- Email: [email protected]
Vacuum quality evaluation for uncooled micro bolometer thermal imager sensors
Microelectronics Reliability 54 (2014) 1758–1763
Contents lists available at ScienceDirect
Microelectronics Reliability journal homepage: www.elsevier.com/locate/microrel
Vacuum quality evaluation for uncooled micro bolometer thermal imager sensors Michael Elßner ⇑ Fraunhofer IMS, Finkenstr. 61, 47057 Duisburg, Germany
a r t i c l e
i n f o
Article history: Received 25 June 2014 Accepted 14 July 2014 Available online 17 August 2014 Keywords: Vacuum quality Hermetic packaging Micro bolometer Infrared imager
a b s t r a c t This paper presents an innovative and effective method of measuring the internal vacuum quality of uncooled micro bolometer thermal imager sensors where the bolometer sensor elements themselves are used for vacuum measurement. A feasible thermal calculation model using an extended Fourier’s Law is presented which is integrated in thermal FEM simulations. Experimental results correlating with FEM simulations prove the feasibility of this method. A measuring range to pressures as low as 5 103 mbar was achieved that fully covers the needed range where the internal package pressure is leading to performance losses of the IRFPA. The vacuum quality evaluation method supported by a developed temperature compensation method is showing a high repetitive accuracy with a remaining mean failure of 0.2%. Without the need to integrate additional pressure sensors this method reduces costs and chip area and it is fast and highly accurate. Therefore, it can be used for stationary test systems as well as in mobile infrared camera systems. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction Un-cooled far infrared micro bolometer focal plane arrays (IRFPAs) are the common state-of-the-art technology for a variety of applications in fields of medicine, automotive, industrial, security, military and consumer thermal imaging. IRFPAs manufactured by the Fraunhofer IMS [1] like other MEMS (micro electro-mechanical systems) need a hermetic package with an integrated vacuum below 102 mbar. Independently from which packaging and bonding process is chosen, the increasing internal pressure directly leads to performance reductions of the IRFPA. The influence of changing pressure on the imager performance was also investigated in [2–4]. For that reason it is necessary to measure and track the internal pressure level of the package to investigate and assure the quality and reliability of the IRFPA. Physical reason [5,6] for the increasing pressure are outgassing processes [7] inside the package which is most critical for packages with very small cavity volumes (<1 lL), as small amounts of gases are leading to sharp increase of pressure. Standard methods of vacuum measurement like the helium leak test are not applicable for small volume packages [8,9] and rest gas analyses are destructive measurements. Other methods like measuring the vacuum related lid deformation changes [10,11] are theoretically possible but not practicable as it is a stationary, ⇑ Tel.: +49 0203 37830 218. E-mail address: [email protected] http://dx.doi.org/10.1016/j.microrel.2014.07.094 0026-2714/Ó 2014 Elsevier Ltd. All rights reserved.
complex, slow and inaccurate measurement. Therefore measuring the pressure via integrated pressure sensors is the only applicable method. As resonant sensors do not have suitable measuring range [11] only sensors based on the Pirani effect [10,12] can be used. In principle Pirani sensors are consisting of thermally sensitive structures in form of a plate, a cantilever beam or a bridge, which are thermally isolated to the substrate material. As the thermal sensitive structure often called ‘‘hot-plate’’ is heated, the heat loss to the ambient through gas conduction is related to the number of gas molecules and thereby to the gas pressure inside the package. This technology is capable of measuring and monitoring the vacuum level inside the package for qualification or calibration purposes. The current procedure for IRFPAs is the design and cofabrication of these sensors on the same substrate as the bolometer structures [12–15], which can be simply achieved because of the similar and highly compatible manufacturing processes. This paper shows the innovative approach of using bolometer sensor elements themselves as vacuum sensors. The developed bolometers from the Fraunhofer IMS, used as vacuum sensors, have the same measuring range and sensitivity like Pirani sensors, which is verified through a combination of thermal calculations with finite element method (FEM) simulations and experimental measurements. The remarkable advantages of this method are that no additional pressure sensor structures are necessary and thereby no changes within the process or design and layout of the IRFPA, so that valuable chip area and costs can be saved. When using the
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bolometers as pressure sensors the existing read-out-circuit (ROIC) of the IRFPA is used. The ROIC is optimized for measuring smallest changes in the bolometer electrical resistance, and thus is perfectly suitable for the vacuum measurement described here. As shown in this paper the measuring range is sufficient for IRFPAs due to the use of the same sensor structure and thermal properties. IRFPAs contain thousands of bolometer elements which enable pressure measurements over thousands of sensor elements over the whole chip size. Along with the opportunity of using the IRFPA’s typical frame rate of thirty frames per second, many thousands of measurement points can be used for post calculations like averaging to maximize the measuring accuracy. As the vacuum measurement has a massive dependence on the ambient and chip temperature, an effective temperature stabilization method was realized that is capable of minimizing the temperature related measurement failures without using additional devices. With this development it is possible to perform accurate vacuum evaluations in mobile infrared camera system without the need of additional temperature stabilizing devices that would increase costs, power consumption and the camera size. With the described methods in this paper a fast and cost saving way of vacuum evaluation with a high accuracy was developed. 2. Calculation models 2.1. Physical bolometer model The IRFPA’s performance [22–25] is described by the responsivity R (1), specified as the bolometer’s output signal in relation to the radiant power, which is typically defined in Bits per Kelvin and the noise equivalent temperature difference (NETD) calculated by (2), that further takes optical parameters and the IRFPAs noise level into account.
R¼
TCR b e U bolo pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 1 þ x2 s2
ð1Þ
4 F 2 Un R A / ðDDTPÞ
ð2Þ
Gth
NETD ¼
where F is the F-number of the infrared optics, Un is the total noise voltage, A is the bolometer pixel area, / is the optical infrared transmittance, DP/DT is the temperature contrast, TCR is the temperature coefficient of the thermal sensitive structure, b is the bolometer pixel fill factor, e the infrared absorption factor, Ubolo is the bolometer bias voltage, Gth the thermal conductivity, x is the reciprocal of the frame read out frequency and s is the thermal time constant. Besides optical and IRFPA specific parameters the responsivity (1) is depending on the bolometer’s thermal conductivity. There are three types of thermal conductivities (3) leading to thermal heat loss, the thermal conductivity of the bolometer legs Gsolid, the thermal heat radiation Grad and the rarefied gas conduction Ggas through unwanted gas molecules inside the package (see Fig. 1).
