Hybrid semiconductor radiation detectors using conductive polymers

Journal Pre-proof Hybrid semiconductor radiation detectors using conductive polymers E. Miyata, H. Miyata, E. Fukasawa, K. Kakizaki, H. Abe, M. Katsumata, M. Sato, T. Suzuki, M. Tamura, A. Umeyama

PII: DOI: Reference:

S0168-9002(19)31466-4 https://doi.org/10.1016/j.nima.2019.163156 NIMA 163156

To appear in:

Nuclear Inst. and Methods in Physics Research, A

Received date : 17 August 2019 Revised date : 14 November 2019 Accepted date : 20 November 2019 Please cite this article as: E. Miyata, H. Miyata, E. Fukasawa et al., Hybrid semiconductor radiation detectors using conductive polymers, Nuclear Inst. and Methods in Physics Research, A (2019), doi: https://doi.org/10.1016/j.nima.2019.163156. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier B.V.

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Hybrid semiconductor radiation detectors using conductive polymers

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E. Miyataa*, H. Miyatab, E. Fukasawaa, K. Kakizakia, H. Abea, M. Katsumatab, 1, M. Satoc, T. Suzukic,

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M. Tamurac, A. Umeyamac

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a

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b

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Graduate School of Science and Technology, Niigata University, Niigata 950–2181, Japan

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Department of Physics, Faculty of Science, Niigata University, Niigata 950–2181, Japan

Carlit Holdings Co., Ltd., Chuo, Tokyo 104–0031, Japan

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*Corresponding author. Tel./fax: +81252626138.

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E-mail: [email protected] (E. Miyata), [email protected] (H. Miyata)

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URL: http://www.hep.sc.niigata-u.ac.jp (E. Miyata, H. Miyata)

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1Present

address: Kanagawa Prefectural Institute of Public Health, Chigasaki 253–0087, Japan

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Abstract

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Organic semiconductor radiation detectors have been developed using conductive polymers as sensor

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materials. Unlike the commonly used inorganic semiconductor detectors, the use of organic semiconductor

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detectors has facilitated large-scale fabrication of cheap and flexible detectors. In this study, a sensor is

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fabricated to improve the radiation sensitivity by combining an n-type titanium oxide (TiO2) semiconductor as

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an additive with a p-type polyaniline (Pani) semiconductor. A maximum detection efficiency of 10% for

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β-rays was achieved using a new comb-type electrode. We report the performance of the newly developed

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hybrid sensors, such as the incident rate dependence of detection efficiency and the long-term stability.

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Keywords: Radiation detector, Organic semiconductor, Hybrid

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1. Introduction

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Semiconductor detectors used for radiation detection have excellent energy and position resolutions.

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Inorganic semiconductor detectors are some of the major radiation detectors in high-energy and nuclear

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physics experiments. For example, silicon vertex detectors (SVD) are strip-type silicon semiconductor

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detectors and are used in the Belle II particle physics experiment [1, 2]. SVDs have a good position resolution

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of a few microns, which is indispensable in detecting the positions of decaying particles in particle physics

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experiments. In recent years, semiconductor detectors have been studied for applications in the field of

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radiology [3, 4], and are essential in various research fields [5, 6].

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However, there are problems associated with the inorganic semiconductor detectors that commonly use

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silicon or germanium crystals. Specifically, inorganic semiconductor detectors are inflexible and require

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high-purity monocrystalline moieties for high performance. It is also difficult to fabricate a large detector

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owing to the increased sensor cost, although particle physics experiments are faced with the need to enlarge

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the detector. To solve this problem, this study focused on the use of conductive polymers without crystal structures as

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the sensor materials for new radiation detectors [7–9]. Conductive polymers have been actively studied for use

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in various devices, such as photodiodes [10–13] and solar cells [14–17]. Photoconductivity and photocatalysts

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had also been studied previously [18, 19]. Organic semiconductor detectors which use conductive polymers

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have excellent features, including the use of low-cost materials and simplified manufacturing processes.

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Unlike inorganic semiconductor detectors, it is possible to fabricate organic semiconductor detectors at large

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scale. The fabrication parameters of organic semiconductor sensors, such as those dependent on the types of

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the organic materials, and the amount of the additive required to alter the conductivity, were optimized in a

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previous study [9]. The maximum detection efficiencies of 30% and 1% were respectively attained with the

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fabricated sensors for α-rays and β-rays [8, 9]. The hybrid-type radiation sensors were fabricated by adding

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the inorganic material TiO2 [20–22] to polyaniline [9]. The hybrid-type sensor whose material is a mixture of

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TiO2/polyaniline, and which comprises a new comb-type electrode to generate high-electric fields to improve

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the detection sensitivity, are studied in detail. This report describes the results of newly developed hybrid-type

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semiconductor radiation detectors.

