches using standard CMOS processes alone realizing all the advantages stated above. The paper provides useful experimentally verified insight on what can be expected from a fully integrated CMOS-based power transfer coil through different media. The remainder of the paper is organized as follows. Section II, provides the required background knowledge to understand the terminologies used in the paper; readers who are familiar with [21] or prefer to focus on the results can skip this section without a loss of continuity. Section III presents the design of the on-chip coil and the transmitter coil. In Section IV, we present the simulation and measurement results for wireless power transfer efficiency through air and biological media. This section also discusses the limits on maximum allowed power transmission to stay under IEEE safety guidelines for human exposure to EM

1932-4545 © 2014 EU

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, is achieved when the two-port is driving an optimum load. The impedance and admittance of the optimum load is shown in (5)–(8) [21]

(5) (6) Fig. 1. The block diagram for a generalized WPT system. The represent the power efficiency through each block.

values

(7) (8)

fields[23] for in vivo applications. Also, a figure of merit is proposed to compare miniaturized WPT coils with different area and/or coil separations. Finally Section V concludes the paper. II. BACKGROUND This section is based on the maximum achievable efficiency approach outlined in [21]. Fig. 1 shows the block diagram of the most general form of a passive WPT system. The power transfer efficiency is defined as

The optimum load is realized using matching networks or multiple coil designs [24]–[26]. The power transfer efficiency through the matching network, , depends on the quality factor of the matching components [21] and is close to 100% when the matching network only consists of capacitors. The maximum two-port efficiency, depends on the design of the WPT coils. In the next section, guidelines are provided for optimizing the geometry of WPT coils under a given set of constraints in order to maximize (3). III. DESIGN OF THE WPT COILS

(1) where is the power delivered to the load and is the power provided by the source ( ). The power efficiency, , can be divided into three parts

(2) where represents the efficiency of the power transfer from a DC source to the input of the Tx coil and is usually represented by the efficiency of the employed power amplifier, represents the power transfer efficiency from the input of the Tx coil to the output of the Rx coil and represents the power transfer efficiency of the matching network. It has been shown that the maximum achievable power transfer efficiency through the two-port, , depends only on the two-port parameters and is given by

(3) where

(4) , , , and , represent the two-port impedance and admittance parameter matrixes from the input of the Tx coil to the output of the Rx coil. The maximum power transfer efficiency,

To illustrate the concepts, the proposed WPT system consists of two spiral coils separated by 10 mm of biological media and air. The receiver coil is integrated on a standard CMOS substrate and its dimensions are bounded by the die area to 2 2.18 while, the transmitter coil is fabricated on a 3oz-FR4 substrate. The two common options for the transmitter coil are wire-wound and printed circuit board (PCB) based coils. The two common types of wire-wound coils are solid wire and litz wire coils. The litz wire coils have the lowest AC resistance among the three options followed by PCB-based coils and solid wire windings [27]. However PCB-based coils are better suited to miniaturization, mass production and are easily modelled and hence were the more appropriate option for our application. The 10 mm Tx-Rx separation is a good estimate for neural implant depth based on the thickness of different tissue layers in an average adult human [28]. The 10 mm distance also serves as a good choice for lab-on-chip applications. In such applications the Tx coil wirelessly powers an Rx coil which is suspended inside a 1.5 ml microcentrifuge tube using a tube filter. The tube itself is typically held inside a microcentrifuge tube storage rack. The distance from the bottom of a typical tube holder to the test tube is 4 mm and the remaining 6 mm is the separation from the bottom of the test tube through the liquid to the bottom of the suspension filter. Hence the 10 mm design choice is an appropriate choice for many lab-on-chip applications. Previous authors have used simplified equations for optimizing a coupled-inductor WPT model in air [10], [29]–[31]. However, as mentioned earlier, ignoring the media during the optimization process incurs large penalties especially at higher frequencies. The biological media is represented using two frequency dependant parameters: conductivity ( ), and permittivity ( ). These parameters are extracted from four

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TABLE I DIELECTRIC PROPERTIES OF BIOLOGICAL MEDIA AT 100 MHZ AND 200 MHZ SORTED BY CONDUCTIVITY

(a)

(b)

Fig. 2. (a) 3D representation of the Tx and Rx coils. (b) Top view of the Tx and Rx coils.

