Focus 26 January 2021

Applied physics and mathematics

This page aims to highlight the most interesting papers published in Nature Communications in the interdisciplinary areas where diverse approaches at the boundaries of physics, mathematics, materials science and engineering take place to create new research opportunities.

Featured articles

The nature of non-phononic excitations in disordered systems

The frequency scaling exponent of low-frequency vibrational excitations in glasses remains controversial in the literature. Here, Schirmacher et al. show that the exponent depends on the statistics of the small values of the local stresses, which is governed by the detail of interaction potential.
- Walter Schirmacher
- Matteo Paoluzzi
- Giancarlo Ruocco
ArticleOpen Access10 Apr 2024 Nature Communications
Predicting multiple observations in complex systems through low-dimensional embeddings

Forecasting the future behaviors based on observed data remains a challenging task especially for large nonlinear systems. The authors propose a data-driven approach combining manifold learning and delay embeddings for prediction of dynamics for all components in high-dimensional systems.
- Tao Wu
- Xiangyun Gao
- Jürgen Kurths
ArticleOpen Access12 Mar 2024 Nature Communications
Reconstructing the evolution history of networked complex systems

Evolution processes of complex networked systems in biology and social sciences, and their underlying mechanisms, still need better understanding. The authors propose a machine learning approach to reconstruct the evolution history of complex networks.
- Junya Wang
- Yi-Jiao Zhang
- Yanqing Hu
ArticleOpen Access2 Apr 2024 Nature Communications
Shaping active matter from crystalline solids to active turbulence

Earlier research has shown that controlling activity in the active matter can lead to either a phase change or a laminar-turbulent transition in active fluids. Authors demonstrate that it is possible to control both the phase transitions between solid, liquid, and gas states and the laminar-to-turbulent transitions in fluid phases by adjusting the activity of a phoretic medium.
- Qianhong Yang
- Maoqiang Jiang
- Lailai Zhu
ArticleOpen Access3 Apr 2024 Nature Communications
Programming mechanics in knitted materials, stitch by stitch

Knitted fabrics are prized for their stretchability, breathability, and long-wearability in everyday life. This study combines experiments and simulations to present a micromechanical approach to understanding the origin of the anisotropic elasticity of four canonical patterns of knitted fabrics.
- Krishma Singal
- Michael S. Dimitriyev
- Elisabetta A. Matsumoto
ArticleOpen Access23 Mar 2024 Nature Communications
TacticAI: an AI assistant for football tactics

In modern football games, data-driven analysis serves as a key driver in determining tactics. Wang, Veličković, Hennes et al. develop a geometric deep learning algorithm, named TacticAI, to solve high-dimensional learning tasks over corner kicks and suggest tactics favoured over existing ones 90% of the time.
- Zhe Wang
- Petar Veličković
- Karl Tuyls
ArticleOpen Access19 Mar 2024 Nature Communications
Higher-order Granger reservoir computing: simultaneously achieving scalable complex structures inference and accurate dynamics prediction

For reservoir computing, improving prediction accuracy while maintaining low computing complexity remains a challenge. Inspired by the Granger causality, Li et al. design a data-driven and model-free framework by integrating the inference process and the inferred results on high-order structures.
- Xin Li
- Qunxi Zhu
- Wei Lin
ArticleOpen Access20 Mar 2024 Nature Communications
Dynamical order and many-body correlations in zebrafish show that three is a crowd

Active matter systems, such as zebrafish groups, demonstrate similar collective dynamics to assemblies of particles, or interacting agents. The authors show that majority of dynamics patterns seen in large zebrafish groups are exhibited by a minimal group of three fish.
- Alexandra Zampetaki
- Yushi Yang
- C. Patrick Royall
ArticleOpen Access22 Mar 2024 Nature Communications
Local prediction-learning in high-dimensional spaces enables neural networks to plan

The task of planning a sequence of actions, and dynamically adjusting the plan in dependence of unforeseen circumstances, remains challenging for artificial intelligence frameworks. The authors introduce a learning approach inspired by cognitive functions, that demonstrates high flexibility and generalization capability in planning tasks, suitable for on-chip learning.
- Christoph Stöckl
- Yukun Yang
- Wolfgang Maass
ArticleOpen Access15 Mar 2024 Nature Communications
Large exchange-driven intrinsic circular dichroism of a chiral 2D hybrid perovskite

