Compact DC Modeling of Tunnel-FETs

En l'última dècada, el transistor d'efecte de camp amb efecte túnel (TFET) ha guanyat molt interès i es maneja com un possible successor de la tecnologia MOSFET convencional. El transport de càrrega en un TFET es basa en el mecanisme de túnel de banda a banda (B2B) i, per tant, el pendent sub-llindar a temperatura ambient pot superar el límit de 60 mV / dec. Per descriure i analitzar el comportament del TFET en les simulacions de circuits, aquesta dissertació introdueix un model compacte de CC per TFET de doble comporta. L'enfocament de modelatge considera l'efecte túnel B2B amb l'efecte parasitari del corrent túnel assistida per trampes (TAT) en l'estat ON i ambipolar del TFET. Inclou un paquet d'equacions compactes per al potencial 2D per descriure el diagrama de banda del TFET. Basat en el diagrama de banda, el B2B i el corrent TAT es deriven per separat. Per fer-ho, primer es troba una expressió compacta per la llargada túnel, que després s'utilitza juntament amb un enfocament numèric robust de tipus Wentzel-Kramers-Brillouin (WKB) per calcular la probabilitat túnel. Després, usant l'equació de túnel de Landauer, la taxa de generació túnel es calcula i s'aproxima per arribar a una expressió de forma tancada per a la densitat de corrent. Amb una aproximació addicional de la densitat de corrent utilitzant una funció matemàtica, s'aconsegueixen expressions compactes per al túnel B2B resultant i el corrent TAT. La verificació del model es realitza amb l'ajuda de les dades de simulació TCAD Sentaurus per diverses configuracions de simulació. A més, la validesa del model es demostra mitjançant mesuraments de TFET complementaris fabricats. Per demostrar l'estabilitat numèrica i la continuïtat, així com la flexibilitat, es realitzen i analitzen simulacions de circuits lògics basats en TFET com un inversor d'una sola etapa o una cel·la SRAM. La combinació del model CC amb un model TFET AC permet una simulació transitòria d'un oscil·lador en anell de 11 etapes.En la última década, el transistor de efecto de campo con efecto túnel (TFET) ha ganado mucho interés y se maneja como un posible sucesor de la tecnología MOSFET convencional. El transporte de carga en un TFET se basa en el mecanismo de túnel de banda a banda (B2B) y, por lo tanto, la pendiente sub-umbral a temperatura ambiente puede superar el límite de 60 mV / dec. Para describir y analizar el comportamiento del TFET en las simulaciones de circuitos, esta disertación introduce un modelo compacto de CC para TFET de doble compuerta. El enfoque de modelado considera el efecto túnel B2B con el efecto parasitario de la corriente túnel asistida por trampas (TAT) en el estado ON y AMBIPOLAR del TFET. Incluye un paquete de ecuaciones compactas del potencial 2D para describir el diagrama de banda del TFET. Basado en el diagrama de banda, el B2B y la corriente TAT se derivan por separado. Para hacerlo, primero se encuentra una expresión compacta para la longitud túnel, que luego se utiliza junto con un enfoque numérico robusto de tipo Wentzel-Kramers-Brillouin (WKB) para calcular la probabilidad túnel. Luego, usando la ecuación de túnel de Landauer, la tasa de generación túnel se calcula y aproxima para llegar a una expresión de forma cerrada para la densidad de corriente. Con una aproximación adicional de la densidad de corriente por una función matemática, se logran expresiones compactas para el túnel B2B resultante y la corriente TAT. La verificación del modelo se realiza con la ayuda de los datos de simulación TCAD Sentaurus para varias configuraciones de simulación. Además, la validez del modelo se demuestra mediante mediciones de TFET complementarios fabricados. Para demostrar la estabilidad numérica y la continuidad, así como la flexibilidad, se realizan y analizan simulaciones de circuitos lógicos basados en TFET como un inversor de una sola etapa o una celda SRAM. La combinación del modelo CC con un modelo TFET AC permite una simulación transitoria de un oscilador en anillo de 11 etapas.In the last decade, the tunnel field-effect transistor (TFET) has gained a lot of interest and is handled as a possible successor of the conventional MOSFET technology. The current transport of a TFET is based on the band-to-band (B2B) tunneling mechanism and therefore, the subthreshold slope at room temperature can overcome the limit of 60 mV/dec. In order to describe and analyze the TFET behavior in circuit simulations, this dissertation introduces a compact DC model for double-gate TFETs. The modeling approach considers the B2B tunneling and the parasitic effect of trap-assisted tunneling (TAT) in the ON- and AMBIPOLAR-state of the TFET. It includes a 2D compact potential equation package to de-scribe the band diagram of the TFET. Based on the band diagram, the B2B tunneling and TAT current part are derived separately. In order to do so, firstly a compact expression for the tunneling length is found, which is then used together with a numerical robust Wentzel-Kramers-Brillouin (WKB) approach to calculate the tunneling probability. Afterwards, using Landauer’s tunneling equation, the tunneling generation rate is calculated and approximated to come to a closed-form expression for the current density. Further approximation of the current density by a mathematical function, compact expressions for the resulting B2B tun-neling and TAT current are achieved. The verification of the model is done with the help of TCAD Sentaurus simulation data for various simulation setups. Furthermore, the validity of the model is proven by measurements of fabricated complementary TFETs. In order to demonstrate the numerical stability and continuity as well as the flexibility, simulations of TFET-based logic circuits like a single-stage inverter or an SRAM cell are performed and analyzed. The combination of the DC model with an TFET AC model allows for a transient simulation of an 11-stage ring oscillator