TABLE II SIMULATION SUBSTRATE FOR COIL OPTIMIZATION

approximate thickness of the IBM 0.13

CMOS die

cole-cole models provided in [32]–[35]. Table I shows these values for various biological media from 100 to 200 MHz. The optimization problem quickly becomes complex as we move away from a simple coupled-inductor model to fully modelling the media as well as the CMOS substrate. Commercial EM simulators have proven effective in accurately modeling WPT coils [11], [21]. However blindly optimizing the coil geometry could take excessive simulation time due to slow convergence of EM simulators. In this design we are using a guided EM-based iterative optimization process to maximize . The EM simulator of choice for this process was Momentum [36] which is a 2.5D simulator. The 2.5D simulators such as Momentum are generally faster and less computationally intensive compared to a full 3D EM simulators such as HFSS [37]. However, these simulators model each substrate layer as a infinite plane and hence cannot accurately model situations where a plane is shared among more than one type of substrate material. As a sanity check, the Momentum simulations for wireless power transfer through PCB-based coils with conductive media between them were cross-verified with HFSS. The WPT system was optimized for wireless power transmission through 10 mm of 0.2 molar NaCl solution and air. As shown in Table I, 0.2 molar NaCl closely mimics the EM properties of blood. The full substrate model used for optimization is shown in Table II. The goal of the optimization process is to find the WPT spiral coil geometries that would maximize the power transfer efficiency through biological media. The coil geometry for a spiral

coil is defined using four parameters: (i) the outer dimensions ( , ), (ii) the trace width, ( ), (iii) the trace spacing, ( ) and (iv) the number of turns, ( ). The algorithm assumes that the Rx is perfectly aligned (i.e., parallel coils with geometric centers aligned) at the center of the Tx coil as shown in Fig. 2. Table III summarizes the optimization algorithm. The algorithm starts by initializing (step 1) the coil geometries. The outer dimension of the Tx coil, is set to , to maximizes the magnetic field strength at 10 mm above the coil center [21]. The receiver coil outer dimensions were constrained by the maximum die area and were set to 2 2.18 to maximize the Rx coil area. The initial trace width and spacing was set to the minimum trace width and spacing allowed by the fabrication process for the Rx and Tx coils. Finally, the optimum wireless power transfer frequency depends on various parameters such as coil dimensions, substrate properties and properties of the biological media. This frequency is in the hundreds of MHz range for wireless power transfer through biological media from a cm-size Tx coil to a mm-sized Rx coil [22]. However, the optimum frequency is reduced when the Rx coil is implemented on a silicon substrate due to its conductivity [21]. Hence in this design, the optimization algorithm explores the frequency range between 100–250 MHz for the optimum WPT efficiency. Nevertheless, one can run the optimization algorithm over a much wider frequency range by accepting the extra simulation time overhead. It is worth noting that the optimum frequency to achieve maximum power transfer efficiency is a strong function of the receiver coil size and drops as the coil area is increased. Hence applications that are restricted to industrial, scientific and medical (ISM) radio bands can take advantage of the 40.68 MHz ISM band by employing a large die area. The optimization process starts (steps 2 and 3) by maximizing the quality factor, , of the transmitter and the receiver coils, over the selected frequency range. During these steps of the optimization process only one coil (and the corresponding substrate) at a time along with the biological media are modelled, which effectively reduces the computational complexity and convergence time of the EM simulations. The optimization process searches the design space using multidimensional gradient descent algorithm for different number of

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TABLE III COIL (TX/RX) GEOMETRY OPTIMIZATION ALGORITHM

spacing of the coils that will be fine tuned during the next steps of the algorithm. In the next two steps of the process (steps 4 and 5), we model the full substrate as shown in Table II. The process optimizes the coil geometries by maximizing the two-port efficiency (3). During this step of the optimization, the coil size, , is also added as an optimization parameter. Finally step 5 optimizes the Rx coil geometry. During this step we also explore using multiple metal layers in series or parallel for Rx coil implementation. The algorithm goes through two iterations and finalizes the coil parameters. A. Optimum Load The proposed algorithm in Table III maximizes the two-port power transfer efficiency when the coils are driving the optimum load (5)–(8). However the absolute value of the optimum load is not reflected in the maximum achievable efficiency (3). The optimum load, can always be realized using matching networks regardless of the actual circuit loading. Yet, the optimum load is a important design parameter for wireless power transfer system. In this subsection we discuss the parameters that affect the choice of the optimum load and provide guidelines for achieving the desired optimum load during the WPT coil design stage. The optimum load, is a function of the coil geometry as well as the media in between the coils as reflected in (7). The actual circuit loading, , however is determined by the power consumption and voltage requirements of the application circuits and hence, (a) is not necessarily equal to , and (b) might vary during the operation of the WPT link. These variations would reduce the two-port efficiency from the maximum achievable efficiency. The context of the discussion now raises the question of whether or not the reduced link efficiency would still be able to support the application circuits. We first address the scenario where the load is directly attached to the receiver coil and then discuss the case where a matching network is employed. Let’s assume the input power to the Tx coil, and the orientation of coils are fixed. It is obvious that when the real part of the load, , reduces to less than the optimum load, the efficiency goes down due to non-optimal loading and at the same time the load requires more power to maintain the same voltage. Therefore, the circuit would not be able to operate properly in these conditions. A complementary question is whether or not the WPT link would be able to support the application circuits when increases above the optimum load value. The loss in two-port efficiency due to the variations in the real part of the parallel load when the coil is driving the optimum susceptance, is given by

