Publikationen 2022

Script list Publications

(1) High Optical Gain in InP-Based Quantum-Dot Material Monolithically Grown on Silicon Emitting at Telecom Wavelengths
R. Balasubramanian, V. Sichkovskyi, C. Corley-Wiciak, F. Schnabel, L. Popilevsky, G. Atiya, I. Khanonkin, A.J. Willinger, O. Eyal, G. Eisenstein, J.P. Reithmaier
Semiconductor Science and Technology 37(5), 055005 (2022)
DOI: 10.1088/1361-6641/ac5d10
We describe the fabrication process and properties of an InP based quantum dot laser structure grown on a 5° off-cut silicon substrate. Several layers of quantum dot-based dislocation filters embedded in GaAs and InP were used to minimize the defect density in the quantum dot active region which comprised eight emitting dot layers. The structure was analyzed using high resolution transmission electron microscopy, atomic force microscopy and photoluminescence. The epitaxial stack was used to fabricate optical amplifiers which exhibit electroluminescence spectra that are typical of conventional InAs quantum dot amplifiers grown on InP substrates. The amplifiers avail up to 20 dB of optical gain, which is equivalent to a modal gain of 46 cm-1.

(2) Low Conductance State Drift Characterization and Mitigation in Resistive Switching Memories (RRAM) for Artificial Neural Networks
A. Baroni, A. Glukhov, E. Perez, Ch. Wenger, D. Ielmini, P. Olivo, C. Zambelli
IEEE Transactions on Device and Materials Reliability 22(3), 340 (2022)
DOI: 10.1109/TDMR.2022.3182133, (KI-IoT)
The crossbar structure of Resistive-switching random access memory (RRAM) arrays enabled the In-Memory Computing circuits paradigm, since they imply the native acceleration of a crucial operations in this scenario, namely the Matrix-Vector-Multiplication (MVM). However, RRAM arrays are affected by several issues materializing in conductance variations that might cause severe performance degradation. A critical one is related to the drift of the low conductance states appearing immediately at the end of program and verify algorithms that are mandatory for an accurate multi-level conductance operation.
In this work, we analyze the benefits of a new programming algorithm that embodies Set and Reset switching operations to achieve better conductance control and lower variability. Data retention analysis performed with different temperatures for 168 hours evidence its superior performance with respect to standard programming approach. Finally, we explored the benefits of using our methodology at a higher abstraction level, through the simulation of an Artificial Neural Network for image recognition task (MNIST dataset). The accuracy achieved shows higher performance stability over temperature and time.

(3) An Energy-efficient In-Memory Computing Architecture for Survival Data Analysis based on Resistive Switching Memories (RRAM)
A. Baroni, A. Glukhov, E. Perez, Ch. Wenger, E. Calore, S.F. Schifano, P. Olivo, D. Ielmini, C. Zambelli
Frontiers in Neuroscience 16, 932270 (2022)
(KI-IoT)
One of the objectives fostered in medical science is the so-called precision medicine, which requires the analysis of a large amount of survival data from patients to deeply understand treatment options. Tools like Machine Learning and Deep Neural Networks are becoming a de-facto standard. Nowadays, computing facilities based on the Von Neumann architecture are devoted to these tasks, yet rapidly hitting a bottleneck in performance and energy efficiency. The In-Memory Computing (IMC) architecture emerged as a revolutionary approach to overcome that issue. In this work, we propose an IMC architecture based on Resistive switching memory (RRAM) crossbar arrays to provide a convenient primitive for matrix–vector multiplication in a single computational step. This opens massive performance improvement in the acceleration of a neural network that is frequently used in survival analysis of biomedical records, namely the DeepSurv. We explored how the synaptic weights mapping strategy and the programming algorithms developed to counter RRAM non-idealities expose a performance/energy trade-off. Finally, we assessed the benefits of the proposed architectures with respect to a GPU-based realization of the same task, evidencing a tenfold improvement in terms of performance and three orders of magnitude with respect to energy efficiency.

(4) Alternative Strategy to Grow Large Surface hBN on Ge Films by Molecular Beam Epitaxy
W. Batista Pessoa, M. Franck, J. Dabrowski, X. Wallart, N. Nuns, M. Lukosius, D. Vignaud
Graphene Conference 2022, 179 (2022)
(2DHetero)

(5) Implementation of Device-to-Device and Cycle-to-Cycle Variability of Memristive Devices in Circuit Simulations
C. Bischoff, J. Leise, E. Perez-Bosch Quesada, E. Perez, Ch. Wenger, A. Kloes
Solid State Electronics 194, 108321 (2022)
DOI: 10.1016/j.sse.2022.108321, (KI-IoT)
We present a statistical procedure for the extraction of parameters of a compact model for memristive devices. Thereby, in a circuit simulation the typical fluctuations of the current-voltage (I-V) characteristics from device-to-device (D2D) and from cycle-to-cycle (C2C) can be emulated. The approach is based on the Stanford model whose parameters play a key role to integrating D2D and C2C dispersion. The influence of such variabilities over the model’s parameters is investigated by using a fitting algorithm fed with experimental data. After this, the statistical distributions of the parameters are used in a Monte Carlo simulation to reproduce the I-V D2D and C2C dispersions which show a good agreement to the measured curves. The results allow the simulation of the on/off current variation for the design of RRAM cells or memristor-based artificial neural networks.

(6) Vibrational Properties in Highly Strained Hexagonal Boron Nitride Bubbles
E. Blundo, A. Surrente, D. Spirito, G. Pettinari, T. Yildirim, L. Baldassarre, C.A. Chavarin, M. Felici, A. Polimeni
Nano Letters 22(4), 1525 (2022)
DOI: 10.1021/acs.nanolett.1c04197
Hexagonal boron nitride (hBN) is widely used as a protective layer for few-atom-thick crystals and heterostructures (HSs), and it hosts quantum emitters working up to room temperature. In both instances, strain is expected to play an important role, either as an unavoidable presence in the HS fabrication or as a tool to tune the quantum emitter electronic properties. Addressing the role of strain and exploiting its tuning potentiality require the development of efficient methods to control it and of reliable tools to quantify it. Here we present a technique based on hydrogen irradiation to induce the formation of wrinkles and bubbles in hBN, resulting in remarkably high strains of ∼2%. By combining infrared (IR) near-field scanning optical microscopy and micro-Raman measurements with numerical calculations, we characterize the response to strain for both IR-active and Raman-active modes, revealing the potential of the vibrational properties of hBN as highly sensitive strain probes.

(7) Analytical Calculation of Inference in Memristor-Based Stochastic Artificial Neural Networks
N. Bogun, E. Perez-Bosch Quesada, E. Perez, Ch. Wenger, A. Kloes, M. Schwarz
Proc. 29th International Conference Mixed Design of Integrated Circuits and Systems (MIXDES 2022), 83 (2022)
DOI: 10.23919/MIXDES55591.2022.9838321, (KI-IoT)

(8) Room Temperature Lasing in GeSn Microdisks Enabled by Strain Engineering
D. Buca, A. Bjelajac, D. Spirito, O. Conception, M. Gromovyi, E. Sakat, X. Lafosse, L. Ferlazzo, N. von den Driesch, Z. Ikonic, D. Grützmacher, G. Capellini, M. El Kurdi
Advanced Optical Materials 2201024 (2022)
DOI: 10.1002/adom.202201024, (DFG GeSn Laser)
The success of GeSn alloys as active material for infrared lasers could pave the way toward a monolithic technology that can be manufactured within mainstream silicon photonics. Nonetheless, for operation on chip, lasing should occur at room temperature or beyond. Unfortunately, despite the intense research in recent years, many hurdles have yet to be overcome. An approach exploiting strain engineering to induce large tensile strain in micro-disk made of GeSn alloy with Sn content of 14 at% is presented here. This method enables robust multimode laser emission at room temperature. Furthermore, tensile strain enables proper valence band engineering; as a result, over a large range of operating temperatures, lower lasing thresholds are observed compared to high Sn content GeSn lasers operating at similar wavelength.

(9) On-Chip Infrared Photonics with Si-Ge-Heterostructures: What is Next?
I.A. Fischer, M. Brehm, M. De Seta, G. Isella, D.J. Paul, M. Virgilio, G. Capellini
APL Photonics 7(5), 050901 (2022)
DOI: 10.1063/5.0078608, (FLASH)
The integration of Ge on Si for photonics applications has reached a high level of maturity: Ge photodetectors are available on the Si platform in foundry processes, and Si/Ge heterostructure multiple quantum-well photodiodes are rapidly progressing toward applications in light modulation. These successes result from decades of development of high-quality material growth and integration, which, more recently, has sparked an increasingly broad field of photonic device research based on Si/Ge heterostructures that extends from quantum cascade lasers to sensors. Here, we highlight selected recent structure and device developments as well as possible future trends that are enabled by the maturity of the SiGe material platform.

(10) Towards the Growth of Hexagonal Boron Nitride on Ge(001)/Si Substrates by Chemical Vapor Deposition
M. Franck, J. Dabrowski, M.A. Schubert, Ch. Wenger, M. Lukosius
Nanomaterials 12, 3260 (2022)
(2DHetero)

(11) Towards the Growth of hBN on Ge/Si Substrates by CVD
M. Franck, J. Dabrowski, M.A. Schubert, Ch. Wenger, M. Lukosius
Proc. Graphene Conference 2022, 164 (2022)
(2DHetero)

(12) Mitigating the Effects of RRAM Process Variation on the Accuracy of Artifical Neural Networks
M. Fritscher, J. Knödtel, M. Mallah, S. Pechmann, E. Perez-Bosch Quesada, T. Rizzi, Ch. Wenger, M. Reichenbach
Proc. 21st International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation (SAMOS 2021), in: Lecture Notes in Computer Science, Springer, LNCS 13227, 401 (2022)
DOI: 10.1007/978-3-031-04580-6_27, (NeuroMem)
In this work, three different RRAM compact models implemented in Verilog-A are analyzed and evaluated in order to reproduce the multilevel approach based on the switching capability of experimental devices. These models are integrated in 1T-1R cells to control their analog behavior by means of the compliance current imposed by the NMOS select transistor. Four different resistance levels are simulated and assessed with experimental verification to account for their multilevel capability. Further, an Artificial Neural Network study is carried out to evaluate in a real scenario the viability of the multilevel approach under study.

(13) Mitigating the Effects of RRAM Process Variation on the Accuracy of Artifical Neural Networks
M. Fritscher, J. Knödtel, M. Mallah, S. Pechmann, E. Perez-Bosch Quesada, T. Rizzi, Ch. Wenger, M. Reichenbach
Proc. 21st International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation (SAMOS 2021), in: Lecture Notes in Computer Science, Springer, LNCS 13227, 401 (2022)
DOI: 10.1007/978-3-031-04580-6_27, (Total Resilience)
In this work, three different RRAM compact models implemented in Verilog-A are analyzed and evaluated in order to reproduce the multilevel approach based on the switching capability of experimental devices. These models are integrated in 1T-1R cells to control their analog behavior by means of the compliance current imposed by the NMOS select transistor. Four different resistance levels are simulated and assessed with experimental verification to account for their multilevel capability. Further, an Artificial Neural Network study is carried out to evaluate in a real scenario the viability of the multilevel approach under study.

(14) Mitigating the Effects of RRAM Process Variation on the Accuracy of Artifical Neural Networks
M. Fritscher, J. Knödtel, M. Mallah, S. Pechmann, E. Perez-Bosch Quesada, T. Rizzi, Ch. Wenger, M. Reichenbach
Proc. 21st International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation (SAMOS 2021), in: Lecture Notes in Computer Science, Springer, LNCS 13227, 401 (2022)
DOI: 10.1007/978-3-031-04580-6_27, (KI-PRO)
In this work, three different RRAM compact models implemented in Verilog-A are analyzed and evaluated in order to reproduce the multilevel approach based on the switching capability of experimental devices. These models are integrated in 1T-1R cells to control their analog behavior by means of the compliance current imposed by the NMOS select transistor. Four different resistance levels are simulated and assessed with experimental verification to account for their multilevel capability. Further, an Artificial Neural Network study is carried out to evaluate in a real scenario the viability of the multilevel approach under study.

(15) Statistical Model of Program/Verify Algorithms in Resistive Switching Memories for In-Memory Neural Network Accelerators
A. Glukhov, V. Milo, A. Baroni, N. Lepri, C. Zambelli, P. Olivo, E. Perez, Ch. Wenger, D. Ielmini
Proc. International Reliability Physics Symposium (IRPS 2022), 3C.3-1 (2022)
DOI: 10.1109/IRPS48227.2022.9764497, (NeuroMem)

(16) Statistical Model of Program/Verify Algorithms in Resistive Switching Memories for In-Memory Neural Network Accelerators
A. Glukhov, V. Milo, A. Baroni, N. Lepri, C. Zambelli, P. Olivo, E. Perez, Ch. Wenger, D. Ielmini
Proc. International Reliability Physics Symposium (IRPS 2022), 3C.3-1 (2022)
DOI: 10.1109/IRPS48227.2022.9764497, (Total Resilience)

(17) Statistical Model of Program/Verify Algorithms in Resistive Switching Memories for In-Memory Neural Network Accelerators
A. Glukhov, V. Milo, A. Baroni, N. Lepri, C. Zambelli, P. Olivo, E. Perez, Ch. Wenger, D. Ielmini
Proc. International Reliability Physics Symposium (IRPS 2022), 3C.3-1 (2022)
DOI: 10.1109/IRPS48227.2022.9764497, (KI-PRO)

(18) Room Temperature Donor Incorporation for Quantum Devices: Arsine on Germanium
E.V.S. Hofmann, T.J.Z. Stock, O. Warschkow, R. Conybeare, N.J. Curson, S.R. Schofield
Materials Science (2022)

(19) Toward Controlling the Al2O3/ZnO Interface Properties by In-Situ ALD Preparation
C. Janowitz, A. Mahmoodinezhad, M. Kot, C. Morales, F. Naumann, P. Plate, M.H. Zoellner, F. Bärwolf, D. Stolarek, Ch. Wenger, K. Henkel, J.I. Flege
Dalton Transactions 51, 9291 (2022)
DOI: 10.1039/d1dt04008a
An Al2O3/ZnO heterojunction was grown on a Si single crystal substrate by subsequent thermal and plasma-assisted atomic layer deposition (ALD) in-situ. The band offsets of the heterointerface were then studied by consecutive removal of the layers by argon sputtering, followed by in-situ X-ray photoelectron spectroscopy. The valence band maximum and conduction band minimum of Al2O3 are found to be 1.1 eV below and 2.3 eV above that of ZnO, resulting in a type-I staggered heterojunction. An apparent reduction of ZnO to elemental Zn in the interface region was detected in the Zn 2p core level and Zn L3MM Auger spectra. This suggests an interface formation different from previous models. The reduction of ZnO to Zn at the interface region accompanied by the creation of oxygen vacancies in the ZnO results in an upward band bending at the interface. Therefore, this study suggests that interfacial properties as the band bending as well as the valence and conduction band offsets should be in-situ controllable to a certain extent by careful selection of the process parameters.

(20) Role of Critical Thickness in SiGe/Si/SiGe Heterostructure Design for Qubits
Y. Liu, K.-P. Gradwohl, C.-H. Lu, T. Remmele, Y. Yamamoto, M.H. Zoellner, T. Schroeder, T. Boeck, H. Amari, C. Richter, M. Albrecht
Journal of Applied Physics 132(8), 085302 (2022)
(SiGeQuant)
We study the critical thickness for the plastic relaxation of the Si quantum well layer embedded in a SiGe/Si/SiGe heterostructure for qubits by plan-view transmission electron microscopy and electron channelling contrast imaging. Misfit dislocation segments form due to the glide of pre-existing threading dislocations at the interface of the Si quantum
well layer beyond a critical thickness given by the Matthews-Blakeslee criterion. Misfit dislocations are mostly 60° dislocations that are split into partials due to the tensile strain field of the Si quantum well layer. By reducing the quantum well thickness below critical thickness, misfit dislocations can be suppressed. A simple model is applied to simulate the misfit dislocation formation and blocking process. We discuss consequences of our findings for the layer stack design of SiGe/Si/SiGe heterostructures for usage in quantum computing hardware.

(21) Graphene Research in 200 mm CMOS Pilot Line
M. Lukosius, R. Lukose, M. Lisker, G. Luongo, M. Elviretti, A. Mai, Ch. Wenger
Proc. 45th International Convention on Information, Communication and Electronic Technology (MIPRO 2022), 113 (2022)
DOI: 10.23919/MIPRO55190.2022.9803362, (2D-EPL)

(22) Graphene Research in 200 mm CMOS Pilot Line
M. Lukosius, R. Lukose, M. Lisker, G. Luongo, M. Elviretti, A. Mai, Ch. Wenger
Proc. 45th International Convention on Information, Communication and Electronic Technology (MIPRO 2022), 113 (2022)
DOI: 10.23919/MIPRO55190.2022.9803362, (GIMMIK)

(23) Modulating the Filamentary Based Resistive Switching Properties of HfO2 Memristive Devices by Adding Al2O3 Layers
M.K. Mahadevaiah, E. Perez, M. Lisker, M.A. Schubert, E. Perez-Bosch Quesada, Ch. Wenger, A. Mai
Electronics (MDPI) 11(10), 1540 (2022)
DOI: 10.3390/electronics11101540, (Neutronics)
The resistive switching properties of HfO2 based 1T-1R memristive devices are electrically modified by adding ultra-thin layers of Al2O3 into the memristive device. Three different types of memristive stacks are fabricated in the 130 nm CMOS technology of IHP. The switching properties of the memristive devices are discussed with respect to forming voltages, low resistance state and high resistance state characteristics and their variabilities. The experimental I–V characteristics of set and reset operations are evaluated by using the quantum point contact model. The properties of the conduction filament in the on and off states of the memristive devices are discussed with respect to the model parameters obtained from the QPC fit.

(24) Modulating the Filamentary Based Resistive Switching Properties of HfO2 Memristive Devices by Adding Al2O3 Layers
M.K. Mahadevaiah, E. Perez, M. Lisker, M.A. Schubert, E. Perez-Bosch Quesada, Ch. Wenger, A. Mai
Electronics (MDPI) 11(10), 1540 (2022)
DOI: 10.3390/electronics11101540, (FMD)
The resistive switching properties of HfO2 based 1T-1R memristive devices are electrically modified by adding ultra-thin layers of Al2O3 into the memristive device. Three different types of memristive stacks are fabricated in the 130 nm CMOS technology of IHP. The switching properties of the memristive devices are discussed with respect to forming voltages, low resistance state and high resistance state characteristics and their variabilities. The experimental I–V characteristics of set and reset operations are evaluated by using the quantum point contact model. The properties of the conduction filament in the on and off states of the memristive devices are discussed with respect to the model parameters obtained from the QPC fit.

(25) Modulating the Filamentary Based Resistive Switching Properties of HfO2 Memristive Devices by Adding Al2O3 Layers
M.K. Mahadevaiah, E. Perez, M. Lisker, M.A. Schubert, E. Perez-Bosch Quesada, Ch. Wenger, A. Mai
Electronics (MDPI) 11(10), 1540 (2022)
DOI: 10.3390/electronics11101540, (NeuroMem)
The resistive switching properties of HfO2 based 1T-1R memristive devices are electrically modified by adding ultra-thin layers of Al2O3 into the memristive device. Three different types of memristive stacks are fabricated in the 130 nm CMOS technology of IHP. The switching properties of the memristive devices are discussed with respect to forming voltages, low resistance state and high resistance state characteristics and their variabilities. The experimental I–V characteristics of set and reset operations are evaluated by using the quantum point contact model. The properties of the conduction filament in the on and off states of the memristive devices are discussed with respect to the model parameters obtained from the QPC fit.

(26) A Proof of Concept of the Bulk Photovoltaic Effect in Non-Uniformly Strained Silicon
C.L. Manganelli, S. Kayser, M. Virgilio
Journal of Applied Physics 131(12), 125706 (2022)
DOI: 10.1063/5.0074426
We numerically investigate non-uniformly strained Si-based systems to demonstrate that, when a well focused laser beam locally excites the sample, the lattice distortion, impacting the band edge profile, causes a spatially dependent photovoltaic effect. It follows that, scanning the sample surface with the pump spot, a photovoltage signal can be acquired and used to quantitatively map the non-uniform strain field. To provide numerical evidence in this direction, we combine mechanical simulations with deformation potential theory to estimate the band-edge energy landscape of a Si lattice strained by an array of SiN stripes fabricated on the top surface. These data are then used to simulate the voltage signal obtained scanning the sample surface with a normal incident pump beam. Our analysis suggests that strain deformation as small as 0.1% can trigger at room temperature robust photovoltaic signals. These results allow to envision the development of a fast, cost effective and non-destructive set-up which leverage on the bulk photovoltaic effect to image the lattice deformation in semiconductor crystals.

(27) In-Memory Principal Component Analysis by Crosspoint Array of Rresistive Switching Memory: A New Hardware Approach for Energy-Efficient Data Analysis in Edge Computing
P. Mannocci, A. Baroni, E. Melacarne, C. Zambelli, P. Olivo, E. Perez, Ch. Wenger, D. Ielmini
IEEE Nanotechnology Magazine 16(2), 4 (2022)
DOI: 10.1109/MNANO.2022.3141515, (KI-IoT)
In-memory computing (IMC) is one of the most promising candidates for data-intensive computing accelerators of machine learning (ML). A key ML algorithm for dimensionality reduction and classification is the principal component analysis (PCA), which heavily relies on matrix-vector multiplications (MVM) for which classic von Neumann architectures are not optimized. Here, we provide the experimental demonstration of a new IMC-based PCA algorithm based on power iteration and deflation executed in a 4-kbit array of resistive switching randomaccess memory (RRAM). The classification accuracy of Wisconsin Breast Cancer dataset reaches 95.43%, close to floating-point implementation. Our simulations indicate a 250x improvement in energy efficiency compared to commercial graphic processing units (GPUs), thus supporting IMC for energy-efficient ML in modern data-intensive computing.

(28) In-Memory Principal Component Analysis by Crosspoint Array of Rresistive Switching Memory: A New Hardware Approach for Energy-Efficient Data Analysis in Edge Computing
P. Mannocci, A. Baroni, E. Melacarne, C. Zambelli, P. Olivo, E. Perez, Ch. Wenger, D. Ielmini
IEEE Nanotechnology Magazine 16(2), 4 (2022)
DOI: 10.1109/MNANO.2022.3141515, (Neutronics)
In-memory computing (IMC) is one of the most promising candidates for data-intensive computing accelerators of machine learning (ML). A key ML algorithm for dimensionality reduction and classification is the principal component analysis (PCA), which heavily relies on matrix-vector multiplications (MVM) for which classic von Neumann architectures are not optimized. Here, we provide the experimental demonstration of a new IMC-based PCA algorithm based on power iteration and deflation executed in a 4-kbit array of resistive switching randomaccess memory (RRAM). The classification accuracy of Wisconsin Breast Cancer dataset reaches 95.43%, close to floating-point implementation. Our simulations indicate a 250x improvement in energy efficiency compared to commercial graphic processing units (GPUs), thus supporting IMC for energy-efficient ML in modern data-intensive computing.

(29) In-Memory Principal Component Analysis by Crosspoint Array of Rresistive Switching Memory: A New Hardware Approach for Energy-Efficient Data Analysis in Edge Computing
P. Mannocci, A. Baroni, E. Melacarne, C. Zambelli, P. Olivo, E. Perez, Ch. Wenger, D. Ielmini
IEEE Nanotechnology Magazine 16(2), 4 (2022)
DOI: 10.1109/MNANO.2022.3141515, (Total Resilience)
In-memory computing (IMC) is one of the most promising candidates for data-intensive computing accelerators of machine learning (ML). A key ML algorithm for dimensionality reduction and classification is the principal component analysis (PCA), which heavily relies on matrix-vector multiplications (MVM) for which classic von Neumann architectures are not optimized. Here, we provide the experimental demonstration of a new IMC-based PCA algorithm based on power iteration and deflation executed in a 4-kbit array of resistive switching randomaccess memory (RRAM). The classification accuracy of Wisconsin Breast Cancer dataset reaches 95.43%, close to floating-point implementation. Our simulations indicate a 250x improvement in energy efficiency compared to commercial graphic processing units (GPUs), thus supporting IMC for energy-efficient ML in modern data-intensive computing.

(30) Low-Frequency Phonon Modes in Layered Silver-Bismuth Double Perovskites: Symmetry, Polarity, and Relation to Phase Transitions
B. Martin-Garcia, D. Spirito, M.-L. Lin, Y.-C. Leng, S. Artyukhin, P.-H. Tan, R. Krahne
Advanced Optical Materials 10(14), 2200240 (2022)
DOI: 10.1002/adom.202200240
Metal-halide perovskites (PSKs) are emergent materials for a large range of applications, and the layered double PSK architectures vastly enrich the opportunities to design their composition, structural properties, and optoelectronic behavior. The stability, crystal phase, and electronic bandgap depend strongly on the bonds and distortions of the octahedra lattice that are at the origin of the vibrational spectrum of these materials. This work investigates the structural dynamics of flakes of exfoliated layered Ag-Bi bromide double PSKs by angle-dependent polarized Raman spectroscopy and density functional theory modeling. The well-defined orientation of the inorganic octahedra lattice with respect to the light polarization allows to correlate the angle-dependent intensity of the Raman signal to the directionality and symmetry of the phonon modes. Low-frequency vibrations are revealed for which a detailed microscopic and group theory assignment of the Raman modes is provided. The temperature-dependent measurements across the phase transitions show marked changes in the phonon frequencies, reveal soft modes, and help to distinguish first from second-order transitions as well as to determine their transition temperature. This provides highly valuable insights to improve the properties of this class of Pb-free PSKs for applications in energy harvesting and optoelectronics.

(31) Kafka-ML: Connecting the Data Stream with ML/AI Frameworks
Ch. Martin, P. Langendörfer, P.S. Zarrin, M. Diaz, B. Rubio
Future Generation Computer Systems 126, 15 (2022)
DOI: 10.1016/j.future.2021.07.037
Machine Learning (ML) and Artificial Intelligence (AI) depend on data sources to train, improve, and make predictions through their algorithms. With the digital revolution and current paradigms like the Internet of Things, this information is turning from static data to continuous data streams. However, most of the ML/AI frameworks used nowadays are not fully prepared for this revolution. In this paper, we propose Kafka-ML, a novel and open-source framework that enables the management of ML/AI pipelines through data streams. Kafka-ML provides an accessible and user-friendly Web user interface where users can easily define ML models, to then train, evaluate, and deploy them for inferences. Kafka-ML itself and the components it deploys are fully managed through containerization technologies, which ensure their portability, easy distribution, and other features such as fault-tolerance and high availability. Finally, a novel approach has been introduced to manage and reuse data streams, which may eliminate the need for data storage or file systems.

(32) Modeling and Design of an Electrically Pumped SiGeSn Microring Laser
B. Marzban, L. Seidel, V. Kiyek, T. Liu, M.H. Zoellner, Z. Ikonic, G. Capellini, D. Buca, J. Schulze, M. Oehme, J. Witzens
Proc. SPIE Photonics West (2022), 12006, 12006K (2022)
DOI: 10.1117/12.2609537, (DFG GeSn Laser)

(33) Solid-State Photoluminescent Quantum Dots for Explosive Detection
F. Mitri, A. De Iacovo, S. De Santis, C. Giansante, D. Spirito, G. Sotgiu, L. Colace
Proc. 10th International Conference on Photonics, Optics and Laser Technology (Photoptics 2022), 48 (2022)
DOI: 10.5220/0010870300003121

(34) In-Depth Characterization of Switching Dynamics in Amorphous HfO2 Memristive Arrays for the Implementation of Synaptic Updating Rules
E. Perez, M.K. Mahadevaiah, E. Perez-Bosch Quesada, Ch. Wenger
Japanese Journal of Applied Physics 61(SM), SM1007 (2022)
DOI: 10.1109/TED.2021.3072868, (NeuroMem)
Accomplishing truly analog conductance modulation in memristive arrays is crucial in order to implement the synaptic plasticity in hardware-based neuromorphic systems. In this paper, such a feature was addressed by exploiting the inherent stochasticity of switching dynamics in amorphous HfO2 technology. A thorough statistical analysis of experimental characteristics measured in 4 kbit arrays by using trains of identical depression/ potentiation pulses with different voltage amplitudes and pulse widths provided the key to develop two different updating rules and to define their optimal programming parameters. The first rule is based on applying a specific number of identical pulses until the conductance value achieves the desired level. The second one utilized only one single pulse with a particular amplitude to achieve the targeted conductance level. In addition, all the results provided by the statistical analysis performed may play an important role in understanding better the switching behavior of this particular technology.

(35) In-Depth Characterization of Switching Dynamics in Amorphous HfO2 Memristive Arrays for the Implementation of Synaptic Updating Rules
E. Perez, M.K. Mahadevaiah, E. Perez-Bosch Quesada, Ch. Wenger
Japanese Journal of Applied Physics 61(SM), SM1007 (2022)
DOI: 10.1109/TED.2021.3072868, (Neutronics)
Accomplishing truly analog conductance modulation in memristive arrays is crucial in order to implement the synaptic plasticity in hardware-based neuromorphic systems. In this paper, such a feature was addressed by exploiting the inherent stochasticity of switching dynamics in amorphous HfO2 technology. A thorough statistical analysis of experimental characteristics measured in 4 kbit arrays by using trains of identical depression/ potentiation pulses with different voltage amplitudes and pulse widths provided the key to develop two different updating rules and to define their optimal programming parameters. The first rule is based on applying a specific number of identical pulses until the conductance value achieves the desired level. The second one utilized only one single pulse with a particular amplitude to achieve the targeted conductance level. In addition, all the results provided by the statistical analysis performed may play an important role in understanding better the switching behavior of this particular technology.

(36) In-Depth Characterization of Switching Dynamics in Amorphous HfO2 Memristive Arrays for the Implementation of Synaptic Updating Rules
E. Perez, M.K. Mahadevaiah, E. Perez-Bosch Quesada, Ch. Wenger
Japanese Journal of Applied Physics 61(SM), SM1007 (2022)
DOI: 10.1109/TED.2021.3072868, (KI-IoT)
Accomplishing truly analog conductance modulation in memristive arrays is crucial in order to implement the synaptic plasticity in hardware-based neuromorphic systems. In this paper, such a feature was addressed by exploiting the inherent stochasticity of switching dynamics in amorphous HfO2 technology. A thorough statistical analysis of experimental characteristics measured in 4 kbit arrays by using trains of identical depression/ potentiation pulses with different voltage amplitudes and pulse widths provided the key to develop two different updating rules and to define their optimal programming parameters. The first rule is based on applying a specific number of identical pulses until the conductance value achieves the desired level. The second one utilized only one single pulse with a particular amplitude to achieve the targeted conductance level. In addition, all the results provided by the statistical analysis performed may play an important role in understanding better the switching behavior of this particular technology.

(37) Activity of AC Electrokinetically Immobilized Horseradish Peroxidase
M. Prüfer, Ch. Wenger, F.F. Bier, E.-M. Laux, R. Hölzel
Electrophoresis
DOI: 10.1002/elps.202200073, (exosurf)
Dielectrophoresis (DEP) is an AC electrokinetic effect mainly used to manipulate cells. Smaller particles, like virions, antibodies, enzymes and even dye molecules can be immobilized by DEP as well. In principle, it was shown that enzymes are active after immobilization by DEP, but no quantification of the retained activity was reported so far. In this study, the activity of the enzyme horseradish peroxidase (HRP) is quantified after immobilization by DEP. For this, HRP is immobilized on regular arrays of titanium nitride ring electrodes of 500 nm diameter and 20 nm widths. The activity of HRP on the electrode chip is measured with a limit of detection of 60 fg HRP by observing the enzymatic turnover of Amplex Red and H2O2 to fluorescent resorufin by fluorescence microscopy. The initial activity of the permanently immobilized HRP equals up to 45% of the activity that can be expected for an ideal monolayer of HRP molecules on all electrodes of the array. Localization of the immobilizate on the electrodes is accomplished by staining with the fluorescent product of the enzyme reaction. The high residual activity of enzymes after AC field induced immobilization shows the method's suitability for biosensing and research applications.

(38) Mixed Dimethylammonium/Methylammonium Lead Halide Perovskite Single Crystals for Improved Structural Stability and Enhanced Photodetection
A. Ray, B. Martin-Garcia, A. Moliterni, N. Casati, K. Moorthy Boopathi, D. Spirito, L. Goldoni, C. Giacobbe, C. Giannini, F. Di Stasio, R. Krahne, L. Manna, A.L. Abdelhady
Advanced Materials 34(7), 2106160 (2022)
DOI: 10.1002/adma.202106160
The solvent acidolysis crystallization technique is utilized to grow mixed dimethylammonium/methylammonium lead tribromide (DMA/MAPbBr3) crystals reaching the highest dimethylammonium incorporation of 44% while maintaining the 3D cubic perovskite phase. These mixed perovskite crystals show suppression of the orthorhombic phase and a lower tetragonal-to-cubic phase-transition temperature compared to MAPbBr3. A distinct behavior is observed in the temperature-dependent photoluminescence properties of MAPbBr3 and mixed DMA/MAPbBr3 crystals due to the different organic cation dynamics governing the phase transition(s). Furthermore, lateral photodetectors based on these crystals show that, at room temperature, the mixed crystals possess higher detectivity compared to MAPbBr3 crystals caused by structural compression and reduced surface trap density. Remarkably, the mixed-crystal devices exhibit large enhancement in their detectivity below the phase-transition temperature (at 200 K), while for the MAPbBr3 devices only insignificant changes are observed. The high detectivity of the mixed crystals makes them attractive for visible-light communication and for space applications. The results highlight the importance of the synthetic technique for compositional engineering of halide perovskites that governs their structural and optoelectronic properties.

(39) New Insights Into the Electronic States of the Ge(001) Surface by Joint Angle-Resolved Photoelectron Spectroscopy and First-Principle Calculation Investigation
F. Reichmann, E. Scalise, A.P. Becker, E.V.S. Hofmann, J. Dabrowski, F. Montalenti, L. Miglio, M. Mulazzi, W.M. Klesse, G. Capellini
Applied Surface Science 571, 151264 (2022)
DOI: 10.1016/j.apsusc.2021.151264
While the Ge(001) surface has been extensively studied, it is still debated whether it is of conducting or semiconducting nature at room temperature. The evidence collected by angle-resolved photoelectron spectroscopy experiments in the past has led to the preliminary attribution of a semiconducting nature at room temperature. In contrast, we show in this work that the pristine Ge(001) surface is conducting at room temperature by using temperature-dependent angle-resolved photoelectron spectroscopy, scanning tunneling microscopy and first principles calculations. Specifically, a surface band located ∼200 meV above the valence band maximum has been observed at room temperature. This surface band shows anisotropic dispersions along the [0 1 0] and [1 1 0] directions, but it disappears at lower measurement temperature, which indicates its occupation by thermally excited electrons. State-of-the-art density functional theory calculations undoubtedly attribute this surface band to the unoccupied π*-band formed by dangling bonds on the c(4 × 2) surface reconstruction, while evidencing fundamental differences with the p(2 × 1) reconstruction. Furthermore, the calculations demonstrate that the valence band structure observed in angle-resolved photoelectron spectroscopy experiments arise from projected bulk states and is thus insensitive to surface contamination. Our results contribute to the fundamental knowledge of the Ge(001) surface and to a better understanding of its role in micro- and opto-electronic devices.

(40) Experimental and Theoretical Investigation of the Surface Electronic Structure of ZnGa2O4(100) Single-Crystals
F. Reichmann, J. Dabrowski, A.P. Becker, W.M. Klesse, K. Irmscher, R. Schewski, Z. Galazka, M. Mulazzi
Physica Status Solidi B 259(3), 2100452 (2022)
DOI: 10.1002/pssb.202100452
A detailed experimental and theoretical investigation on the surface electronic structure of ZnGa2O4(100) bulk single-crystals, with a special emphasis on the surface preparation, is presented in this article. The surface crystallizes in the bulk-derived structure, even at low annealing temperatures. Thermal treatments in ultra-high vacuum have detrimental effects, as they cannot remove the carbon contamination and induce substantial zinc losses, further exacerbated by sputtering. A short sputtering duration and annealing in oxygen atmosphere dramatically reduce the zinc and oxygen losses in the crystal surface, leading to a contamination-free, crystalline surface of nearly stoichiometric composition. The investigation of the valence states along the high symmetry directions of the Brillouin zone compares favorably with ab initio pseudopotential calculations, indicating a good surface quality and overall agreement with theory. An in-depth analysis of the measured and simulated valence band peak intensities reveals difficulties associated with the precise description of the metal-oxygen hybridization. This study provides a first fundamental understanding of the electronic structure of ZnGa2O4, while also indicating that the surface thermal instability is a challenging task that should be taken into account for the fabrication of heterostructures based on ZnGa2O4.

(41) Modification of the Ge(001) Subsurface Electronic Structure after Adsorption of Sn
F. Reichmann, A.P. Becker, E.V.S. Hofmann, N.J. Curson, W.M. Klesse, G. Capellini
Applied Surface Science 599, 153884 (2022)
DOI: 10.1016/j.apsusc.2022.153884
In this work, we investigate how the electronic structure of the Ge(001) surface is modified by the adsorption of Sn atoms. We extend a previously established growth model of the Sn wetting layer formation on Ge(001) with a detailed analysis of surface core-level shifts, observing a prevalence of symmetric Sn ad-dimers at a Sn coverage above 1 ML. The valence band structure of Ge(001) features reveals the appearance of a non-dispersive electronic state after the adsorption of Sn. We correlate the presence of this state to the interaction of electronic states from a Sn ad-dimer configuration with the surface resonances of the Ge up-dimer. Post-deposition annealing leads to full incorporation of Sn and, consequently, to the disappearance of valence band state attributable to Sn ad-atoms. Notably, the adsorption and/or incorporation of Sn removes a Ge(001) surface state above the valence band maximum. The Fermi-level remains pinned close to the valence band maximum, indicating the initial stages of a Schottky barrier formation. Overall, these results provide new fundamental insights into the electronic structure of Sn on Ge(001), crucial for the development of SnGe electronics devices, and more generally of use for understanding the controlled alloying of isoelectronic layered materials.

(42) Tailoring Photoluminescence by Strain-Engineering in Layered Perovskite Flakes
D. Spirito, M. Barra-Burillo, F. Calavalle, C.L. Manganelli, M. Gobbi, R. Hillenbrand, F. Casanova, L. Hueso, B. Martin-Garcia
Nano Letters 22(10), 4153 (2022)
DOI: 10.1021/acs.nanolett.2c00909
Strain is an effective strategy to modulate the optoelectronic properties of 2D materials, but it has been almost unexplored in layered hybrid organic–inorganic metal halide perovskites (HOIPs) due to their complex band structure and mechanical properties. Here, we investigate the temperature-dependent microphotoluminescence (PL) of 2D (C6H5CH2CH2NH3)2Cs3Pb4Br13 HOIP subject to biaxial strain induced by a SiO2 ring platform on which flakes are placed by viscoelastic stamping. At 80 K, we found that a strain of <1% can change the PL emission from a single peak (unstrained) to three well-resolved peaks. Supported by micro-Raman spectroscopy, we show that the thermomechanically generated strain modulates the bandgap due to changes in the octahedral tilting and lattice expansion. Mechanical simulations demonstrate the coexistence of tensile and compressive strain along the flake. The observed PL peaks add an interesting feature to the rich phenomenology of photoluminescence in 2D HOIPs, which can be exploited in tailored sensing and optoelectronic devices.

(43) Raman Spectroscopy in Layered Hybrid Organic-Inorganic Metal Halide Perovskites
D. Spirito, Y. Asensio, L.E. Hueso, B. Martín-García
Journal of Physics: Materials 5(3), 034004 (2022)
DOI: 10.1088/2515-7639/ac7977
The continuous progress in the synthesis and characterization of materials in the vast family of hybrid organic-inorganic metal halide perovskites (HOIPs) has been pushed by their exceptional properties mainly in optoelectronic applications. These works highlight the peculiar role of lattice vibrations, which strongly interact with electrons, resulting in coupled states affecting the optical properties. Among these materials, layered (2D) HOIPs have emerged as a promising material platform to address some issues of their three-dimensional counterparts, such as ambient stability and ion migration. Layered HOIPs consist of inorganic layers made of metal halide octahedra separated by layers composed of organic cations. They have attracted much interest not only for applications, but also for their rich phenomenology due to their crystal structure tunability. Here, we give an overview of the main experimental findings achieved via Raman spectroscopy in several configurations and set-ups, and how they contribute to shedding light on the complex structural nature of these fascinating materials. We focus on how the phonon spectrum comes from the interplay of several factors. First, the inorganic and organic parts, whose motions are coupled, contribute with their typical modes which are very different in energy. Nonetheless, the interaction between them is relevant, as it results in low-symmetry crystal structures. Then, the role of external stimuli, such as temperature and pressure, which induce phase transitions affecting the spectrum through change in symmetry of the lattice, octahedral tilting and arrangement of the molecules. Finally, the relevant role of the coupling between the charge carriers and optical phonons is highlighted.

(44)
sSNOM Characterization of the IR-active Vibrational Mode in Highly Strained hBN

D. Spirito, E. Blundo, A. Surrente, G. Pettinari, T. Yildirim, C.A. Chavarin, M. Felici, A. Polimeni, L. Baldassarre
Proc. 47th International Conference on Infrared, Millimeter and Terahertz Waves (IRMMW-THz 2022), (2022)

(45) AC Electrokinetic Immobilization of Influenza Virus
S. Stanke, Ch. Wenger,, F.F. Bier, R. Hölzel
Electrophoresis 43(12), 1309 (2022)
DOI: 10.1002/elps.202100324, (BioBic)
The use of alternating current (AC) electrokinetic forces, like dielectrophoresis and AC electroosmosis, as a simple and fast method to immobilize sub-micrometer objects onto nanoelectrode arrays is presented. Due to its medical relevance, the influenza virus is chosen as a model organism. One of the outstanding features is that the immobilization of viral material to the electrodes can be achieved permanently, allowing subsequent handling independently from the electrical setup. Thus, by using merely electric fields, we demonstrate that the need of prior chemical surface modification could become obsolete. The accumulation of viral material over time is observed by fluorescence microscopy. The influences of side effects like electrothermal fluid flow, causing a fluid motion above the electrodes and causing an intensity gradient within the electrode array, are discussed. Due to the improved resolution by combining fluorescence microscopy with deconvolution, it is shown that the viral material is mainly drawn to the electrode edge and to a lesser extent to the electrode surface. Finally, areas of application for this functionalization technique are presented.

(46) A Novel Graphene Adjustable-Barriers Transistor with Ultra-High Current Gain
C. Strobel, C.A. Chavarin, K. Richter, M. Knaut, J. Reif, S. Völkel, A. Jahn, M. Albert, Ch. Wenger, R. Kirchner, J.W. Bartha, T. Mikolajick
ACS Applied Materials & Interfaces 14(34), 39249 (2022)
(FFLEXCOM (D020))
A graphene-based three-terminal Barristor device was proposed to overcome the low on/off ratios and insufficient current saturation of conventional graphene field-effect transistors. In this study, we fabricated and analyzed a novel graphene-based transistor which resembles the structure of the Barristor but uses a different operation condition. This new device, termed graphene adjustable-barriers transistor (GABT), utilizes a semiconductor-based gate rather than a metal-insulator gate structure to modulate the device currents. The key feature of the device are two graphene-semiconductor Schottky barriers with different heights which are controlled simultaneously by the gate voltage. Due to the asymmetry of the barriers the drain current exceeds the gate current by several orders of magnitude. Thus, the GABT can be considered as an amplifier with an alterable current gain. In this work, a silicon-graphene-germanium GABT with an ultra-high current gain (ID/Iup to 8.106) was fabricated and the device functionality was demonstrated. Additionally, a capacitance model is applied to predict the theoretical device performance resulting in an on-off ratio above 106, a subthreshold swing of 66 mV/dec. and a drive current of about 1x10A/cm².

(47) Improved Graphene-Base Heterojunction Transistor with Different Collector Semi­conductors for High-Frequency Applications
C. Strobel, C.A. Chavarin, S. Leszczynski, K. Richter, M. Knaut, J. Reif, S. Völkel, M. Albert, Ch. Wenger, J.W. Bartha,T. Mikolajick
Advanced Materials Letters 13(1), 011688 (2022)
DOI: 10.5185/amlett.2022.011688, (FFLEXCOM (D020))

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