2017 ISSCC会议第4节：动态视觉传感器与生物芯片技术综述
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"在2017年的国际固态电路会议（ISSCC2017）上，Session 4重点关注了"Imagers"领域的重要进展。该会议汇集了全球顶尖的科研成果，展示了最新的技术和创新。以下两个主题代表了当天的部分亮点：
1. 题为"4.1A 640×480 Dynamic Vision Sensor with a 9μm Pixel and 300Meps Address-Event Representation"的论文，由三星先进技术研究院的B.Son团队呈现。他们展示了一款动态视觉传感器，其特点是具有9微米像素分辨率，支持高达300百万事件每秒（Meps）的速率。传感器采用增强型逻辑放大器，并利用全合成的字串式组地址事件表示方法对事件进行处理，这提高了数据传输效率和能效。
2. 另一个引人注目的研究是"InPaper 4.2"，由InSilixa公司的A.Hassibi介绍，他们展示了一个完全集成的CMOS荧光生物芯片，专用于多通道聚合酶链反应（PCR）过程。这款生物芯片系统采用了0.25微米标准CMOS工艺，具备116分贝的检测动态范围。芯片内部集成了32×32个基于荧光的生物传感器像素阵列，具备在芯片上实现±4°C每秒的热/冷循环能力，以及集成的多介电发射滤镜，有效光学密度（OD）达到3.6，且结合了固定在芯片上的DNA捕捉机制，这使得该系统在生物医学检测领域具有很高的应用潜力。
这些研究不仅体现了固态电路技术在图像传感器和生物医疗检测方面的前沿突破，也预示着未来在微型化、高效率和多功能集成方面的趋势。参会者和行业专家通过这些研究成果，可以深入理解并探讨如何将这些技术应用于诸如自动驾驶、无人机监控、生命科学实验等实际应用场景中，推动科技的不断发展和创新。"
68 • 2017 IEEE International Solid-State Circuits Conference
ISSCC 2017 / SESSION 4 / IMAGERS / 4.2
4.2 A Fully Integrated CMOS Fluorescence Biochip for
Multiplex Polymerase Chain-Reaction (PCR)
Processes
Arjang Hassibi, Rituraj Singh, Arun Manickam, Ruma Sinha,
Bob Kuimelis, Sara Bolouki, Pejman Naraghi-Arani, Kirsten Johnson,
Mark McDermott, Nicholas Wood, Piyush Savalia, Nader Gamini
InSilixa, Sunnyvale, CA
Integration and miniaturization of bio-molecular detection systems into electronic
biosensors and lab-on-chip platforms is of great importance. One widely
recognized application area for such devices is nucleic acid (DNA and RNA)
detection, specifically, nucleic acid amplification testing (NAAT), which relies on
enzymatic processes such as polymerase chain reaction (PCR) to increase the
copy number of target sequences and detecting them spectroscopically [1,2].
Here, we present a fully integrated CMOS DNA biosensor array (biochip) for
clinical NAAT capable of performing multiplex (parallel) PCR in one ~40µL reaction
chamber using on-chip thermo-cycling (±4°C sec
-1
heat/cool rate), real-time
amplicon-probe hybridization detection (up to target 1000 unique sequences),
and solid-phase (surface) melt-curve analysis from 40 to 90°C with 0.3°C
resolution. The detection modality is continuous-wave fluorescence with an
effective pass-band to stop-band optical density (OD) of ~3.6 using an inverse
fluorophore assay [3] that requires no labeling, or sandwich probes [4] in the
reaction mix. Unlike electro-analytical biochips [5], the transducer surface as well
as surface chemistries of this system, are chemically and thermally stable and do
not degrade during PCR thermo-cycling.
In Fig. 4.2.1, the biochip module and its 32×32 biosensing pixels is illustrated.
The 7×9mm
2
die is packaged on a thermally conductive PCB substrate. A flow-
through and optically transparent fluidic cap is mounted on it such that its sensing
surface is exposed to the reaction (PCR) chamber and accessible only through
the fluidic inlet and outlet. Each 100×100µm
2
biosensor (pixel) includes a CMOS-
integrated photo-sensor and a resistive heater. Each pixel is further augmented
by a multi-dielectric interference filter (fabricated post-CMOS) and fluorogenic
DNA capture probes covalently attached to its SiO
2
surface using a silanization
process. An external LED source is utilized to excite the fluorophore conjugated
to the capture probes.
The biosensing pixel block diagram and the chip architecture are shown in Fig.
4.2.2. The LED excitation flux, F
X
, passes through the transparent fluidic cap and
excites the fluorogenic probes to emit photon flux F
E
, at longer wavelengths
(typically >20nm). Both F
X
and F
E
hit the emission filter, which is specifically
designed to preferentially block F
X
and allow F
E
to pass. It is important to note
that while α, the attenuation level of F
X
, is high (e.g., α > 10
3
), in practical
fluorescence assays, F
E
< F
X
/α, which requires the high-dynamic range photo-
sensor to detect small signals in presence of a large background.
