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R.A. Norte
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15 records found
1
Master thesis
(2026)
-
A. Noschese, G.J. Verbiest, R.H. Guis, R.A. Norte, L. Norder, Silvana Pereira
The continued scaling of integrated circuits has driven overlay tolerances in semiconductor lithography to the single-nanometre level. Conventional optical overlay metrology, however, becomes unreliable when the layers above the target structure are optically opaque, as is increasingly the case in advanced back-end-of-line stacks. This thesis investigates the use of photonic crystals (PtCs) as optical transducers in a pump–probe photoacoustic measurement scheme, with the long-term objective of enabling overlay sensing through optically opaque substrates.
The working principle relies on the steep reflectance resonance of a PtC fabricated on the metallic surface layer: an acoustic wave generated by the absorption of a femtosecond pump pulse deforms the crystal lattice, shifting the resonance and producing a large change in probe reflectance. A square lattice PtC with circular holes milled into an aluminum film on a silicon substrate is used throughout.
The thesis makes three main contributions. First, a simulation framework based on the Stanford Stratified Structure Solver (S4) is extended to incorporate the realistic illumination conditions of both experimental setups used in this work: the angular spread and Gaussian weighting of the focused probe beam, and the fiber-tip geometry of the reflectance spectroscopy setup. Second, photonic crystal structures are fabricated by focused-ion-beam milling and electron-beam lithography on aluminum films, and their geometry is verified by atomic force microscopy. Third, the fabricated structures are characterized on a pump–probe photoacoustic setup and on a broadband reflectance spectroscopy setup.
The experimental results confirm that the photonic crystal enhances the photoacoustic signal amplitude by approximately 282% relative to a plain aluminum film, corresponding to a reduction in measurement averaging time by a factor of approximately 14. The FFT spectra of the photoacoustic signal exhibit two peaks whose frequencies are governed by the lattice period and are consistent with substrate-dominated surface acoustic waves propagating at the Rayleigh velocity of silicon (v ≈ 4900 ms−1), in close analogy with the phononic crystal framework established in prior literature. The reflectance spectra show geometry-dependent resonance features that shift horizontally with the lattice period and vertically with the hole radius, in qualitative agreement with the S4 simulations. Incorporating the angular averaging model into the simulations significantly improves the agreement with the measured spectra, confirming the importance of accounting for realistic illumination conditions in any future geometry optimization. ...
The working principle relies on the steep reflectance resonance of a PtC fabricated on the metallic surface layer: an acoustic wave generated by the absorption of a femtosecond pump pulse deforms the crystal lattice, shifting the resonance and producing a large change in probe reflectance. A square lattice PtC with circular holes milled into an aluminum film on a silicon substrate is used throughout.
The thesis makes three main contributions. First, a simulation framework based on the Stanford Stratified Structure Solver (S4) is extended to incorporate the realistic illumination conditions of both experimental setups used in this work: the angular spread and Gaussian weighting of the focused probe beam, and the fiber-tip geometry of the reflectance spectroscopy setup. Second, photonic crystal structures are fabricated by focused-ion-beam milling and electron-beam lithography on aluminum films, and their geometry is verified by atomic force microscopy. Third, the fabricated structures are characterized on a pump–probe photoacoustic setup and on a broadband reflectance spectroscopy setup.
The experimental results confirm that the photonic crystal enhances the photoacoustic signal amplitude by approximately 282% relative to a plain aluminum film, corresponding to a reduction in measurement averaging time by a factor of approximately 14. The FFT spectra of the photoacoustic signal exhibit two peaks whose frequencies are governed by the lattice period and are consistent with substrate-dominated surface acoustic waves propagating at the Rayleigh velocity of silicon (v ≈ 4900 ms−1), in close analogy with the phononic crystal framework established in prior literature. The reflectance spectra show geometry-dependent resonance features that shift horizontally with the lattice period and vertically with the hole radius, in qualitative agreement with the S4 simulations. Incorporating the angular averaging model into the simulations significantly improves the agreement with the measured spectra, confirming the importance of accounting for realistic illumination conditions in any future geometry optimization. ...
The continued scaling of integrated circuits has driven overlay tolerances in semiconductor lithography to the single-nanometre level. Conventional optical overlay metrology, however, becomes unreliable when the layers above the target structure are optically opaque, as is increasingly the case in advanced back-end-of-line stacks. This thesis investigates the use of photonic crystals (PtCs) as optical transducers in a pump–probe photoacoustic measurement scheme, with the long-term objective of enabling overlay sensing through optically opaque substrates.
The working principle relies on the steep reflectance resonance of a PtC fabricated on the metallic surface layer: an acoustic wave generated by the absorption of a femtosecond pump pulse deforms the crystal lattice, shifting the resonance and producing a large change in probe reflectance. A square lattice PtC with circular holes milled into an aluminum film on a silicon substrate is used throughout.
The thesis makes three main contributions. First, a simulation framework based on the Stanford Stratified Structure Solver (S4) is extended to incorporate the realistic illumination conditions of both experimental setups used in this work: the angular spread and Gaussian weighting of the focused probe beam, and the fiber-tip geometry of the reflectance spectroscopy setup. Second, photonic crystal structures are fabricated by focused-ion-beam milling and electron-beam lithography on aluminum films, and their geometry is verified by atomic force microscopy. Third, the fabricated structures are characterized on a pump–probe photoacoustic setup and on a broadband reflectance spectroscopy setup.
The experimental results confirm that the photonic crystal enhances the photoacoustic signal amplitude by approximately 282% relative to a plain aluminum film, corresponding to a reduction in measurement averaging time by a factor of approximately 14. The FFT spectra of the photoacoustic signal exhibit two peaks whose frequencies are governed by the lattice period and are consistent with substrate-dominated surface acoustic waves propagating at the Rayleigh velocity of silicon (v ≈ 4900 ms−1), in close analogy with the phononic crystal framework established in prior literature. The reflectance spectra show geometry-dependent resonance features that shift horizontally with the lattice period and vertically with the hole radius, in qualitative agreement with the S4 simulations. Incorporating the angular averaging model into the simulations significantly improves the agreement with the measured spectra, confirming the importance of accounting for realistic illumination conditions in any future geometry optimization.
