20794

IEEE SENSORS JOURNAL, VOL. 24, NO. 13, 1 JULY 2024

Pulsed-Heating System With an Integrated
Metal-Oxide Sensor Array Scheming
Low-Power Temperature Modulation
Yohsuke Shiiki , Shintaro Nagata, Shoo Saga, Yi Tan , Member, IEEE,
Tsunaki Takahashi, Member, IEEE, Takeshi Yanagida ,and Hiroki Ishikuro , Member, IEEE

Abstract—Sensor integration and low-power operation are
required to collect different molecular information. However,
it is challenging to integrate different types of sensors onto
a single chip. To obtain multiple molecular information, temperature modulation of metal-oxide gas sensors is highly
effective since it allows for the variation in sensor molecularsensitivity based on the operating temperature. This article covers a proposed novel system using metal-oxide gas
sensors. The temperatures of the sensors are controlled byadopting self-heated sensors, which achieve local temperature increase and low-power operation. To simultaneously
heat multiple sensors, we implemented a printed circuit board (PCB) for pulsed-heating scheme and streamlined intended
input power with a proportional–integral–derivative (PID) controller. The performance of the implemented circuit isevaluated, and a maximum error rate of 1.7% of heating accuracy and 0.68% of average readout accuracy is ensured. As aproof-of-concept of the proposed gas sensory system, an array of 16 self-heated sensors was fabricated on a chip andtested with reactive gas molecules. The PID controller set the input power in 8 ms and kept constant power while sensor
resistance changed. The proposed pulsed-heating measurement and conventional continuous-heating measurement
were experimentally compared. The results of the experimental comparison suggest that while the sensitivity of the
proposed pulsed-heating measurement decreases slightly, the power consumption due to heating can be reduced by up
to 1/16.
Index Terms— Low-power system, metal-oxide gas sensor, sensory circuits.

I. I NTRODUCTION
OLLECTING molecular information is a requirementof many gas-sensing applications, and to meet that
requirement, smart systems with multiple gas sensors haverecently been developed. While conventional applications,such as air-quality monitoring [1], healthcare [2], and toxic-

C

Manuscript received 24 March 2024; accepted 19 April 2024. Date of
publication 8 May 2024; date of current version 1 July 2024. This work
was supported in part by the Japan Science and Technology Agency(JST), Core Research for Evolutional Science and Technology (CREST)(Japan), under Grant JPMJCR22C4. The work of Yohsuke Shiiki was
supported by the JST Support for Pioneering Research Initiated by
the Next Generation (SPRING) under Grant JPMJSP2123. The workof Tsunaki Takahashi was supported by JST Precursory Research for
Embryonic Science and Technology (PRESTO) (Japan) under Grant
JPMJPR19M6. The associate editor coordinating the review of thisarticle and approving it for publication was Dr. Bo Wang. (Corresponding
author: Yohsuke Shiiki.)
Yohsuke Shiiki, Shoo Saga, Yi Tan, and Hiroki Ishikuro are with the
Department of Electronics and Electrical Engineering, Keio University,
Yokohama 223-8522, Japan (e-mail: shiiki@iskr.elec.keio.ac.jp).
Shintaro Nagata, Tsunaki Takahashi, and Takeshi Yanagida arewith the Department of Applied Chemistry, University of Tokyo, Tokyo
113-8656, Japan.
Digital Object Identifier 10.1109/JSEN.2024.3396376

gas detection [3], use a single gas sensor, “smart” applications
use multiple integrated gas sensors [4], [5], [6], [7], [8], [9].
These integrated gas-sensor systems can cover a wide range
of applications with advanced data processing. They are often
called an “electronic nose” (E-nose) because the sensor’s
function is similar to that of mammalian noses.
Since advanced sensor systems for the Internet-of-Things(IoT) applications, portable gas-sensor devices with low-power
consumption are often useful and beneficial. For example,
in one work, a capacitive micromachined ultrasonic transducer(CMUT) array has been used for measuring gases [10], [11].
A wearable gas-sensory system based on the CMUT array was
shown to consume a power of 1.62 mW during measurement.
Although six CMUT sensors were implemented, the area
occupied by each sensor was larger than 1 mm2 . In anotherwork, four commercial gas-sensor integrated circuits, namely,
BME680, were used and these four formed a gas-sensor
array [12]. The operating temperature was configured at
different levels to classify three different types of gases.
Its power consumption in ultralow-power mode was low as
0.09 mA × 1.8 V. However, the heaters used to control

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SHIIKI et al.: PULSED-HEATING SYSTEM WITH AN INTEGRATED METAL-OXIDE SENSOR ARRAY

Fig. 1. Application of temperature modulation to a single sensor.