Compact DC Modeling of Tunnel-FETs

En l'última dècada, el transistor d'efecte de camp amb efecte túnel (TFET) ha guanyat molt interès i es maneja com un possible successor de la tecnologia MOSFET convencional. El transport de càrrega en un TFET es basa en el mecanisme de túnel de banda a banda (B2B) i, per tant, el pendent sub-llindar a temperatura ambient pot superar el límit de 60 mV / dec. Per descriure i analitzar el comportament del TFET en les simulacions de circuits, aquesta dissertació introdueix un model compacte de CC per TFET de doble comporta. L'enfocament de modelatge considera l'efecte túnel B2B amb l'efecte parasitari del corrent túnel assistida per trampes (TAT) en l'estat ON i ambipolar del TFET. Inclou un paquet d'equacions compactes per al potencial 2D per descriure el diagrama de banda del TFET. Basat en el diagrama de banda, el B2B i el corrent TAT es deriven per separat. Per fer-ho, primer es troba una expressió compacta per la llargada túnel, que després s'utilitza juntament amb un enfocament numèric robust de tipus Wentzel-Kramers-Brillouin (WKB) per calcular la probabilitat túnel. Després, usant l'equació de túnel de Landauer, la taxa de generació túnel es calcula i s'aproxima per arribar a una expressió de forma tancada per a la densitat de corrent. Amb una aproximació addicional de la densitat de corrent utilitzant una funció matemàtica, s'aconsegueixen expressions compactes per al túnel B2B resultant i el corrent TAT. La verificació del model es realitza amb l'ajuda de les dades de simulació TCAD Sentaurus per diverses configuracions de simulació. A més, la validesa del model es demostra mitjançant mesuraments de TFET complementaris fabricats. Per demostrar l'estabilitat numèrica i la continuïtat, així com la flexibilitat, es realitzen i analitzen simulacions de circuits lògics basats en TFET com un inversor d'una sola etapa o una cel·la SRAM. La combinació del model CC amb un model TFET AC permet una simulació transitòria d'un oscil·lador en anell de 11 etapes.En la última década, el transistor de efecto de campo con efecto túnel (TFET) ha ganado mucho interés y se maneja como un posible sucesor de la tecnología MOSFET convencional. El transporte de carga en un TFET se basa en el mecanismo de túnel de banda a banda (B2B) y, por lo tanto, la pendiente sub-umbral a temperatura ambiente puede superar el límite de 60 mV / dec. Para describir y analizar el comportamiento del TFET en las simulaciones de circuitos, esta disertación introduce un modelo compacto de CC para TFET de doble compuerta. El enfoque de modelado considera el efecto túnel B2B con el efecto parasitario de la corriente túnel asistida por trampas (TAT) en el estado ON y AMBIPOLAR del TFET. Incluye un paquete de ecuaciones compactas del potencial 2D para describir el diagrama de banda del TFET. Basado en el diagrama de banda, el B2B y la corriente TAT se derivan por separado. Para hacerlo, primero se encuentra una expresión compacta para la longitud túnel, que luego se utiliza junto con un enfoque numérico robusto de tipo Wentzel-Kramers-Brillouin (WKB) para calcular la probabilidad túnel. Luego, usando la ecuación de túnel de Landauer, la tasa de generación túnel se calcula y aproxima para llegar a una expresión de forma cerrada para la densidad de corriente. Con una aproximación adicional de la densidad de corriente por una función matemática, se logran expresiones compactas para el túnel B2B resultante y la corriente TAT. La verificación del modelo se realiza con la ayuda de los datos de simulación TCAD Sentaurus para varias configuraciones de simulación. Además, la validez del modelo se demuestra mediante mediciones de TFET complementarios fabricados. Para demostrar la estabilidad numérica y la continuidad, así