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2. Radiation sensor fabrication

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Polyaniline (Pani), which is the main material of the sensors, is obtained with high purity with chemical

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polymerization. The sensors were fabricated by combining the p-type semiconductor (Pani) with an n-type

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semiconductor (TiO2). The mixing ratio of TiO2 to the total amount is 30wt%. The compound

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1-methyl-2-pyrrolidone (NMP) was used as a solvent, and the solution combined Pani and TiO2 in a circular

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Teflon container. The paste in the container was heated at 150 °C and was turned into a gel plate. The plate

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was heated for six hours to dry. We refer to the fabricated circular plate as the Pani/TiO2 sheet. The Pani/TiO2

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sheet is 12 mm in diameter and 1–2 mm in thickness. Optical microscopy photographs of the surfaces and

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cross-sections of the polished Pani/TiO2 sheet are shown in Fig. 1. A complex structure is made with many

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TiO2 particles between Pani. This mixed structure of Pani and TiO2 resembles the bulk heterojunction

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structure in the field of organic solar cells [16, 17]. There are many p–n junction surfaces in the sensor. The

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schematic of the bulk heterojunction structures is shown in Fig. 2. The bulk heterojunction structures are

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applied in the field of the solar cell. The complicated structures of the p-type and n-type semiconductors that

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have a large p–n junction surface areas have improved detection efficiency [16, 17].

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Gold electrodes with thickness values in the range of 200–300 nm were deposited to both the front (anode)

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and back (cathode) sides of the Pani/TiO2 sheet with the sputtering device. Formerly, the anode side had a flat

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circular electrode [9]. In this research, a new comb-type electrode is used in the anode side (Fig.3). The

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electric field is strong near the comb edge. Accordingly, it is easy to collect the charge carriers produced by

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radiation. Therefore, the detection efficiency is expected to be improved. A gold-plated tungsten wire used for

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signal readout was attached to the anode side using silver paste. We refer to the completed sensor as the hybrid

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comb-type electrode sensor. The sensor resistance was several tens of GΩ.

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3．Experiment

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3.1 Experimental setup and readout circuit

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The experimental setup used for the evaluation of the sensor performance is shown in Fig. 4. The center section on the sensor surface was irradiated by β-rays using a 90Sr source (1.73 MBq at August 1, 2017)

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through an aluminum collimator (thickness 10 mm, hole diameter 2 mm). A cylindrical spacer made of

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aluminum was inserted between the source and the collimator to reduce the solid angle and irradiation rate of

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the β-rays. A trigger counter was composed of a plastic scintillator (10 mm×10 mm×2 mm) connected to a

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3/8 in photomultiplier tube (H3164, applied voltage: -900 V, Hamamatsu Photonics K.K.).

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When β-rays are irradiated to the trigger counter through the hybrid comb-type electrode sensor, they lose energy inside the hybrid sensor. The bias voltage was applied to the hybrid sensor and the signals of the

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generated charge carriers were amplified seven times with a pulse amplifier (KN501, NIM, Kaizuworks

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Corporation). The sensor signals were measured with an online data acquisition system that used an

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analog-to-digital converter (ADC, VME-V005, charge integrated type, 14 bits, 61 fC/count, Hoshin

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Electronics Co., Ltd.) and a VME crate. Gate signals with temporal widths of 250 ns were generated by the

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trigger counter and supplied to the ADC.

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3.2 Analysis method

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The output signals from the sensor were observed with the use of an oscilloscope (Fig. 5). The rise time was

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very short and was approximately equal to 10 ns. Examples of the pedestal and the β-ray signal charge

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distributions of the sensor measured by the ADC are shown in Fig. 6. To calculate the detection efficiency, the

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number of signal events was counted separately from the pedestal events. A clock module (KN270, NIM,

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Kaizuworks Corporation) was used to generate NIM level trigger pulses to measure the pedestal (noise)

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distribution of the ADC.

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The mean μ and the standard deviation σ of the pedestal distribution were calculated by fitting them with the Gaussian function (Fig. 6(a)). The cut value (CV) was defined as

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CV = μ+3σ .

