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Olli-Pekka Kilpi

Publications and source records attributed to Olli-Pekka Kilpi.

4 recordsLinked to original sources

Graphene FET Process and Analysis Optimization in 200 mm Pilot Line Environment

The maturity of the chemical vapor deposition graphene-based device processing has increased from chip level demonstrations to wafer-scale fabrication in the past few years. Due to this wafer-scale, electrical characterization and analysis of the fabricated devices has become increasingly important to enable extraction of multiple parameters with minimal number of measurements for the quality control purposes critical for industrial uptake of 2D materials-based devices. As a crucial step, we demonstrate optimization of complementary metal-oxide semiconductor (CMOS) back-end-of-line (BEOL) compatible graphene field-effect transistor (GFET) fabrication and analysis including the gate stack, bottom contact, graphene patterning and encapsulation process steps. The analysis methods include atomic force microscopy, scanning electron microscopy and most importantly electrical characterization. The electrical characterization focuses on comparing different test structures and extraction methods for mobility, contact resistance, IV-curve hysteresis and doping parameters. The comparison shows that the selected measurement test structures and analysis methods can have a large impact on the extracted values and should thus be considered when comparing data sets between different sources. The analysis shows that the optimized process offers high device yield of 98 % with good doping uniformity, contact resistance and mobility as well as low IV-curve hysteresis values on 200 mm wafers.

cond-mat.mes-hall

Wafer-scale graphene field-effect transistor biosensor arrays with monolithic CMOS readout

The reliability of analysis is becoming increasingly important as point-of-care diagnostics are transitioning from single analyte detection towards multiplexed multianalyte detection. Multianalyte detection benefits greatly from complementary metal-oxide semiconductor (CMOS) integrated sensing solutions, offering miniaturized multiplexed sensing arrays with integrated readout electronics and extremely large sensor counts. The development of CMOS back end of line integration compatible graphene field-effect transistor (GFET) based biosensing has been rapid during the last few years, both in terms of the fabrication scale-up and functionalization towards biorecognition from real sample matrices. The next steps in industrialization relate to improving reliability and require increased statistics. Regarding functionalization towards truly quantitative sensors and on-chip bioassays with improved statistics require sensor arrays with reduced variability in functionalization. Such multiplexed bioassays, whether based on graphene or on other sensitive nanomaterials, are among the most promising technologies for label-free electrical biosensing. As an important step towards that, we report wafer-scale fabrication of CMOS integrated GFET arrays with high yield and uniformity, designed especially for biosensing applications. We demonstrate the operation of the sensing platform array with 512 GFETs in simultaneous detection for sodium chloride concentration series. This platform offers a truly statistical approach on GFET based biosensing and further to quantitative and multi-analyte sensing. The reported techniques can also be applied to other fields relying on functionalized GFETs, such as gas or chemical sensing or infrared imaging.

cond-mat.mes-hall

Characterization of Predictable Quantum Efficient Detector over a wide range of incident optical power and wavelength

We investigate the Predictable Quantum Efficient Detector (PQED) in the visible and near-infrared wavelength range. The PQED consists of two n-type induced junction photodiodes with $Al_2O_3$ entrance window. Measurements are performed at the wavelengths of 488 nm and 785 nm with incident power levels ranging from 100 $μ$W to 1000 $μ$W. A new way of presenting the normalized photocurrents on a logarithmic scale as a function of bias voltage reveals two distinct negative slope regions and allows direct comparison of charge carrier losses at different wavelengths. The comparison indicates mechanisms that can be understood on the basis of different penetration depths at different wavelengths (0.77 $μ$m at 488 nm and 10.2 $μ$m at 785 nm). The difference in the penetration depths leads also to larger difference in the charge-carrier losses at low bias voltages than at high voltages due to the voltage dependence of the depletion region.

physics.optics

Nano-thermoelectric infrared bolometers

Infrared (IR) radiation detectors are used in numerous applications from thermal imaging to spectroscopic gas sensing. Obtaining high speed and sensitivity, low-power operation and cost-effectiveness with a single technology remains to be a challenge in the field of IR sensors. By combining nano-thermoelectric transduction and nanomembrane photonic absorbers, we demonstrate uncooled IR bolometer technology that is material-compatible with large-scale CMOS fabrication and provides fast and high sensitivity response to long-wavelength IR (LWIR) around 10 $μ$m. The fast operation speed stems from the low heat capacity metal layer grid absorber connecting the sub-100 nm-thick n- and p-type Si nano-thermoelectric support beams, which convert the radiation induced temperature rise into voltage. The nano-thermoelectric transducer-support approach benefits from enhanced phonon surface scattering in the beams leading to reduction in thermal conductivity, which enhances the sensitivity. We demonstrate different size nano-thermoelectric bolometric photodetector pixels with LWIR responsitivities, specific detectivities and time constants in the ranges 179-2930 V/W, 0.15-3.1$\cdot10^{8}$ cmHz$^{1/2}$/W and 66-3600 $μ$s, respectively. We benchmark the technology against different LWIR detector solutions and show how nano-thermoelectric detector technology can reach the fundamental sensitivity limits posed by phonon and photon thermal fluctuation noise.

physics.app-ph