turns. It then selects the combinations of trace width, spacing and number of turns that resulted in the maximum quality factor and updates the initial values for each coil. The convergence time depends on the minimum chosen step size for the algorithm. However since only one of the coils is modelled at this step, the simulations are fast. Hence these steps quickly provide an initial value for the trace width, number of turns and the

(9) which is roughly equal to than 1 (low efficiency links).

when

is much smaller

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5

(10)

depends on the input voltage swing and is effectively reduced when the input swing is comparable to transistor threshold voltages. The voltage amplitude on the receiver coil depends on the load resistance and when the coil is driving the optimum load is given by

Therefore as the load, increases from the optimum load, , the power delivered to the load would be reduced to

(13)

(11)

The total link efficiency from the Tx coil to the output of the rectifier is

Under fixed input power of and for an optimum load, , the maximum power delivered to the load is

On the other hand the power required for the load to maintain the same voltage would be reduced to (12) Hence as long as , the power delivered to the load would be able to satisfy the voltage requirements. Since , a low efficiency link ( ) would always be able to support the application circuits. In fact it can easily be shown that the inequality is always true as long as and regardless of the value. Therefore, we can conclude that in the absence of a matching network, the minimum parallel load or peak deliverable power determines the desired optimum load. Another option is to realize the optimum load using matching networks, which would lift the constraint on the absolute value of the optimum load. However, a fixed matching network would only be able provide the optimum loading for one specific designed load. Therefore as the load varies during the operation of the link, the efficiency would deviate from maximum achievable efficiency. Thus, once again we are faced with a similar dilemma of whether or not the link would always be able to support the application circuits. One of the most popular choices for matching networks are L-sections [20], [38]. It can be shown (see Appendix A) that, for a lossless L-section, as long as the matching network is designed for the minimum parallel load or peak deliverable power loading, the link would always be able to satisfy the power requirements regardless of load variations and the absolute value of the optimum load. In practice however, on-chip matching networks occupy large area and reduce the overall efficiency [39]. In addition to this, the power transfer efficiency through an L-match decreases as the difference between the optimal load and the actual load increases [21]. Therefore, it is desirable for the optimum load to be close to the worst-case load of the circuit and avoid using on-chip matching networks. Please note that these derivations assume that the input power to the two-port is unaffected by the variations in due to the very small coupling coefficient. In scenarios where the coils are strongly coupled, the transmitter would require some sort of adaptive input matching to provide a constant power into the Tx coil. Another important design consideration that affects the choice of the optimum load is the voltage swing on the receiver coil. The conversion of the harvested energy into DC form is commonly carried out using a rectifier. The rectifier efficiency

(14) Therefore, in applications were the input power or efficiency are poor, one might modify the coil geometry to increase the optimum load (7) and hence the receiver voltage amplitude, to compensate for the low input voltage swing despite the possible deviation from the optimum coil geometry. In other words, accepting losses in maximum achievable efficiency to obtain improved rectifier efficiency. The optimum load in (7) can be represented in terms of two-port Z parameters, assuming that

(15) , the optimum load, (15) In low efficiency links where is mainly a function of the Rx coil and is only weakly dependant on the Tx coil parameters and the media. Therefore, the desired optimum load value can be achieved by modifying the Rx coil. As a first order approximation, the inductance increases with number of turns squared and resistance increases with the number of turns. Therefore, the optimum load tends to increase with more turns in the Rx coil. For example connecting two metal layers in series or increasing the number of turns would increase the optimum load, while reducing the number of turns reduces the optimum load. In conclusion, realizing the desired optimum load value, optimizing the coils for maximum achievable efficiency and the maximizing the total link efficiency do not always coincide. Therefore, depending on the application the designer faces a multi-objective optimization problem. The optimization function in step 5 can be modified to a multi-objective interactive optimization [40] problem or the designer can include the power efficiency for the matching network and rectifier efficiency as part of the optimization goal. In this design the desired optimum load was chosen to be . This value translates to an optimum load of 1.2 at the output of an ideal full-wave rectifier. This resistance corresponds to approximately delivering 10 mW of power at a 3.3 V supply or equivalently 1 mW of power at 1.2 V supply. B. Final Design Parameters Table IV shows the finalized design parameters. Unlike WPT through air, the fringing electromagnetic fields generated by WPT coils operating in the vicinity of biological media, pass through conductive media with high permittivity