Gth ¼ Ggas þ Gsolid þ Grad
ð3Þ
2.2. Thermal heat model 2.2.1. Gsolid The calculation of the solid heat conduction is performed by Fourier’s Law of heat conduction (4,5) and is defined by the geometrical bolometer leg design, with the leg area A, the leg length l and the material specific thermal conductivity k of the different material layers.
~ q ¼ krT
ð4Þ
Gsolid ¼ k A=l
ð5Þ
Fig. 1. Types of thermal conductivities of bolometer sensors.
2.2.2. Grad The heat loss through thermal radiation is calculated by Stefan– Boltzmann’s law (6). Where r is the Stefan–Boltzmann constant (5.670 108 W m2 K4), e is the material’s emission coefficient, T1 is the temperature of the bolometer membrane and T2 is the temperature of the IRFPA substrate. The calculated heat conductivity through radiation (7) in typical areas of 109 W/K are quite small but as Fraunhofer IMS bolometers have a very low solid heat conductivity in a similar order of magnitude the radiation cannot be neglected.
Q_ rad ¼ r e A ðT 41 T 42 Þ Grad ¼ 2 Q_ rad =ðT 1 T 2 Þ
ð6Þ ð7Þ
2.2.3. Ggas The heat transfer via gas conduction (9) is based on molecular flow which can be proved in calculating the package internal density of the gas flow via the Knudsens-number, resulting in high orders of magnitude of 106 at 103 mbar. At Knudsens-numbers higher than 10 gas leaves continuum flow and Fourier’s Law becomes invalid [16,17] and gas convection has no effect. Evaluated methods in [12,18,19] provide a simplified but best suitable calculation model forming a so called ’Extended Fourier’s Law shown here. The heat flux qgas is then calculated by the thermal conductivity of the rarefied gas kgas and the membrane distance D by using (9)–(13). The heat transfer occurs from the membrane to the substrate and to the lid so the calculations have to be done for both distances.
Ggas ¼ qgas =DT
ð8Þ
qgas ¼ kgas DT=D kSubstrat kgas ¼ 4L 1 þ 3D 1 kSubstrat ¼ nv cL 3 rffiffiffiffiffiffiffiffiffiffiffiffiffi P 8kB T 1 v ¼ n¼ kB T 1 pm kb T 1 L ¼ pffiffiffi 2 p d2 p
ð9Þ ð10Þ ð11Þ c¼
3 kB 2
ð12Þ ð13Þ
where L is the mean free path, n the molecular number per unit vol the mean molecular speed, c the specific heat per molecule, ume, v kB the Boltzmann Constant = 1.38 1023 (J/K), m the mass of the molecules, p the package internal pressure and d the molecular diameter. For this calculation specific material parameters of the outgassed molecules have to be identified by performing gas analyses using mass spectrometry. Fig. 2 shows a simplified model of the bolometer heat loss by gas conduction. Gas molecules that contact the bolometer surface are heated and transfer the thermal heat to the package wall and
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substrate or lid surface. The resulting heat loss relates to the amount of gas inside the package and consequently to the package internal pressure. 2.3. Measuring principle The principle of the vacuum measurement is described in the following. In applying a voltage Ubolo with a specific period of time t over the ROIC, the bolometer is heated by joule’s law. The temperature rise in the bolometer through self-heating is calculated by (16) after [21]. The temperature is not only depending on the electrical power Pelekt, the thermal capacity Cth, the pulse or heating time t and the TCR but also on the thermal conductivity Gth of the bolometer structures (3). Over the device lifetime outgassing processes inside the package are leading to an increasing pressure level p and equally to increasing heat loss through gas conduction. In conclusion the bolometer temperature Tbolo through self-heating is depending on gas conduction and package internal pressure. Thus the pressure can be evaluated by the heat loss and the changing electrical resistance Relect and electrical current Ibolo of the bolometer by (17). Typical IRFPA read-out frequencies that can be used for the vacuum measurement are 30 Hz. This high measurement frequency in combination with the possibility to read out multiple bolometers depending on the ROIC structure, many thousand measurement points per second can be obtained. Post calculations like averaging are achieving a high measuring accuracy that can filter noise and bolometer fluctuations very effectively. For this type of vacuum measurement it must be possible to read out one bolometer multiple times in a row in order to create a high temperature increase within the bolometer for high measurement output. But if the heating time and thus temperature is too high, the heat cannot be fully released before the next read-out cycle and an offset is generated that reduces the measurement signal output. The measurement values of each bolometer are ideally calculated in relative changes by calculating the changes to the first of the multiple measurements.
Pelect ¼
U 2bolo =Relect
¼ Gth T
Relect ¼ R0 ð1 þ TCR DTÞ Pelect U2 t ¼ bolo C th Relect Gth ¼ Gth =ðTCR U bolo Þ
ð14Þ ð15Þ
DT ¼
ð16Þ
Ibolo
ð17Þ
D ¼ TCR DT nt Sd
ð18Þ
Fig. 2. Simplified model with one symbolic bolometer of the package internal heat transfer by gas molecules, red ball: heated gas molecule, blue ball: cooled gas molecule (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.).
with nt the number of readout cycles and sd a ROIC specific conversion factor transferring changes of the relative resistance into digital values. The sensor output values DD can be calculated by using (18) and (16). In general absolute pressure measurements are possible but process deviations are typically leading to offset failures. Calibration measurements to eliminate the offset are possible but often not needed as the relative measurement of the sensor output compared to the initial values are fully sufficient to track the vacuum quality, as a change in the vacuum level is the main point of interest. The advantages of this method are that there are no additional pressure sensors needed like in [12–15]. Therefore an IRFPA redesign is not necessary as the production process is unchanged, chips size is reduced and costs are saved.