Li et al. report large circular dichroism in 2D chiral perovskite single crystals, arises from the inorganic sublattice, instead of chiral ligands, driven by electron-hole exchange interactions. This is evidenced by both reflective circular dichroism spectroscopy and ab initio theory.
- Shunran Li
- Xian Xu
- Peijun Guo
ArticleOpen Access22 Mar 2024 Nature Communications
Emerging opportunities and challenges for the future of reservoir computing

Reservoir Computing has shown advantageous performance in signal processing and learning tasks due to compact design and ability for fast training. Here, the authors discuss the parallel progress of mathematical theory, algorithm design and experimental realizations of Reservoir Computers, and identify emerging opportunities as well as existing challenges for their large-scale industrial adoption.
- Min Yan
- Can Huang
- Jie Sun
PerspectiveOpen Access6 Mar 2024 Nature Communications
Low-frequency vibrational density of states of ordinary and ultra-stable glasses

Power-law scaling of low-frequency vibrational density of states is widely observed in glassy materials, yet the value of scaling exponents remains controversial. Here, Xu et al. identify two scaling exponents by separating stable from unstable glass to reconcile the debate in the literature.
- Ding Xu
- Shiyun Zhang
- Ning Xu
ArticleOpen Access16 Feb 2024 Nature Communications
Elasticity-controlled jamming criticality in soft composite solids

Soft composite solids are building blocks for many functional and biological materials, yet it remains challenging to predict their mechanical properties. Zhao et al. propose a criticality framework to connect the mechanics to the critical behaviour near the shear-jamming transition of the dispersed inclusions.
- Yiqiu Zhao
- Haitao Hu
- Qin Xu
ArticleOpen Access24 Feb 2024 Nature Communications
Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks

Predicting the evolution of dynamical systems remains challenging, requiring high computational effort or effective reduction of the system into a low-dimensional space. Here, the authors present a data-driven approach for predicting the evolution of systems exhibiting spatiotemporal dynamics in response to external input signals.
- Francesco Regazzoni
- Stefano Pagani
- Alfio Quarteroni
ArticleOpen Access28 Feb 2024 Nature Communications
Learning stochastic dynamics and predicting emergent behavior using transformers

Learning the dynamics governing a simulation or experiment usually requires coarse graining or projection, as the number of transition rates typically grows exponentially with system size. The authors show that transformers, neural networks introduced initially for natural language processing, can be used to parameterize the dynamics of large systems without coarse graining.
- Corneel Casert
- Isaac Tamblyn
- Stephen Whitelam
ArticleOpen Access29 Feb 2024 Nature Communications
Anticipating regime shifts by mixing early warning signals from different nodes

Early warning signals for rapid regime shifts in complex networks are of importance for ecology, climate and epidemics, where heterogeneities in network nodes and connectivity make construction of early warning signals challenging. The authors propose a method for selecting an optimal set of nodes from which a reliable early warning signal can be obtained.
- Naoki Masuda
- Kazuyuki Aihara
- Neil G. MacLaren
ArticleOpen Access5 Feb 2024 Nature Communications
Sequential stacking link prediction algorithms for temporal networks

Link prediction in temporal networks is relevant for many real-world systems, however, current approaches are usually characterized by high computational costs. The authors propose a temporal link prediction framework based on the sequential stacking of static network features, for improved computational speed, appropriate for temporal networks with completely unobserved or partially observed target layers.
- Xie He
- Amir Ghasemian
- Peter J. Mucha
ArticleOpen Access14 Feb 2024 Nature Communications
A magnetic multi-layer soft robot for on-demand targeted adhesion

Magnetic soft robots offer a non-invasive way to deliver bioadhesives to targeted lesion sites to accelerate the healing. Authors present a magnetic multi-layer soft robot that is capable of performing navigated locomotion on biological tissues and on-demand multi-target adhesion at different sites.
- Ziheng Chen
- Yibin Wang
- Jiangfan Yu
ArticleOpen Access20 Jan 2024 Nature Communications
Reconfigurable droplet networks