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TABLE IV FINAL COIL GEOMETRY

Fig. 3. 3D visualization of the receiver coil. The distance between the two metal layers is not to scale and has been exaggerated for clarity.

and increase the parasitic capacitance and the AC resistance of these coils. As a result, the quality factor of the coils decreases with an increasing number of turns. The effect of s large number of turns on the quality factor is amplified in the presence of a lossy substrate. Hence, optimum WPT coils for biomedical applications tend to have a lower number of turns compared to air-optimized coils [21], [41]. The simulations also confirmed our expectations. The coils with a large number of turns always resulted in inferior performance over the chosen frequency range. Hence, unlike conventional WPT coils, the final optimized coils only have a few turns. In order to minimize the eddy current losses in the Tx coil, the transmitter trace width was tapered from 2000 to 1500 as we moved to inner turns of the spiral. A narrower trace width reduces the eddy current losses in the inner turns where the time-varying magnetic flux is maximum [42]. However tapering was not performed on the Rx coil. The eddy currents in the Rx coil trace are generated by the Tx coil fields as well as the induced current flowing in the Rx coil. However the magnetic flux due to the Tx coil dominates. Since the Rx coil occupies a small area in the geometric center of the Tx coil, both inner and outer traces of the Rx coil experience an approximately uniform magnetic flux. As a result tapering the Rx coil does not improve the efficiency. As confirmation, our EM simulations did not show any advantage in tapering the Rx coil. Once the coil geometry was finalized we made modifications to the on-chip coil to comply with the process design rules for maximum metal width and maximum metal density. As a result, the second top metal layer, ( ), of the receiver was broken down into five parallel strips. These strips were shorted together as often as possible based on the maximum metal density rules of the process. Enforcing these DRC rules however reduced by less than 1 dB. Another design rule that needs to be satisfied is the metal fill requirements. The issue of metal fill restriction requires extra attention when it comes to on-chip inductors. In this design the metal fill constraint on the two top metal layers ( , ) was mainly satisfied due to the relatively large on-chip coil. The fill constraint on the remaining layers however was satisfied by placing floating metal fills underneath the inductor traces and above the active circuits as allowed by the layout rules. The floating metal pieces provide shielding from the lossy substrate and increase the Q while satisfying the metal fill constraint. The floating shield outperforms the commonly used patterned ground shielding (PGS) technique in terms of quality factor improvement [43]. This is especially important in WPT links since the ground planes can reduce the power transfer efficiency. Hence, we used the metal fill constraint to our advantage. Fig. 3 shows a 3D visualization of the Rx coil. The receiver coil was

Fig. 4. Die Micrograph showing a 2.2 receiver coil.

2.2

die and the 2

2.18

Fig. 5. Transmitter coil fabricated with 3oz copper on FR4.

fabricated in a 0.13 IBM CMOS process along with application circuits while the transmitter coil was fabricated using standard PCB technology. Fig. 4 depicts the die micrograph and Fig. 5 shows the transmitter PCB. The next section discusses the simulation and measurement results. IV. SIMULATION AND MEASUREMENT RESULTS In this section, we present the simulation and measurement results for the maximum achievable WPT efficiency of the implemented inductive link. To begin, we present the simulation and measurement results for the receiver coil. In addition, we present experimental results for the power transfer efficiency to the integrated receiver and make comparisons with existing publications whenever possible. The power transfer efficiency measurement and the coil characterization were performed using an Agilent E8361A PNA Microwave Network Analyzer. The measurements were performed at a few selected frequencies through air, liquid (7 mm of 0.2 molar NaCl solution and 3 mm of air) and tissue (7.5 mm of bovine muscle and 2.5 mm of air), for a total of 10 mm separation in each scenario. During these measurements, the receiver and transmitter coils were perfectly aligned (i.e., parallel coils with geometric centers

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Fig. 7. The receiver coil geometric modelling in Momentum.