3. FEM simulation and practical results 3.1. Simulation results FEM (Finite Element Method) simulations performed by Comsol Multiphysics are used to evaluate the thermal behaviour and the sensor capabilities. Basis is a 3D model with the specific Fraunhofer IMS bolometer design and material specifications. An industry common pixel pitch of 17 lm was chosen. The simulations physical model involve the joule heating through the electrical stimulation, the solid heat transfer (4), the thermal heat radiation (6) and the pressure related heat loss through the Extended Fourier’s Law (9). The electrical stimulation with the pulsed voltage Ubolo and a specific pulse length t is identical to the experimental implementation. The evaluated electrical resistance changes at different pressure levels from ambient to 103 mbar are shown in the red (-&-) curve of Fig. 4.
3.2. Experimental measurement The experimental measurements are carried out in two steps. At first a single bolometer sensor element that could be contacted directly was examined to verify the FEM simulations. The bolometer resistance is measured direct and analog by standard equipment like a function generator for the pulsed bolometer voltage and an oscilloscope to evaluate the bolometer resistance at these heating phases. In the second step the vacuum measurements were performed with the ROIC and a specific control pattern, optimized for a maximum sensitivity, reading hundreds of bolometers simultaneously. The pressure values are evaluated by the changing image data values representing the bolometer resistances. A test setup shown in Fig. 3 has been developed where the decapsulated IRFPA with removed lid is operating in a vacuum environment with a controllable pressure level and reference pressure gauges based on the Pirani effect and cold cathode gauge. The IRFPA is connected via a vacuum tight through-connection to a control unit which is connected to the PC. As the vacuum measurement is highly temperature dependent a temperature controller (TEC) should be used to achieve comparable and temperature independent results. The results of the single bolometer measurements shown in Fig. 4’s blue (-.-) curve are in great conformity to the simulation results proving the validity of the proposed thermal calculation models. In the second step the vacuum measurements were performed with the ROIC controlling and reading thousands of bolometers simultaneously. The measurement results averaged over all bolometers and 30 frames were shown in the green (--) curve of Fig. 4.
M. Elßner / Microelectronics Reliability 54 (2014) 1758–1763
Fig. 3. Vacuum measurement test setup used for calibration measurements.
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accurate and very fast measurement in the laboratory where the IRFPAs are measured mainly for qualification and process control means. And second the implementation in the infrared camera system where vacuum quality and furthermore the IRFPA’s performance can be evaluated by this measurement. In this way a performance loss, a broken package and defect IRFPA can be detected. Furthermore the sensor outputs can be adjusted according the potential vacuum loss leading to responsivity reduction by using (1) or a calibration measurement were the relationship between the IRFPA’s responsivity and the vacuum measurements results were determined. An appropriated stationary test system consists of an air conditioning system that stabilizes the ambient temperature and a TEC that stabilizes the chip temperature precisely. An additional black body radiator should be used to guarantee constant radiation input through the lid, even though this contribution to the bolometer temperature is quite small. The extended hardware setup shown in Fig. 5 is needed as the main critical influence on the measurement’s accuracy and repeatability is the bolometer’s and IRFPA’s temperature, which has to be controlled and stabilized in order to gain consistent measurements. In contrast to the stationary test environment show in Fig. 5 the implementation in a camera system does most commonly not comprehend any temperature stabilizing countermeasures like TECs. Just the unwanted influence of incoming ambient thermal radiation through the lid can be eliminated by the camera’s shutter. The IRFPA is subjected to ambient or camera internal temperature fluctuations and the IRFPAs self-heating. As shown in Fig. 6’s blue (-.-) curve, huge measurement failures over 100% are occurring by a temperature increase of 10 K. Consequently new temperature controlling counter measures have to be implemented without the help of supporting devices. 3.4. Temperature compensation
Fig. 4. Red: Results of the FEM simulations in relative changes (-&-), blue: single bolometer results (-.-) and green: IRFPA measurements (- -) curve. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
It can be seen that the sensor has high pressure sensitivity in the area of 10+1 mbar to 101 mbar but a decreasing sensitivity at pressures below 101 mbar. The IRFPA measurements were performed with a specific heating pattern that is optimized for achieving a maximum sensitivity in low pressure areas but also resulting in an upper measurement border of 10+1 mbar. Analyzing the measurements results a boundary can be seen at 5 103 mbar where the pressure related resistance changes disappear in noise. Measurements in [20] show that there is a performance loss at pressures higher than 0.1 torr (1.3 101 mbar) and [13] identified performance loss above 102 torr. This correlates with the performed measurements here. At pressures below 5 103 mbar gas conduction is not influencing the bolometer performance any more as the heat loss becomes negligible and consequently cannot be measured any more. This can be proved in calculating the thermal conductivity based on gas conduction with Eqs. (8)–(13). At 5 103 mbar this thermal conduction is two magnitudes smaller than the thermal conductivity by solid heat transfer and thermal radiation.
Ideally the IRFPA is showing the same measurement values independent of the chip temperature. But with fluctuating temperatures the bolometer’s electrical resistance Relect and current Ibolo is changing (17). This can be evaluated by using a control algorithm that tunes the bolometer voltage, which is directly related to the electrical resistance, through the ROIC until a reference current is reached. In most cases this current is not directly measureable until it is instantly converted by an Analog–Digital-Converter (ADC) into digital values to reduce noise. In this case the offset
3.3. Practical implementation The calculation and simulation results show that the measuring principle described here is highly suitable for vacuum evaluations. Two principle applications are targeted. First a stationary high
Fig. 5. Hardware setup for a stationary vacuum measurement system with controlled ambient conditions.
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M. Elßner / Microelectronics Reliability 54 (2014) 1758–1763
4. Conclusion The measurement range and sensitivity of the vacuum measuring principle, described in this paper are capable to measure any pressure increase that is leading to performance losses of the IRFPA. The highly accurate vacuum measurements with a mean failure of 0.2% are performed by using a developed temperature compensation algorithm that minimizes temperature related measurement deviations effectively. With this enhancement not only fast stationary measurements in a laboratory environment are possible but also mobile vacuum measurements in infrared camera systems. Based on the technology described here further customer or application specific calculation methods are implementable. For example by tracking the performance loss and vacuum quality a user profile can be generated and the devices lifetime can be calculated in real-time. It is furthermore possible to adjust the infrared camera sensor output with the vacuum evaluations results if degradations are measured. The functionality and validity of the vacuum evaluation method which are described here were successfully proven in use with the IRFPAs manufactured at the Fraunhofer IMS. Fig. 6. Comparison of the relative vacuum measuring failures, blue: without any control algorithm (-N-), red: with a voltage self-compensation (-.-) and green: a combined voltage and temperature compensation (-&-) (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
voltage is controlled to a specific digital output value. Evaluating the relative changes in the bolometer offset voltage after the controlling to a reference or starting value, the temperature dependency of this ratio can be seen. Thus the temperature dependent vacuum sensor error can be calculated and subtracted out by the changing bolometer offset voltage ratio and a specific transfer factor. In an experiment with ten different temperature steps from 295 K to 305 K that are controlled with an accuracy of 0.01 K, the vacuum sensor outputs are measured and the residual relative deviations are shown in Fig. 6. Evaluating the red (-.-) curve in Fig. 6 in contrast to the blue (-N-) one, it can be seen that the algorithm reduces the sensor measuring error effectively. But as this method works fine within small temperature deviations of some several Kelvins it can be seen that the sensor failures increase with rising temperature changes. At a temperature increase of 10 K a residual deviation of nearly 9% is remaining. This is due to non-linearity and complex temperature dependencies of the whole IRFPA chip and the ROIC. An improvement to further sensor error reduction is the integration of a temperature sensor that has to be implemented within the IRFPA design. In case that the temperature sensor values have reasonable deviations over different production lots or devices an initial calibration measurement has to be done, where bolometer offset voltage and temperature sensor values are stored as references in the Pc or respectively in the memory of the camera system. The resulting temperature dependent sensor deviations with the enhanced method are shown in Fig. 6 in the green (-&-) curve. The residual deviations are very small and the sensor measurement results are nearly temperature independent. Thus the critical influence of the temperature can be eliminated very effectively and the vacuum sensor’s repetitive accuracy is greatly improved. In this way the vacuum measurements cannot only be succeeded in the ideal stationary measuring environment as described in Fig. 5 but also in mobile infrared camera systems. Executed repetitive measurements with a total of 20 measurements at each of five different days were carried out, showing a repetitive accuracy of approximately 99.98% with a calculated statistical standard deviation of 0.2% proofing the high viability of this measurement.
Acknowledgements This research was supported by the Fraunhofer Institute for Microelectronic Circuits and Systems (IMS) and the University of Duisburg-Essen. References [1] Weiler D et al. Improvements of a digital 25 lm pixel-pitch uncooled amorphous silicon TEC-less VGA IRFPA with massively parallel Sigma-DeltaADC readout. In: Paper 80121F (proceedings of SPIE 8012) infrared technology and applications XXXVII, 25 April 2011, Orlando, Florida, USA Bellingham. WA: SPIE; 2011. [2] Premachandran CS, Khan N, Xiaowu Z, Chong CS, Chai TC. Design & development of a new thermally stable high vacuum IR bolometer package. In: Proc 53rd Electron Compon Technol Conf 2003. p. 392–6. [3] Premachandran C, Chong S, Chai T, Iyer M. Vacuum packaging development and testing for an uncooled IR bolometer device. In: Proc 54th Electron Compon Technol Conf 2004. p. 951–5. [4] Garcia-Blanco S, LeFoulgoc K, Desroches Y, Caron JS, Topart P, Alain C, et al. Wafer-level hermetic vacuum micro packaging technology for IR detector applications. In: Proc IEEE LEOS Annu Meet Conf 2009. p. 57–8. [5] Wang B, Tanaka S, Guo B, Vereecke G, Severi S, Witvrouw A, et al. Outgassing study of thin films used for poly-SiGe based vacuum packaging of MEMS. Elsevier Ltd; 2011. [6] Jousten K. Thermal outgassing, Physikalisch-Technische Bundesanstalt, Berlin, Germany. [7] de Segovia JL. Physics of outgassing, Instituto de Fiscia Aplicada [CETEF L. Torres Quevedo]. Madrid, Spain: CSIC; 1999. [8] Nese M, Bernstein RW, Johansen I-R, Spooren R. New method for testing hermeticity of silicon sensor structures sensors actuators. In: Proceedings of The 8th international conference on solid-state sensors and actuators, sensors and actuators A: physical, vol. 53. 1996. p. 349–52. [9] Lellouchi D et al. A new method for the hermeticity testing of wafer-level packaging, iopscience.iop.org, January 2010. [10] Li Q, Goosen H, Keulen Fv, van Beek J, Zhang G. Assessment of testing methodologies for thin-film vacuum MEMS packages, July 2008. [11] Bosseboeuf A, Grandchamp JP, Breluzeau C, Lani S, Palomo J, Bouville D. Vacuum measurement in wafer level encapsulations by interference microscopy. Springer; 2006. [12] Xiao B, Dong T, Halvorsen E, Yang Z, Zhang Y, Hoivik N, et al. Integrated micro pirani gauge based hermetical package monitoring for uncooled VOx bolometer FPAs. Springer; 2010. [13] Sisto MM, Blanco SG, Le Noc L, Tremblay B, Desroches Y, Sol Caron J, et al. Pressure sensing in vacuum hermetic micropackaging for MOEMS-MEMS, reliability, packaging, testing, and characterization of MEMS/MOEMS and Nanodevices IX. In: Proc of SPIE, vol. 7592. 2010. [14] Dong T, Xiao B, Elfving A, Yang Z, Tran-Minh N, Halvorsen E, et al. Pirani gauge based hermeticity monitoring for un-cooled micro bolometer array. In: IEEE proceedings of 16th IPFA, China, 2009. [15] Weng PK, Shie J-S. Micro-Pirani vacuum gauge. National Chiao Tung University, 1001 Ta Hsueh Road, Hsinchu, Taiwan, Republic of China: Institute of Electra-Optical Engineering; 1993. [16] Kamiadakis G, Beskok A, Alum N. Microflows and nanoflows: fundamentals and simulations. New York: Springer; 2005.