The working principle relies on the steep reflectance resonance of a PtC fabricated on the metallic surface layer: an acoustic wave generated by the absorption of a femtosecond pump pulse deforms the crystal lattice, shifting the resonance and producing a large change in probe reflectance. A square lattice PtC with circular holes milled into an aluminum film on a silicon substrate is used throughout.
The thesis makes three main contributions. First, a simulation framework based on the Stanford Stratified Structure Solver (S4) is extended to incorporate the realistic illumination conditions of both experimental setups used in this work: the angular spread and Gaussian weighting of the focused probe beam, and the fiber-tip geometry of the reflectance spectroscopy setup. Second, photonic crystal structures are fabricated by focused-ion-beam milling and electron-beam lithography on aluminum films, and their geometry is verified by atomic force microscopy. Third, the fabricated structures are characterized on a pump–probe photoacoustic setup and on a broadband reflectance spectroscopy setup.
The experimental results confirm that the photonic crystal enhances the photoacoustic signal amplitude by approximately 282% relative to a plain aluminum film, corresponding to a reduction in measurement averaging time by a factor of approximately 14. The FFT spectra of the photoacoustic signal exhibit two peaks whose frequencies are governed by the lattice period and are consistent with substrate-dominated surface acoustic waves propagating at the Rayleigh velocity of silicon (v ≈ 4900 ms−1), in close analogy with the phononic crystal framework established in prior literature. The reflectance spectra show geometry-dependent resonance features that shift horizontally with the lattice period and vertically with the hole radius, in qualitative agreement with the S4 simulations. Incorporating the angular averaging model into the simulations significantly improves the agreement with the measured spectra, confirming the importance of accounting for realistic illumination conditions in any future geometry optimization.
Training state-of-the-art AI models is growing far more costly than digital hardware can sustain, motivating analog photonic substrates that perform matrix multiplication directly in the propagation of light. Inference on such hardware is established, but training is not: backpropagation requires a backward pass and exact gradients that an analog chip cannot natively provide. Forward-only, backpropagation-free learning offers a way around this, yet it has been demonstrated only for multilayer perceptrons and convolutional networks, never for the Transformer, the architecture that now dominates AI and whose self-attention couples every position across the sequence, resisting purely local objectives.
This thesis asks whether a Transformer can be trained using only the forward-pass operations a photonic substrate provides, and characterizes what such training costs. The proposed method combines a layer-wise Forward-Forward prototype-based objective, directional-derivative gradient estimation (with no backward pass and no automatic differentiation), and a softmax-free Spherical attention adapted from the Kramers-Kronig kernel, with the four attention projections trained one at a time in a round-robin schedule; six training variants are compared across seven vision and sequence tasks to isolate the gradient estimator and the update schedule. The answer is affirmative: the fully forward-only variant trains a Transformer to a useful operating point on six of the seven tasks. Locality, not the forward-only gradient alone, is what makes this possible, and the depth-resilience of local learning is shown to extend, conditionally, to self-attention. The remaining gap to backpropagation has three sources, two inherent to forward-only learning (local credit assignment and gradient-estimation variance) and one architectural (the softmax-free attention cannot form the sharp selection that content-addressed retrieval requires). Because every operation reduces to a forward pass and a measured scalar loss, the method is a candidate for in-situ training on a photonic chip, the validation step this work points to. ...
This thesis asks whether a Transformer can be trained using only the forward-pass operations a photonic substrate provides, and characterizes what such training costs. The proposed method combines a layer-wise Forward-Forward prototype-based objective, directional-derivative gradient estimation (with no backward pass and no automatic differentiation), and a softmax-free Spherical attention adapted from the Kramers-Kronig kernel, with the four attention projections trained one at a time in a round-robin schedule; six training variants are compared across seven vision and sequence tasks to isolate the gradient estimator and the update schedule. The answer is affirmative: the fully forward-only variant trains a Transformer to a useful operating point on six of the seven tasks. Locality, not the forward-only gradient alone, is what makes this possible, and the depth-resilience of local learning is shown to extend, conditionally, to self-attention. The remaining gap to backpropagation has three sources, two inherent to forward-only learning (local credit assignment and gradient-estimation variance) and one architectural (the softmax-free attention cannot form the sharp selection that content-addressed retrieval requires). Because every operation reduces to a forward pass and a measured scalar loss, the method is a candidate for in-situ training on a photonic chip, the validation step this work points to. ...
Training state-of-the-art AI models is growing far more costly than digital hardware can sustain, motivating analog photonic substrates that perform matrix multiplication directly in the propagation of light. Inference on such hardware is established, but training is not: backpropagation requires a backward pass and exact gradients that an analog chip cannot natively provide. Forward-only, backpropagation-free learning offers a way around this, yet it has been demonstrated only for multilayer perceptrons and convolutional networks, never for the Transformer, the architecture that now dominates AI and whose self-attention couples every position across the sequence, resisting purely local objectives.
This thesis asks whether a Transformer can be trained using only the forward-pass operations a photonic substrate provides, and characterizes what such training costs. The proposed method combines a layer-wise Forward-Forward prototype-based objective, directional-derivative gradient estimation (with no backward pass and no automatic differentiation), and a softmax-free Spherical attention adapted from the Kramers-Kronig kernel, with the four attention projections trained one at a time in a round-robin schedule; six training variants are compared across seven vision and sequence tasks to isolate the gradient estimator and the update schedule. The answer is affirmative: the fully forward-only variant trains a Transformer to a useful operating point on six of the seven tasks. Locality, not the forward-only gradient alone, is what makes this possible, and the depth-resilience of local learning is shown to extend, conditionally, to self-attention. The remaining gap to backpropagation has three sources, two inherent to forward-only learning (local credit assignment and gradient-estimation variance) and one architectural (the softmax-free attention cannot form the sharp selection that content-addressed retrieval requires). Because every operation reduces to a forward pass and a measured scalar loss, the method is a candidate for in-situ training on a photonic chip, the validation step this work points to.