Fig. 6. The raw measured versus simulated quality factor and inductance for the on-chip Rx coil.

aligned). The NaCl solution mimics the electromagnetic properties ( , ) of blood at the frequency range of interest as shown in Table I. The receiver coil was implemented using the two top metal layers ( and ) of the CMOS process connected in series. Each metal layer has two turns which resulted in a total of 4 turns. Fig. 6 shows the raw measured and simulated inductance and quality factor of the on-chip coil in air. The measurements revealed a peak quality factor of 11.05 at 101 MHz for the integrated Rx coil. The simulated quality factor however was 12.3 and occurred at 130 MHz. It is apparent that the maximum measured quality factor is 10% smaller than the simulation results. Likewise, the measured self-resonance frequency (SRF) is shifted from the simulation results by approximately 20%. This reduction in the quality factor and the SRF is expected due to process variations and the simplified modelling. For example, the sheet resistance of metal layers in a standard CMOS process may vary by as much as 20%. In addition to this, the receiver is filled with active and passive components as well as shielding metal fill blocks both underneath and in the middle of the coil. None of which is accounted for by the process parameters provided by the foundry. However these structures effect the capacitance and hence the SRF of the inductor. This level of detail is extremely difficult to model due to the computationally intensive nature of the simulations and requires considerable processing power. We modeled these circuit elements using large squares of metal at various layers in the middle of the die. Fig. 7 shows the Momentum model for the receiver coil. Nevertheless, these metal pieces would not represent the worst-case loops for eddy currents. As a result the measured quality factor and SRF are lowered from the simulation results. It is evident from Fig. 6 that by properly designing the Rx coil and with an appropriate choice of frequency we can implement coils with high quality factor on a standard CMOS process. It is worth noting that the 20% shift in the SRF may appear to be due to changes in inductance value however variations in capacitance fully explain the experimentally observed results. Fig. 8 shows the measured inductance value as well as both the

Fig. 8. Measured and simulated inductance.

raw and de-embedded simulation results from Momentum. The de-embedded simulation data are obtained by mathematically shunting a capacitor with the raw simulation data to account for the extra capacitance due to active and passive circuitry and metal fill blocks in the middle and underneath the coil. This is similar to the de-embedding process that is commonly used in measuring on-chip inductors [44]. One possible solution to the metal fill modeling problem is reducing the thickness of the substrate dielectric layers in the EM simulation to mimic the metal fill effect to match the measurement results [45]. The recommended reduction in the dielectric thickness, is give by (16) (16) where is the dielectric thickness and FF is the fill factor. This reduction has a similar effect as introducing metal fill [45]. However obtaining a good match requires several iterations and parameter optimization. Next, the maximum achievable efficiency through air was calculated based on the measured S parameters at four different frequency points. This was performed by measuring

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Fig. 11. WPT efficiency measurement in the presence of 7.5 mm bovine muscle. (Please note that the microscope was removed during the measurements.)

Fig. 9. The Block Diagram for WPT efficiency measurement setup.

Fig. 10. WPT efficiency measurement in the presence of 0.2 molar NaCl solution. Please note that the microscope was removed during the measurements.

-parameters of the two-port and then calculating based on the measured data. The block diagram for the measurement setup is shown in Fig. 9. The chip block diagram shows the Rx coil as well as a 9.14 pF capacitor that was integrated on-chip with the coil. We used a 40 GHz probe from GGB and the Agilent E8361A PNA for measurements. Figs. 10 and 11 show the actual measurement setup. It is worth noting that a 1.5 cm thick plexiglass plate was added to the measurement setup to effectively separate the coils from the conductive metal wafer chuck of the probe station and eliminate losses due to induced eddy currents. In addition to this the microscope in the figure was removed during the measurements to avoid any coupling between the transmitter and the conductive metal body of the microscope. As an example, Fig. 12 shows the measured and (17) provides the measured -parameter matrix at 187 MHz.

Fig. 12. Measured and simulated at 10 mm of separation through air.

from the transmitter to the receiver coil

the full

(17) The peak measured was 1.42% and occurred at 187 MHz. Once again we noticed a frequency mismatch between the simulation and measurement results. The peak from simulations was 1.8% and occurred at

Fig. 13. The WPT efficiency through air with 10 mm of Rx-Tx coil separation.

210 MHz. Fig. 13 shows the measured along with the simulation results. In most implant and LoC applications, the power transfer has to be achieved through conductive biological media such as muscle, fat, blood, etc. In order to characterize the WPT efficiency through biological media, further measurements were conducted on the WPT through 0.2 molar NaCl solution and bovine muscle. To best mimic a lab-on-chip scenario, we attached the bottom part of a microcentrifuge tube to the transmitter coil and filled it with NaCl solution. Due to the clearance

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Fig. 14. The measured WPT Efficiency through 7 mm of microcentrifuge-shaped 0.2 molar NaCl solution and 3 mm of air and plastic along with simulation results for both 7 mm 0.2 molar NaCl solution and 3 mm of air and 5.5 mm of 0.2 molar NaCl solution and 4.5 mm of air.