como la flexibilidad, se realizan y analizan simulaciones de circuitos lógicos basados en TFET como un inversor de una sola etapa o una celda SRAM. La combinación del modelo CC con un modelo TFET AC permite una simulación transitoria de un oscilador en anillo de 11 etapas.In the last decade, the tunnel field-effect transistor (TFET) has gained a lot of interest and is handled as a possible successor of the conventional MOSFET technology. The current transport of a TFET is based on the band-to-band (B2B) tunneling mechanism and therefore, the subthreshold slope at room temperature can overcome the limit of 60 mV/dec. In order to describe and analyze the TFET behavior in circuit simulations, this dissertation introduces a compact DC model for double-gate TFETs. The modeling approach considers the B2B tunneling and the parasitic effect of trap-assisted tunneling (TAT) in the ON- and AMBIPOLAR-state of the TFET. It includes a 2D compact potential equation package to de-scribe the band diagram of the TFET. Based on the band diagram, the B2B tunneling and TAT current part are derived separately. In order to do so, firstly a compact expression for the tunneling length is found, which is then used together with a numerical robust Wentzel-Kramers-Brillouin (WKB) approach to calculate the tunneling probability. Afterwards, using Landauer’s tunneling equation, the tunneling generation rate is calculated and approximated to come to a closed-form expression for the current density. Further approximation of the current density by a mathematical function, compact expressions for the resulting B2B tun-neling and TAT current are achieved. The verification of the model is done with the help of TCAD Sentaurus simulation data for various simulation setups. Furthermore, the validity of the model is proven by measurements of fabricated complementary TFETs. In order to demonstrate the numerical stability and continuity as well as the flexibility, simulations of TFET-based logic circuits like a single-stage inverter or an SRAM cell are performed and analyzed. The combination of the DC model with an TFET AC model allows for a transient simulation of an 11-stage ring oscillator

Effects of complex movements on the brain as a result of increased decision-making

Non-linearity is considered to be an essential property of complex systems. The associated high sensitivity of the result on the constraints leads to fundamental problems of a system description based on variables selected in the reductionist tradition. The attempt to compensate the problems by averaging data leads to the neglect of the individual and the moment. However, both is of enormous importance for effective therapy, training, and learning. The theory of differential learning suggests an alternative approach to dealing with these problems. With constantly changing complex whole-body movements, extensive decisions are demanded from the learner, which lead to brain states through an overstraining of the working memory, as it were, as they are also known after mindfulness meditation

Guided sparse camera pose estimation

In this paper, we present an idea for a sparse approach to calculate camera poses from RGB images and laser distance measurements to perform subsequent facade reconstruction. The core idea is to guide the image recording process by choosing distinctive features with the laser range finder, e.g. building or window corners. From these distinctive features, we can establish correspondences between views to compute metrically accurate camera poses from just a few precise measurements. In our experiments, we achieve reasonable results in building facade reconstruction with only a fraction of features compared to standard structure from motion