the array’s operating temperature typically consume a powerof 17 mA × 1.8 V for each sensor. Other recent works
targeting IoT applications have also been reported [2], [13],[14]. However, the tradeoff between the number of integrated
sensors and power consumption has proved to be a criticallimitation of such sensor arrays. In addition, if size and power
consumption of the sensor system are considered, the numberof integrated sensors is limited to around 40 [15].
Among semiconductor gas sensors, metal-oxide gas sensors have advantages of sensitivity, response time, and low
cost [16]. The capability of highly integrated metal-oxide
gas sensors is one of the substantial features of IoT orreal-time applications. In a previous work, we fabricated agas-sensor array made of SnO2 nanofilm [17]. The size ofeach of the 1024 sensors in the array (fabricated in a 6 ×
6 mm2 area) was 100 × 100 µm2 . Although all the sensors
consisted of homogeneous SnO2 , this work showed the future
possibility of implementing an array with as many sensors as amammalian nose. These notable characteristics of metal-oxide
gas sensors thus make them suitable for IoT applications.
To decrease power consumption of the sensor array, low-powergas sensors have been focused on. Since most metal-oxide
sensors need to be operated at high temperature, power
consumption is dominated by the sensor’s heater. In [18],an optimal package for MOX gas sensor was proposed todecrease cost and power. To heat the sensor up to 250 ◦ C,
an external heater consumes between 500 and 1100 mW. Fromthe perspective of power consumption, low-power gas sensors
have been investigated [19]. Promising techniques for ensuring
metal-oxide sensors are sensitive during low-power operation
as implementing a microheater or a self-heating mechanism.
While the evaluation of the power consumption of the sensors
is required, the whole sensory system (including interface
circuits) should also be evaluated.
For the next generation of gas sensory systems, the limitations due to tradeoffs between number, size, and power
consumption of sensors must be overcome. However, it is challenging for present process technologies to integrate various
sensor materials on a single chip. To integrate various types ofgas sensors onto one chip, as shown in Fig. 1, “temperature
modulation” is a promising technique. By applying temperature modulation, it is possible to vary the sensitivity of asingle metal-oxide sensor with regard to different molecules
adsorbed under different temperatures [20]. For example, themulticomponent gases toluene and butanone were detectedwith a SnO2 sensor [21]. By changing the temperature of thesensor, the sensor’s response to binary component gases canbe varied. Temperature modulation is a favorable technology
because it enables many sensors to be emulated by controlling
thermal conditions. However, in view of maintaining low

20795

power consumption, the way to drive different sensors at
different temperatures should be considered.
In the present work, there is an aim to improve sensory
performance, specifically, low power consumption, high integration, and high sensitivity. We have developed a novel
sensory system by combining self-heating, temperature modulation, and pulsed operation techniques. This system adopts
a self-heated sensor system because such sensors can be
integrated in a small area at different temperatures. In addition,
self-heating enables low-power operation [22], [23]. During
operation of the developed sensory system, the power input ofeach sensor is varied. However, setting the temperature of eachsensor independently requires multiple power sources, which
enlarge the interface circuit and increase the power consumption. Pulsed heating is therefore applied [22], [24], [25], andthe total power consumption of the whole sensory system isassessed. It is also notable that pulsed heating maintains sensor
sensitivity while considerably decreasing power consumption
per sensor. In many previous studies, measurements have been
conducted using general-purpose measurement equipment.
However, though using the general-purpose measurement
equipment, input power to each sensor could not be controlled
constantly. In this study, we therefore designed a dedicatedsystem for the sensors, which when enabled can control input
power fast and precisely while achieving measurements by
16 self-heated sensors simultaneously. As a proof-of-concept,
an array of SnO2 sensors was fabricated, and the sensor
interface was implemented on a printed circuit board (PCB).
Considering the convenience as a portable device, we assumed
3.3–3.7-V input, a typical supply voltage of a Li+ battery,as the power source for the sensors.
The rest of this article is organized as follows: Section II
describes the concept of the proposed sensor system.
Section III describes the hardware design, including the SnO2
sensors and circuits. Section IV describes the operation flowof the sensor system. Section V describes the evaluation of
the circuit performance. Fixed-value resistances are used asdummy sensors, and the power consumption is evaluated,along with the accuracy of the setting power and reading
resistance. Section VI describes the experimental results of thesystem with the self-heated sensors. Section VII concludes thisarticle.
II. OVERVIEW OF P ROPOSED S ENSORY S YSTEM
The sensory system integrates 16 self-heated metal-oxide
sensors, controls the temperature, and reads the resistanceof the sensors under the assumption of a supply voltageof 3.3 V. The sensors are driven by pulse heating, which has
two significant advantages: 1) achieving low-power operation
while keeping high sensitivity and 2) making it possible to use
a single dc–dc converter to generate different bias voltages foreach sensor. The response of the sensor is shown in Fig. 2(a).
In contrast to conventional continuous heating, intermittent
heating causes sensor resistance to fluctuate. According to
the figure, the response of the sensor to active gas (in termsof resistance change) is in the order of minutes, which ismuch longer than the period of heating. When the sensor is
not heated, the heat dissipates, and its resistance returns toAuthorized licensed use limited to: University of Tokyo. Downloaded on September 05,2024 at 02:35:11 UTC from IEEE Xplore. Restrictions apply.