This thesis asks whether a Transformer can be trained using only the forward-pass operations a photonic substrate provides, and characterizes what such training costs. The proposed method combines a layer-wise Forward-Forward prototype-based objective, directional-derivative gradient estimation (with no backward pass and no automatic differentiation), and a softmax-free Spherical attention adapted from the Kramers-Kronig kernel, with the four attention projections trained one at a time in a round-robin schedule; six training variants are compared across seven vision and sequence tasks to isolate the gradient estimator and the update schedule. The answer is affirmative: the fully forward-only variant trains a Transformer to a useful operating point on six of the seven tasks. Locality, not the forward-only gradient alone, is what makes this possible, and the depth-resilience of local learning is shown to extend, conditionally, to self-attention. The remaining gap to backpropagation has three sources, two inherent to forward-only learning (local credit assignment and gradient-estimation variance) and one architectural (the softmax-free attention cannot form the sharp selection that content-addressed retrieval requires). Because every operation reduces to a forward pass and a measured scalar loss, the method is a candidate for in-situ training on a photonic chip, the validation step this work points to.
From levitating living organisms to developing high-Q resonators, diamagnetic levitation has become a powerful technique to mechanically isolate objects. Its ability to work at room temperature without power consumption and simple setups has found many applications in precision measurements, including accelerometers, MEMS devices, mass sensors, and motion stages. By using the strong diamagnetic properties of materials like pyrolytic graphite, both micro- and macro-scale objects can be stably levitated. This allows for systems that reduce mechanical losses and provide high isolation. Therefore, diamagnetic levitation is ideal for creating ultra-low dissipation mechanical systems with high quality factors (Q-factor). However, a key challenge remains, the damping caused by eddy currents that occur due to motion through a changing magnetic fields. These currents dissipate energy and limit the performance of these levitated systems by lowering their Q-factor.
This thesis explores the optimization of pyrolytic graphite-based composite resonators to enhance the Q-factor. By combining finite element method (FEM) simulations with Multi-Objective Particle Swarm Optimization (MOPSO), we investigate how plate geometry and segmentation can suppress eddy currents and reduce damping. Composite plates with insulating epoxy are fabricated and levitated over a 2x2 array of NdFeB permanent magnets. Experimental validations demonstrate a significant increase in Q-factor, particularly when combining segmentation and optimised shape, reaching values up to 420,000. This work contributes to the advancement of high-Q levitating resonators and highlights the importance of geometry and materials in achieving ultra-low dissipation. ...
From levitating living organisms to developing high-Q resonators, diamagnetic levitation has become a powerful technique to mechanically isolate objects. Its ability to work at room temperature without power consumption and simple setups has found many applications in precision measurements, including accelerometers, MEMS devices, mass sensors, and motion stages. By using the strong diamagnetic properties of materials like pyrolytic graphite, both micro- and macro-scale objects can be stably levitated. This allows for systems that reduce mechanical losses and provide high isolation. Therefore, diamagnetic levitation is ideal for creating ultra-low dissipation mechanical systems with high quality factors (Q-factor). However, a key challenge remains, the damping caused by eddy currents that occur due to motion through a changing magnetic fields. These currents dissipate energy and limit the performance of these levitated systems by lowering their Q-factor.
This thesis explores the optimization of pyrolytic graphite-based composite resonators to enhance the Q-factor. By combining finite element method (FEM) simulations with Multi-Objective Particle Swarm Optimization (MOPSO), we investigate how plate geometry and segmentation can suppress eddy currents and reduce damping. Composite plates with insulating epoxy are fabricated and levitated over a 2x2 array of NdFeB permanent magnets. Experimental validations demonstrate a significant increase in Q-factor, particularly when combining segmentation and optimised shape, reaching values up to 420,000. This work contributes to the advancement of high-Q levitating resonators and highlights the importance of geometry and materials in achieving ultra-low dissipation.
Micro- and nanoelectromechanical (MEM/NEM) resonators are used in numerous fields of engineering and are crucial for time keeping, synchronization, and sensing applications. These systems are subjected to energy dissipation, which is a limiting factor in the performance. Extensive understanding is essential when nonlinearities show up in both stiffness and dissipation, to design appropriately. Focusing on dissipative mechanisms, this paper explores the vibrational behavior of a suspended clamped-clamped beam fabricated from silicon-nitride in the nonlinear regime. This study reveals a notorious decay in ringdown, when the resonator is decoupled from its vibrational power. A sustained amplitude is observed for up to 8 seconds. Though the exact source of this anomaly remains elusive, it is suggested that it might include modal coupling and/or optomechanical effects
...
Micro- and nanoelectromechanical (MEM/NEM) resonators are used in numerous fields of engineering and are crucial for time keeping, synchronization, and sensing applications. These systems are subjected to energy dissipation, which is a limiting factor in the performance. Extensive understanding is essential when nonlinearities show up in both stiffness and dissipation, to design appropriately. Focusing on dissipative mechanisms, this paper explores the vibrational behavior of a suspended clamped-clamped beam fabricated from silicon-nitride in the nonlinear regime. This study reveals a notorious decay in ringdown, when the resonator is decoupled from its vibrational power. A sustained amplitude is observed for up to 8 seconds. Though the exact source of this anomaly remains elusive, it is suggested that it might include modal coupling and/or optomechanical effects
Master thesis
(2023)
-
A. PRABHAKHARAN, P.G. Steeneken, R.A. Norte, Richard Pleeging, Joost van Beek, Gerard Rietjens
Hermeticity is a measure of how well a package is leak-tight. Many Micro-Electro-Mechanical Systems (MEMS) sensors, actuators, and microelectronic devices need a defined cavity environment for optimal performance, hence measuring the package leak rate is critical for lifetime prediction. MEMS devices are generally packaged through the wafer-bonding technique. The MEMS device is produced on a wafer with a cavity and bonded to a cap wafer to seal the hole. Reducing the cap wafer thickness allows it to deflect due to the cavity interior-exterior pressure differential. Consequently, if leakage occurs, the deflection will
change. By measuring these deflections, it is possible to quantify leak rates.
In order to use it as an in-line testing process, this research aims to determine the accuracy of the deflection method for determining the leak rates. To achieve this, our approach involved designing and leak testing test structures (or devices) using an experimental setup that can vary pressure, supply desired species
inside a vacuum chamber, and measure deflection using an interferometer to determine leak rates. Deflections are converted to leak rates using a formulated analytical expression, subsequently utilized to determine the error involved in measuring leak rates.