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(1)

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Regarding the distribution of the signal charge generated by the energy loss of the β-rays, the events which

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had charges smaller than the CV were eliminated and identified as noise equivalent events (Fig. 6 (b)). The

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method used to calculate the detection efficiency is the same as the one used in our previous study [9]. The

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detection efficiency was determined based on the following equation:

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(2)

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where

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is the number of events greater than CV in the pedestal distribution (number of accidental coincidence events),

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and

is the number of events of the sensor signals above CV,

is the total number of signal events,

is the total number of events in the pedestal distribution.

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4. Results and discussion

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The detection efficiency was obtained from the measurement of the output charge based on the application

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of bias voltages to the hybrid sensors. For performance evaluation, various dependencies of the detection

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efficiency, such as the applied bias voltage, the incident β-ray rate, and the long-term stability, were measured.

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4.1 Bias voltage dependence of β-ray detection efficiency

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The bias voltage dependence of β-ray detection efficiency is shown in Fig. 7 for two sensors (sensor name:

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N170720 and N171221). Sensor N170720 was fabricated on July 20, 2017 and sensor N171221 was

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fabricated on December 21, 2017. The output signals for the β-ray injection were measured in the sensitive

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bias voltage range that ranged from 1400 V to 2800 V. For higher voltages, both sensors exhibited discharge

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phenomena in which the output charges were generated without incident β-rays. The sensors N170720 and

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N171221 respectively discharged when the bias voltages were higher than 2800 V and 2500 V. The detection

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efficiency increased linearly and monotonously as a function of the bias voltage.

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The detection efficiency did not seem to be saturated even at the maximum voltage. It can be increased by increasing the bias voltage if a method is developed to prevent the discharge of the sensor. 4.2 Incident rate dependence of detection efficiency

To measure the incident rate dependence of the β-ray detection efficiency, the incident rate was reduced by

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using a spacer as shown in Fig. 8. A cylindrical spacer made of aluminum was inserted between the 90Sr

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source and the collimator to reduce the solid angle.

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The β-ray incident rate

was calculated by equation (3) in the case of point source (Table 1).

(counts/s) is the number of β-ray injections on a sensor, and

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(mm) is the spacer length, and

(counts/s) is the source intensity,

(mm) is the collimator diameter.

(3)

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The sensor was located at a distance of 6 mm from the lower part of the collimator (Fig. 8). The number of

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β-rays irradiated at the center of the sensor after passing through the collimator was counted by a trigger

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counter. Because the diameter (3.5 mm) of the radiation source part is larger than the diameter (2 mm) of the

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collimator, as indicated in Fig.8, the β-ray that has been emitted within a diameter of 2 mm from the central

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part of the radiation source is used and calculated according to equation (3) (Table1). In equation (3), the

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energy difference of the β-rays emitted owing to the β-decay was not considered.

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The incident rate

was calculated for the same setup with the Geant4 simulator (Table 1) [23, 24]. The

β-rays were irradiated on the sensor with the use of a 90Sr source and a collimator. The number of β-rays was

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counted and they were expressed as an incident rate in units of counts per second (cps). The 90Sr source is a

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circular plate with a diameter of 3.5 mm. The calculated number of β-rays irradiated on the sensor is shown in

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Table 1. The calculated errors of the Geant4 simulation are the statistical errors. The β-rays emitted from the

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entire source part (diameter of 3.5 mm) were simulated in Geant4. The β-rays which lost energy at the edge of

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the lower part of the collimator and which were incident on the sensor were also included when the β-rays had

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high energies. These β-rays were not included in the calculation of equation (3). The Geant4 simulation

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performed calculations based on the consideration of the β-ray energy spectrum from the β-decay of 90Sr and

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Y. The obtained incident rate depended on the energy of the β-rays.

According to the following reasons, the trigger rate, which is the number of trigger signals generated by a

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trigger counter, are in the range of 1/10–1/25 compared with the calculated value of the Geant4 simulation

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(Table1). When the β-rays irradiate a sensor, the low energy β-ray stops owing to the energy loss, or its track

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deflects considerably owing to the multiple Coulomb scatterings. These β-rays did not irradiate the trigger

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counter. Moreover, the signal pulse height of the trigger counter for the low-energy β-rays did not reach the

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trigger threshold (-25 mV). Therefore, the trigger rate was smaller than that calculated by the Geant4

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simulator in which the low-energy β-ray, which was generated by the β-decay, was simulated.