M. Elßner / Microelectronics Reliability 54 (2014) 1758–1763 [17] Yang S, Tao W. Heat transfer. 3rd. Beijing: Higher Education Press; 1998. [18] Chen G. Nanoscale energy transport and conversion. New York: Oxford University Press; 2005. [19] Dong T, Yang Z. Measurement and modeling of R141b condensation heat transfer in silicon rectangular microchannels. J Micromech Microeng 2008;18:12–27. [20] He X, Karunasiri G, Mei T, Zeng WJ, Neuzil P, Sridhar U. Performance of microbolometer focal plane arrays under varying pressure. IEEE Electron Device Lett 2000;21(5). [21] Jansson C, Ringh U, Liddiard K. Theoretical analysis of pulse bias heating of bolometers and effectiveness of pulse bias compensation. In: Proceedings of SPIE, San Diego, USA; vol. 2552. 1995. p. 644–53.
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[22] Marasco PL, Dereniak EL. Uncooled infrared sensor performance. In: Proceedings of SPIE, San Diego, USA; vol. 2020. 1993. p. 363–78. [23] Kruse PW. Uncooled thermal imaging arrays, systems and applications. Bellingham, WA, USA: SPIE Press; 2001. [24] Wood RA. Uncooled microbolometer infrared sensor arrays. In: Capper P, Elliott CT, editors. Infrared emitters and detectors. Norwell, Massachusetts: Kluwer Academic Publishers; 2001. [25] Zerov VY, Malyarov VG, Khrebtov IA. Calculational modeling of the main characteristics of an uncooled linear microbolometer array. J Opt Technol 2004;7(3):153–7.
Contents lists available at ScienceDirect
Microelectronics Reliability journal homepage: www.elsevier.com/locate/microrel
Vacuum quality evaluation for uncooled micro bolometer thermal imager sensors Michael Elßner ⇑ Fraunhofer IMS, Finkenstr. 61, 47057 Duisburg, Germany
a r t i c l e
i n f o
Article history: Received 25 June 2014 Accepted 14 July 2014 Available online 17 August 2014 Keywords: Vacuum quality Hermetic packaging Micro bolometer Infrared imager
a b s t r a c t This paper presents an innovative and effective method of measuring the internal vacuum quality of uncooled micro bolometer thermal imager sensors where the bolometer sensor elements themselves are used for vacuum measurement. A feasible thermal calculation model using an extended Fourier’s Law is presented which is integrated in thermal FEM simulations. Experimental results correlating with FEM simulations prove the feasibility of this method. A measuring range to pressures as low as 5 103 mbar was achieved that fully covers the needed range where the internal package pressure is leading to performance losses of the IRFPA. The vacuum quality evaluation method supported by a developed temperature compensation method is showing a high repetitive accuracy with a remaining mean failure of 0.2%. Without the need to integrate additional pressure sensors this method reduces costs and chip area and it is fast and highly accurate. Therefore, it can be used for stationary test systems as well as in mobile infrared camera systems. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction Un-cooled far infrared micro bolometer focal plane arrays (IRFPAs) are the common state-of-the-art technology for a variety of applications in fields of medicine, automotive, industrial, security, military and consumer thermal imaging. IRFPAs manufactured by the Fraunhofer IMS [1] like other MEMS (micro electro-mechanical systems) need a hermetic package with an integrated vacuum below 102 mbar. Independently from which packaging and bonding process is chosen, the increasing internal pressure directly leads to performance reductions of the IRFPA. The influence of changing pressure on the imager performance was also investigated in [2–4]. For that reason it is necessary to measure and track the internal pressure level of the package to investigate and assure the quality and reliability of the IRFPA. Physical reason [5,6] for the increasing pressure are outgassing processes [7] inside the package which is most critical for packages with very small cavity volumes (<1 lL), as small amounts of gases are leading to sharp increase of pressure. Standard methods of vacuum measurement like the helium leak test are not applicable for small volume packages [8,9] and rest gas analyses are destructive measurements. Other methods like measuring the vacuum related lid deformation changes [10,11] are theoretically possible but not practicable as it is a stationary, ⇑ Tel.: +49 0203 37830 218. E-mail address: [email protected] http://dx.doi.org/10.1016/j.microrel.2014.07.094 0026-2714/Ó 2014 Elsevier Ltd. All rights reserved.
complex, slow and inaccurate measurement. Therefore measuring the pressure via integrated pressure sensors is the only applicable method. As resonant sensors do not have suitable measuring range [11] only sensors based on the Pirani effect [10,12] can be used. In principle Pirani sensors are consisting of thermally sensitive structures in form of a plate, a cantilever beam or a bridge, which are thermally isolated to the substrate material. As the thermal sensitive structure often called ‘‘hot-plate’’ is heated, the heat loss to the ambient through gas conduction is related to the number of gas molecules and thereby to the gas pressure inside the package. This technology is capable of measuring and monitoring the vacuum level inside the package for qualification or calibration purposes. The current procedure for IRFPAs is the design and cofabrication of these sensors on the same substrate as the bolometer structures [12–15], which can be simply achieved because of the similar and highly compatible manufacturing processes. This paper shows the innovative approach of using bolometer sensor elements themselves as vacuum sensors. The developed bolometers from the Fraunhofer IMS, used as vacuum sensors, have the same measuring range and sensitivity like Pirani sensors, which is verified through a combination of thermal calculations with finite element method (FEM) simulations and experimental measurements. The remarkable advantages of this method are that no additional pressure sensor structures are necessary and thereby no changes within the process or design and layout of the IRFPA, so that valuable chip area and costs can be saved. When using the
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bolometers as pressure sensors the existing read-out-circuit (ROIC) of the IRFPA is used. The ROIC is optimized for measuring smallest changes in the bolometer electrical resistance, and thus is perfectly suitable for the vacuum measurement described here. As shown in this paper the measuring range is sufficient for IRFPAs due to the use of the same sensor structure and thermal properties. IRFPAs contain thousands of bolometer elements which enable pressure measurements over thousands of sensor elements over the whole chip size. Along with the opportunity of using the IRFPA’s typical frame rate of thirty frames per second, many thousands of measurement points can be used for post calculations like averaging to maximize the measuring accuracy. As the vacuum measurement has a massive dependence on the ambient and chip temperature, an effective temperature stabilization method was realized that is capable of minimizing the temperature related measurement failures without using additional devices. With this development it is possible to perform accurate vacuum evaluations in mobile infrared camera system without the need of additional temperature stabilizing devices that would increase costs, power consumption and the camera size. With the described methods in this paper a fast and cost saving way of vacuum evaluation with a high accuracy was developed. 2. Calculation models 2.1. Physical bolometer model The IRFPA’s performance [22–25] is described by the responsivity R (1), specified as the bolometer’s output signal in relation to the radiant power, which is typically defined in Bits per Kelvin and the noise equivalent temperature difference (NETD) calculated by (2), that further takes optical parameters and the IRFPAs noise level into account.