Explaining the unique nature of individual gait patterns with deep learning

Machine learning (ML) techniques such as (deep) artificial neural networks (DNN) are solving very successfully a plethora of tasks and provide new predictive models for complex physical, chemical, biological and social systems. However, in most cases this comes with the disadvantage of acting as a black box, rarely providing information about what made them arrive at a particular prediction. This black box aspect of ML techniques can be problematic especially in medical diagnoses, so far hampering a clinical acceptance. The present paper studies the uniqueness of individual gait patterns in clinical biomechanics using DNNs. By attributing portions of the model predictions back to the input variables (ground reaction forces and full-body joint angles), the Layer-Wise Relevance Propagation (LRP) technique reliably demonstrates which variables at what time windows of the gait cycle are most relevant for the characterisation of gait patterns from a certain individual. By measuring the time-resolved contribution of each input variable to the prediction of ML techniques such as DNNs, our method describes the first general framework that enables to understand and interpret non-linear ML methods in (biomechanical) gait analysis and thereby supplies a powerful tool for analysis, diagnosis and treatment of human gait

The power output of local obscured and unobscured AGN: crossing the absorption barrier with Swift/BAT and IRAS

The Swift/BAT 9-month catalogue of active galactic nuclei (AGN) provides an unbiased census of local supermassive black hole accretion, and probes to all but the highest levels of absorption in AGN. We explore a method for characterising the bolometric output of both obscured and unobscured AGN by combining the hard X-ray data from Swift/BAT (14-195keV) with the reprocessed IR emission as seen with the IRAS all-sky surveys. This approach bypasses the complex modifications to the SED introduced by absorption in the optical, UV and 0.1-10 keV regimes and provides a long-term, average picture of the bolometric output of these sources. We broadly follow the approach of Pozzi et al. for calculating the bolometric luminosities by adding nuclear IR and hard X-ray luminosities, and consider different approaches for removing non-nuclear contamination in the large-aperture IRAS fluxes. Using mass estimates from the M_BH-L_bulge relation, we present the Eddington ratios \lambda_Edd and 2-10 keV bolometric corrections for a subsample of 63 AGN (35 obscured and 28 unobscured) from the Swift/BAT catalogue, and confirm previous indications of a low Eddington ratio distribution for both samples. Importantly, we find a tendency for low bolometric corrections (typically 10-30) for the obscured AGN in the sample (with a possible rise from ~15 for \lambda_Edd<0.03 to ~32 above this), providing a hitherto unseen window onto accretion processes in this class of AGN. This finding is of key importance in calculating the expected local black hole mass density from the X-ray background since it is composed of emission from a significant population of such obscured AGN. Analogous studies with high resolution IR data and a range of alternative models for the torus emission will form useful future extensions to this work. (Abridged)Comment: 19 pages, 16 figures, 2 tables. Accepted for publication in MNRA

Current state and future prospects of EEG and fNIRS in robot-assisted gait rehabilitation : a brief review

Gait and balance impairments are frequently considered as the most significant concerns among individuals suffering from neurological diseases. Robot-assisted gait training (RAGT) has shown to be a promising neurorehabilitation intervention to improve gait recovery in patients following stroke or brain injury by potentially initiating neuroplastic changes. However, the neurophysiological processes underlying gait recovery through RAGT remain poorly understood. As non-invasive, portable neuroimaging techniques, electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) provide new insights regarding the neurophysiological processes occurring during RAGT by measuring different perspectives of brain activity. Due to spatial information about changes in cortical activation patterns and the rapid temporal resolution of bioelectrical changes, more features correlated with brain activation and connectivity can be identified when using fused EEG-fNIRS, thus leading to a detailed understanding of neurophysiological mechanisms underlying motor behavior and impairments due to neurological diseases. Therefore, multi-modal integrations of EEG-fNIRS appear promising for the characterization of neurovascular coupling in brain network dynamics induced by RAGT. In this brief review, we surveyed neuroimaging studies focusing specifically on robotic gait rehabilitation. While previous studies have examined either EEG or fNIRS with respect to RAGT, a multi-modal integration of both approaches is lacking. Based on comparable studies using fused EEG-fNIRS integrations either for guiding non-invasive brain stimulation (NIBS) or as part of brain-machine interface (BMI) paradigms, the potential of this methodologically combined approach in RAGT is discussed. Future research directions and perspectives for targeted, individualized gait recovery that optimize the outcome and efficiency of RAGT in neurorehabilitation were further derived