20796IEEE SENSORS JOURNAL, VOL. 24, NO. 13, 1 JULY 2024

Fig. 2. Descriptions of the proposed sensory system combining the techniques of the self-heated sensor, temperature modulation, pulse
heating, and constant-power control. (a) Response of the developed sensory system in terms of resistance which are operated by conventional
continuous heating and the proposed pulse heating. (b) Improvement of sensitivity of constant-power measurement compared with constant-voltage
measurement. (c) Precise control of sensor temperature control in the case of the proposed constant-power measurement.

room-temperature resistance. Since the time constant for heatdissipation differs from that for heating, resulting in a gradual
return of the resistance during the heat dissipation process. The
resistance of the sensor is read when the sensor is not heated.
On the surface of the sensor, active gas molecules are adsorbed
when the sensor temperature is high. The adsorbed molecules
remain on the sensor surface after heating is stopped. By plotting the measured resistance in this way, it is possible to obtainthe new envelope curve, which presents a new sensor responsethat contains molecule information.
The temperature of each self-heated sensor can increase
rapidly. The heating-pulse duration is therefore much shorter(about 100 ms) than the gas response time. This advantage
makes it possible to heat the integrated sensors in a short time.
The sequence of heating and reading of the integrated sensors
is shown in Fig. 3. While sensor 1 (heated) is cooling, theother 15 sensors are sequentially heated. The temperature ofeach sensor is independently controlled. To generate Joule heatof 2–6 mW (corresponding to temperature increase of around31 ◦ C−93 ◦ C) for sensor resistance in the range of 5−50 k,
bias voltage of 5−15 V is required.
The pulsed-heating measurement for the self-heated sensors
is controlled by a microcontroller, enabling the implementationof constant-power heating. During constant-power heating,the sensor temperature also remains constant in a manner that ensures consistent sensor sensitivity. As a result,it becomes possible to set the optimal sensitivity for specific molecules [Fig. 2(b)]. When the sensor is heated,
reactive gas molecules are adsorbed, and when the sensor temperature decreases, the adsorbed molecules remainon the surface [Fig. 2(c)]. By reading the sensor resistanceat the low temperature, an increase in sensitivity can be
expected [22].

Fig. 3. Heating and reading sequences of the integrated sensors.

Fig. 4. Thermal-control circuit.

III. C IRCUIT D ESIGN
A. Thermal-Control Circuit
The thermal-control circuit manages the temperature of eachsensor in the proposed sensory system. The dc–dc converter
generates various bias voltages from a 3.3-V input. The
schematic is shown in Fig. 4. The output voltage of the

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SHIIKI et al.: PULSED-HEATING SYSTEM WITH AN INTEGRATED METAL-OXIDE SENSOR ARRAY

20797

Fig. 5. Overall circuit design.

dc–dc converter is determined by a digital-to-analog converter(DAC) placed (with an output resistor) before the feedback
input of the dc–dc converter. The DAC value is updated by
the proportional–integral–derivative (PID) controller, whichmonitors the current through the sensor. The voltage applied
across the shunt resistor is amplified by the current sense
amplifier and then read by the ADC. One of the sensors isconnected to the thermal-control circuit by the multiplexers(MUXs) and heated. The input power to the selected sensor is
calculated from the DAC and ADC values. The input powerkeeps constant while the resistance of the sensor changes
by adsorption of active gases and temperature fluctuations.
In practice, a low-pass filter is used to decrease large switching
noise from the dc–dc converter which is caused by the highresistance of the sensor. As the frequency of the switching
noise is high, an LC filter is selected as the low-pass filter.
B. Readout Circuit
The thermal-control circuit can read sensor resistance fromthe DAC and ADC values. However, the estimated valueof output voltage is not accurate because it depends on theoffset voltage of feedback of the dc–dc converter, mismatch of
feedback resistors, and the resolution of the DAC. In addition,
generating voltage with the dc–dc converter requires extra
power consumption. Therefore, a low-power readout circuit,with readout error in the order of 0.1%, was implemented.
During reading of sensor resistance, one of the sensors isconnected to a transimpedance amplifier (TIA), and a bias
voltage of 1 V is applied to the sensor. The bias voltage
is generated by a voltage divider circuit. The readout error
derived from the input offset voltage of the amplifier and theparasitic resistance of the switches is calibrated.
C. Overall Circuit Design
The thermal-control circuit is operated at 15 V (maximum), while the readout circuit is operated at 3.3 V. Thus,

high-voltage-tolerant, 4PST analog switches are selected forhigh-side switches. For the low-side switches, a 16:1 MUX
is used. The overall circuit design is shown in Fig. 5. Highside switch ADG1439 is driven by VHT , and the other circuitcomponents are driven by Vin . VHT is determined by the 10-bit
DAC value as follows:
DDAC
VDAC = Vin · 10(1)2 − 1VFB
VDAC − VFB
VHT = ROUT ·−+ VFB . (2)
RFBHT
RDAC
DDAC denotes the digital value of DAC. ROUT , RDAC , and
RFBHT are set to 1 M, 250 k, and 100 k, respectively.
Thus, the resolution of VHT is calculated as follows:
VHTLSB = 13 mV . . .