Earlier methods for droplet network stabilization require extremely precise control and manipulation with considerable energy consumption, making them difficult to implement. Here, the authors present 2D interfacial networks, formed by irreversible interfacial interactions between polymer chains dissolved in one liquid and ligands dissolved in a second immiscible liquid at random points along the chains.
- Shuyi Sun
- Shuailong Li
- Shaowei Shi
ArticleOpen Access5 Feb 2024 Nature Communications
β-Variational autoencoders and transformers for reduced-order modelling of fluid flows

Reduced-order models provide better understanding for complex spatio-temporal dynamics of fluid flows with high numbers of degrees of freedom and non-linear interactions. The authors propose a variational autoencoder and transformer framework for learning the temporal dynamics of the nonlinear reduced-order models relevant for fluid dynamics, weather forecasting, and biomedical engineering.
- Alberto Solera-Rico
- Carlos Sanmiguel Vila
- Ricardo Vinuesa
ArticleOpen Access14 Feb 2024 Nature Communications
Chiral active particles are sensitive reporters to environmental geometry

There hasn’t been much experimental attention to the interaction of chiral active particles with complex environments. Chan et al. propose an interesting granular particle system based on natural plant seeds to examine the transport of chiral active matter in complex surroundings.
- Chung Wing Chan
- Daihui Wu
- Rui Zhang
ArticleOpen Access16 Feb 2024 Nature Communications
Flow-induced periodic chiral structures in an achiral nematic liquid crystal

Under strong surface or geometric constraints, achiral nematic liquid crystals can form chiral structures. Using pressure driven flow, Zhang et al. show a pathway to mirror symmetry breaking that does not require such constraints and that occurs in nematic lyotropic chromonic liquid crystals.
- Qing Zhang
- Weiqiang Wang
- Irmgard Bischofberger
ArticleOpen Access8 Jan 2024 Nature Communications
A retrofit sensing strategy for soft fluidic robots

In existing soft robotic sensing strategies, additional components and design changes are often required to sense the environment. Zou et al. introduce a retrofit self-sensing strategy for soft pneumatic actuators, utilizing internal pressure variations arising from interactions.
- Shibo Zou
- Sergio Picella
- Johannes T. B. Overvelde
ArticleOpen Access15 Jan 2024 Nature Communications
Unconventionally fast transport through sliding dynamics of rodlike particles in macromolecular networks

Transport of rodlike particles in macromolecular networks is relevant to various biological processes and technological applications, where thin rods have been mainly in focus. Here the authors investigate diffusion dynamics of thick rods in confinement media of macromolecular networks, and uncover dependence of translational diffusion upon rod length.
- Xuanyu Zhang
- Xiaobin Dai
- Li-Tang Yan
ArticleOpen Access15 Jan 2024 Nature Communications
Epidemic graph diagrams as analytics for epidemic control in the data-rich era

Approaches for assessing epidemic risks meet challenges when dealing with high-resolution data available nowadays, that includes behaviors, disease progression, and interventions. The authors propose an analytical framework to compute the epidemic threshold for arbitrary models of diseases, interventions, and hosts contact patterns.
- Eugenio Valdano
- Davide Colombi
- Vittoria Colizza
ArticleOpen Access20 Dec 2023 Nature Communications
DomiRank Centrality reveals structural fragility of complex networks via node dominance

Identification of nodes that play a crucial role in the complex network functionality is of high relevance for supply, transportation, and epidemic spreading networks. The authors propose a metric to evaluate nodal dominance based on competition dynamics that integrate local and global topological information, revealing fragile structures in complex networks.
- Marcus Engsig
- Alejandro Tejedor
- Chaouki Kasmi
ArticleOpen Access2 Jan 2024 Nature Communications
Learning low-rank latent mesoscale structures in networks