constraint on the probe tip, we could only reliably place the microcentrifuge tube within 1.5 mm of the probe tip before the tube would touch the end of the probe tip. The test tube contained 7 mm of NaCl and the total distance between the transmitter and chip was 10 mm. The tube top was sealed with a 300 thick plastic layer and was placed 200 away from the transmitter coil. Fig. 10 shows the measurement setup. The power transfer efficiency through NaCl solution was on average reduced by 1.5 dB relative to air at the frequencies of interest. The peak power efficiency based on the measured -parameters was 0.94% at 185 MHz. The power transfer efficiency through NaCl was simulated in Momentum to cross-check the results. The simulation setup in Momentum however could not accurately model the measurement setup. This is due to the 2.5D nature of the Momentum software. Each defined substrate layer is modeled as an infinite plane. In our measurement setup however, the microcentrifuge tube containing the NaCl solution only partially covered (finite plane) the coils as shown in Fig. 10. In addition to this, the bottom of the tube is cone shaped hence the effective volume of the tube is smaller compared to a fully cylindrical tube. By modifying the thickness of NaCl layer from 7 mm to 5.5 mm in simulations, we were able to match the NaCl volume within 10%. The remainder of the 10 mm was modelled with air similar to the measurement setup. Fig. 14 shows the simulation versus measurement results for through NaCl solution. We also characterized the WPT efficiency through bovine muscle. The transmitter was positioned 10 mm away from the receiver coil. We used 7.5 mm thick bovine muscle in between the transmitter and the receiver coil and completely covered the Tx coil extending beyond the Tx coil on all sides. The bovine muscle was positioned 1 mm away from the transmitter and 1.5 mm away from the receiver to ensure clearance of the probe tip. Fig. 11 shows the measurement setup. was measured at three different frequencies and is compared with the simulation results for bovine muscle in Fig. 15. A fair comparison between different published wireless power transfer coils is not straight forward as each use a different technology, coil size, separation, frequency and media. In order to make a fair comparison with other published results, we propose a figure-of-merit (FOM) for wireless power

9

Fig. 15. The WPT Efficiency through 7.5 mm thick bovine muscle and 2.5 mm of air.

efficiency in mm-sized receivers with separation distances on the order of 10 mm. The wireless power transfer efficiency in (3) can be approximated by when . As a first order approximation, , where is the mutual inductance between the coils. The mutual inductance itself can be approximated by (18) when receiver coil dimensions are much smaller than the transmitter coil and the two coils are parallel with their geometric centers aligned.

(18) where is the magnetic field strength and is the current in the transmitter coil. In addition to this the magnetic field strength, , of a square loop with optimum outer edge length of a separation distance represented by

at is given by [21], [46] (19)

Combining (19) with (18) results in

(20) scale with the square root of Finally the coil resistance, the coil area multiplied by the number of turns or (21) and using (21) and (20) we can show Assuming, how the power transfer efficiency scales with the receiver coil area.

(22) Equation (22) provides one mechanism to make fair comparisons between WPT systems with different coil geometry and separations. We propose a figure-of-merit (FOM) for wireless

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TABLE V COMPARISON OF WPT EFFICIENCY

TABLE VI 6-LAYER HEAD MODEL

power efficiency in mm-sized receivers with separation distances on the order of 10 mm. The efficiency in miniaturized WPT systems scales with receiver Area and coil severation according to . Considering this facts, we propose the following figure of merit:

(23) where efficiency, is in percentage, represents the separation between the coils in mm and is the area occupied by the receiver coil with dimension. A larger value for the FOM is better. However the FOM only considers first-order effects and can only be used to compare designs with similar area and separations. With this proviso, Table V shows a comparison of this work with the best published results based on the proposed FOM. Note that stated efficiency in all cases is derived from measured -parameters. It is evident from the table that in fact a fully integrated power receiver can out-perform the coils designed on PCB or coils designed using custom fabrication techniques. Another consideration in designs for in vivo applications is the limit for safe exposure to radio-frequency energy. This limit is specified in terms of a unit referred to as the Specific Absorption Rate (SAR). SAR is a measure of the rate at which radio frequency energy is absorbed by the body. In other words SAR limits the heating of conductive tissues due to transmitter EM fields by limiting the maximum allowed transmit power. The combination of SAR limits and the link efficiency determine the maximum deliverable power to the load. In the U.S., the SAR value is limited to 1.6 W/Kg averaged over 1 gram of tissue by the Federal Communications Commission (FCC). In Europe, the Comité Européen de NormalisationÉlectrotechnique (CENELEC) limits the SAR value to 2 W/Kg averaged over 10 grams of tissue. To investigate the maximum deliverable power to the load we chose neural implants as the target application. The SAR value was simulated using HFSS based on a 6-layer head model (skin, fat, skull, dura, cerebrospinal fluid (CSF) and brain) shown in Table VI and illustrated in Fig. 16. The maximum allowed transmitter power to stay under the SAR limit was calculated across several frequencies when the transmitter coil was positioned 3 mm away from the head. Fig. 17 shows the results. We also calculated the maximum allowed transmitter power versus transmitter distance to the head when

Fig. 16. HFSS Model showing the transmitter and a slice of the 6-Layer head model for SAR simulations.