R¼
TCR b e U bolo pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 1 þ x2 s2
ð1Þ
4 F 2 Un R A / ðDDTPÞ
ð2Þ
Gth
NETD ¼
where F is the F-number of the infrared optics, Un is the total noise voltage, A is the bolometer pixel area, / is the optical infrared transmittance, DP/DT is the temperature contrast, TCR is the temperature coefficient of the thermal sensitive structure, b is the bolometer pixel fill factor, e the infrared absorption factor, Ubolo is the bolometer bias voltage, Gth the thermal conductivity, x is the reciprocal of the frame read out frequency and s is the thermal time constant. Besides optical and IRFPA specific parameters the responsivity (1) is depending on the bolometer’s thermal conductivity. There are three types of thermal conductivities (3) leading to thermal heat loss, the thermal conductivity of the bolometer legs Gsolid, the thermal heat radiation Grad and the rarefied gas conduction Ggas through unwanted gas molecules inside the package (see Fig. 1).
Gth ¼ Ggas þ Gsolid þ Grad
ð3Þ
2.2. Thermal heat model 2.2.1. Gsolid The calculation of the solid heat conduction is performed by Fourier’s Law of heat conduction (4,5) and is defined by the geometrical bolometer leg design, with the leg area A, the leg length l and the material specific thermal conductivity k of the different material layers.
~ q ¼ krT
ð4Þ
Gsolid ¼ k A=l
ð5Þ
Fig. 1. Types of thermal conductivities of bolometer sensors.
2.2.2. Grad The heat loss through thermal radiation is calculated by Stefan– Boltzmann’s law (6). Where r is the Stefan–Boltzmann constant (5.670 108 W m2 K4), e is the material’s emission coefficient, T1 is the temperature of the bolometer membrane and T2 is the temperature of the IRFPA substrate. The calculated heat conductivity through radiation (7) in typical areas of 109 W/K are quite small but as Fraunhofer IMS bolometers have a very low solid heat conductivity in a similar order of magnitude the radiation cannot be neglected.
Q_ rad ¼ r e A ðT 41 T 42 Þ Grad ¼ 2 Q_ rad =ðT 1 T 2 Þ
ð6Þ ð7Þ
2.2.3. Ggas The heat transfer via gas conduction (9) is based on molecular flow which can be proved in calculating the package internal density of the gas flow via the Knudsens-number, resulting in high orders of magnitude of 106 at 103 mbar. At Knudsens-numbers higher than 10 gas leaves continuum flow and Fourier’s Law becomes invalid [16,17] and gas convection has no effect. Evaluated methods in [12,18,19] provide a simplified but best suitable calculation model forming a so called ’Extended Fourier’s Law shown here. The heat flux qgas is then calculated by the thermal conductivity of the rarefied gas kgas and the membrane distance D by using (9)–(13). The heat transfer occurs from the membrane to the substrate and to the lid so the calculations have to be done for both distances.
Ggas ¼ qgas =DT
ð8Þ
qgas ¼ kgas DT=D kSubstrat kgas ¼ 4L 1 þ 3D 1 kSubstrat ¼ nv cL 3 rffiffiffiffiffiffiffiffiffiffiffiffiffi P 8kB T 1 v ¼ n¼ kB T 1 pm kb T 1 L ¼ pffiffiffi 2 p d2 p
ð9Þ ð10Þ ð11Þ c¼
3 kB 2
ð12Þ ð13Þ
where L is the mean free path, n the molecular number per unit vol the mean molecular speed, c the specific heat per molecule, ume, v kB the Boltzmann Constant = 1.38 1023 (J/K), m the mass of the molecules, p the package internal pressure and d the molecular diameter. For this calculation specific material parameters of the outgassed molecules have to be identified by performing gas analyses using mass spectrometry. Fig. 2 shows a simplified model of the bolometer heat loss by gas conduction. Gas molecules that contact the bolometer surface are heated and transfer the thermal heat to the package wall and
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substrate or lid surface. The resulting heat loss relates to the amount of gas inside the package and consequently to the package internal pressure. 2.3. Measuring principle The principle of the vacuum measurement is described in the following. In applying a voltage Ubolo with a specific period of time t over the ROIC, the bolometer is heated by joule’s law. The temperature rise in the bolometer through self-heating is calculated by (16) after [21]. The temperature is not only depending on the electrical power Pelekt, the thermal capacity Cth, the pulse or heating time t and the TCR but also on the thermal conductivity Gth of the bolometer structures (3). Over the device lifetime outgassing processes inside the package are leading to an increasing pressure level p and equally to increasing heat loss through gas conduction. In conclusion the bolometer temperature Tbolo through self-heating is depending on gas conduction and package internal pressure. Thus the pressure can be evaluated by the heat loss and the changing electrical resistance Relect and electrical current Ibolo of the bolometer by (17). Typical IRFPA read-out frequencies that can be used for the vacuum measurement are 30 Hz. This high measurement frequency in combination with the possibility to read out multiple bolometers depending on the ROIC structure, many thousand measurement points per second can be obtained. Post calculations like averaging are achieving a high measuring accuracy that can filter noise and bolometer fluctuations very effectively. For this type of vacuum measurement it must be possible to read out one bolometer multiple times in a row in order to create a high temperature increase within the bolometer for high measurement output. But if the heating time and thus temperature is too high, the heat cannot be fully released before the next read-out cycle and an offset is generated that reduces the measurement signal output. The measurement values of each bolometer are ideally calculated in relative changes by calculating the changes to the first of the multiple measurements.
