Engineering 1/f noise in porous silicon thin films for thermal sensing applications

Sharma, Prakash Chandra; Dell, John; Parish, Giacinta; Keating, Adrian

doi:10.1016/j.micromeso.2021.111302

Cited by 14 publications

(5 citation statements)

References 19 publications

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“…As a result of the measured data, by performing the PMA process under the condition of D 2 forming gas, at 10 atm and 300 • C for 30 min, it is observed that the resistance decreased by about 60% compared to the reference microbolometer, and the TCR values increased up to 48.2%. Therefore, the fabricated a-Si microbolometers treated by the PMA process show TCR values of 2.4~3.5%/K and 1/f noise levels of around 10 −11 /Hz, which are comparable to those of the previously reported literatures [27][28][29]. Moreover, it is confirmed that the noise characteristics are improved in inverse proportion to the patten width of resistance layer.…”

Section: Electrical Characteristics Of the A-si Microbolometers After The Pma Processsupporting

confidence: 84%

“…Therefore, it is necessary to reduce the aforementioned noises of the a-Si based microbolometers to realize the high-resolution thermal image with high quality [26]. In this respect, P. Sharma et al recently reported TCR values of 6-7%/K along with 1/f noise constant of 10 −12 in a porous Si-thin film with an optimized porosity of 60-75%, by passivating the surface at 600 • C to stabilize the film against atmospheric oxidation [27]. Moreover, there were reports on the results of comparing TCR values and 1/f noise characteristics according to the crystal structure of boron-doped hydrogenated mixed-phase silicon films for the IR device application [28,29].…”

Section: Introductionmentioning

confidence: 99%

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Noise Improvement of a-Si Microbolometers by the Post-Metal Annealing Process

Song

Park

et al. 2021

Sensors

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To realize high-resolution thermal images with high quality, it is essential to improve the noise characteristics of the widely adopted uncooled microbolometers. In this work, we applied the post-metal annealing (PMA) process under the condition of deuterium forming gas, at 10 atm and 300 °C for 30 min, to reduce the noise level of amorphous-Si microbolometers. Here, the DC and temperature coefficient of resistance (TCR) measurements of the devices as well as 1/f noise analysis were performed before and after the PMA treatment, while changing the width of the resistance layer of the microbolometers with 35 μm or 12 μm pixel. As a result, the microbolometers treated by the PMA process show the decrease in resistance by about 60% and the increase in TCR value up to 48.2% at 10 Hz, as compared to the reference device. Moreover, it is observed that the noise characteristics are improved in inverse proportion to the width of the resistance layer. This improvement is attributed to the cured poly-silicon grain boundary through the hydrogen passivation by heat and deuterium atoms applied during the PMA, which leads to the uniform current path inside the pixel.

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Section: Electrical Characteristics Of the A-si Microbolometers After The Pma Processsupporting

confidence: 84%

Section: Introductionmentioning

confidence: 99%

Noise Improvement of a-Si Microbolometers by the Post-Metal Annealing Process

Song

Park

et al. 2021

Sensors

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“…Porous metals have many applications in daily life and industry, such as filtration, sound absorber [1,2], thermal energy storage [3], electrochemical isolation equipment or biomedical materials [4]. Meanwhile, powder metallurgy techniques are the preferred method of manufacturing porous metals [5].…”

Section: Related Workmentioning

confidence: 99%

ARIMA-FEM Method with Prediction Function to Solve the Stress–Strain of Perforated Elastic Metal Plates

Chen

Dai

Zheng

2022

Metals

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Stress analysis and deformation prediction have always been the focuses of the field of mechanics. The accurate force prediction in plate deformation plays important role in the production, processing and performance analysis of materials. In this paper, we propose an ARIMA-FEM method, which can be used to solve some mechanical problems of 2D porous elastic plate. We have given a detailed theory and solving steps of ARIMA-FEM. In addition, three numerical examples are given to predict the stress–strain of thin porous elastic metal plates. This article uses CST, LST and Q4 elements to discrete the rectangular plates, square plates and circle plates with holes. As for variable force prediction, this paper compared with linear regression, nonlinear regression and neural network prediction, and the results show that the ARIMA method has a higher prediction accuracy. Furthermore, we calculate the numerical solution at four mesh scales, and the numerical convergence is consistent with the theoretical convergence, which also shows the effectiveness of our method. The image smoothing algorithm is applied to keep edge information with high resolution, which can more concisely describe the plate internal changes. Finally, the application scope of ARIMA-FEM, model expansion, superconvergence analysis and other issues have been given enlightening views in the discussion section. In fact, this algorithm combined statistics and mechanics. It also reflects the knowledge integration of interdisciplinary and uses it better to serve practical applications.

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“…As for the thermal properties of nanoporous silicon, the most interesting application concerns thermoresistive sensors. Recently, it has been established that porous silicon, in contrast to the bulk material, can solve the problem of the thermal incompatibility of materials, which is met in thermal sensors [ 15 , 16 ]. It becomes possible to tune the desired physical properties of sensors using only porous silicon.…”

Section: Introductionmentioning

confidence: 99%

Thermal Properties of Porous Silicon Nanomaterials

Федоров

Teplinskaia

2022

Materials

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The thermal properties, including the heat capacity, thermal conductivity, effusivity, diffusivity, and phonon density of states of silicon-based nanomaterials are analyzed using a molecular dynamics calculation. These quantities are calculated in more detail for bulk silicon, porous silicon, and a silicon aerocrystal (aerogel), including the passivation of the porous internal surfaces with hydrogen, hydroxide, and oxygen ions. It is found that the heat capacity of these materials increases monotonically by up to 30% with an increase in the area of the porous inner surface and upon its passivation with these ions. This phenomenon is explained by a shift of the phonon density of states of the materials under study to the low-frequency region. In addition, it is shown that the thermal conductivity of the investigated materials depends on the degree of their porosity and can be changed significantly upon the passivation of their inner surface with different ions. It is demonstrated that, in the various simulated types of porous silicon, the thermal conductivity changes by 1–2 orders of magnitude compared with the value for bulk silicon. At the same time, it is found that the nature of the passivation of the internal nanosilicon surfaces affects the thermal conductivity. For example, the passivation of the surfaces with hydrogen does not significantly change this parameter, whereas a passivation with oxygen ions reduces it by a factor of two on average, and passivation with hydroxyl ions increases the thermal conductivity by a factor of 2–3. Similar trends are observed for the thermal effusivities and diffusivities of all the types of nanoporous silicon under passivation, but, in that case, the changes are weaker (by a factor of 1.5–2). The ways of tuning the thermal properties of the new nanostructured materials are outlined, which is important for their application.

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Engineering 1/f noise in porous silicon thin films for thermal sensing applications

Cited by 14 publications

References 19 publications

Noise Improvement of a-Si Microbolometers by the Post-Metal Annealing Process

Noise Improvement of a-Si Microbolometers by the Post-Metal Annealing Process

ARIMA-FEM Method with Prediction Function to Solve the Stress–Strain of Perforated Elastic Metal Plates

Thermal Properties of Porous Silicon Nanomaterials

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