Using the experimental setup, the test devices were effectively characterized for sensitivity using pressure-induced deflection measurements, with experimental sensitivity values closely matching the theory. Further, air leak testing was performed on devices interconnected with nanometer-gap size leak channels to
gain first-hand knowledge of leakage. Experimental leak rates matched well with analytical models, proving that flow through devices having leak channels can be characterized. Ultimately, the setup enabled successful helium leak testing of devices without any defined leak channels.
The helium leak-tested samples were circular membranes of diameters: 2000, 1600, 1400, 1300, and 1100 μm with a thickness of 40 μm bonded to a cavity depth of 3.24 μm. Uncertainty analysis associated with leak rate measurement revealed that when considering a certain cavity depth and membrane thickness,
the membrane with the largest diameter would exhibit the least amount of uncertainty. This was also observed through experiments, for the diameter of 2000 μm, a clear linear trend of deflection reduction due to the helium leakage was observed during a two-week period of deflection measurements. Whereas, for the diameter of 1100 μm, it was not possible to observe the same linear trend of deflection reduction, indicating that even more no.of.days is required to determine an accurate leak rate.
In the end, a short analysis was made using the cavity design having the 2000 μm membrane, which had the least uncertainty in measuring the leak rate. This analysis aimed to ascertain the designed test structure’s usefulness in measuring leak rates of the MEMS packages. Based on the analysis, it was concluded that large-volume wafer-bonded MEMS packages (> 1 mm3) with an acceptable cavity pressure increase of 10 mbar could be tested using the deflection method and our proposed test structure design to guarantee their lifetime. ...
change. By measuring these deflections, it is possible to quantify leak rates.
In order to use it as an in-line testing process, this research aims to determine the accuracy of the deflection method for determining the leak rates. To achieve this, our approach involved designing and leak testing test structures (or devices) using an experimental setup that can vary pressure, supply desired species
inside a vacuum chamber, and measure deflection using an interferometer to determine leak rates. Deflections are converted to leak rates using a formulated analytical expression, subsequently utilized to determine the error involved in measuring leak rates.
Using the experimental setup, the test devices were effectively characterized for sensitivity using pressure-induced deflection measurements, with experimental sensitivity values closely matching the theory. Further, air leak testing was performed on devices interconnected with nanometer-gap size leak channels to
gain first-hand knowledge of leakage. Experimental leak rates matched well with analytical models, proving that flow through devices having leak channels can be characterized. Ultimately, the setup enabled successful helium leak testing of devices without any defined leak channels.
The helium leak-tested samples were circular membranes of diameters: 2000, 1600, 1400, 1300, and 1100 μm with a thickness of 40 μm bonded to a cavity depth of 3.24 μm. Uncertainty analysis associated with leak rate measurement revealed that when considering a certain cavity depth and membrane thickness,
the membrane with the largest diameter would exhibit the least amount of uncertainty. This was also observed through experiments, for the diameter of 2000 μm, a clear linear trend of deflection reduction due to the helium leakage was observed during a two-week period of deflection measurements. Whereas, for the diameter of 1100 μm, it was not possible to observe the same linear trend of deflection reduction, indicating that even more no.of.days is required to determine an accurate leak rate.
In the end, a short analysis was made using the cavity design having the 2000 μm membrane, which had the least uncertainty in measuring the leak rate. This analysis aimed to ascertain the designed test structure’s usefulness in measuring leak rates of the MEMS packages. Based on the analysis, it was concluded that large-volume wafer-bonded MEMS packages (> 1 mm3) with an acceptable cavity pressure increase of 10 mbar could be tested using the deflection method and our proposed test structure design to guarantee their lifetime. ...
Hermeticity is a measure of how well a package is leak-tight. Many Micro-Electro-Mechanical Systems (MEMS) sensors, actuators, and microelectronic devices need a defined cavity environment for optimal performance, hence measuring the package leak rate is critical for lifetime prediction. MEMS devices are generally packaged through the wafer-bonding technique. The MEMS device is produced on a wafer with a cavity and bonded to a cap wafer to seal the hole. Reducing the cap wafer thickness allows it to deflect due to the cavity interior-exterior pressure differential. Consequently, if leakage occurs, the deflection will
change. By measuring these deflections, it is possible to quantify leak rates.
In order to use it as an in-line testing process, this research aims to determine the accuracy of the deflection method for determining the leak rates. To achieve this, our approach involved designing and leak testing test structures (or devices) using an experimental setup that can vary pressure, supply desired species
inside a vacuum chamber, and measure deflection using an interferometer to determine leak rates. Deflections are converted to leak rates using a formulated analytical expression, subsequently utilized to determine the error involved in measuring leak rates.
Using the experimental setup, the test devices were effectively characterized for sensitivity using pressure-induced deflection measurements, with experimental sensitivity values closely matching the theory. Further, air leak testing was performed on devices interconnected with nanometer-gap size leak channels to
gain first-hand knowledge of leakage. Experimental leak rates matched well with analytical models, proving that flow through devices having leak channels can be characterized. Ultimately, the setup enabled successful helium leak testing of devices without any defined leak channels.
The helium leak-tested samples were circular membranes of diameters: 2000, 1600, 1400, 1300, and 1100 μm with a thickness of 40 μm bonded to a cavity depth of 3.24 μm. Uncertainty analysis associated with leak rate measurement revealed that when considering a certain cavity depth and membrane thickness,
the membrane with the largest diameter would exhibit the least amount of uncertainty. This was also observed through experiments, for the diameter of 2000 μm, a clear linear trend of deflection reduction due to the helium leakage was observed during a two-week period of deflection measurements. Whereas, for the diameter of 1100 μm, it was not possible to observe the same linear trend of deflection reduction, indicating that even more no.of.days is required to determine an accurate leak rate.
In the end, a short analysis was made using the cavity design having the 2000 μm membrane, which had the least uncertainty in measuring the leak rate. This analysis aimed to ascertain the designed test structure’s usefulness in measuring leak rates of the MEMS packages. Based on the analysis, it was concluded that large-volume wafer-bonded MEMS packages (> 1 mm3) with an acceptable cavity pressure increase of 10 mbar could be tested using the deflection method and our proposed test structure design to guarantee their lifetime.
change. By measuring these deflections, it is possible to quantify leak rates.