Fig. 17. Maximum allowed transmitter power to stay below the FCC SAR limit when the transmitter is positioned 3 mm from the head.

Fig. 18. Maximum allowed transmitter power to stay below the FCC SAR limit when the transmitter is operating at 160 MHz.

the transmitter was operating at 160 MHz. The results are shown in Fig. 18. In these simulations we used the more restrictive FCC limit. The maximum allowed power for CENELEC is always higher than the FCC limit. For example the maximum allowed power

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CMOS FOR WIRELESS POWER TRANSFER

of our transmitter working at 160 MHz and 4 mm away from the head is limited to 146 mW for FCC while it can transmit 183 mW under the same conditions using the CENELEC limit. Therefore, the proposed design can deliver milliwatts of power to the load while staying under the SAR constraint. These power transfer limits can be improved by modifying the transmitter design [50], [51] or reducing the frequency of operation. However these modification can degrade the link efficiency. In addition to this, for a given FOM value, one can always improve the maximum power delivered to the load by increasing both the transmitter distance from the body and the Rx coil area, hence maintaining a constant efficiency. Another issue that has to be considered with respect to implant safety is the implant power density. According to [52] the maximum allowed power density is 500 to keep temperature changes below 1 . Therefore, to first order, for a given FOM, the efficiency would also scale with load power requirements. Therefore, the 2 2.18 proposed design can deliver milliwatts of power to the load while staying under the power density limit stated above. V. CONCLUSION In this paper we have presented a design strategy, CMOS prototype and measured experimental results for an on-chip coil that was fabricated using a standard CMOS process with no post-fabrication processing. The WPT system out-performs other published results with respect to a FOM that accounts for size and separation. It is evident from our measurement results that by following the proposed design strategy, employing proper layout techniques and an optimum choice of frequency, an integrated coil can usefully be used for both in vivo and in vitro applications. The integrated coil occupies a 2 2.18 area in 0.13 CMOS process. Based on the measured -parameters, the coil achieves a peak quality factor of 11.05 and a maximum power efficiency of 1.4% through 10 mm of air. We further showed that the chip can achieve approximately 1% efficiency through 7 mm depth of 0.2 molar of sodium chloride solution and 3 mm of air. In addition to this we achieved a WPT efficiency of 0.8% through 7.5 mm of bovine muscle and 2.5 mm of air. The proposed transmitter can safely emit over 100 mW of power at 160 MHz to a neural implant while staying under SAR limitations. Therefore, we can conclude that this design allows for a fully integrated mm-sized WPT Rx coil utilizing only standard CMOS that is capable of providing milliwatts of wireless power at centimeter distances through conductive biological media.

Fig. 19. L-match sections for

11

.

(25) where

is defined as

(26) Without loss of generality, lets assume that the optimum load resistance, is times smaller than the desired load, . In other words (27) changes to , Now if the load resistance, the input resistance will change from to , in parallel with , which changes both the two-port conductance and susceptance from their optimum values. The percentage deviation from the optimum susceptance when is proportional to and hence is commonly small. Nevertheless, for scenarios where the deviation is significant an adaptive matching network is essential. As for the real part of the load, which is the main focus of this appendix, the two-port efficiency would degrade according to (9). Therefore, for a lossless matching network, the delivered power, is reduced to (11) where represents the deviation of the parallel load from the optimum load.

(28) The desired power for maintaining the same minimum voltage is

APPENDIX L-SECTION MATCHING NETWORK

(29)

Fig. 19 shows a single L-section matching network. The L-match is designed to transform the circuit load to a smaller optimum load . Under the given constraintthe L-section component values are

(24)

is defined in (10). Hence as long as , the link would remain operational. The above condition translates to

where

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Fig. 20. Matching network on transmitter side.