(3)

A 12-bit ADC is used in the heat-current sensing andresistance readout. Shunt resistance RSHUNT is 24.9, and thegain of the current sense amplifier (INA190A2) is 50. Heatcurrent, Iheat , is calculated as follows:
VOUT1
.
(4)
Iheat =
AINA190 · RSHUNT
Here, AINA190 is the gain of the current sense amplifier. The
resolution of the heat current is thus expressed as
IheatLSB = 647 nA.

(5)

For the TIA in the readout circuit, a zero-drift amplifier(LTC2066) is selected. The sensor resistance is calculated as
RFBTIA
Rsensor =
− RSW
(6)
RbL
1 − VOUTR
Vin · RbH
DADCR
VOUTR = Vin · 12
.
(7)
2 −1
RSW denotes the total parasitic resistance, which is acharacteristic of analog switches and metal wires, and DADCR
denotes the digital value of the ADC in the readout circuit.

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20798IEEE SENSORS JOURNAL, VOL. 24, NO. 13, 1 JULY 2024

Fig. 7. Example of rearrangement of input power in accordance withresistance.

Fig. 6. Flowchart of readout operation.

The mechanical switch (EG 4208) is not related to the
proposed system. However, it was used to input external
voltage into the sensor array and measure the current flowing
into the sensor resistance. During the operation of the system,
all the poles are connected to the dc–dc converter.
IV. O PERATION F LOW
It is important to determine: 1) the appropriate operation sequence of the sensors due to the presence of both
high-voltage ICs and low-voltage ICs in the overall circuitand 2) the potential impact of switching noise from thedc–dc converter in the readout circuit. This consideration
leads to improvements in power consumption. Furthermore,
if the variation in the resistances of the metal-oxide sensors isdetermined, the power supply can be optimized.
The designed operation sequence of the overall systemand the configurations of each circuit are shown in Fig. 6.
The condition that Vin is supplied to the circuit is called“standby.” After initiating standby, the operation moves to“first readout” stage, in which all the initial resistances of
the integrated sensors are measured. The high side of eachsensor is connected to Vin , while the low side is sequentiallyconnected to the readout circuit for measurement. The results(resistances) of “first readout” are used to determine which
sensor to apply the respective input power to. Since the power
converter has a predetermined upper limit, it was reconfigured

to apply a higher power to sensors with lower resistances.
Thus, the user-defined array of input powers is rearranged inaccordance with the ascending order of resistances. This process is illustrated using a specific example in Fig. 7. Standby
and first readout are executed only once (at the beginningof the operation sequence), and they are followed by a loop
composed of sensor heating and resistance reading. The circuit
configuration of the loop is composed of three stages: “PowerManagement IC (PMIC) wake-up,” “heating,” and “readout.”
Each functional block of the circuit is turned on and off as
follows.
1) The high sides of all the sensors are connected to theground to prevent high voltage generated by the dc–dc
converter from causing crosstalk in readout circuits.
2) The readout circuit is disabled.
3) The dc–dc converter and DAC are turned on.
4) The 16:1 MUX connects the current sense circuit witha heated sensor. The other pole of the 16:1 MUX isconnected to another sensor.
5) The 4PST switches connect the dc–dc converter with theheated sensor. The other sensors are connected to Vin .
6) The current sense amplifier is turned on, and the PID
control starts with ADC and DAC.
7) The dc–dc converter and DAC are disabled.
8) The current sense amplifier is disabled.
9) The TIAr is enabled.
10) The 1:16 MUX connects a nonheated sensor with thereadout circuit. Nonheated sensors are selected one by
one after measuring the output voltage with ADC.
Operations (1)–(3) are part of the PMIC wake-up stage.
Next, in the heating stage, the selected sensor is heated inoperations (4)–(6). It should be noted that the switching timingof analog switches is precisely controlled because high voltage
may damage low-voltage ICs. In the experiment, the heatingtime was around 100 ms. After that time passes, the dc–dc
converter is disabled, and operations (9)–(10) are performed.
In operation (10), the resistances of the sensors other thanthe heated sensor are measured sequentially. After operation(10) is finished, the readout operation goes back to step (1) of
PMIC wake-up.
V. C IRCUITS M EASUREMENTS
To verify the practicality of the proposed measurement method, we implement the circuit and system using

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SHIIKI et al.: PULSED-HEATING SYSTEM WITH AN INTEGRATED METAL-OXIDE SENSOR ARRAY

20799

Fig. 9. Measurement results of the readout accuracy.