In order to use it as an in-line testing process, this research aims to determine the accuracy of the deflection method for determining the leak rates. To achieve this, our approach involved designing and leak testing test structures (or devices) using an experimental setup that can vary pressure, supply desired species
inside a vacuum chamber, and measure deflection using an interferometer to determine leak rates. Deflections are converted to leak rates using a formulated analytical expression, subsequently utilized to determine the error involved in measuring leak rates.
Using the experimental setup, the test devices were effectively characterized for sensitivity using pressure-induced deflection measurements, with experimental sensitivity values closely matching the theory. Further, air leak testing was performed on devices interconnected with nanometer-gap size leak channels to
gain first-hand knowledge of leakage. Experimental leak rates matched well with analytical models, proving that flow through devices having leak channels can be characterized. Ultimately, the setup enabled successful helium leak testing of devices without any defined leak channels.
The helium leak-tested samples were circular membranes of diameters: 2000, 1600, 1400, 1300, and 1100 μm with a thickness of 40 μm bonded to a cavity depth of 3.24 μm. Uncertainty analysis associated with leak rate measurement revealed that when considering a certain cavity depth and membrane thickness,
the membrane with the largest diameter would exhibit the least amount of uncertainty. This was also observed through experiments, for the diameter of 2000 μm, a clear linear trend of deflection reduction due to the helium leakage was observed during a two-week period of deflection measurements. Whereas, for the diameter of 1100 μm, it was not possible to observe the same linear trend of deflection reduction, indicating that even more no.of.days is required to determine an accurate leak rate.
In the end, a short analysis was made using the cavity design having the 2000 μm membrane, which had the least uncertainty in measuring the leak rate. This analysis aimed to ascertain the designed test structure’s usefulness in measuring leak rates of the MEMS packages. Based on the analysis, it was concluded that large-volume wafer-bonded MEMS packages (> 1 mm3) with an acceptable cavity pressure increase of 10 mbar could be tested using the deflection method and our proposed test structure design to guarantee their lifetime.
Diamagnetic levitation presents a promising platform for realizing resonant sensors and energy harvesters. The technique offers mechanical isolation from the environment while operating with zero power consumption. This unique feature ensures exceptional sensitivity and accuracy in numerous applications. However, the presence of eddy currents in the levitating plate, induced by the alternating magnetic field, poses challenges, leading to increased damping and subsequently limiting the performance of levitating resonators. To address these issues, this study proposes a novel solution through the segmentation of diamagnetic plates. By dividing a pyrolytic graphite plate into smaller blocks, the flow of eddy currents is effectively restricted, resulting in reduced damping and significantly higher Q factors. By comparing the theoretical predictions using a FEM model from an earlier study with the measurements conducted the proposed technique is further validated. This comparative analysis demonstrates the effectiveness of the segmentation approach in mitigating damping due to eddy currents. Furthermore, the implementation of the proposed method led to remarkable results, with achieved Q factors exceeding 150 thousand.
...
Diamagnetic levitation presents a promising platform for realizing resonant sensors and energy harvesters. The technique offers mechanical isolation from the environment while operating with zero power consumption. This unique feature ensures exceptional sensitivity and accuracy in numerous applications. However, the presence of eddy currents in the levitating plate, induced by the alternating magnetic field, poses challenges, leading to increased damping and subsequently limiting the performance of levitating resonators. To address these issues, this study proposes a novel solution through the segmentation of diamagnetic plates. By dividing a pyrolytic graphite plate into smaller blocks, the flow of eddy currents is effectively restricted, resulting in reduced damping and significantly higher Q factors. By comparing the theoretical predictions using a FEM model from an earlier study with the measurements conducted the proposed technique is further validated. This comparative analysis demonstrates the effectiveness of the segmentation approach in mitigating damping due to eddy currents. Furthermore, the implementation of the proposed method led to remarkable results, with achieved Q factors exceeding 150 thousand.
Master thesis
(2023)
-
J.A. Scheepstra, P.G. Steeneken, W.J. Westerveld, P. Castro Rodríguez, N. Bhattacharya, R.A. Norte
In a world increasingly dominated by technological advancements, the demand for high-quality microphones has never been more present. Seamless speech recognition and the development of userfriendly hearing aids remain significant challenges. State-of-the-art micro-electromechanical system (MEMS) microphones are reaching their bottlenecks in terms of thermo-acoustic noise, caused by the acoustic resistance of the parallel plate capacitor. This constrains the achievable signal-to-noise ratio (SNR). This thesis presents a novel solution to address these challenges through the application of silicon photonics technology in the development of a silicon photonic microphone. Silicon photonics is a technology that uses silicon as an optical medium to create photonic systems with sub-micrometre precision, which can be used to create ultra-sensitive sensing devices. The optical sensors are fabricated on standard silicon-on-insulator (SOI) wafers, allowing for seamless integration with the precise and cost-effective complementary metal-oxide-semiconductor (CMOS) process. The optomechanical
sensitivity of the proposed microphone is derived for three different cladding materials that could be deposited on the wafer in the fabrication process. The thermal acoustic noise of the microphone is quantified. As the integrated photonic circuit does not require a backplate the design potentially reduces the thermal acoustic noise of current microphones by 44 %. The optimized design for the laboratory setup that is considered for this thesis can theoretically result in an SNR of 73.1 dB, which is roughly 5 dB more than the current state-of-the-art microphone technology.
...
sensitivity of the proposed microphone is derived for three different cladding materials that could be deposited on the wafer in the fabrication process. The thermal acoustic noise of the microphone is quantified. As the integrated photonic circuit does not require a backplate the design potentially reduces the thermal acoustic noise of current microphones by 44 %. The optimized design for the laboratory setup that is considered for this thesis can theoretically result in an SNR of 73.1 dB, which is roughly 5 dB more than the current state-of-the-art microphone technology.
...
In a world increasingly dominated by technological advancements, the demand for high-quality microphones has never been more present. Seamless speech recognition and the development of userfriendly hearing aids remain significant challenges. State-of-the-art micro-electromechanical system (MEMS) microphones are reaching their bottlenecks in terms of thermo-acoustic noise, caused by the acoustic resistance of the parallel plate capacitor. This constrains the achievable signal-to-noise ratio (SNR). This thesis presents a novel solution to address these challenges through the application of silicon photonics technology in the development of a silicon photonic microphone. Silicon photonics is a technology that uses silicon as an optical medium to create photonic systems with sub-micrometre precision, which can be used to create ultra-sensitive sensing devices. The optical sensors are fabricated on standard silicon-on-insulator (SOI) wafers, allowing for seamless integration with the precise and cost-effective complementary metal-oxide-semiconductor (CMOS) process. The optomechanical
sensitivity of the proposed microphone is derived for three different cladding materials that could be deposited on the wafer in the fabrication process. The thermal acoustic noise of the microphone is quantified. As the integrated photonic circuit does not require a backplate the design potentially reduces the thermal acoustic noise of current microphones by 44 %. The optimized design for the laboratory setup that is considered for this thesis can theoretically result in an SNR of 73.1 dB, which is roughly 5 dB more than the current state-of-the-art microphone technology.
sensitivity of the proposed microphone is derived for three different cladding materials that could be deposited on the wafer in the fabrication process. The thermal acoustic noise of the microphone is quantified. As the integrated photonic circuit does not require a backplate the design potentially reduces the thermal acoustic noise of current microphones by 44 %. The optimized design for the laboratory setup that is considered for this thesis can theoretically result in an SNR of 73.1 dB, which is roughly 5 dB more than the current state-of-the-art microphone technology.
SnV centres in diamond are a promising candidate for quantum internet applications because of their strong spin-photon interface, long spin coherence times, and insensitivity to electric fields. Integrating them in diamond waveguides could strongly improve entanglement rates and could make for a scalable design. In this thesis, we show using simulations that rectangular <110> waveguides are good candidates for high emitter-waveguide coupling, reaching a maximum of 79%. Optimal dimensions are 250 nm x 120 nm (width x height). This also falls inside the single-mode regime for the emitted light. The measured lifetime limits for the linewidth of Γ = 25 MHz, dephasing of Γ_𝑑 = 10 MHz, and >10 seconds long spectral stability in the bulk diamond sample, together with an APD dark count rate of 171 Hz should lead to a transmission dip around resonance of Δ𝑇/𝑇 = 25%, which we predict using a different simulation. The currently obtained taper coupling from diamond waveguide to optical fiber is approximately 10%. This is probably enough to see the transmission dip, but it needs to be improved for future experiments. Post-selecting SnV centres in waveguides and using Purcell enhancement to boost ZPL emission can further improve these results.
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SnV centres in diamond are a promising candidate for quantum internet applications because of their strong spin-photon interface, long spin coherence times, and insensitivity to electric fields. Integrating them in diamond waveguides could strongly improve entanglement rates and could make for a scalable design. In this thesis, we show using simulations that rectangular <110> waveguides are good candidates for high emitter-waveguide coupling, reaching a maximum of 79%. Optimal dimensions are 250 nm x 120 nm (width x height). This also falls inside the single-mode regime for the emitted light. The measured lifetime limits for the linewidth of Γ = 25 MHz, dephasing of Γ_𝑑 = 10 MHz, and >10 seconds long spectral stability in the bulk diamond sample, together with an APD dark count rate of 171 Hz should lead to a transmission dip around resonance of Δ𝑇/𝑇 = 25%, which we predict using a different simulation. The currently obtained taper coupling from diamond waveguide to optical fiber is approximately 10%. This is probably enough to see the transmission dip, but it needs to be improved for future experiments. Post-selecting SnV centres in waveguides and using Purcell enhancement to boost ZPL emission can further improve these results.
Conventional Topology Optimization (TO) enables the inverse design of nanophotonic structures by specifying the objective and constraints without a predefined topological concept. Yet, extreme scenarios such as the design of a lightsail pose challenges that require new solutions. Here, a convolutional neural network (CNN) based TO methodology is extended to optimize a two-dimensional photonic crystal used to design a lightsail that aims to reach the nearest star (Alpha Centauri) within 20 years by achieving 20% of the speed of light. The CNN-TO performance is compared to a more conventional method of moving asymptotes (MMA) based TO by optimizing a photonic crystal unit-cell for the 2016 Starshot Initiative parameters. The CNN-TO requires up to 40% fewer iterations than MMA-TO to reach better performance under different operational conditions. The generated design turned out to be easy to fabricate, allowing them to be produced with optical lithography. Additionally, a study regarding the design challenges of the lightsail has been performed, which resulted in an optimization considering the functionality of the sail. Additionally, the study showed the sensitivity of the resulting design to varying objectives and materials. Therefore, underlining the necessity of considering multiple operating conditions (e.g. laser alignment and cooling) within the design process. ...
Conventional Topology Optimization (TO) enables the inverse design of nanophotonic structures by specifying the objective and constraints without a predefined topological concept. Yet, extreme scenarios such as the design of a lightsail pose challenges that require new solutions. Here, a convolutional neural network (CNN) based TO methodology is extended to optimize a two-dimensional photonic crystal used to design a lightsail that aims to reach the nearest star (Alpha Centauri) within 20 years by achieving 20% of the speed of light. The CNN-TO performance is compared to a more conventional method of moving asymptotes (MMA) based TO by optimizing a photonic crystal unit-cell for the 2016 Starshot Initiative parameters. The CNN-TO requires up to 40% fewer iterations than MMA-TO to reach better performance under different operational conditions. The generated design turned out to be easy to fabricate, allowing them to be produced with optical lithography. Additionally, a study regarding the design challenges of the lightsail has been performed, which resulted in an optimization considering the functionality of the sail. Additionally, the study showed the sensitivity of the resulting design to varying objectives and materials. Therefore, underlining the necessity of considering multiple operating conditions (e.g. laser alignment and cooling) within the design process.