(30) . ThereThe above inequality always holds as long as fore as long as the load resistance increases from the designed value, the two-port would always be able to satisfy the voltage requirements. A similar analysis can be done for the matching networks on the transmitter side. The fabricated chip contains power delivery circuits such as rectifiers and regulators [53]. In order to test the efficiency under real load conditions, we employed an L-match using two capacitors on the transmitter side to provide a 50 loading for the power amplifier. The values of these capacitors depend on the frequency of operation. At 160 MHz the series and the parallel capacitors in Fig. 20 had values of 19 pF and 193 pF, respectively. ACKNOWLEDGMENT The authors would like to thank CMC for fabrication support. REFERENCES [1] W. Greatbatch and C. F. Holmes, “History of implantable devices,” Med. Biol. Mag., vol. 10, no. 3, pp. 38–41, Sep. 1991. [2] C. Sauer, M. Stanacevic, G. Cauwenberghs, and N. Thakor, “Power harvesting and telemetry in CMOS for implanted devices,” IEEE Trans. Circuits Syst. I, Reg. Papers, vol. 52, no. 12, pp. 2605–2613, Dec. 2005. [3] M. Ghovanloo and K. Najafi, “A modular 32-site wireless neural stimulation microsystem,” IEEE J. Solid-State Circuits, vol. 39, no. 12, pp. 2457–2466, Dec. 2004. [4] R. R. Harrison, P. T. Watkins, R. J. Kier, R. O. Lovejoy, D. J. Black, B. Greger, and F. Solzbacher, “A low-power integrated circuit for a wireless 100-electrode neural recording system,” IEEE J. Solid-State Circuits, vol. 42, no. 1, pp. 123–133, Jan. 2007. [5] S. B. Lee, H. M. Lee, M. Kiani, U. Jow, and M. Ghovanloo, “An inductively powered scalable 32-channel wireless neural recording system-on-a-chip for neuroscience applications,” IEEE Trans. Biomed. Circuits Syst., vol. 4, no. 6, pp. 360–371, Dec. 2010. [6] D. Pivonka, A. Yakovlev, A. Poon, and T. Meng, “A mm-sized wirelessly powered and remotely controlled locomotive implant,” IEEE Trans. Biomed. Circuits Syst., vol. 6, no. 6, pp. 523–532, Dec. 2012. [7] M. Mark, Y. Chen, C. Sutardja, C. Tang, S. Gowda, M. Wagner, D. 2 Mbps 330 fJ/b transponder for Werthimer, and J. Rabaey, “A 1 implanted neural sensors,” in Proc. Symp. VLSI Circuits, Jun. 2011, pp. 168–169. [8] D. Yeager, W. Biederman, N. Narevsky, E. Alon, and J. Rabaey, “A miniaturized (0.125 ) wireless neural fully-integrated 10.5 sensor,” in Proc. Symp. VLSI Circuits, Jun. 2012, pp. 72–73. [9] J. Olivo, S. S. Ghoreishizadeh, S. Carrara, and G. D. Micheli, “Electronic implants: Power delivery and management,” in Proc. Design, Automation and Test in Europe Conf., Mar. 2013, pp. 1540–1545. [10] W. H. Ko, S. P. Liang, and C. Fung, “Design of radio-frequency powered coils for implant instruments,” Med. Biol. Eng. Comput., vol. 15, pp. 634–640, Nov. 1977.

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Meysam Zargham received the B.Sc. degree from the Sharif University of Technology, Tehran, Iran, the M.Sc. degree from the University of Alberta, Edmonton, AB, Canada, and the Ph.D. degree in electrical engineering from the University of Toronto, Toronto, ON, Canada, in 2005, 2008, and 2014, respectively. While working toward the M.Sc. degree, he was involved in many different projects in a variety of groups, including the design of analog LDPC decoders, micro-fluidic lab-on-a-chip design, and the modeling of carbon nanotube transistors. While working toward the Ph.D. degree, he designed a fully integrated, wireless CMOS sensor platform for biomedical applications. He joined Qualcomm Inc. in 2014.

P. Glenn Gulak (M’90–SM’96) received the Ph.D. degree from the University of Manitoba, Winnipeg, MB, Canada, in 1984. He is a Professor in the Department of Electrical and Computer Engineering at the University of Toronto, Toronto, ON, Canada. Currently, he holds the Edward S. Rogers Sr. Chair in Electrical and Computer Engineering. He was a Research Associate at Stanford University, Stanford, CA, USA, in the Computer Systems Lab (1985-1986) and the Information Systems Lab (1986-1988). His current research interests are in the areas of algorithms, circuits, and CMOS implementations of digital baseband communication systems, as well as in the area of CMOS biosensors. He has authored or coauthored more than 150 publications in refereed journals and refereed conference proceedings. In addition, he has received numerous teaching awards for undergraduate courses taught in both the Department of Computer Science and the Department of Electrical and Computer Engineering at the University of Toronto. Dr. Gulak served as a member of the Signal Processing and later the Technology Directions Technical Subcommittees of ISSCC, and then as Technical Program Chair of ISSCC 2001. He received the IEEE Millennium Medal in 2001 and currently serves as VP Publications for SSCS and as a member of the IEEE Publications and Services Products Board.