Pelect ¼
U 2bolo =Relect
¼ Gth T
Relect ¼ R0 ð1 þ TCR DTÞ Pelect U2 t ¼ bolo C th Relect Gth ¼ Gth =ðTCR U bolo Þ
ð14Þ ð15Þ
DT ¼
ð16Þ
Ibolo
ð17Þ
D ¼ TCR DT nt Sd
ð18Þ
Fig. 2. Simplified model with one symbolic bolometer of the package internal heat transfer by gas molecules, red ball: heated gas molecule, blue ball: cooled gas molecule (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.).
with nt the number of readout cycles and sd a ROIC specific conversion factor transferring changes of the relative resistance into digital values. The sensor output values DD can be calculated by using (18) and (16). In general absolute pressure measurements are possible but process deviations are typically leading to offset failures. Calibration measurements to eliminate the offset are possible but often not needed as the relative measurement of the sensor output compared to the initial values are fully sufficient to track the vacuum quality, as a change in the vacuum level is the main point of interest. The advantages of this method are that there are no additional pressure sensors needed like in [12–15]. Therefore an IRFPA redesign is not necessary as the production process is unchanged, chips size is reduced and costs are saved.
3. FEM simulation and practical results 3.1. Simulation results FEM (Finite Element Method) simulations performed by Comsol Multiphysics are used to evaluate the thermal behaviour and the sensor capabilities. Basis is a 3D model with the specific Fraunhofer IMS bolometer design and material specifications. An industry common pixel pitch of 17 lm was chosen. The simulations physical model involve the joule heating through the electrical stimulation, the solid heat transfer (4), the thermal heat radiation (6) and the pressure related heat loss through the Extended Fourier’s Law (9). The electrical stimulation with the pulsed voltage Ubolo and a specific pulse length t is identical to the experimental implementation. The evaluated electrical resistance changes at different pressure levels from ambient to 103 mbar are shown in the red (-&-) curve of Fig. 4.
3.2. Experimental measurement The experimental measurements are carried out in two steps. At first a single bolometer sensor element that could be contacted directly was examined to verify the FEM simulations. The bolometer resistance is measured direct and analog by standard equipment like a function generator for the pulsed bolometer voltage and an oscilloscope to evaluate the bolometer resistance at these heating phases. In the second step the vacuum measurements were performed with the ROIC and a specific control pattern, optimized for a maximum sensitivity, reading hundreds of bolometers simultaneously. The pressure values are evaluated by the changing image data values representing the bolometer resistances. A test setup shown in Fig. 3 has been developed where the decapsulated IRFPA with removed lid is operating in a vacuum environment with a controllable pressure level and reference pressure gauges based on the Pirani effect and cold cathode gauge. The IRFPA is connected via a vacuum tight through-connection to a control unit which is connected to the PC. As the vacuum measurement is highly temperature dependent a temperature controller (TEC) should be used to achieve comparable and temperature independent results. The results of the single bolometer measurements shown in Fig. 4’s blue (-.-) curve are in great conformity to the simulation results proving the validity of the proposed thermal calculation models. In the second step the vacuum measurements were performed with the ROIC controlling and reading thousands of bolometers simultaneously. The measurement results averaged over all bolometers and 30 frames were shown in the green (--) curve of Fig. 4.
M. Elßner / Microelectronics Reliability 54 (2014) 1758–1763
Fig. 3. Vacuum measurement test setup used for calibration measurements.
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accurate and very fast measurement in the laboratory where the IRFPAs are measured mainly for qualification and process control means. And second the implementation in the infrared camera system where vacuum quality and furthermore the IRFPA’s performance can be evaluated by this measurement. In this way a performance loss, a broken package and defect IRFPA can be detected. Furthermore the sensor outputs can be adjusted according the potential vacuum loss leading to responsivity reduction by using (1) or a calibration measurement were the relationship between the IRFPA’s responsivity and the vacuum measurements results were determined. An appropriated stationary test system consists of an air conditioning system that stabilizes the ambient temperature and a TEC that stabilizes the chip temperature precisely. An additional black body radiator should be used to guarantee constant radiation input through the lid, even though this contribution to the bolometer temperature is quite small. The extended hardware setup shown in Fig. 5 is needed as the main critical influence on the measurement’s accuracy and repeatability is the bolometer’s and IRFPA’s temperature, which has to be controlled and stabilized in order to gain consistent measurements. In contrast to the stationary test environment show in Fig. 5 the implementation in a camera system does most commonly not comprehend any temperature stabilizing countermeasures like TECs. Just the unwanted influence of incoming ambient thermal radiation through the lid can be eliminated by the camera’s shutter. The IRFPA is subjected to ambient or camera internal temperature fluctuations and the IRFPAs self-heating. As shown in Fig. 6’s blue (-.-) curve, huge measurement failures over 100% are occurring by a temperature increase of 10 K. Consequently new temperature controlling counter measures have to be implemented without the help of supporting devices. 3.4. Temperature compensation
Fig. 4. Red: Results of the FEM simulations in relative changes (-&-), blue: single bolometer results (-.-) and green: IRFPA measurements (- -) curve. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
It can be seen that the sensor has high pressure sensitivity in the area of 10+1 mbar to 101 mbar but a decreasing sensitivity at pressures below 101 mbar. The IRFPA measurements were performed with a specific heating pattern that is optimized for achieving a maximum sensitivity in low pressure areas but also resulting in an upper measurement border of 10+1 mbar. Analyzing the measurements results a boundary can be seen at 5 103 mbar where the pressure related resistance changes disappear in noise. Measurements in [20] show that there is a performance loss at pressures higher than 0.1 torr (1.3 101 mbar) and [13] identified performance loss above 102 torr. This correlates with the performed measurements here. At pressures below 5 103 mbar gas conduction is not influencing the bolometer performance any more as the heat loss becomes negligible and consequently cannot be measured any more. This can be proved in calculating the thermal conductivity based on gas conduction with Eqs. (8)–(13). At 5 103 mbar this thermal conduction is two magnitudes smaller than the thermal conductivity by solid heat transfer and thermal radiation.