Optical microscopes are fundamentally limited to a resolution of several hundreds of nanometers by the diffraction of light. Single-molecule localization microscopy (SMLM) circumvents this limit by sparsely exciting fluorescent molecules at different time instances. Single molecules can subsequently be localized with improved precision over the diffraction limit. Due to their high frame rate, single-photon avalanche diode (SPAD) arrays are imagers that can be used for SMLM. Most SPADs have to recharge after each photon arrival. During this recharging period, the SPAD is insensitive to more photon arrivals. As a result, SPAD arrays will measure zero or one photons for each pixel in each frame, whereas scientific complementary metal-oxide semiconductor (sCMOS) imagers and electron multiplying charge-coupled devices (EMCCD) have a discrete frame output. Here, we describe the photon arrivals in the image formation model of the SPAD array as a binomial process rather than as a Poissonian process. In addition, we quantify the minimum theoretical uncertainty of single-molecule localizations using a binomial Cramér-Rao lower bound and benchmark it with simulated and experimental data. We show that if the expected photon count is larger than one for all pixels within one standard deviation of a Gaussian point spread function, the binomial CRLB gives a 46% higher theoretical uncertainty than the Poissonian CRLB. Without saturation, which is the case for most SMLM applications, the binomial CRLB model gives the same uncertainty as the Poissonian CRLB. Therefore, the binomial CRLB can be used to predict and benchmark localization uncertainty for SMLM with SPAD arrays for all practical emitter intensities.
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Optical microscopes are fundamentally limited to a resolution of several hundreds of nanometers by the diffraction of light. Single-molecule localization microscopy (SMLM) circumvents this limit by sparsely exciting fluorescent molecules at different time instances. Single molecules can subsequently be localized with improved precision over the diffraction limit. Due to their high frame rate, single-photon avalanche diode (SPAD) arrays are imagers that can be used for SMLM. Most SPADs have to recharge after each photon arrival. During this recharging period, the SPAD is insensitive to more photon arrivals. As a result, SPAD arrays will measure zero or one photons for each pixel in each frame, whereas scientific complementary metal-oxide semiconductor (sCMOS) imagers and electron multiplying charge-coupled devices (EMCCD) have a discrete frame output. Here, we describe the photon arrivals in the image formation model of the SPAD array as a binomial process rather than as a Poissonian process. In addition, we quantify the minimum theoretical uncertainty of single-molecule localizations using a binomial Cramér-Rao lower bound and benchmark it with simulated and experimental data. We show that if the expected photon count is larger than one for all pixels within one standard deviation of a Gaussian point spread function, the binomial CRLB gives a 46% higher theoretical uncertainty than the Poissonian CRLB. Without saturation, which is the case for most SMLM applications, the binomial CRLB model gives the same uncertainty as the Poissonian CRLB. Therefore, the binomial CRLB can be used to predict and benchmark localization uncertainty for SMLM with SPAD arrays for all practical emitter intensities.
A research gap exists in a targeted drug delivery into the brain with an implant placed on the outer surface of the cerebral cortex. If an implant with spatial control that can release drugs to a target location can be developed, it will provide efficient treatment opportunities for a variety of brain disorders such as strokes. One of the questions in realizing this implant is how to activate the drug release mechanism. Light is a promising activation stimulus due to its spatial precision and flexibility in the optical path. This thesis is a feasibility study into carrying light inside such a brain implant using a photonic crystal waveguide. Such a device must be soft and maintain its functionality during the mechanical bending imposed on the implant by the geometry and movement of the brain. A flexible 2D photonic crystal is simulated using COMSOL Multiphysics with the goal of designing a waveguide that functions with infrared light. The dispersion diagram of the photonic crystal is plotted to design for a bandgap at the operating wavelength. The transmission through a linear waveguide is calculated for the deformed state of the implant in mechanical bending, which is modeled as a 2D strain. A metallo-photonic crystal with photoresist nanopillars coated with a gold thin film and embedded in a flexible PDMS matrix is selected as the prototype for fabrication. The nanopillar arrays that form the photonic crystal waveguide are printed using two-photon polymerization (2PP), deposited with gold then transferred into photosensitive PDMS by drop casting. For characterization, a tapered rib waveguide is designed for light coupling and an optical end-fire test setup is built for transmission measurements on the fabricated device.
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A research gap exists in a targeted drug delivery into the brain with an implant placed on the outer surface of the cerebral cortex. If an implant with spatial control that can release drugs to a target location can be developed, it will provide efficient treatment opportunities for a variety of brain disorders such as strokes. One of the questions in realizing this implant is how to activate the drug release mechanism. Light is a promising activation stimulus due to its spatial precision and flexibility in the optical path. This thesis is a feasibility study into carrying light inside such a brain implant using a photonic crystal waveguide. Such a device must be soft and maintain its functionality during the mechanical bending imposed on the implant by the geometry and movement of the brain. A flexible 2D photonic crystal is simulated using COMSOL Multiphysics with the goal of designing a waveguide that functions with infrared light. The dispersion diagram of the photonic crystal is plotted to design for a bandgap at the operating wavelength. The transmission through a linear waveguide is calculated for the deformed state of the implant in mechanical bending, which is modeled as a 2D strain. A metallo-photonic crystal with photoresist nanopillars coated with a gold thin film and embedded in a flexible PDMS matrix is selected as the prototype for fabrication. The nanopillar arrays that form the photonic crystal waveguide are printed using two-photon polymerization (2PP), deposited with gold then transferred into photosensitive PDMS by drop casting. For characterization, a tapered rib waveguide is designed for light coupling and an optical end-fire test setup is built for transmission measurements on the fabricated device.