Fig. 8. (a) Developed PCB. Fixed-value resistors are mounted insteadof the sensors to measure circuit performance. (b) Resistances (measured by digital multimeter) of the mounted resistors.

commercial ICs and a PCB. Measuring the control accuracy
and power consumption of the system allows for identification of circuit-related challenges. Instead of actual sensors,
fixed-value “dummy” resistors were used in the performance
evaluations.
A. Developed PCB
The implemented PCB with dummy resistors is shown in
Fig. 8(a). Its size is 21 × 14.5 cm2 , and it was controlled
by a Nucleo-F767ZI microcontroller unit (MCU). As dummy
sensors, 15 fixed resistors and one variable resistor were used.
The resistance values were selected randomly in the range
of 5–70 k and checked with a digital multimeter, PC7000,
Sanwa, as shown in Fig. 8(b). The analog power supply (Vin ),3.3 V, was generated by an E3631A triple-output dc power
supply (Keysight Technologies). During all the measurements
and experiments, the MCU is connected to a PC via a USB
cable. The digital power supply (DVDD), 3.3 V, was generated
on the MCU board.
B. Readout Accuracy
To evaluate the readout accuracy, 7680 points of data werecollected for each resistor. Resistance is calculated with (6)and (7). The exact values of resistances RFBTIA , RbL , and RbH
are unknown, and the switch resistance RSW is inaccurately
specified in the datasheet. Therefore, those parameters were
estimated by optimization. In the optimization process, thefollowing evaluation function is minimized:
RMeasured − RTrue
RTrue

(8)

where RMeasured is the calculated results with the estimatedparameters, and RTrue is the value measured by the digital multimeter. With the optimized parameters, readout accuracy was
obtained as shown in Fig. 9. The left vertical axis represents
resistance, while the right vertical axis represents error rate.
The dotted lines labeled “Ideal” line and “Quantization error,”
respectively, show true resistance and theoretically minimum
error rate of a 12-bit ADC resolution. “Measured value” and“Measured error” represent resistance and its readout error,
calculated from the average of the obtained 7680 ADC values
without optimization. It is clear that the error rate increases
in the high-resistance region between 20 and 70 k due tothe quantization error of the ADC. On the contrary, error
rate rises rapidly in the low-resistance region due to the
fixed parasitic resistance of the switches. “Calibrated value”
and “Calibrated error” represent resistance and its error rate;
an average of 7680 resistance values were calculated with
optimized parameters. It is shown that the readout error is
reduced to the theoretical minimum. In addition, to evaluate
the variation of readout error, coefficient of variation (CV) is
calculated and shown for indexes 0, 3, 4, 6, and 8 of theresistors. CV is the ratio of the standard deviation to themean of the 7680 points of the resistances. Since the ADC
quantization error has larger impact on the readout accuracy,
CV becomes larger as the measured resistance increases.
C. Input Power Accuracy
The input power accuracy of the sensor is determined by
the accuracies of the heat-current sensing readout and the
dc–dc converter output. As for the developed sensory system,
an input power of 1 mW corresponds to a temperature increaseof about 15.5 K. It has been reported that the temperaturedependence of metal-oxide sensors becomes significant witha 10 K difference [20]. The target accuracy was therefore set
to achieve an input-power resolution of 0.1 mW for controllinga 1.5-K temperature difference.
To evaluate the heat-current sensing accuracy, an ammeter(34401A, Keysight Technologies) and external voltage source
were connected in series with one of the sensors through the

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20800IEEE SENSORS JOURNAL, VOL. 24, NO. 13, 1 JULY 2024

Fig. 10. Sensing accuracy of the heat current.