Network structures can be examined at different scales, and subnetworks in the form of motifs can provide insights into global network properties. The authors propose an approach to decompose a network into a set of latent motifs, which can be used for network comparison, network denoising, and edge inference.
- Hanbaek Lyu
- Yacoub H. Kureh
- Mason A. Porter
ArticleOpen Access3 Jan 2024 Nature Communications
Temporal dendritic heterogeneity incorporated with spiking neural networks for learning multi-timescale dynamics

Brain-inspired spiking neural networks have shown their capability for effective learning, however current models may not consider realistic heterogeneities present in the brain. The authors propose a neuron model with temporal dendritic heterogeneity for improved neuromorphic computing applications.
- Hanle Zheng
- Zhong Zheng
- Lei Deng
ArticleOpen Access4 Jan 2024 Nature Communications
The D-Mercator method for the multidimensional hyperbolic embedding of real networks

Embedding of complex networks in the latent geometry allows for a better understanding of their features. The authors propose a framework for mapping complex networks into high-dimensional hyperbolic space to capture their intrinsic dimensionality, navigability and community structure.
- Robert Jankowski
- Antoine Allard
- M. Ángeles Serrano
ArticleOpen Access21 Nov 2023 Nature Communications
Learning few-shot imitation as cultural transmission

The modelling of human-like behaviours is one of the challenges in the field of Artificial Intelligence. Inspired by experimental studies of cultural evolution, the authors propose a reinforcement learning approach to generate agents capable of real-time third-person imitation.
- Avishkar Bhoopchand
- Bethanie Brownfield
- Lei M. Zhang
ArticleOpen Access28 Nov 2023 Nature Communications
Augmenting interpretable models with large language models during training

Prediction and interpretation tasks may be challenging in high-stakes applications, such as medical decision-making, or systems with compute-limited hardware. The authors introduce an augmented framework for leveraging the knowledge learned by Large Language Models to build interpretable models which are both accurate and efficient.
- Chandan Singh
- Armin Askari
- Jianfeng Gao
ArticleOpen Access30 Nov 2023 Nature Communications
A colloidal viewpoint on the sausage catastrophe and the finite sphere packing problem

Packing a finite number of spheres in a compact cluster does not always result in the densest packing. Here, the authors provide a physical realization of the finite sphere packing problem by enclosing colloids in a flaccid lipid vesicle and mapping out a state diagram that displays linear, planar, and cluster conformations of spheres, as well as bistable states that alternate between cluster-plate and plate-linear conformations.
- Susana Marín-Aguilar
- Fabrizio Camerin
- Marjolein Dijkstra
ArticleOpen Access30 Nov 2023 Nature Communications
Spatiotemporal dynamics of traffic bottlenecks yields an early signal of heavy congestions

Heavy traffic jams are difficult to predict due to the complexity of traffic dynamics. The authors propose a framework to unveil identifiable early signals and predict the eventual outcome of traffic bottlenecks, which may be useful for designing effective methods preventing traffic jams.
- Jinxiao Duan
- Guanwen Zeng
- Shlomo Havlin
ArticleOpen Access4 Dec 2023 Nature Communications
Optimal free-surface pumping by an undulating carpet

Pumping fluids at small scales near fluid-fluid interfaces remains challenging. Pandey et al. present a pump that drives interfacial flow by traveling waves on a deformable boundary.
- Anupam Pandey
- Zih-Yin Chen
- Sunghwan Jung
ArticleOpen Access25 Nov 2023 Nature Communications
Functional Janus structured liquids and aerogels

A combination of functional nanoparticles and liquid streaming can be used to generate structures for the fabrication of soft functional materials. In this study, authors demonstrate the creation of Janus-structured liquids with anisotropic and programmable distributions of nanoparticles by utilizing interfacial assembly and jamming of nanoparticles at the liquid-liquid interface.
- Ahmadreza Ghaffarkhah
- Seyyed Alireza Hashemi
- Mohammad Arjmand
ArticleOpen Access28 Nov 2023 Nature Communications
Constructing temporal networks with bursty activity patterns

Many real-world systems are characterized by bursty dynamics with interchanging periods of intense activity and quiescence. The authors propose a method to construct temporal networks that match a given activity pattern, and apply it to empirical bursty patterns.
- Anzhi Sheng
- Qi Su
- Joshua B. Plotkin
ArticleOpen Access11 Nov 2023 Nature Communications
Environmental memory boosts group formation of clueless individuals

