Fault-Tolerant Multi-Level Logic Decoder for Nanoscale Crossbar Memory Arrays

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When arranged in a crossbar configuration, resistive memory devices can be used to execute Matrix-Vector Multiplications (MVMs), the most dominant operation of many Machine Learning (ML) algorithms, in constant time complexity. Nonetheless, when performing ...

The use of meteorological radars to study snowfall microphysical properties and processes is well established, in particular via a few distinct techniques: the use of radar polarimetry, of multi-frequency radar measurements, and of the radar Doppler spectr ...

The current machine learning paradigm relies on continuous representations and fixed neural network architectures to approximate environmental structures, leading to challenges with continual learning, internal structure design, and goal-directed behavior ...

Recent progress in computer vision has been driven by a simple yet transformative observation: the potential of 30-year-old neural networks can be unlocked by massively scaling their parameters and the amount of human-labeled training data. This breakthrou ...

The material and exact shape of a nanostructure determine its optical response, which is especially strong for plasmonic metals. Unfortunately, only a few plasmonic metals are available, which limits the spectral range where these strong optical effects ca ...

Proteins are the molecular machines of life, driving essential biological processes such as enzymatic catalysis, cellular signaling, and immune responses. The ability to design entirely new proteins with desired structures and functions has immense implica ...

Fundamental aspects and state-of-the-art results of thermal scanning probe lithography (t-SPL) are reviewed here. t-SPL is an emerging direct-write nanolithography method with many unique properties which enable original or improved nano-patterning in appl ...

The fabrication of defined and high-quality metal nanostructures is an ongoing topic of research. Direct-write deposition of copper nanostructures is of great value for many fields of research and industrial applications. Focused electron beam induced depo ...

Data-driven techniques are increasingly used to replace electronic-structure calculations of matter. In this context, a relevant question is whether machine learning (ML) should be applied directly to predict the desired properties or combined explicitly w ...

The channel impulse response (CIR) of the wireless propagation channel is influenced by the surrounding environment and thus can be used to retrieve environmental information such as location, the presence of objects, and the speed of objects. In this work ...

New cell-imprint surface modification techniques based on direct-cell photolithography and optical soft lithography using poly(dimethylsiloxane) (PDMS) cell imprints are presented for enhanced cell-based studies. The core concept of engineering materials f ...

In proximity mask aligner photolithography, diffraction of light at the mask pattern is the predominant source for image shape distortions such as line end shortening and corner rounding. One established method to mitigate the impact of diffraction is opti ...

Electrochemical sensors play a pivotal role in advancing therapeutic drug monitoring (TDM) and personalized therapy. However, the insufficient selectivity of electrochemical sensors based on cytochromes P450 poses a great need for innovative machine learni ...

The creation of high fidelity synthetic data has long been an important goal in machine learning, particularly in fields like finance where the scarcity of available training and test data make it difficult to utilize many of the deep learning techniques w ...

This work presents a novel hybrid (physics- and data -driven) model for short-term (intra-day and day-ahead, 3h -24h) wind power forecasting (STWPF). Traditionally, STWPF predictors admitted very few meteorological variables only from the grid points close ...

Downscaling of the minimal feature size, or the gate length has been the key for the exponential im-provement of the performance of the logic CMOS integrated circuits over the last six decades. How-ever, since about 2003, some fundamental limits in the dev ...

Water is a crucial resource for all forms of life, yet it is becoming increasingly scarce. A significant portion of water loss in urban and industrial areas is attributed to leaks. Addressing this issue is critical for enhancing efficiency, sustainability, ...

Thermal scanning probe lithography (t-SPL) is an advanced lithography technique in which a heated atomic force microscope tip locally modifies a sample material. Due to the nanometer-sized tip apex diameter, t-SPL enables patterning of sub-10 nm structures ...

We present and discuss Talbot mask-aligner lithography, relying on a continuous wave laser emitting at 193nm for the illumination. In this source, a diode laser at 772nm is amplified by a tapered amplifier in master-oscillator power-amplifier configuration ...

For the back-end microfabrication in integrated circuits and for the manufacturing of light emitting diodes, proximity mask-aligner lithography is still the tool of choice, due to its simplicity and low costs. However, the downscaling of functional element ...

Fault-Tolerant Multi-Level Logic Decoder for Nanoscale Crossbar Memory Arrays

Chattez avec Graph Search

LIONHEART: A Layer-based Mapping Framework for Heterogeneous Systems with Analog In-Memory Computing Tiles

Dual-frequency spectral radar retrieval of snowfall microphysics: a physics-driven deep-learning approach

Modelleyen: Continual Learning and Planning via Structured Modelling of Environment Dynamics

Exploiting Representation Similarities in Self-Supervised Learning for Vision Tasks

A Low-Temperature Annealing Method for Alloy Nanostructures and Metasurfaces: Unlocking a Novel Degree of Freedom

Computational design of complex protein folds and soluble analogs of membrane proteins

Thermal scanning probe lithography-a review

Electron Beam Induced Copper Deposition from Carboxylate Precursors and the Study of Underlying Growth Mechanisms

Electronic Excited States from Physically Constrained Machine Learning

Learning-based Hand Gesture Classification using Channel Impulse Response with UWB

Cell-Imprint Surface Modification by Contact Photolithography-Based Approaches: Direct-Cell Photolithography and Optical Soft Lithography Using PDMS Cell Imprints

Computational rule-based approach for corner correction of non-Manhattan geometries in mask aligner photolithography

Identification and Quantification of Multiple Drugs by Machine Learning on Electrochemical Sensors for Therapeutic Drug Monitoring

Macroeconomic Conditioned Synthetic Financial Markets

A hybrid physics-based and data-driven model for intra-day and day-ahead wind power forecasting considering a drastically expanded predictor search space

Fabrication and Characterisation of Epitaxial PMN-PT Nano-structures

A two-phase approach for leak detection and localization in water distribution systems using wavelet decomposition and machine learning

Nanoscale Lithography and Thermometry with Thermal Scanning Probes

Mask-aligner Talbot lithography using a 193 nm CW light source

Improving the resolution in mask-aligner lithography