mechanical switch, EG 4208A. In the meantime, the other
resistors were connected to the ground through the 4PST
switches. The measured ADC values and the ammeter-values
were compared for accuracy. The current used for measurement determining the accuracy was 0.3–1 mA in 0.1-mA steps.
The measurement results are plotted in Fig. 10. Each plot iscalculated with (4) after obtaining and averaging 8196 ADC
data. The horizontal axis represents the reference currents
measured by the ammeter. The left vertical axis represents
current measured by the heat-current sensing circuit, while
the right vertical axis represents its error rate. According to
the results, the RMSE is 0.021%, which is accurate enough toachieve power control with 0.1-mW resolution.
For evaluation of output accuracy of the dc–dc converter,
the 12th resistor, with resistance of 33.2 k, was set as theload resistance of the converter. The analog switches wereconfigured to connect the resistor with the dc–dc converter andthe shunt resistor, while the other resistors were connected to
the ground. The 10-bit DAC was configured from 0 to 1000,with variable steps. Output voltage VHT was measured bya digital multimeter (34410A, Keysight Technologies). The
measurement results for voltage are plotted in Fig. 11. The
horizontal axis represents the DAC value, and the left verticalaxis represents the output voltage of the dc–dc converter.
The line “Vout ” represents the measured output value. The
green dotted line “Calculated” represents the expected output
voltage, which is calculated from the DAC values with (1)and (2). The line “Error rate” shows the relative error between
measured voltage and expected voltage. According to thegraph, dc–dc output voltage can swing in the range of around
4–18 V with a maximum error rate of 1.7%. Although,according to the datasheet of LTC3129, the upper limit ofoutput voltage is 15 V.
From the above-described results it is proved that the power
consumption of the sensors can be calculated from the DAC
and ADC values with a maximum error rate of 1.7%. In thisstudy, the input powers for the sensors were controlled in therange of 3–6 mW. Within this range, the input power can be
set with absolute error of 0.05–0.1 mW.

Fig. 11. Accuracy of output of the dc–dc converter.

TABLE IM EASURED R ESULTS OF P OWER C ONSUMPTION

D. Power Consumption
Using the developed PCB, power consumption for each
operation mode was evaluated. In the evaluation, power consumption of the MCU was excluded. Analog power-supply
voltage was applied to the ICs and flowing current wasmeasured. The measurement results of the power consumption
are listed in Table I. The 12th fixed-value resistor (33.2 k)was measured. The period of one heating pulse was set to
113 ms because it takes around 6 ms until the output of the
PID controller stabilizes. Readout operation takes 12.9 ms tomeasure 15 sensors after heating one sensor. In the standby
operation, quiescent current was 33.5 µA as most of the ICs
were in shutdown. The largest power was consumed during theheating operation with the dc–dc converter. Based on our survey of ICs, there are few dc–dc converters that are optimized
for output currents in the range of tens of microamperes. Whilesome ICs use burst mode to improve efficiency, the increased
ripple noise made it unsuitable for our system. Therefore,
in this study, the stability of supply voltage was prioritizedrather than efficiency. During the readout operation, most of
the power is consumed in the amplifier and ADC. Averaged
powers of heating and readout in the table are calculated using
the operating time and measured current, divided by periodical
time of a cycle of PMIC wake-up, heating, and readout, with

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SHIIKI et al.: PULSED-HEATING SYSTEM WITH AN INTEGRATED METAL-OXIDE SENSOR ARRAY20801

the outcome of 142 ms. Power consumption of 16 sensors
out of the averaged power consumption is calculated with theassumption that resistances of the 16 sensors are 33.2 k.
In the calculation, 9 and 1 V are applied to each sensor during
heating and readout, respectively.
VI. S ENSORY E XPERIMENTS
The 16 self-heated metal-oxide (SnO2 ) sensors were integrated on a chip and measured with the proposed system.
The sensor resistance changed in accordance with temperaturechange and gas inflow. By observing the resistance changes
during sensor heating, it was confirmed that the heating controlof the pulse-heating system followed resistance fluctuation.
The sensor responses to an active gas measured under conventional constant heating and under the proposed pulse heatingwere compared, showing that power consumption of eachsensor was decreased while the sensitivity of each sensor wasmaintained. The self-heated sensor responses under different
temperatures were measured, showing the sensor sensitivity ischanged by temperature modulation.
A. Sensor Device
The self-heated sensors consisted of SnO2 nanofilm lateralchannel devices [17] fabricated on synthetic quartz substrateusing radio frequency (RF) sputtering, photolithography, andlift-off techniques. The 5/100-nm-thick Ti/Pt films were
deposited as electrodes using RF sputtering. The thickness,length, and width of the SnO2 nanofilm channel were 20 nm,
10 µm, and 5 µm, respectively. A microscope image ofthe fabricated SnO2 -nanofilm-channel sensor is shown in
Fig. 12(a). This image confirms successful fabrication of
the designed sensor devices. Thermal resistance (Rth ) of the
SnO2 -nanofilm-channel sensor devices, calculated using the
3-D finite element method [26], is shown in Fig. 12(b).
Rth is defined as 1T /P, where 1T and P are the increasein averaged temperature of SnO2 channel and input power(I × V ), respectively. Rth is considered to represent thedegree of self-heating: devices with larger Rth reach higher
temperatures during the self-heating operations. The channel
size of the devices has a significant impact on Rth because
the 3-D heat-dissipation path is determined by the channel
region containing the heat source during self-heating. In thisstudy, the channel length and width were set to 10 and 5 µm,
respectively, based on thermal simulations.
B. Experimental Setups
During the operation, as shown in Fig. 13, an external heater
maintained the temperature of the sensors at 200 ◦ C, which
was verified with a thermal camera (VarioCAM HD head,
Japan Laser Corporation) [17]. The PCB (hereafter “sensor
board”) had a slot to accommodate the sensor chip. An external
heater was attached to the backside of the sensor board, andthe sensor chip was placed on the heater. The sensor chipand the heater were connected to the sensor board by gold
wires. Every experiment started a few minutes after the heater
was turned on. The experimental setup of the PCB and sensor
chip in the experimental configuration is shown in Fig. 14.

