Publications related to Data-driven control in atomic force microscopy using a genetic algorithm

Related publications (15)

Improving the accuracy and interpretability of neural networks for wind power forecasting

Fernando Porté Agel, Jiannong Fang, Wenlong Liao

Deep neural networks (DNNs) are receiving increasing attention in wind power forecasting due to their ability to effectively capture complex patterns in wind data. However, their forecast errors are severely limited by the local optimal weight issue in opt ...

2025

2D Metalorganic Ferromagnets

Diego Radillo Ochoa, Céline Hensky, Christian Wäckerlin, Quy Hien Le

Low-dimensional materials exhibiting stable magnetic ordering are interesting from a fundamental point of view as well as for future application in information technologies. Metalorganic magnets, created by linking metal atoms with specific organic molecul ...

WILEY2025

Engineering Spin Interaction Channels of FePc on Au(111)

Wolf-Dieter Schneider

We demonstrate the reversible control of interactions between a local molecular spin, hosted within an iron phthalocyanine (FePc) molecule, and the conduction electrons of a supporting Au(111) surface. Using the tip of a scanning tunneling microscope, we d ...

American Chemical Society (ACS)2025

Learning Barrier-Certified Polynomial Dynamical Systems for Obstacle Avoidance with Robots

Aude Billard

Established techniques that enable robots to learn from demonstrations are based on learning a stable dynamical system (DS). To increase the robots' resilience to perturbations during tasks that involve static obstacle avoidance, we propose incorporating b ...

IEEE2024

Conductive ferroelectric domain walls in Pb(Zr,Ti)O3 for neuromorphic applications

Felix Risch

Over the last decades, the digital revolution has continuously increased the demand for more computational power. However, with the exponential rise of artificial intelligence applications in virtually every aspect of today's life, these additional demands ...

EPFL2024

Learning to Optimize with Convergence Guarantees Using Nonlinear System Theory

Luca Furieri, Andrea Martin

The increasing reliance on numerical methods for controlling dynamical systems and training machine learning models underscores the need to devise algorithms that dependably and efficiently navigate complex optimization landscapes. Classical gradient desce ...

2024

Diffusion Moving-Average Adaptation Over Networks

Ali H. Sayed

Recently, the diffusion moving-average (D-MA) scheme has been proposed as a way to combat noisy links over adaptive networks. However, the current theoretical results focus on networks with mean-square error costs where the optimal local solution agrees wi ...

2024

Selectively Exciting and Probing Radiative Plasmon Modes on Short Gold Nanorods by Scanning Tunneling Microscope-Induced Light Emission

Olivier Martin

We study the plasmon modes of gold nanorods (as short as similar to 100 nm) on a nonmetallic conductive substrate using scanning tunneling microscope-induced light emission (STM-LE) with a nonplasmonic tungsten tip at room temperature in high vacuum (10-7 ...

AMER CHEMICAL SOC2023

CONFIG: Constrained Efficient Global Optimization for Closed-Loop Control System Optimization with Unmodeled Constraints

Colin Neil Jones, Yuning Jiang, Wenjie Xu

In this paper, the CONFIG algorithm, a simple and provably efficient constrained global optimization algorithm, is applied to optimize the closed-loop control performance of an unknown system with unmodeled constraints. Existing Gaussian process based clos ...

Elsevier2023

Multi-Level Monte Carlo Methods for Uncertainty Quantification and Risk-Averse Optimisation

Sundar Subramaniam Ganesh

This work aims to study the effects of wind uncertainties in civil engineering structural design. Optimising the design of a structure for safety or operability without factoring in these uncertainties can result in a design that is not robust to these per ...

EPFL2022

NIR Fluorescence lifetime macroscopic imaging with a time-gated SPAD camera

Edoardo Charbon, Claudio Bruschini, Arin Can Ülkü

The performance of SwissSPAD2 (SS2), a large scale, widefield time-gated CMOS SPAD imager developed for fluorescence lifetime imaging, has recently been described in the context of visible range and fluorescence lifetime imaging microscopy (FLIM) of dyes w ...

SPIE-INT SOC OPTICAL ENGINEERING2022

Engineering Optically Active Defects in Hexagonal Boron Nitride Using Focused Ion Beam and Water

Aleksandra Radenovic, Andras Kis, Georg Fantner, Ahmet Avsar, Michal Daniel Macha, Evgenii Glushkov, Vytautas Navikas, Nathan Cyprien Arsène Ronceray, Aqeel Ahmed, Cheol Yeon Cheon, Esther Braun

Hexagonal boron nitride (hBN) has emerged as a promising material platform for nanophotonics and quantum sensing, hosting optically active defects with exceptional properties such as high brightness and large spectral tuning. However, precise control over ...

AMER CHEMICAL SOC2022

A Practical Guide to Supervised Deep Learning for Bioimage Analysis: Challenges and good practices

Daniel Sage, Virginie Sophie Uhlmann, Laurène Donati

The variety of bioimage data and their quality have dramatically increased over the last decade. In parallel, the number of proposed deep learning (DL) models for their analysis grows by the day. Yet, the adequate reuse of published tools by practitioners ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

On improving the efficiency of modifier adaptation via directional information

Dominique Bonvin

In real-time optimization, the solution quality depends on the model ability to predict the plant KarushKuhn-Tucker (KKT) conditions. In the case of non-parametric plant-model mismatch, one can add input-affine modifiers to the model cost and constraints a ...

PERGAMON-ELSEVIER SCIENCE LTD2022

Deep Q-learning agent for building earthquake resisting wall

Katrin Beyer, Qianqing Wang, Ketson Roberto Maximiano Dos Santos

The construction of dry-joint brick masonry that is subject to seismic loading can be modelled as a strategy problem wherein bricks must be laid to form a load resisting structure. To learn how to mount bricks while considering relevant engineering criteri ...

2022