Indirect coordination among individuals through the environment typically requires some basic levels of communication and information processing. Dias et al. introduce a coordination mechanism that emerges in a population of clueless individuals, facilitated by environmental memory, culminating in group formation.
- Cristóvão S. Dias
- Manish Trivedi
- Giorgio Volpe
ArticleOpen Access13 Nov 2023 Nature Communications
A generalized Knudsen theory for gas transport with specular and diffuse reflections

Knudsen theory and Smoluchowski model perform poorly for ballistic gas transport. Qian et al. propose a generalized Knudsen theory to describe gas nanoflow, reconciling both extreme specular reflection and complete diffuse reflection.
- JianHao Qian
- HengAn Wu
- FengChao Wang
ArticleOpen Access15 Nov 2023 Nature Communications
Electroconvective viscous fingering in a single polyelectrolyte fluid on a charge selective surface

When a low-viscosity fluid displaces into a higher viscosity fluid, the liquid-liquid interface becomes unstable causing finger-like patterns. These patterns are usually observed in two fluids, but here Kim et al. describes the development of fingers in a single polyelectrolyte fluid adjacent to a charge-selective interface under the influence of a potential gradient.
- Jeonghwan Kim
- Joonhyeon Kim
- Rhokyun Kwak
ArticleOpen Access17 Nov 2023 Nature Communications
Three-degrees-of-freedom orientation manipulation of small untethered robots with a single anisotropic soft magnet

Existing magnetic actuation systems using a single permanent magnet can only achieve 2-DoF orientation manipulation. Wang et al. propose a magnetic actuation method that uses a single anisotropic soft magnet instead of a permanent magnet to enable full 3-DoF orientation manipulation of small, untethered robots.
- Heng Wang
- Junhao Cui
- Yuxiang Han
ArticleOpen Access18 Nov 2023 Nature Communications
Simultaneous and independent topological control of identical microparticles in non-periodic energy landscapes

External fields can control the motion of colloidal particles inducing different trajectories depending on for instance the particle size. The authors here use nonperiodic energy landscapes and topological protection to transport a collection of identical colloidal particles simultaneously and independently.
- Nico C. X. Stuhlmüller
- Farzaneh Farrokhzad
- Daniel de las Heras
ArticleOpen Access18 Nov 2023 Nature Communications
Non-reciprocity across scales in active mixtures

Non-reciprocal interactions (NRI) are ubiquitous in active systems, but, in the presence of NRI, it is difficult to predict which microscopic systems correspond to a given macroscopic description. Dinelli et al. relate microscopic and macroscopic dynamics of active mixtures and show that non-reciprocity strongly depends on the scale of description.
- Alberto Dinelli
- Jérémy O’Byrne
- Julien Tailleur
ArticleOpen Access3 Nov 2023 Nature Communications
Spontaneous shock waves in pulse-stimulated flocks of Quincke rollers

Dielectric colloids suspended in a weak electrolyte and energized by a static electric field called Quincke rollers are the model system to study active matter. Zhang et al. report the formation of spontaneous shockwaves in the colloidal Quincke rollers under the temporal activity modulations.
- Bo Zhang
- Andreas Glatz
- Alexey Snezhko
ArticleOpen Access3 Nov 2023 Nature Communications
Bioinspired soft robots for deep-sea exploration

High pressure and low temperature are the greatest challenges faced by scientists to explore deep oceans, which remain largely unknow to us today. Li et al. review these challenges and give insight into designing soft robots, inspired by deep-sea creatures, that enable resilient operations in harsh conditions.
- Guorui Li
- Tuck-Whye Wong
- Tiefeng Li
PerspectiveOpen Access4 Nov 2023 Nature Communications
The nature and nurture of network evolution

Degree distributions are often used as informative descriptions of complex networks, however previous studies mainly focused on characterizing the tail of the distribution. The authors propose an evolutionary model that integrates the weight and degree of a node, which allows to better capture degree and degree ratio distributions of real networks and replicate their evolution processes.
- Bin Zhou
- