Publications 2025
Script list Publications
(1) Hardware-Friendly Nyström Approximation for Water Treatment Anomaly Detection
M. Aftowicz, M. Fritscher, K. Lehniger, Ch. Wenger, P. Langendörfer, M. Brzozowski
Proc. 50th IEEE Industrial Electronics Society (IECON 2024), (2025)
DOI: 10.1109/IECON55916.2024.10905880, (KISS-KI)
(2) Enhanced Response and Recovery Observed in CNTs Gas Sensor using ZnO/HfO2 Bilayer Memristor Heater
M. Ali, D. Lee, I. Ahmad, M. Chae, K.H. Kim, H.–D. Kim
Sensors and Actuators B: Chemical 431, 137403 (2025)
DOI: 10.1016/j.snb.2025.137403
In carbon nanotubes (CNTs) based gas sensors, external energy sources are used to enhance the response and recovery characteristics, However, they have significant energy consumption and are constrained by size limitations. In this work, to solve them, we propose a ZnO/HfO2 bilayer–memristor heater (MH) embedded CNTs gas sensor. Firstly, when tuning the thickness of ZnO in the MH, we observed a thickness dependency in the response characteristic, which can be explained by the variation in the gap of the ruptured conduction filament (CF). As a result, the 70 nm–ZnO MH, which had the longest gap between the ruptured CF and the CNTs layer, demonstrated the highest response of 58.3%. This response is 54.1% higher than that of the conventional CNTs gas sensor. In addition, in a pulse recovery study, we observed that the MH–embedded CNTs gas sensor returned to its initial state within only 1 ms after gas detection, which is 35ⅹ105 times faster than a conventional CNTs sensor. These results indicate that the heating caused by the MH can effectively raise the temperature of the insulator near its surface, meaning that MH can be a good candidate as a heater in the microscale gas sensors.
(3) Comparing Short and Long-Term Reliability of HfO2 and Al:HfO2 RRAM Devices
A. Baroni, E. Pérez, K.D.S. Reddy, S. Pechmann, Ch. Wenger, D. Ielmini, C. Zambelli
Proc. IEEE International Integrated Reliability Workshop (IIRW 2024), (2025)
DOI: 10.1109/IIRW62856.2024.10947134
(4) Optimized Two-Step Growth of Large Surface Two-Dimensional Boron Nitride on Ge (001) Films by Molecular Beam Epitaxy
W. Batista-Pessoa, M. Franck, N. Nuns, J. Dabrowski, M. Achehboune, J.-F. Colomer, L. Henrard, M. Lukosius, X. Wallart, D. Vignaud
Applied Surface Science 699, 163165 (2025)
DOI: 10.1016/j.apsusc.2025.163165, (2DHetero)
The growth of two-dimensional boron nitride (2D-BN) thin films on Ge (001) has been studied, with the ultimate goal of integrating this material into Si technology. Molecular beam epitaxy was used in a dedicated ultra-high vacuum chamber. To avoid the formation of thermal pits on heating the Ge film above ∼ 760 °C, a two-step procedure was optimized. A thin 2D-BN buffer layer is first grown at ∼ 730 °C using two independent cells for B and N, aimed at stabilizing the Ge surface and to prevent thermal pits formation upon further heating. The second-step at 800 °C makes use of another precursor, gaseous borazine, in the same chamber. The growth proceeds in a step-flow mode, and results in homogeneous nano-crystalline large-surface 2D-BN films with a ∼ 1 nm roughness.
(5) Correlation between Linear Conductance Variability and Accuracy in Neuromorphic Computing using AuNP-DNA/HfO2 Bilayer Memristor Devices
M. Chae, D. Lee, H. Lee, Y. Jang, T. Kim, Y. Kim, H.-D. Kim
Measurement 248, 116960 (2025)
DOI: 10.1016/j.measurement.2025.116960
Memristor-based neuromorphic computing needs to improve energy efficiency using eco-friendly materials, but a single active layer with traditional materials still requires an improvement in reliability and performance. We propose a bilayers-memristor with gold nanoparticle (AuNP)-DNA for artificial synapse applications. As a result, the HfO2/AuNP-DNA-based memristor exhibits excellent linear weight update and large conductance ratio characteristics with high reliability and tunability. The high linearity of synaptic weights, achieved through simple programming according to pulse amplitude, can particularly enhance the device’s energy efficiency and learning accuracy in neural network applications. We assess the accuracy of the modified national institute of standards and technology simulations to compare the classification accuracy depending on linearity and the ratio of weight update. As a result, the smallest validation loss is observed at –7 V depression voltage, which has the best linearity and optimal conductance ratio, suggesting the potential application of the proposed memristor in neuromorphic computing.
(6) Impact of Biased Cooling on the Operation of Undoped Silicon Quantum Well Field-Effect Devices for Quantum Circuit Applications
L.K. Diebel, L.G. Zinkl, A. Hötzinger, F. Reichmann, M. Lisker, Y. Yamamoto, D. Bougeard
AIP Advances 15(3), 035301 (2025)
DOI: 10.1063/5.0250968, (QUASAR)
Gate-tunable semiconductor nanosystems are getting more and more important in the realization of quantum circuits. While such devices are typically cooled to operation temperature with zero bias applied to the gate, biased cooling corresponds to a non-zero gate voltage being applied before reaching the operation temperature. We systematically study the effect of biased cooling on different undoped SiGe/Si/SiGe quantum well field-effect stacks designed to accumulate and density-tune two-dimensional electron gases (2DEGs). In an empirical model, we show that biased cooling of the undoped FES induces a static electric field, which is constant at operation temperature and superimposes onto the field exerted by the top gate onto the 2DEG. We show that the voltage operation window of the field-effect-tuned 2DEG can be chosen in a wide range of voltages via the choice of the biased cooling voltage. Importantly, quality features of the 2DEG such as the mobility or the temporal stability of the 2DEG density remain unaltered under biased cooling.
(7) Investigating Impacts of Local Pressure and Temperature on CVD Growth of Hexagonal Boron Nitride on Ge(001)/Si
M. Franck, J. Dabrowski, M.A. Schubert. D. Vignaud, M. Achehboune, J.-F. Colomer, L. Henrard, Ch. Wenger, M. Lukosius
Advanced Materials Interfaces 12(1), 2400467 (2025)
DOI: 10.1002/admi.202400467, (2DHetero)
The chemical vapor deposition (CVD) growth of hexagonal boron nitride (hBN) on Ge substrates is a promising pathway to high-quality hBN thin films without metal contaminations for microelectronic applications, but the effect of CVD process parameters on the hBN properties is not well understood yet. The influence of local changes in pressure and temperature due to different reactor configurations on the structure and quality of hBN films grown on Ge(001)/Si is studied. Injection of the borazine precursor close to the sample surface results in an inhomogeneous film thickness, attributed to an inhomogeneous pressure distribution at the surface, as shown by computational fluid dynamics simulations. The additional formation of nanocrystalline islands is attributed to unfavorable gas phase reactions due to the radiative heating of the injector. Both issues are mitigated by increasing the injector-sample distance, leading to an 86% reduction in pressure variability on the sample surface and a 200 °C reduction in precursor temperature. The resulting hBN films exhibit no nanocrystalline islands, improved thickness homogeneity, and high crystalline quality (Raman FWHM = 23 cm−1). This is competitive with hBN films grown on other non-metal substrates but achieved at lower temperature and with a low thickness of only a few nanometers.
(8) Sensing of Hemin Binding to Albumin using Ge-based Plasmonic Antennas Operating in the THz Range
E. Hardt, R. Varricchio, C.A. Chavarin, G. De Simone, O. Skibitzki, P. Ascenzi, A. di Masi, G. Capellini
IEEE Sensors Journal 25(8), 12881 (2025)
DOI: 10.1109/JSEN.2025.3545736, (iCampus II)
Albumin-based biofunctionalized biosensors have the potential to be utilized for the detection of physiological ligands (e.g., heme) and of pathogenic proteins. In human cells, heme is always bound to proteins due to its toxic nature. However, free heme can be present within tissue and in the bloodstream as a consequence of hemolysis or under pathological conditions like malaria or sickle cell anemia. Therefore, the development of an albumin-based heme biosensor could be relevant from a biomedical viewpoint. In this study, we developed a protein-sensing platform by immobilizing albumin on CMOS-compatible Ge-based THz plasmonic antennas via drop-cast biofunctionalization. To set up the biosensor, the sensing platform was used to quantitatively measure the binding of hemin, a well-known physiological ligand of albumin. This measurement was performed using THz time-domain spectroscopy in dichroic transmission mode, achieving a sensitivity of approximately ~ 200 GHz/mM of the HSA:hemin complex. These preliminary results support the use of CMOS-compatible Ge-based THz plasmonic antennas as innovative sensors that could be monolithically integrated with conventional electronics for storage, processing, and communication into an all-in-one system.
(9) Sensing of Hemin Binding to Albumin using Ge-based Plasmonic Antennas Operating in the THz Range
E. Hardt, R. Varricchio, C.A. Chavarin, G. De Simone, O. Skibitzki, P. Ascenzi, A. di Masi, G. Capellini
IEEE Sensors Journal 25(8), 12881 (2025)
DOI: 10.1109/JSEN.2025.3545736, (IHP- Roma Tre University Joint Lab)
Albumin-based biofunctionalized biosensors have the potential to be utilized for the detection of physiological ligands (e.g., heme) and of pathogenic proteins. In human cells, heme is always bound to proteins due to its toxic nature. However, free heme can be present within tissue and in the bloodstream as a consequence of hemolysis or under pathological conditions like malaria or sickle cell anemia. Therefore, the development of an albumin-based heme biosensor could be relevant from a biomedical viewpoint. In this study, we developed a protein-sensing platform by immobilizing albumin on CMOS-compatible Ge-based THz plasmonic antennas via drop-cast biofunctionalization. To set up the biosensor, the sensing platform was used to quantitatively measure the binding of hemin, a well-known physiological ligand of albumin. This measurement was performed using THz time-domain spectroscopy in dichroic transmission mode, achieving a sensitivity of approximately ~ 200 GHz/mM of the HSA:hemin complex. These preliminary results support the use of CMOS-compatible Ge-based THz plasmonic antennas as innovative sensors that could be monolithically integrated with conventional electronics for storage, processing, and communication into an all-in-one system.
(10) The Effects of Short-Term Air Exposure of the Monocrystal HfSe2 Surface
K. Kwiecien, J. Raczyński, A. Puchalska, E. Nowak, E. Chłopocka, D. Kot, M. Szybowicz, L. Jurczyszyn, W. Koczorowski
Applied Surface Science 690, 162546 (2025)
DOI: 10.1016/j.apsusc.2025.162546
We report the impact of short-term sequential exposure to air–atmosphere conditions on the mechanically exfoliated surface of HfSe2 monocrystal. Our scanning electron microscopy studies show the early surface oxidation dynamics with a rapid increase of the Se-rich blister coverage. Further X-ray photoemission and energy dispersive spectroscopy measurements reveal a progressive diffusion of O atoms into the bulk and HfO2 layer formation on the surface during the exposure time. Finally, Raman spectroscopy measurements confirm the coexistence of HfSe2 and HfO2 on the surface. However, the Raman spectroscopy technique does not allow quantitative determination of the degree of short-term surface oxidation. Additionally, we confirm the conclusions drawn from the experimental results with the results of the density functional theory calculations of the O/HfSe2 adsorption system. The presented results hold substantial technological significance from the point of view of the application of HfSe2 in electronics by filling the gap in the early oxidation dynamics under ambient conditions.
(11) Electrically Pumped GeSn Micro-Ring Lasers
T. Liu, L. Seidel, O. Concepcion, V. Reboud, A. Chelnokov, G. Capellini, M. Oehme, D. Grützmacher, D. Buca
IEEE Journal of Selected Topics in Quantum Electronics 31(1), 8100307 (2025)
DOI: 10.1109/JSTQE.2024.3489712, (DFG GeSn Laser)
Recent progress in the quest for CMOS-integrable GeSn light sources comprises the optically-pumped laser operating at room temperature and the first demonstrations of electrically pumped lasers. In this work, the performance of electrically-pumped double heterostructure GeSn ring laser diodes are evaluated as a function of their geometry and pumping pulse time. In particular, the trade-off between the band structure, i.e. the directness of the GeSn band gap, and the device heat dissipation is discussed in terms of their impact on the emission intensity and threshold current density.
(12) A Statistical and Modeling Study on the Effects of Radiation on Au/Ta/ZrO2(Y)/Pt/Ti Memristive Devices
D. Maldonado, A. Cantudo, D.V. Guseinov, M.N. Koryazhkina,, E.V. Okulich, D.I. Tetelbaum, N.O. Bartev, N.G. Danchenko, V.A. Pikar, A.V. Teterevkov, F. Jiménez-Molinos, A.N. Mikhaylov, J.B. Roldán
Chaos, Solitons & Fractals 191, 115909 (2025)
DOI: 10.1016/j.chaos.2024.115909
In this study we have investigated the impact of radiation on the performance and reliability of Au/Ta/ZrO2(Y)/Pt/Ti memristive devices, with a particular focus on understanding the changes induced by ion irradiation. A comprehensive experimental approach was employed, involving irradiation with various ion species, including H⁺, Ne⁺, O⁺, and Kr⁺ to simulate different radiation environments. Thus, advanced statistical and modeling techniques to analyze the effects of irradiation on the resistive switching (RS) characteristics of the devices have been employed. Results revealed significant alterations in the RS parameters post-irradiation, including set and reset voltages and currents. These changes were found to vary depending on the ion species and dosage, with heavier ions such as Kr⁺ causing more pronounced effects. The findings are supported by detailed Monte Carlo simulations, which provided insights into the distribution of vacancies within the memristive devices under neutron irradiation. The experimental data, combined with the modeling results, indicate that ion irradiation can lead to the formation of defect structures that critically affect the performance of memristive devices.
(13) Strain Engineering in Semiconductor Materials
C.L. Manganelli, D. Spirito, P. Farrell, J. Frigerio, A. De Iacovo, D. Marian, M. Virgilio
Physica Status Solidi - Rapid Research Letters 19(1), 2400383 (2025)
DOI: 10.1002/pssr.202400383
Strain engineering has become an essential strategy in theadvancement of semiconductor technologies, providing a power-ful mean to modulate the electronic, optical, and mechanicalproperties of materials. By introducing controlled deformationinto crystal lattices, this approach enables enhanced carriermobility, tailored bandgap energies, and improved device perfor-mance across applications in photonics, optoelectronics, andquantum technologies.
(14) In Situ X-Ray Photoelectron Spectroscopy Study of Atomic Layer Deposited Cerium Oxide on SiO2: Substrate Influence on the Reaction Mechanism During the Early Stages of Growth
C. Morales, M. Gertig, M. Kot, C.A. Chavarin, M.A. Schubert, M.H. Zoellner, Ch. Wenger, K. Henkel, J.I. Flege
Advanced Materials Interfaces 12(5), 2400537 (2024)
DOI: 10.1002/admi.202400537, (iCampus II)
Thermal atomic layer deposition (ALD) of cerium oxide using commercial Ce(thd)4 precursor and O3 on SiO2 substrates is studied employing in-situ X-ray photoelectron spectroscopy (XPS). The system presents a complex growth behavior determined by the change in the reaction mechanism when the precursor interacts with the substrate or the cerium oxide surface. During the first growth stage, non-ALD side reactions promoted by the substrate affect the growth per cycle, the amount of carbon residue on the surface, and the oxidation degree of cerium oxide. On the contrary, the second growth stage is characterized by a constant growth per cycle in good agreement with the literature, low carbon residues, and almost fully oxidized cerium oxide films. This distinction between two growth regimes is not unique to the CeOx/SiO2 system but can be generalized to other metal oxide substrates. Furthermore, the film growth deviates from the ideal layer-by-layer mode, forming micrometric inhomogeneous and defective flakes that eventually coalesce for deposit thicknesses above 10 nm. The ALD-cerium oxide films present less order and a higher density of defects than films grown by physical vapor deposition techniques, likely affecting their reactivity in oxidizing and reducing conditions.
(15) HyRPF: Hybrid RRAM Prototyping on FPGA
D. Reiser, J. Knödtel, L. Almeeva, J. Wen, A. Baroni, M. Krstic, M. Reichenbach
Proc. 24th International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation (SAMOS 2024) in: Lecture Notes in Computer Science, LNCS 15226, 199 (2025)
DOI: 10.1007/978-3-031-78377-7_14
(16) Analytical Model for Parasitic Resistances of Crossbar Arrays Suitable for Open-Loop Programming Schemes Reliability Analysis
T. Rizzi, T. Zanotti, N. Lepri, E. Pérez, F.M. Puglisi, D. Ielmini, C. Zambelli
Proc. IEEE International Integrated Reliability Workshop (IIRW 2024), (2025)
DOI: 10.1109/IIRW62856.2024.10947147, (HYB-RISC)
(17) Investigation of Dislocations Introduced in Si Wafer During Flash Lamp Annealing by Photoluminescence Spectroscopy
D. Ryzhak, G. Kissinger, A. Ehlert, A. Sattler, D. Spirito, D. Kot
Physica Status Solidi A 222(8), 2400753 (2025)
DOI: 10.1002/pssa.202400753, (Siltronic Project)
Dislocations are generated in Si wafers during flash lamp annealing for 20 ms. The samples have been etched to different depths and macro-photoluminescence (PL) spectra have been recorded for different dislocation densities. A micro-PL investigation is also carried out on a cross section of a sample. Four characteristic emission peaks are found, which are the well-known D1, D2, D3, and D4 lines. The findings demonstrate a significant influence of the defect densities on the PL spectra of the D lines by using both the micro- and the macro-PL setups, and show a correlation of the PL intensities with etch pit density measured against the depth of the wafer. Additionally, the D lines dependency on temperature is explored, offering insights into the underlying mechanisms. The D lines exhibit a pronounced temperature dependence, which can be attributed to various factors including phonon interactions and thermal expansion effects. The influence of nickel contamination is also examined.
(18) AI-Driven Model for Optimized Pulse Programming of Memristive Devices
B. Spetzler, M. Fritscher, S. Park, N. Kim, Ch. Wenger, M. Ziegler
APL Machine Learning 3(2), 026103 (2025)
DOI: 10.1063/5.0251113, (DI-SIGN-HEP)
Next-generation artificial intelligence (AI) hardware based on memristive devices offers a promising approach to reducing the increasingly large energy consumption of AI applications. However, programming memristive AI hardware to achieve a desired synaptic weight configuration remains challenging because it requires accurate and energy-efficient algorithms for selecting the optimal weight-update pulses. Here, we present a computationally efficient AI model for predicting the weight update of memristive devices and guiding device programming. The synaptic weight-update behavior of bilayer HfO2/TiO2 memristive devices is characterized over a range of pulse parameters to provide experimental data for the AI model. Three different artificial neural network (ANN) configurations are trained and evaluated regarding the amount of training data required for accurate predictions and the computational costs. Finally, we apply the model to an antipulse weight-update process to demonstrate its performance. The results show that accurate and computationally inexpensive predictions are possible with comparatively few datasets and small ANNs. The normalized weight-update processes are predicted with accuracies comparable with larger model architectures but require only 896 floating point operations and 8.33 nJ per inference. This makes the model a promising candidate for integration into AI-driven device controllers as a precise and energy-efficient solution for memristive device programming.
(19) AI-Driven Model for Optimized Pulse Programming of Memristive Devices
B. Spetzler, M. Fritscher, S. Park, N. Kim, Ch. Wenger, M. Ziegler
APL Machine Learning 3(2), 026103 (2025)
DOI: 10.1063/5.0251113, (HYB-RISC)
Next-generation artificial intelligence (AI) hardware based on memristive devices offers a promising approach to reducing the increasingly large energy consumption of AI applications. However, programming memristive AI hardware to achieve a desired synaptic weight configuration remains challenging because it requires accurate and energy-efficient algorithms for selecting the optimal weight-update pulses. Here, we present a computationally efficient AI model for predicting the weight update of memristive devices and guiding device programming. The synaptic weight-update behavior of bilayer HfO2/TiO2 memristive devices is characterized over a range of pulse parameters to provide experimental data for the AI model. Three different artificial neural network (ANN) configurations are trained and evaluated regarding the amount of training data required for accurate predictions and the computational costs. Finally, we apply the model to an antipulse weight-update process to demonstrate its performance. The results show that accurate and computationally inexpensive predictions are possible with comparatively few datasets and small ANNs. The normalized weight-update processes are predicted with accuracies comparable with larger model architectures but require only 896 floating point operations and 8.33 nJ per inference. This makes the model a promising candidate for integration into AI-driven device controllers as a precise and energy-efficient solution for memristive device programming.
(20) AI-Driven Model for Optimized Pulse Programming of Memristive Devices
B. Spetzler, M. Fritscher, S. Park, N. Kim, Ch. Wenger, M. Ziegler
APL Machine Learning 3(2), 026103 (2025)
DOI: 10.1063/5.0251113, (6G-RIC)
Next-generation artificial intelligence (AI) hardware based on memristive devices offers a promising approach to reducing the increasingly large energy consumption of AI applications. However, programming memristive AI hardware to achieve a desired synaptic weight configuration remains challenging because it requires accurate and energy-efficient algorithms for selecting the optimal weight-update pulses. Here, we present a computationally efficient AI model for predicting the weight update of memristive devices and guiding device programming. The synaptic weight-update behavior of bilayer HfO2/TiO2 memristive devices is characterized over a range of pulse parameters to provide experimental data for the AI model. Three different artificial neural network (ANN) configurations are trained and evaluated regarding the amount of training data required for accurate predictions and the computational costs. Finally, we apply the model to an antipulse weight-update process to demonstrate its performance. The results show that accurate and computationally inexpensive predictions are possible with comparatively few datasets and small ANNs. The normalized weight-update processes are predicted with accuracies comparable with larger model architectures but require only 896 floating point operations and 8.33 nJ per inference. This makes the model a promising candidate for integration into AI-driven device controllers as a precise and energy-efficient solution for memristive device programming.
(21) RRAMulator: An Efficient FPGA-based Emulator for RRAM Crossbar with Device Variability and Energy Consumption Evaluation
J. Wen, F. Vargas, F. Zhu, D. Reiser, A. Baroni, M. Fritscher, E. Perez, M. Reichenbach, Ch. Wenger, M. Krstic
Microelectronics Reliability 168, 115630 (2025)
DOI: 10.1016/j.microrel.2025.115630, (6G-RIC)
The in-memory computing (IMC) systems based on emerging technologies have gained significant attention due to their potential to enhance performance and energy efficiency by minimizing data movement between memory and processing unit, which is especially beneficial for data-intensive applications. Designing and evaluating systems utilizing emerging memory technologies, such as resistive RAM (RRAM), poses considerable challenges due to the limited support from electronics design automation (EDA) tools for rapid development and design space exploration. Additionally, incorporating technology-dependent variability into system-level simulations is critical to accurately assess the impact on system reliability and performance. To bridge this gap, we propose RRAMulator, a field-programmable gate array (FPGA) based hardware emulator for RRAM crossbar array. To avoid the complex device models capturing the nonlinear current–voltage (IV) relationships that degrade emulation speed and increase hardware utilization, we propose a device and variability modeling approach based on device measurements. We deploy look-up tables (LUTs) for device modeling and use the multivariate kernel density estimation (KDE) method to augment existing data, extending data variety and avoiding repetitive data usage. The proposed emulator achieves cycle-accurate, real-time emulations and provides information such as latency and energy consumption for matrix mapping and vector–matrix multiplications (VMMs). Experimental results show a significant reduction in emulation time compared to conventional behavioral simulations. Additionally, an RRAM-based discrete Fourier transform (DFT) accelerator is analyzed as a case study featuring a range of in-depth system assessments.
(22) Elektronische Nasen
Ch. Wenger
99 Zukunftsobjekte aus der Lausitz, 1st Edition, Editor: J. Staemmler, Ch.Links Verlag, 203 (2025)
(23) Piezoresistivity of Epitaxial SiGe
Y. Yamamoto, W.-C. Wen, N. Inomata, A.A. Corley-Wiciak, D. Ryzhak, C. Corley-Wiciak, Z. Zhijian, R. Sorge, B. Tillack, T. Ono
ECS Journal of Solid State Science and Technology 14(4), 045001 (2025)
DOI: 10.1149/2162-8777/adc488
Piezoresistivity of B- and P-doped epitaxial Si1-xGex (x=10-30%) is investigated to assess its application potential for thin film strain sensors. The gauge factor (GF) is calculated based on the change in resistivity to the externally induced compressive uniaxial strain along the current flow direction. In the case of B-doped SiGe, the resistivity decreases under the induced compressive strain which may be related to hole mobility enhancement, while no influence on the resistivity of the P-doped SiGe. A significant increase in the GF is observed by lowering B concentration. At the same B concentration, slightly higher GF is observed for higher Ge content. Moreover, the GF is slightly improved by lowering the SiGe growth temperature, which may be related to improved crystallinity indicated by capacitance-voltage characteristics of metal-oxide-semiconductor structure using the epitaxial SiGe on Si. These results suggest that the low-doped p-type SiGe deposited at low temperature has reasonable GF and can potentially be applied in strain sensors.
(24) On the Bulk Photovoltaic Effect in the Characterization of the Strained Germanium Microstructures
I. Zaitsev, D. Spirito, J. Frigerio, C.A. Chavarin, A. Lüdge, W. Lüdge. R. Giani, M. Virgilio, C.L. Manganelli
Physica Status Solidi - Rapid Research Letters 19(1), 2400220 (2025)
DOI: 10.1002/pssr.202400220
Strain engineering serves as an effective method for optimizing electronic and optical properties in semiconductor devices, with applications including the enhancement of optical emission in Ge and GeSn-based devices, improvement of carrier mobility, and second harmonic generation in silicon photonics structures. Current methods for deformation characterization in semiconductors, such as XRD and Raman spectroscopy, often require bulky and expensive setups and are limited in vertical resolution. Consequently, techniques capable of measuring lattice strain while overcoming these drawbacks are highly desirable.
This study proposes a proof of concept for a cost-effective, compact, fast, and non-destructive approach to probe non-uniform strain fields and additional material properties by exploiting the bulk photovoltage effect. We benchmark the method with an array of silicon nitride stripes deposited under varying pressure conditions on a germanium substrate. Initially, their surface strains are verified through Raman spectroscopy. The deformations are replicated in a finite element method platform by integrating mechanical simulations with deformation potential theory, thereby estimating the band edge energy landscape.
Finally, the study discusses the theoretical behavior of the photovoltage signal, considering semiconductor properties, defects, doping, and deformation. The findings offer insights into the development of advanced techniques for strain and transport analysis in semiconductor materials.
M. Aftowicz, M. Fritscher, K. Lehniger, Ch. Wenger, P. Langendörfer, M. Brzozowski
Proc. 50th IEEE Industrial Electronics Society (IECON 2024), (2025)
DOI: 10.1109/IECON55916.2024.10905880, (KISS-KI)
(2) Enhanced Response and Recovery Observed in CNTs Gas Sensor using ZnO/HfO2 Bilayer Memristor Heater
M. Ali, D. Lee, I. Ahmad, M. Chae, K.H. Kim, H.–D. Kim
Sensors and Actuators B: Chemical 431, 137403 (2025)
DOI: 10.1016/j.snb.2025.137403
In carbon nanotubes (CNTs) based gas sensors, external energy sources are used to enhance the response and recovery characteristics, However, they have significant energy consumption and are constrained by size limitations. In this work, to solve them, we propose a ZnO/HfO2 bilayer–memristor heater (MH) embedded CNTs gas sensor. Firstly, when tuning the thickness of ZnO in the MH, we observed a thickness dependency in the response characteristic, which can be explained by the variation in the gap of the ruptured conduction filament (CF). As a result, the 70 nm–ZnO MH, which had the longest gap between the ruptured CF and the CNTs layer, demonstrated the highest response of 58.3%. This response is 54.1% higher than that of the conventional CNTs gas sensor. In addition, in a pulse recovery study, we observed that the MH–embedded CNTs gas sensor returned to its initial state within only 1 ms after gas detection, which is 35ⅹ105 times faster than a conventional CNTs sensor. These results indicate that the heating caused by the MH can effectively raise the temperature of the insulator near its surface, meaning that MH can be a good candidate as a heater in the microscale gas sensors.
(3) Comparing Short and Long-Term Reliability of HfO2 and Al:HfO2 RRAM Devices
A. Baroni, E. Pérez, K.D.S. Reddy, S. Pechmann, Ch. Wenger, D. Ielmini, C. Zambelli
Proc. IEEE International Integrated Reliability Workshop (IIRW 2024), (2025)
DOI: 10.1109/IIRW62856.2024.10947134
(4) Optimized Two-Step Growth of Large Surface Two-Dimensional Boron Nitride on Ge (001) Films by Molecular Beam Epitaxy
W. Batista-Pessoa, M. Franck, N. Nuns, J. Dabrowski, M. Achehboune, J.-F. Colomer, L. Henrard, M. Lukosius, X. Wallart, D. Vignaud
Applied Surface Science 699, 163165 (2025)
DOI: 10.1016/j.apsusc.2025.163165, (2DHetero)
The growth of two-dimensional boron nitride (2D-BN) thin films on Ge (001) has been studied, with the ultimate goal of integrating this material into Si technology. Molecular beam epitaxy was used in a dedicated ultra-high vacuum chamber. To avoid the formation of thermal pits on heating the Ge film above ∼ 760 °C, a two-step procedure was optimized. A thin 2D-BN buffer layer is first grown at ∼ 730 °C using two independent cells for B and N, aimed at stabilizing the Ge surface and to prevent thermal pits formation upon further heating. The second-step at 800 °C makes use of another precursor, gaseous borazine, in the same chamber. The growth proceeds in a step-flow mode, and results in homogeneous nano-crystalline large-surface 2D-BN films with a ∼ 1 nm roughness.
(5) Correlation between Linear Conductance Variability and Accuracy in Neuromorphic Computing using AuNP-DNA/HfO2 Bilayer Memristor Devices
M. Chae, D. Lee, H. Lee, Y. Jang, T. Kim, Y. Kim, H.-D. Kim
Measurement 248, 116960 (2025)
DOI: 10.1016/j.measurement.2025.116960
Memristor-based neuromorphic computing needs to improve energy efficiency using eco-friendly materials, but a single active layer with traditional materials still requires an improvement in reliability and performance. We propose a bilayers-memristor with gold nanoparticle (AuNP)-DNA for artificial synapse applications. As a result, the HfO2/AuNP-DNA-based memristor exhibits excellent linear weight update and large conductance ratio characteristics with high reliability and tunability. The high linearity of synaptic weights, achieved through simple programming according to pulse amplitude, can particularly enhance the device’s energy efficiency and learning accuracy in neural network applications. We assess the accuracy of the modified national institute of standards and technology simulations to compare the classification accuracy depending on linearity and the ratio of weight update. As a result, the smallest validation loss is observed at –7 V depression voltage, which has the best linearity and optimal conductance ratio, suggesting the potential application of the proposed memristor in neuromorphic computing.
(6) Impact of Biased Cooling on the Operation of Undoped Silicon Quantum Well Field-Effect Devices for Quantum Circuit Applications
L.K. Diebel, L.G. Zinkl, A. Hötzinger, F. Reichmann, M. Lisker, Y. Yamamoto, D. Bougeard
AIP Advances 15(3), 035301 (2025)
DOI: 10.1063/5.0250968, (QUASAR)
Gate-tunable semiconductor nanosystems are getting more and more important in the realization of quantum circuits. While such devices are typically cooled to operation temperature with zero bias applied to the gate, biased cooling corresponds to a non-zero gate voltage being applied before reaching the operation temperature. We systematically study the effect of biased cooling on different undoped SiGe/Si/SiGe quantum well field-effect stacks designed to accumulate and density-tune two-dimensional electron gases (2DEGs). In an empirical model, we show that biased cooling of the undoped FES induces a static electric field, which is constant at operation temperature and superimposes onto the field exerted by the top gate onto the 2DEG. We show that the voltage operation window of the field-effect-tuned 2DEG can be chosen in a wide range of voltages via the choice of the biased cooling voltage. Importantly, quality features of the 2DEG such as the mobility or the temporal stability of the 2DEG density remain unaltered under biased cooling.
(7) Investigating Impacts of Local Pressure and Temperature on CVD Growth of Hexagonal Boron Nitride on Ge(001)/Si
M. Franck, J. Dabrowski, M.A. Schubert. D. Vignaud, M. Achehboune, J.-F. Colomer, L. Henrard, Ch. Wenger, M. Lukosius
Advanced Materials Interfaces 12(1), 2400467 (2025)
DOI: 10.1002/admi.202400467, (2DHetero)
The chemical vapor deposition (CVD) growth of hexagonal boron nitride (hBN) on Ge substrates is a promising pathway to high-quality hBN thin films without metal contaminations for microelectronic applications, but the effect of CVD process parameters on the hBN properties is not well understood yet. The influence of local changes in pressure and temperature due to different reactor configurations on the structure and quality of hBN films grown on Ge(001)/Si is studied. Injection of the borazine precursor close to the sample surface results in an inhomogeneous film thickness, attributed to an inhomogeneous pressure distribution at the surface, as shown by computational fluid dynamics simulations. The additional formation of nanocrystalline islands is attributed to unfavorable gas phase reactions due to the radiative heating of the injector. Both issues are mitigated by increasing the injector-sample distance, leading to an 86% reduction in pressure variability on the sample surface and a 200 °C reduction in precursor temperature. The resulting hBN films exhibit no nanocrystalline islands, improved thickness homogeneity, and high crystalline quality (Raman FWHM = 23 cm−1). This is competitive with hBN films grown on other non-metal substrates but achieved at lower temperature and with a low thickness of only a few nanometers.
(8) Sensing of Hemin Binding to Albumin using Ge-based Plasmonic Antennas Operating in the THz Range
E. Hardt, R. Varricchio, C.A. Chavarin, G. De Simone, O. Skibitzki, P. Ascenzi, A. di Masi, G. Capellini
IEEE Sensors Journal 25(8), 12881 (2025)
DOI: 10.1109/JSEN.2025.3545736, (iCampus II)
Albumin-based biofunctionalized biosensors have the potential to be utilized for the detection of physiological ligands (e.g., heme) and of pathogenic proteins. In human cells, heme is always bound to proteins due to its toxic nature. However, free heme can be present within tissue and in the bloodstream as a consequence of hemolysis or under pathological conditions like malaria or sickle cell anemia. Therefore, the development of an albumin-based heme biosensor could be relevant from a biomedical viewpoint. In this study, we developed a protein-sensing platform by immobilizing albumin on CMOS-compatible Ge-based THz plasmonic antennas via drop-cast biofunctionalization. To set up the biosensor, the sensing platform was used to quantitatively measure the binding of hemin, a well-known physiological ligand of albumin. This measurement was performed using THz time-domain spectroscopy in dichroic transmission mode, achieving a sensitivity of approximately ~ 200 GHz/mM of the HSA:hemin complex. These preliminary results support the use of CMOS-compatible Ge-based THz plasmonic antennas as innovative sensors that could be monolithically integrated with conventional electronics for storage, processing, and communication into an all-in-one system.
(9) Sensing of Hemin Binding to Albumin using Ge-based Plasmonic Antennas Operating in the THz Range
E. Hardt, R. Varricchio, C.A. Chavarin, G. De Simone, O. Skibitzki, P. Ascenzi, A. di Masi, G. Capellini
IEEE Sensors Journal 25(8), 12881 (2025)
DOI: 10.1109/JSEN.2025.3545736, (IHP- Roma Tre University Joint Lab)
Albumin-based biofunctionalized biosensors have the potential to be utilized for the detection of physiological ligands (e.g., heme) and of pathogenic proteins. In human cells, heme is always bound to proteins due to its toxic nature. However, free heme can be present within tissue and in the bloodstream as a consequence of hemolysis or under pathological conditions like malaria or sickle cell anemia. Therefore, the development of an albumin-based heme biosensor could be relevant from a biomedical viewpoint. In this study, we developed a protein-sensing platform by immobilizing albumin on CMOS-compatible Ge-based THz plasmonic antennas via drop-cast biofunctionalization. To set up the biosensor, the sensing platform was used to quantitatively measure the binding of hemin, a well-known physiological ligand of albumin. This measurement was performed using THz time-domain spectroscopy in dichroic transmission mode, achieving a sensitivity of approximately ~ 200 GHz/mM of the HSA:hemin complex. These preliminary results support the use of CMOS-compatible Ge-based THz plasmonic antennas as innovative sensors that could be monolithically integrated with conventional electronics for storage, processing, and communication into an all-in-one system.
(10) The Effects of Short-Term Air Exposure of the Monocrystal HfSe2 Surface
K. Kwiecien, J. Raczyński, A. Puchalska, E. Nowak, E. Chłopocka, D. Kot, M. Szybowicz, L. Jurczyszyn, W. Koczorowski
Applied Surface Science 690, 162546 (2025)
DOI: 10.1016/j.apsusc.2025.162546
We report the impact of short-term sequential exposure to air–atmosphere conditions on the mechanically exfoliated surface of HfSe2 monocrystal. Our scanning electron microscopy studies show the early surface oxidation dynamics with a rapid increase of the Se-rich blister coverage. Further X-ray photoemission and energy dispersive spectroscopy measurements reveal a progressive diffusion of O atoms into the bulk and HfO2 layer formation on the surface during the exposure time. Finally, Raman spectroscopy measurements confirm the coexistence of HfSe2 and HfO2 on the surface. However, the Raman spectroscopy technique does not allow quantitative determination of the degree of short-term surface oxidation. Additionally, we confirm the conclusions drawn from the experimental results with the results of the density functional theory calculations of the O/HfSe2 adsorption system. The presented results hold substantial technological significance from the point of view of the application of HfSe2 in electronics by filling the gap in the early oxidation dynamics under ambient conditions.
(11) Electrically Pumped GeSn Micro-Ring Lasers
T. Liu, L. Seidel, O. Concepcion, V. Reboud, A. Chelnokov, G. Capellini, M. Oehme, D. Grützmacher, D. Buca
IEEE Journal of Selected Topics in Quantum Electronics 31(1), 8100307 (2025)
DOI: 10.1109/JSTQE.2024.3489712, (DFG GeSn Laser)
Recent progress in the quest for CMOS-integrable GeSn light sources comprises the optically-pumped laser operating at room temperature and the first demonstrations of electrically pumped lasers. In this work, the performance of electrically-pumped double heterostructure GeSn ring laser diodes are evaluated as a function of their geometry and pumping pulse time. In particular, the trade-off between the band structure, i.e. the directness of the GeSn band gap, and the device heat dissipation is discussed in terms of their impact on the emission intensity and threshold current density.
(12) A Statistical and Modeling Study on the Effects of Radiation on Au/Ta/ZrO2(Y)/Pt/Ti Memristive Devices
D. Maldonado, A. Cantudo, D.V. Guseinov, M.N. Koryazhkina,, E.V. Okulich, D.I. Tetelbaum, N.O. Bartev, N.G. Danchenko, V.A. Pikar, A.V. Teterevkov, F. Jiménez-Molinos, A.N. Mikhaylov, J.B. Roldán
Chaos, Solitons & Fractals 191, 115909 (2025)
DOI: 10.1016/j.chaos.2024.115909
In this study we have investigated the impact of radiation on the performance and reliability of Au/Ta/ZrO2(Y)/Pt/Ti memristive devices, with a particular focus on understanding the changes induced by ion irradiation. A comprehensive experimental approach was employed, involving irradiation with various ion species, including H⁺, Ne⁺, O⁺, and Kr⁺ to simulate different radiation environments. Thus, advanced statistical and modeling techniques to analyze the effects of irradiation on the resistive switching (RS) characteristics of the devices have been employed. Results revealed significant alterations in the RS parameters post-irradiation, including set and reset voltages and currents. These changes were found to vary depending on the ion species and dosage, with heavier ions such as Kr⁺ causing more pronounced effects. The findings are supported by detailed Monte Carlo simulations, which provided insights into the distribution of vacancies within the memristive devices under neutron irradiation. The experimental data, combined with the modeling results, indicate that ion irradiation can lead to the formation of defect structures that critically affect the performance of memristive devices.
(13) Strain Engineering in Semiconductor Materials
C.L. Manganelli, D. Spirito, P. Farrell, J. Frigerio, A. De Iacovo, D. Marian, M. Virgilio
Physica Status Solidi - Rapid Research Letters 19(1), 2400383 (2025)
DOI: 10.1002/pssr.202400383
Strain engineering has become an essential strategy in theadvancement of semiconductor technologies, providing a power-ful mean to modulate the electronic, optical, and mechanicalproperties of materials. By introducing controlled deformationinto crystal lattices, this approach enables enhanced carriermobility, tailored bandgap energies, and improved device perfor-mance across applications in photonics, optoelectronics, andquantum technologies.
(14) In Situ X-Ray Photoelectron Spectroscopy Study of Atomic Layer Deposited Cerium Oxide on SiO2: Substrate Influence on the Reaction Mechanism During the Early Stages of Growth
C. Morales, M. Gertig, M. Kot, C.A. Chavarin, M.A. Schubert, M.H. Zoellner, Ch. Wenger, K. Henkel, J.I. Flege
Advanced Materials Interfaces 12(5), 2400537 (2024)
DOI: 10.1002/admi.202400537, (iCampus II)
Thermal atomic layer deposition (ALD) of cerium oxide using commercial Ce(thd)4 precursor and O3 on SiO2 substrates is studied employing in-situ X-ray photoelectron spectroscopy (XPS). The system presents a complex growth behavior determined by the change in the reaction mechanism when the precursor interacts with the substrate or the cerium oxide surface. During the first growth stage, non-ALD side reactions promoted by the substrate affect the growth per cycle, the amount of carbon residue on the surface, and the oxidation degree of cerium oxide. On the contrary, the second growth stage is characterized by a constant growth per cycle in good agreement with the literature, low carbon residues, and almost fully oxidized cerium oxide films. This distinction between two growth regimes is not unique to the CeOx/SiO2 system but can be generalized to other metal oxide substrates. Furthermore, the film growth deviates from the ideal layer-by-layer mode, forming micrometric inhomogeneous and defective flakes that eventually coalesce for deposit thicknesses above 10 nm. The ALD-cerium oxide films present less order and a higher density of defects than films grown by physical vapor deposition techniques, likely affecting their reactivity in oxidizing and reducing conditions.
(15) HyRPF: Hybrid RRAM Prototyping on FPGA
D. Reiser, J. Knödtel, L. Almeeva, J. Wen, A. Baroni, M. Krstic, M. Reichenbach
Proc. 24th International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation (SAMOS 2024) in: Lecture Notes in Computer Science, LNCS 15226, 199 (2025)
DOI: 10.1007/978-3-031-78377-7_14
(16) Analytical Model for Parasitic Resistances of Crossbar Arrays Suitable for Open-Loop Programming Schemes Reliability Analysis
T. Rizzi, T. Zanotti, N. Lepri, E. Pérez, F.M. Puglisi, D. Ielmini, C. Zambelli
Proc. IEEE International Integrated Reliability Workshop (IIRW 2024), (2025)
DOI: 10.1109/IIRW62856.2024.10947147, (HYB-RISC)
(17) Investigation of Dislocations Introduced in Si Wafer During Flash Lamp Annealing by Photoluminescence Spectroscopy
D. Ryzhak, G. Kissinger, A. Ehlert, A. Sattler, D. Spirito, D. Kot
Physica Status Solidi A 222(8), 2400753 (2025)
DOI: 10.1002/pssa.202400753, (Siltronic Project)
Dislocations are generated in Si wafers during flash lamp annealing for 20 ms. The samples have been etched to different depths and macro-photoluminescence (PL) spectra have been recorded for different dislocation densities. A micro-PL investigation is also carried out on a cross section of a sample. Four characteristic emission peaks are found, which are the well-known D1, D2, D3, and D4 lines. The findings demonstrate a significant influence of the defect densities on the PL spectra of the D lines by using both the micro- and the macro-PL setups, and show a correlation of the PL intensities with etch pit density measured against the depth of the wafer. Additionally, the D lines dependency on temperature is explored, offering insights into the underlying mechanisms. The D lines exhibit a pronounced temperature dependence, which can be attributed to various factors including phonon interactions and thermal expansion effects. The influence of nickel contamination is also examined.
(18) AI-Driven Model for Optimized Pulse Programming of Memristive Devices
B. Spetzler, M. Fritscher, S. Park, N. Kim, Ch. Wenger, M. Ziegler
APL Machine Learning 3(2), 026103 (2025)
DOI: 10.1063/5.0251113, (DI-SIGN-HEP)
Next-generation artificial intelligence (AI) hardware based on memristive devices offers a promising approach to reducing the increasingly large energy consumption of AI applications. However, programming memristive AI hardware to achieve a desired synaptic weight configuration remains challenging because it requires accurate and energy-efficient algorithms for selecting the optimal weight-update pulses. Here, we present a computationally efficient AI model for predicting the weight update of memristive devices and guiding device programming. The synaptic weight-update behavior of bilayer HfO2/TiO2 memristive devices is characterized over a range of pulse parameters to provide experimental data for the AI model. Three different artificial neural network (ANN) configurations are trained and evaluated regarding the amount of training data required for accurate predictions and the computational costs. Finally, we apply the model to an antipulse weight-update process to demonstrate its performance. The results show that accurate and computationally inexpensive predictions are possible with comparatively few datasets and small ANNs. The normalized weight-update processes are predicted with accuracies comparable with larger model architectures but require only 896 floating point operations and 8.33 nJ per inference. This makes the model a promising candidate for integration into AI-driven device controllers as a precise and energy-efficient solution for memristive device programming.
(19) AI-Driven Model for Optimized Pulse Programming of Memristive Devices
B. Spetzler, M. Fritscher, S. Park, N. Kim, Ch. Wenger, M. Ziegler
APL Machine Learning 3(2), 026103 (2025)
DOI: 10.1063/5.0251113, (HYB-RISC)
Next-generation artificial intelligence (AI) hardware based on memristive devices offers a promising approach to reducing the increasingly large energy consumption of AI applications. However, programming memristive AI hardware to achieve a desired synaptic weight configuration remains challenging because it requires accurate and energy-efficient algorithms for selecting the optimal weight-update pulses. Here, we present a computationally efficient AI model for predicting the weight update of memristive devices and guiding device programming. The synaptic weight-update behavior of bilayer HfO2/TiO2 memristive devices is characterized over a range of pulse parameters to provide experimental data for the AI model. Three different artificial neural network (ANN) configurations are trained and evaluated regarding the amount of training data required for accurate predictions and the computational costs. Finally, we apply the model to an antipulse weight-update process to demonstrate its performance. The results show that accurate and computationally inexpensive predictions are possible with comparatively few datasets and small ANNs. The normalized weight-update processes are predicted with accuracies comparable with larger model architectures but require only 896 floating point operations and 8.33 nJ per inference. This makes the model a promising candidate for integration into AI-driven device controllers as a precise and energy-efficient solution for memristive device programming.