To address this impediment, we take advantage of a unipolar ΔΣ photo-sensor
circuit in each pixel to maximize the effective well-capacity without compromising
the noise performance. As shown in Fig. 4.2.2, the photocurrent, I
PH
, generated
by the in-pixel nwell-psub photodiode, is first integrated by a CTIA (Σ operation).
Subsequently, the CTIA output is compared to a fixed reference voltage by a
clocked comparator (quantizer) and its output, D
OUT
, triggers the subtraction of
the appropriate charge (ΔQ
1
or ΔQ
2
) from the CTIA (Δ operation).
All 1024 individual pixels, including 13 temperature-sensor pixels that have
covered photodiodes, can individually be addressed. By using row and column
decoders, the digital (D
OUT
(i,j)) and analog (A
OUT
(i,j)) outputs are brought off-chip
using serialized LVDS buffer and multiplexed analog column amplifiers,
respectively. The chip includes a passive 10W multi-finger resistive heater
integrated using the top metal layer with traces in every pixel.
Figure 4.2.3 shows the detailed pixel circuitry and the timing diagram of the charge
subtraction (Δ operation) based on D
OUT
. The oversampling clock,
CLK
ΣΔ
= 100kHz, triggers the comparator and the generated D
OUT
chooses between
two 100kHz clocks, CLK
1
and CLK
2
, with different duty cycles to divert I
REF
= 1µA
into the CTIA input. The pulse durations are programmable between 10 to 100ns
in every 10µs, corresponding to 1-to-10nA continuous current subtraction, which
accommodates tunable charge subtraction for both low and high-gain modes.
The optical performance of the pixels without the emission filter is shown in Fig.
4.2.4. The maximum external QE is ~42% at 650nm and the measured detection
dynamic range >10
5
. The SNR in high-gain mode is ~1dB below shot-noise limit
for I
PH
> 15fA and limited by quantization noise below that level. As evident, the
pixel dark current, I
D
can become significant when measuring at assay
temperatures >70°C. To mitigate this, we use correlated double sampling at each
temperature, subtracting two measurements, one with the LED on and one with
the LED off.
The SEM cross-section of the pixel with emission filter is shown in Fig. 4.2.5. This
filter is a long-pass multi-dielectric (TiO
2
and SiO
2
) interference filter designed
and fabricated at wafer level with a cut-off wavelength of 585nm. Like all
interference filters, the transmittance is a function of angle of incidence (AOI) and
shifts to lower wavelength at higher AOIs. This characteristic significantly
diminishes α for F
X
in high-scattering aqueous media of biosensors and lab-on-
chip. To address this challenge, we specifically optimized the layer thicknesses
to have minimal shift vs. AOI and took advantage of a dual-fluorophore structure
to increase the fluorescence Stokes shift. In this structure, two fluorophores,
namely fluorescein (FAM) and tetramethylrhodamine (TAM), are conjugated in
close proximity to each other on the end of DNA probe. The excitation of FAM at
490nm can therefore result in the fluorescence resonance energy transfer to TAM
due to the FAM-TAM emission-absorption spectral overlap and produce emission
at 580nm, enhancing the Stokes shift to >90nm. As shown in the Fig. 4.2.5, the
use of FAM-TAM in addition to optimizing the filter, ensures minimal F
X
leakage
at AOI < 50° and effective OD remains around 3.6.
In Fig. 4.2.6, an example usage of this biochip, enabling a respiratory infection
panel NAAT, is shown. A 7-plex PCR in the reaction chamber simultaneously
amplifies unique sequences of the 7 viruses listed (FluA, FluB, etc.) using on-chip
thermal cycling. All 14 PCR primers include a quencher molecule. On successful
PCR amplification, if the targets are present in the chamber, amplicons with
quenchers are generated. Such amplicons, are then captured by the matching
DNA probes, and modulate (reduce) the FAM-TAM signal at the corresponding
pixel (i.e., inverse fluorescence method). The measured results demonstrate that,
by using this method and the biochip, we can identify the presence of these
viruses in the sample by measuring the fluorescence signal at the pixels and
further validate the result by analyzing the DNA-amplicon melt-curve.
References:
[1] C. Zhang and D. Xing, “Miniaturized PCR Chips for Nucleic Acid Amplification
and Analysis: Latest Advances and Future Trends”, Nucleic Acids Res., vol. 35,
no. 13, 2007.
[2] A. Hassibi, “CMOS Biochips for Point-of-care Molecular Diagnostics”, Hot
Chips, 2014.
[3] A. Hassibi, et al., “Real-time DNA Microarray Analysis”, Nucleic Acids Res.,
vol. 37, no. 20, 2009.
[4] H. Wang, et al., “A Frequency-shift CMOS Magnetic Biosensor Array with
Single-bead Sensitivity and No External Magnet”, ISSCC, pp. 438-439, Feb. 2009.
[5] P.M. Levine, et al., “Active CMOS Sensor Array for Electrochemical
Biomolecular Detection”, IEEE JSSC, vol. 43, no. 8, 2008.
978-1-5090-3758-2/17/$31.00 ©2017 IEEE
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