Ideally the IRFPA is showing the same measurement values independent of the chip temperature. But with fluctuating temperatures the bolometer’s electrical resistance Relect and current Ibolo is changing (17). This can be evaluated by using a control algorithm that tunes the bolometer voltage, which is directly related to the electrical resistance, through the ROIC until a reference current is reached. In most cases this current is not directly measureable until it is instantly converted by an Analog–Digital-Converter (ADC) into digital values to reduce noise. In this case the offset
3.3. Practical implementation The calculation and simulation results show that the measuring principle described here is highly suitable for vacuum evaluations. Two principle applications are targeted. First a stationary high
Fig. 5. Hardware setup for a stationary vacuum measurement system with controlled ambient conditions.
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4. Conclusion The measurement range and sensitivity of the vacuum measuring principle, described in this paper are capable to measure any pressure increase that is leading to performance losses of the IRFPA. The highly accurate vacuum measurements with a mean failure of 0.2% are performed by using a developed temperature compensation algorithm that minimizes temperature related measurement deviations effectively. With this enhancement not only fast stationary measurements in a laboratory environment are possible but also mobile vacuum measurements in infrared camera systems. Based on the technology described here further customer or application specific calculation methods are implementable. For example by tracking the performance loss and vacuum quality a user profile can be generated and the devices lifetime can be calculated in real-time. It is furthermore possible to adjust the infrared camera sensor output with the vacuum evaluations results if degradations are measured. The functionality and validity of the vacuum evaluation method which are described here were successfully proven in use with the IRFPAs manufactured at the Fraunhofer IMS. Fig. 6. Comparison of the relative vacuum measuring failures, blue: without any control algorithm (-N-), red: with a voltage self-compensation (-.-) and green: a combined voltage and temperature compensation (-&-) (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
voltage is controlled to a specific digital output value. Evaluating the relative changes in the bolometer offset voltage after the controlling to a reference or starting value, the temperature dependency of this ratio can be seen. Thus the temperature dependent vacuum sensor error can be calculated and subtracted out by the changing bolometer offset voltage ratio and a specific transfer factor. In an experiment with ten different temperature steps from 295 K to 305 K that are controlled with an accuracy of 0.01 K, the vacuum sensor outputs are measured and the residual relative deviations are shown in Fig. 6. Evaluating the red (-.-) curve in Fig. 6 in contrast to the blue (-N-) one, it can be seen that the algorithm reduces the sensor measuring error effectively. But as this method works fine within small temperature deviations of some several Kelvins it can be seen that the sensor failures increase with rising temperature changes. At a temperature increase of 10 K a residual deviation of nearly 9% is remaining. This is due to non-linearity and complex temperature dependencies of the whole IRFPA chip and the ROIC. An improvement to further sensor error reduction is the integration of a temperature sensor that has to be implemented within the IRFPA design. In case that the temperature sensor values have reasonable deviations over different production lots or devices an initial calibration measurement has to be done, where bolometer offset voltage and temperature sensor values are stored as references in the Pc or respectively in the memory of the camera system. The resulting temperature dependent sensor deviations with the enhanced method are shown in Fig. 6 in the green (-&-) curve. The residual deviations are very small and the sensor measurement results are nearly temperature independent. Thus the critical influence of the temperature can be eliminated very effectively and the vacuum sensor’s repetitive accuracy is greatly improved. In this way the vacuum measurements cannot only be succeeded in the ideal stationary measuring environment as described in Fig. 5 but also in mobile infrared camera systems. Executed repetitive measurements with a total of 20 measurements at each of five different days were carried out, showing a repetitive accuracy of approximately 99.98% with a calculated statistical standard deviation of 0.2% proofing the high viability of this measurement.
Acknowledgements This research was supported by the Fraunhofer Institute for Microelectronic Circuits and Systems (IMS) and the University of Duisburg-Essen. References [1] Weiler D et al. Improvements of a digital 25 lm pixel-pitch uncooled amorphous silicon TEC-less VGA IRFPA with massively parallel Sigma-DeltaADC readout. In: Paper 80121F (proceedings of SPIE 8012) infrared technology and applications XXXVII, 25 April 2011, Orlando, Florida, USA Bellingham. WA: SPIE; 2011. [2] Premachandran CS, Khan N, Xiaowu Z, Chong CS, Chai TC. Design & development of a new thermally stable high vacuum IR bolometer package. In: Proc 53rd Electron Compon Technol Conf 2003. p. 392–6. [3] Premachandran C, Chong S, Chai T, Iyer M. Vacuum packaging development and testing for an uncooled IR bolometer device. In: Proc 54th Electron Compon Technol Conf 2004. p. 951–5. [4] Garcia-Blanco S, LeFoulgoc K, Desroches Y, Caron JS, Topart P, Alain C, et al. Wafer-level hermetic vacuum micro packaging technology for IR detector applications. In: Proc IEEE LEOS Annu Meet Conf 2009. p. 57–8. [5] Wang B, Tanaka S, Guo B, Vereecke G, Severi S, Witvrouw A, et al. Outgassing study of thin films used for poly-SiGe based vacuum packaging of MEMS. Elsevier Ltd; 2011. [6] Jousten K. Thermal outgassing, Physikalisch-Technische Bundesanstalt, Berlin, Germany
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