(20) AI-Driven Model for Optimized Pulse Programming of Memristive Devices
B. Spetzler, M. Fritscher, S. Park, N. Kim, Ch. Wenger, M. Ziegler
APL Machine Learning 3(2), 026103 (2025)
DOI: 10.1063/5.0251113, (6G-RIC)
Next-generation artificial intelligence (AI) hardware based on memristive devices offers a promising approach to reducing the increasingly large energy consumption of AI applications. However, programming memristive AI hardware to achieve a desired synaptic weight configuration remains challenging because it requires accurate and energy-efficient algorithms for selecting the optimal weight-update pulses. Here, we present a computationally efficient AI model for predicting the weight update of memristive devices and guiding device programming. The synaptic weight-update behavior of bilayer HfO2/TiO2 memristive devices is characterized over a range of pulse parameters to provide experimental data for the AI model. Three different artificial neural network (ANN) configurations are trained and evaluated regarding the amount of training data required for accurate predictions and the computational costs. Finally, we apply the model to an antipulse weight-update process to demonstrate its performance. The results show that accurate and computationally inexpensive predictions are possible with comparatively few datasets and small ANNs. The normalized weight-update processes are predicted with accuracies comparable with larger model architectures but require only 896 floating point operations and 8.33 nJ per inference. This makes the model a promising candidate for integration into AI-driven device controllers as a precise and energy-efficient solution for memristive device programming.
(21) RRAMulator: An Efficient FPGA-based Emulator for RRAM Crossbar with Device Variability and Energy Consumption Evaluation
J. Wen, F. Vargas, F. Zhu, D. Reiser, A. Baroni, M. Fritscher, E. Perez, M. Reichenbach, Ch. Wenger, M. Krstic
Microelectronics Reliability 168, 115630 (2025)
DOI: 10.1016/j.microrel.2025.115630, (6G-RIC)
The in-memory computing (IMC) systems based on emerging technologies have gained significant attention due to their potential to enhance performance and energy efficiency by minimizing data movement between memory and processing unit, which is especially beneficial for data-intensive applications. Designing and evaluating systems utilizing emerging memory technologies, such as resistive RAM (RRAM), poses considerable challenges due to the limited support from electronics design automation (EDA) tools for rapid development and design space exploration. Additionally, incorporating technology-dependent variability into system-level simulations is critical to accurately assess the impact on system reliability and performance. To bridge this gap, we propose RRAMulator, a field-programmable gate array (FPGA) based hardware emulator for RRAM crossbar array. To avoid the complex device models capturing the nonlinear current–voltage (IV) relationships that degrade emulation speed and increase hardware utilization, we propose a device and variability modeling approach based on device measurements. We deploy look-up tables (LUTs) for device modeling and use the multivariate kernel density estimation (KDE) method to augment existing data, extending data variety and avoiding repetitive data usage. The proposed emulator achieves cycle-accurate, real-time emulations and provides information such as latency and energy consumption for matrix mapping and vector–matrix multiplications (VMMs). Experimental results show a significant reduction in emulation time compared to conventional behavioral simulations. Additionally, an RRAM-based discrete Fourier transform (DFT) accelerator is analyzed as a case study featuring a range of in-depth system assessments.
(22) Elektronische Nasen
Ch. Wenger
99 Zukunftsobjekte aus der Lausitz, 1st Edition, Editor: J. Staemmler, Ch.Links Verlag, 203 (2025)
(23) Piezoresistivity of Epitaxial SiGe
Y. Yamamoto, W.-C. Wen, N. Inomata, A.A. Corley-Wiciak, D. Ryzhak, C. Corley-Wiciak, Z. Zhijian, R. Sorge, B. Tillack, T. Ono
ECS Journal of Solid State Science and Technology 14(4), 045001 (2025)
DOI: 10.1149/2162-8777/adc488
Piezoresistivity of B- and P-doped epitaxial Si1-xGex (x=10-30%) is investigated to assess its application potential for thin film strain sensors. The gauge factor (GF) is calculated based on the change in resistivity to the externally induced compressive uniaxial strain along the current flow direction. In the case of B-doped SiGe, the resistivity decreases under the induced compressive strain which may be related to hole mobility enhancement, while no influence on the resistivity of the P-doped SiGe. A significant increase in the GF is observed by lowering B concentration. At the same B concentration, slightly higher GF is observed for higher Ge content. Moreover, the GF is slightly improved by lowering the SiGe growth temperature, which may be related to improved crystallinity indicated by capacitance-voltage characteristics of metal-oxide-semiconductor structure using the epitaxial SiGe on Si. These results suggest that the low-doped p-type SiGe deposited at low temperature has reasonable GF and can potentially be applied in strain sensors.
(24) On the Bulk Photovoltaic Effect in the Characterization of the Strained Germanium Microstructures
I. Zaitsev, D. Spirito, J. Frigerio, C.A. Chavarin, A. Lüdge, W. Lüdge. R. Giani, M. Virgilio, C.L. Manganelli
Physica Status Solidi - Rapid Research Letters 19(1), 2400220 (2025)
DOI: 10.1002/pssr.202400220
Strain engineering serves as an effective method for optimizing electronic and optical properties in semiconductor devices, with applications including the enhancement of optical emission in Ge and GeSn-based devices, improvement of carrier mobility, and second harmonic generation in silicon photonics structures. Current methods for deformation characterization in semiconductors, such as XRD and Raman spectroscopy, often require bulky and expensive setups and are limited in vertical resolution. Consequently, techniques capable of measuring lattice strain while overcoming these drawbacks are highly desirable.
This study proposes a proof of concept for a cost-effective, compact, fast, and non-destructive approach to probe non-uniform strain fields and additional material properties by exploiting the bulk photovoltage effect. We benchmark the method with an array of silicon nitride stripes deposited under varying pressure conditions on a germanium substrate. Initially, their surface strains are verified through Raman spectroscopy. The deformations are replicated in a finite element method platform by integrating mechanical simulations with deformation potential theory, thereby estimating the band edge energy landscape.
Finally, the study discusses the theoretical behavior of the photovoltage signal, considering semiconductor properties, defects, doping, and deformation. The findings offer insights into the development of advanced techniques for strain and transport analysis in semiconductor materials.