Vibration energy harvesters are especially interesting to use in an environment where there is one dominant vibration frequency present because then the harvesters can be designed to resonate at that specific frequency. To spread out the power yield over more frequencies a multi-modal harvester can be used which can resonate at multiple frequencies. A vibration with more than one sine wave can be manifested in a number of ways. The two frequencies can be present simultaneously, or they can alternate each other. How the energy harvesters react to these different vibration inputs is researched in this paper. Two fundamentally different multi-modal energy harvesters are used here. One which can be described by a coupled system of equations and one uncoupled. Two prototypes of an uncoupled and one coupled device are made and tested on an electromagnetic shaker. The vibration signals are sent to the shaker and the power output of the energy harvesters is measured using piezoelectric transducers mounted to the mechanisms. The results show that a phaseshift in the sine wave input signal generally results in a increase in power, where a decrease was assumed beforehand. When switching the input vibration from the first to the second eigenfrequency the power output does drop significantly, but the coupled mechanism has a substantially higher power output than the uncoupled device. And when the mechanisms are excited by a vibration with two eigenfrequencies at the same time no significant difference between the two can be observed, nor does the power output drop significantly. While the comparison between these two mechanisms is probably accurate, the quantitative conclusions must be taken with a grain of salt as it was noticed in a later stage of the research that the vibration signals were not consistent over the entire time period. At this point it is unclear if an overall better mechanism can be picked between the coupled and uncoupled one. However, it is shown that both have their distinct advantages where they outperform their counterpart, which can be used for designing a better energy harvester in future applications
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Vibration energy harvesters are especially interesting to use in an environment where there is one dominant vibration frequency present because then the harvesters can be designed to resonate at that specific frequency. To spread out the power yield over more frequencies a multi-modal harvester can be used which can resonate at multiple frequencies. A vibration with more than one sine wave can be manifested in a number of ways. The two frequencies can be present simultaneously, or they can alternate each other. How the energy harvesters react to these different vibration inputs is researched in this paper. Two fundamentally different multi-modal energy harvesters are used here. One which can be described by a coupled system of equations and one uncoupled. Two prototypes of an uncoupled and one coupled device are made and tested on an electromagnetic shaker. The vibration signals are sent to the shaker and the power output of the energy harvesters is measured using piezoelectric transducers mounted to the mechanisms. The results show that a phaseshift in the sine wave input signal generally results in a increase in power, where a decrease was assumed beforehand. When switching the input vibration from the first to the second eigenfrequency the power output does drop significantly, but the coupled mechanism has a substantially higher power output than the uncoupled device. And when the mechanisms are excited by a vibration with two eigenfrequencies at the same time no significant difference between the two can be observed, nor does the power output drop significantly. While the comparison between these two mechanisms is probably accurate, the quantitative conclusions must be taken with a grain of salt as it was noticed in a later stage of the research that the vibration signals were not consistent over the entire time period. At this point it is unclear if an overall better mechanism can be picked between the coupled and uncoupled one. However, it is shown that both have their distinct advantages where they outperform their counterpart, which can be used for designing a better energy harvester in future applications
The exceptional material properties of bulk diamond like high stiffness, high thermal conductivity, wide optical transparency, chemical inertness and bio-compatibility make it the material of choice in many high-end applications. Most present-day diamond micro-devices are fabricated by costly and time-consuming top-down methods, such as focussed ion beam milling or reactive ion etching. Hence, bottom-up methods that incorporate selective seeding and chemical vapour deposition (CVD) to produce micro-patterned poly-crystalline diamond are of interest. The present work introduces two novel methods for the bottom-up synthesis of nanocrystalline diamond micro-structures. The first method is based on the precise dispensing of nanodiamond dispersions from a hollow AFM cantilever and is used to manufacture freestanding diamond micro-resonators which are analysed on their frequency response. The second method incorporates maskless lithography to create stencils for selective seeding and enables patterned diamond growth on the single digit micrometer scale. A future step of growing such micro-structures in electrically conductive diamond could open up a vast new range up applications.
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The exceptional material properties of bulk diamond like high stiffness, high thermal conductivity, wide optical transparency, chemical inertness and bio-compatibility make it the material of choice in many high-end applications. Most present-day diamond micro-devices are fabricated by costly and time-consuming top-down methods, such as focussed ion beam milling or reactive ion etching. Hence, bottom-up methods that incorporate selective seeding and chemical vapour deposition (CVD) to produce micro-patterned poly-crystalline diamond are of interest. The present work introduces two novel methods for the bottom-up synthesis of nanocrystalline diamond micro-structures. The first method is based on the precise dispensing of nanodiamond dispersions from a hollow AFM cantilever and is used to manufacture freestanding diamond micro-resonators which are analysed on their frequency response. The second method incorporates maskless lithography to create stencils for selective seeding and enables patterned diamond growth on the single digit micrometer scale. A future step of growing such micro-structures in electrically conductive diamond could open up a vast new range up applications.
In pursuit of extremely sensitive sensors, the dimensions of these sensors get smaller and smaller. Small scale resonators are commonly used as sensors by relating changes in the dynamic behaviour to a sensed quantity. Conventionally, the dynamics used for sensing are in the linear regime. But at smaller scales the dynamic range of the linear regime decreases. Therefore, it is of interest to investigate the dynamic behaviour in the nonlinear regime, as with the decreasing scale of the resonators this becomes inevitable. Especially, little is known about the frequency stability in this region. The frequency stability is an indication for the potential sensitivity that the resonator can have as sensor. By using phase locked loop (PLL) the frequency stability around the resonance frequency of nonlinear resonators can be obtained. This research contains attempts to control multilayer graphene drums around its fundamental resonance frequency with PLL. In addition, the frequency stability at these points are presented by measure of the Allan deviation. There are roughly two different distributions of the frequency stability over the frequency response obtained. One resonator shows behaviour attributed to internal resonance. This internal resonance is linked to an increase of nonlinear damping. Combining that with a simple simulation model, a relation was found between increased nonlinear damping and an improvement of frequency stability.
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In pursuit of extremely sensitive sensors, the dimensions of these sensors get smaller and smaller. Small scale resonators are commonly used as sensors by relating changes in the dynamic behaviour to a sensed quantity. Conventionally, the dynamics used for sensing are in the linear regime. But at smaller scales the dynamic range of the linear regime decreases. Therefore, it is of interest to investigate the dynamic behaviour in the nonlinear regime, as with the decreasing scale of the resonators this becomes inevitable. Especially, little is known about the frequency stability in this region. The frequency stability is an indication for the potential sensitivity that the resonator can have as sensor. By using phase locked loop (PLL) the frequency stability around the resonance frequency of nonlinear resonators can be obtained. This research contains attempts to control multilayer graphene drums around its fundamental resonance frequency with PLL. In addition, the frequency stability at these points are presented by measure of the Allan deviation. There are roughly two different distributions of the frequency stability over the frequency response obtained. One resonator shows behaviour attributed to internal resonance. This internal resonance is linked to an increase of nonlinear damping. Combining that with a simple simulation model, a relation was found between increased nonlinear damping and an improvement of frequency stability.