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The bias voltage applied to a sensor and the detection efficiency of a sensor to the trigger rate (Table 1) are

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plotted in Fig. 9. The detection efficiency improves at low-trigger rates that the incident rate of the β-rays is

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small owing to the small solid angle. When the incident rate of the β-rays is high, new charges are generated

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by a newer β-ray before the old charges generated by the previous β-ray have reached the sensor’s electrode.

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The new charges sense the weak electric field shielded by the previous charges. The detection efficiency then

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decreases. In the case of low β-ray incident rates, the detection efficiency improved because the previous

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charges had already reached the electrode and there was no electric field screening. When the trigger rate was ≤ 2–3 cps, which corresponds to ≤ 35 cps for the incident β-rays according to the

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Geant4 simulation (Table1), the detection efficiency of the sensors (N170720, N171221) reached almost 10%

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or more (Fig. 9).

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The ADC distributions which are represented by the measured charge spectra for several incident rates

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(trigger rates: 1.8 cps, 7.0 cps, 29 cps, and 144 cps) of the β-rays, are shown in Figs. 10 and 11. Signal events

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with large electric charges are observed owing to the ctenoid electrode. The subsequent charge collection can

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be delayed when the incident β-ray rate is low (Fig. 10(a), Fig. 11(a)). By contrast, the charge collection by

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the ctenoid electrode owing to the electric field screening of the charges generated from the previous β-ray

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incidence (when the incident rate was high) were assumed to be inefficient. As a result, numerous signal

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events with small electric charges are observed (Fig. 10(d), Fig. 11(d)).

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To confirm this, the signal events with values ≥ μ+30σ (1400 channel = 9 pC) are defined as large-charge

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events. The ratio of the amount of these events to the total number of signal events (≥ μ+3σ) was calculated,

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and the incident rate dependence of this ratio is plotted (Fig. 12). The ratio of the large-charge events

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increased (or decreased) when the incident rate was low (or high).

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4.3 Long-term stability of detection efficiency

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The long-term stability was measured to assess the detection efficiency of the sensor. Fig. 13 shows the

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relation between the detection efficiency and the lapsed days after the fabrication of the sensor N171221. The

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applied voltage to the sensor was 2300 V, and each incident rate (trigger rate) of the β-rays is shown using the

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corresponding symbol. When the incident rate was low, the detection efficiency was almost constant for

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approximately one year and seven months after the sensor was fabricated. Conversely, the detection efficiency

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exhibited a gradual improvement in the first three months when the incident rate was high.

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The applied voltage dependence of the detection efficiency of this sensor was measured four times at each month. The results are shown in Fig. 14. The detection efficiency was measured within the applied voltage

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range of 1600–2600 V for a β-ray incident rate (trigger rate) of 144 cps. This sensor was fabricated on

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December 21, 2017. The detection efficiency improved gradually and did not depend on the applied voltage in

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the first three months after the sensor was fabricated. This phenomenon appeared when the sensor begun to be

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used at high incident rates (trigger rates). This was a similar phenomenon to "Annealing" which was observed

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with a specific type of radiation detector. Although a more detailed study is necessary to understand this

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phenomenon in the future, we presently explain it as follows.

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The resin film for protection was not placed on our hybrid sensor, unlike the commercial PIN photodiode (e.g., S1337–1010BR: Hamamatsu Photonics K.K.) that used the silicon crystal for the detection of light.

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Therefore, when the sensors were not used, they were stored in the vacuum desiccator. One of the reasons for

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the aforementioned phenomenon is attributed to the fact that there is a possibility that impurities come off

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from the sensor and the sensor performance improves following vacuum storage for a prolonged time period

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(approximately three months). A secondary reason was attributed to the fact that the electrochemical reactions

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that influenced the electrical characteristics of the p-type and n-type semiconductor materials may have

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occurred in the sensor owing a) the high-voltage impression during the measurement, b) oxidation in air, and

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c) the vacuum environment used for storage. We plan to clarify these issues in future research studies.

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5. Summary

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We developed a hybrid radiation sensor which was synthesized based on the mixture of TiO2 and the

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organic semiconductor polyaniline. A β-ray detection efficiency ≥ 10% was achieved, and the reproducibility

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of the results was also confirmed. The reasons for which the performance improved compared with our

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previous sensors [9] were based on the improved conditions of the mixture of the p-type and n-type

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semiconductor materials and the use of a ctenoid electrode. This sensor had a complex structure owing to the mixture of the p-type polyaniline and n-type TiO2.

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Therefore, the surface areas of the boundary of the p-type and n-type semiconductors were large, the depletion

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layer with the radiation sensitivity broadened, and increased radiation detection efficiency was obtained. A

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ctenoid electrode can efficiently collect the carrier electrons owing to the increased electric field generated in

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the ctenoid edges compared with the round plate electrode used in our previous work [9].