Fig. 12. (a) Microscope image of fabricated SnO2 nanofilm channel
sensor. (b) Simulated thermal resistance of SnO2 -nanofilm-channel
sensor. Channel length was set to 10 µm.

Fig. 13.
board.

Connections between sensor, external heater, and sensor

Fig. 14. Developed PCB with a gas pathway and a self-heated metaloxide sensor chip.

The sensor board was mounted on the controller board with
the STM32 MCU. There were two power lines, the DVDD
and the analog power supply (AVDD). A PC supplied the
DVDD through the MCU board. The AVDD was supplied
from a dc voltage source instrument. The sensors were coveredby a chamber to suppress environmental noise.
C. Monitoring PID Control
The data of the current readout of ADC and DAC were
captured during the PID operation. It should be noted that theaccuracy is around 0.01%–0.04% in the case of monitoring

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20802IEEE SENSORS JOURNAL, VOL. 24, NO. 13, 1 JULY 2024

Fig. 16. Initial resistances and input power of the integrated sensors.

Fig. 17. Measured resistance of the second sensor.

Fig. 15. (a) PID control following the resistance change, the estimated temperature corresponding to the relevant power is displayed.
(b) Enlarged view during the change in the input power.

heat current and around 0.5%–1.5% in the case of monitoringheating voltage. To verify the PID control, the input power
to the sensor was periodically switched according to thefollowing sequence:
2.5 mW → 3 mW → 3.5 mW → 3 mW
→ 2.5 mW → 3 mW · · ·(9)During this operation, the external heater was turned off.
The sensor resistance was calculated with the ADC and
DAC values in the thermal-control circuit. The results of
the input power and the sensor-resistance change are shownin Fig. 15(a). In this plot, 10 000 data points were obtainedin 15.4 s. The left vertical axis represents input power, and theright vertical axis represents resistance of the heated sensor.
The results show that sensor resistance changes with inputpower fluctuation, and the PID control tracks the changes.
A zoomed-in view of the period between 2.97 and 3.01 s in
the graph is shown in Fig. 15(b). The input power changes at
2.99 s and reaches the target power within 8 ms.
D. Measurement Results
The 16 sensors were implemented on the sensor board,and input powers to the sensors were varied in the range

of 2–6 mW. Initial resistances of the sensors measured in thefirst-readout stage are listed in Fig. 16. Only the seventh sensor
could not be measured (due to a sensor damage). It should be
noted that one ADC data were used to calculate resistance insensor measurements. The measured resistance of the second
sensor is shown in Fig. 17. In the measurements, the sensors
were continuously driven by pulsed heating. Gas was injected
through the gas pathway in the chamber: At Time = zero,N2 was filled and injected into the chamber for about 180 s.
At around Time = 180 s, NO2 (10 ppm) was injected into thechamber with N2 dilution for 60 s. After NO2 injection, input
gas was switched to N2 , and it was kept until Time = 400 s.
Each sensor was heated every 15 readouts, and the difference
in resistances of the consecutive 15 readouts represents thetemperature change in each sensor. It was found that sensor
resistance increases slowly and returns to room-temperature
resistance right after the heating pulses are biased. It should
be noted that the time constants of the sensor-temperaturechanges differ in the cases of the increasing and decreasing
slopes. The plots of the graph can be decimated.
To verify pulse-heated measurement, a comparative experiment was conducted with a conventional continuous-heatedmethod. The same gas control was used in both the measurements, and constant input power to the second sensor
was maintained. The result of the experimental comparison
is shown in Fig. 18. It is clear from the figure that the sensor
responds to NO2 , successfully in both the methods. Although
the measured sensitivity decreases in the case of pulse-heating
method, the heating time decreases to 1/16.
From the above-described experimental comparison of thepulse-heating measurement, the temperature dependencies of

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SHIIKI et al.: PULSED-HEATING SYSTEM WITH AN INTEGRATED METAL-OXIDE SENSOR ARRAY

20803

of pulsed-heating duration, which was decreased by around
1/16 per sensor. In addition, we confirmed that the sensitivityof the integrated sensors varied under modulated temperature
which showed the different characteristics of their sensitivity,
even though the integrated sensors were of identical design.
R EFERENCES

Fig. 18.
Comparison of the sensor responses between thecontinuous-heating measurement and pulse-heating measurement.
In the case of pulse heating, instantaneous power is 5 mW.

Fig. 19. Measured temperature dependencies. Instantaneous power foreach sensor varies from 2 to 6 mW. According to Fig. 12(b), the instantaneous temperatures are 200 ◦ C + 15.5 K/mW·(instantaneous power).
For example, if the instantaneous power is 4 mW, the instantaneoustemperature is 262 ◦ C.

NO2 sensitivity for different input powers were observed. The
responses of indexes 0, 1, 2, 6, 10, and 11 of sensors areshown in Fig. 19. The measured resistances were converted
into their resistance change rate because their base resistances
under N2 are different. The sensor response rate is the highest
at input power of 4 mW, and it gradually decreases as input
power deviates from 4 mW.
VII. C ONCLUSION
We proposed a novel method of pulsed heating of integrated
self-heated metal-oxide sensors. As a proof-of-concept of thismethod, a dedicated PCB for applying constant-power heating
pulses to the sensors was developed. The performances ofthe power consumption were evaluated with the accuraciesof heating and readout. Compared with the conventional
continuous-heating method, the proposed pulsed heating was
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Yohsuke Shiiki received the B.S., M.S., andPh.D. degrees from the Department of Electronics and Electrical Engineering, Keio University,
Yokohama, Japan, in 2018, 2020, and 2023,
respectively.
Currently, he is an Assistant Professor of
the Department of Electronics and ElectricalEngineering, where he is focusing on signal
processing and low-power system design for
integrated sensors.

Shintaro Nagata received the B.E. and M.E. degrees in applied chemistry from the University of Tokyo, Tokyo, Japan, in 2021 and 2023,
respectively.
He worked on nanoscale metal-oxide gas sensors.

Shoo Saga received the B.S. and M.S. degrees from the Department
of Electronics and Electrical Engineering, Keio University, Yokohama,Japan, in 2020 and 2022, respectively.
He has been working on analog sensor front-ends.

Yi Tan (Member, IEEE) received the B.Eng.
degree in electronic and electrical engineeringfrom the Southern University of Science andTechnology, Shenzhen, China, in 2018, and the
M.Sc. degree in electronic and electrical engineering from Keio University, Tokyo, Japan, in
2020 and 2024, respectively.
He is currently working as a Researcher at
Keio University. His research interests include
analog/mixed-signal and power management IC
designs.

Tsunaki Takahashi (Member, IEEE) received
the B.E., M.E., and Dr.Eng. degrees in electricaland electronics engineering from Tokyo Instituteof Technology, Tokyo, Japan, in 2009, 2011, and2013, respectively.
In 2014, he joined the Department of Electrical and Electronics Engineering, Keio University, Tokyo, Japan, as an Assistant Professor
and started research on self-heating effects ofnanoscale MOSFETs. In 2017, he joined theInstitute for Materials Chemistry and Engineering, Kyushu University, Fukuoka, Japan, as a Research AssistantProfessor and started research on chemical sensor devices using
nanoscale metal oxides. In 2020, he joined the Department of Applied
Chemistry, University of Tokyo, Tokyo, as a Research Associate Professor and started research on integrated chemical sensor system,
where he is currently an Associate Professor, where he is focusing on
discrimination of mixed molecules using integrated chemical sensors.

Takeshi Yanagida received the B.E. and
M.E. degrees in chemical engineering from
Osaka Prefecture University, Osaka, Japan,
in 1995 and 1997, respectively, and the
Ph.D. degree from Teesside University, Middlesbrough, England, in 2002.
In 1997, he joined Matsushita Electric Works
Company, Ltd., Tokyo Japan. In 2005, he joined
the SANKEN, Osaka University, Suita, Japan,
as an Assistant Professor. In 2015, he joined
the Institute for Materials Chemistry and Engineering, Kyushu University, Fukuoka, Japan, as a Professor. In 2020,
he joined the Department of Applied Chemistry, University of Tokyo,
Tokyo as a Professor.

Hiroki Ishikuro (Member, IEEE) received the
B.S., M.S., and Ph.D. degrees in electrical engineering from the University of Tokyo, Tokyo,
Japan, in 1994, 1996, and 1999, respectively.
In 1999, he joined the System LSI Researchand Development Center, Toshiba Corporation,
Kawasaki, Japan, where he was involved indeveloping CMOS-RF and mixed-signal circuits
for wireless interface chips. In 2006, he joined
the Department of Electronics and Electrical Engineering, Keio University, Tokyo, Japan,
as an Assistant Professor and started research on high-speed inductivecoupling links for 3-D chip integration and noncontact connectors, where
he is currently a Professor, he is focusing on mixed-signal circuits andsystem designs for low-power sensor interfaces.
Dr. Ishikuro was a member of the Technical Program Committee for
Symposium on VLSI Circuits and the Technical Program Committee for
Custom Integrated Circuits Conference (CICC).

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