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We achieved a improved β-ray detection efficiency (10%) of the hybrid radiation detector with the organic semiconductor. This value was approximately ten times better than that of the previous report [9]. The β-ray

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incident rate dependence and the long-term stability were measured to assess the β-ray detection efficiency of

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the hybrid sensor.

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Based on the elicited outcomes, it was shown that the detection efficiency improved when the incident rate

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decreased. Specifically, the detection efficiencies ≥ 10 % were obtained at trigger rates ≤ 2–3 cps. This trigger

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rate corresponded to a β-ray incident rate ≤ 35 cps according to the Geant4 simulations.

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The detection efficiency has been stable with trigger rates ≤ 7 cps for a period of one year and seven months after the sensor was fabricated. A higher incident rate was noted, and the detection efficiency improved

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gradually for approximately three months after the fabrication of the sensor.

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The parameter optimization study for the hybrid radiation sensor continued and the detection efficiency

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improved further. We expect that high-efficiency radiation detection can be realized with the hybrid type

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sensor that combined inorganic and organic semiconductors, such as a high-density sensor which is increased

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the energy loss of β-ray in the sensor. Additional studies are needed to elucidate and quantify the electrical

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properties of the sensor materials with regard to the influences of the applied voltage, oxidation in air, and

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radiation detection performance of the sensor.

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Conflict of interest

Declaration of Interest: none

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Acknowledgments

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We express our gratitude for the support offered by Mr. Hiroki Morii, a technical staff member in the

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Faculty of Science, Niigata University. This work was supported by the Japanese Society for the Promotion of

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Science (JSPS) KAKENHI [grant numbers 20654022, 15K13482].

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Fig. 1. Optical micrographs of a Pani/TiO2 sheet (a) on the surface and (b) in a cross-section. Corresponding

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micrographs of a Pani sheet (c) on the surface and (d) in a cross-section.

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Fig. 2. Schematic of the bulk heterojunction structure.

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Fig. 3. Hybrid comb-type electrode sensor (Sensor N171221 fabricated on December 21, 2017).

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Fig. 4. Experimental setup used for the evaluation of the sensor performance.

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Fig. 5. Typical output signals observed by an oscilloscope (Sensor N171221, bias voltage 1900 V). Fig. 6. Analog-to-digital converter (ADC) distributions for (a) pedestal events and (b) β-ray signal events (Sensor N170720, bias voltage 2500 V). Fig. 7. Bias voltage dependence of β-ray detection efficiency (●: Sensor N170720 fabricated on July 20, 2017 and measured on November 4, 2017, ○: Sensor N171221 fabricated on December 21, 2017 and measured on March 27, 2018). Fig. 8. Alignment of source, spacer, collimator, sensor, and trigger counter. Fig. 9. Trigger rate dependence of the detection efficiency (●: Sensor N170720 fabricated on July 20, 2017 and measured on November 13, 2017 with an applied voltage of 2500 V, ○: Sensor N171221 fabricated on December 21, 2017 and measured on March 29, 2018 with an applied voltage of 2300 V). Fig. 10. Signal charge distributions as a function of the incident rate (trigger rate) of the β-rays for (a) 1.8 cps, (b) 7.0 cps, (c) 29 cps, and (d) 144 cps (Sensor N170720 fabricated on July 20, 2017 and measured on November 13, 2017 with an applied voltage of 2500 V). Fig. 11. Signal charge distributions as a function of the incident rate (trigger rate) of the β-rays for (a) 1.8 cps, (b) 7.0 cps, (c) 29 cps, and (d) 144 cps (Sensor N171221 fabricated on December 21, 2017 and measured on March 29, 2017 with an applied voltage of 2300 V).

331 332 333 334 335 336 337 338 339 340 341 342 343 344 345

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Journal Pre-proof Fig. 12. Dependence of β-ray incident rate (trigger rate) of the fraction of large-charge events (number of signal events with intensities > μ + 30σ/number of signal events with intensities > μ + 3σ). (●：Sensor N170720 fabricated on July 20, 2017 and measured on November 13, 2017 with an applied voltage of 2500 V, ○: Sensor N171221 fabricated on December 21, 2017 and measured on March 29, 2018 with an applied voltage of 2300 V). Fig. 13. Long-term stability of the detection efficiency (Sensor N171221 fabricated on December 21, 2017 and measured with an applied voltage of 2300 V, incident trigger rate of β-rays for △: 1.8 cps, ▲: 7.0 cps, ○: 29 cps, ●: 144 cps). Fig. 14. Applied voltage dependence of the detection efficiency for different measurement dates (Sensor N171221 fabricated on December 21, 2017 and measured with an incident trigger rate of β-rays of 144 cps on ●: December 27, 2017, ○: January 26, 2018, ▲: February 27, 2018, △：March 27, 2018).

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Table 1. Number of β-rays irradiated on the sensor as a function of the spacer size.

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Figure.1

(b)

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TiO2

Pani

(c)

(d)

Figure.2

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Anode

TiO2

Pani

Cathode

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Figure.3

Terminal to cathode

Au anode

Au plated W wire

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Figure.4 90Sr

Shield Box

β-ray source

Spacer (None, 20 mm, 50 mm, 110 mm) Collimator (2 mmΦ) Sensor Scintillator

Trigger Counter

Trigger Signal

PMT

H.V H.V cut capacitance

Sensor Signal Amplifier (Gain:7)

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Figure.5 +0.1

Pulse height [V]

0.0 -0.1 -0.2 -0.3 -0.4 -0.5

-100

-75

-50

-25

0

25

Time [ns]

50

75

100

Figure.6

(a)

500 400 300 200 100 0

104 103

CV

1200 1210 1220 1230 1240 1250 1260 1270 1280 1290 1300

Channel

Events

Events

600

(b)

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700

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CV

102 10 1

1000

1500

2000

2500

Channel

3000

3500

4000

Figure.7

●N170720 〇 N171221

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Detection efficiency [%]

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4

2

0 1000

1500

2000

2500

Bias voltage [V]

3000

Figure.8 90Sr

β-ray source

2.3 mm

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Source part (3.5 mmΦ)

Spacer (None, 20 mm, 50 mm, 110 mm)

r

d Collimator (2 mmΦ)

10 mm 6 mm

Sensor 8 mm Trigger counter

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Figure.9

●N170720 〇 N171221

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Detection efficiency [%]

12

10 8 6 4 2

0 1

2 3 456

10

2

3 456

100

Trigger rates [cps]

2 3 4 5

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Figure.10 (a)

(b)

Events

103

102 10 1 1000

1500

2000

102

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Events

103

2500

3000

3500

10 1

1000

4000

1500

2000

(c) 104

3500

4000

3000

3500

4000

(d)

103

Events

Events

3000

104

103 102

102

10

10

1 1000

2500

Cannel

Cannel

1500

2000

2500

Cannel

3000

3500

4000

1 1000

1500

2000

2500

Cannel

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Figure.11 (a)

(b)

103

Events

102

102

10

10

1 1000

1500

2000

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Events

103

2500

3000

3500

4000

1 1000

1500

2000

(c)

2500

3000

3500

4000

3000

3500

4000

Cannel

Cannel

(d)

104 103

Events

Events

103 102

102

10

10

1 1000

1 1500

2000

2500

Cannel

3000

3500

4000

1000

1500

2000

2500

Cannel

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Figure.12

●N170720 〇 N171221

0.6

0.4

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Fraction of large-charge events

0.8

0.2

0.0 1

2

3 4 56

10

2

3 4 56

Trigger rates [cps]

100

2

3 4 5

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Figure.13

12

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Detection efficiency [%]

10 8 6 4 2

●144 cps 〇 29 cps ▲ 7.0 cps △1.8 cps

0 0

100

200

300

400

Lapsed days [day]

500

600

Figure.14

●Dec. 27, 2017 ○Jan. 26, 2018 ▲ Feb. 27, 2018 △Mar. 27, 2018

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Detection efficiency [%]

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5 4 3 2 1

0 1200

1600

2000

2400

Bias voltage [V]

2800

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β-rays incident rates (cps:counts per second) Equation (3)

Geant4 simulation

Trigger rate

0 10 20 50 90 110

929 ± 119 284 ± 31 135 ± 14 36 ± 3.7 13 ± 1.4 9.4 ± 0.9

3511 ± 5.9 1043 ± 3.2 432 ± 2.1 94 ± 1.0 33 ± 0.6 22 ± 0.5

144.3 ± 0.49 62.4 ± 0.32 28.9 ± 0.22 7.0 ± 0.11 2.6 ± 0.07 1.8 ± 0.06

　 　 　 　 　 　

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Spacer size (mm)

　 　 　 　 　 　

Journal Pre-proof *Declaration of Interest Statement

Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: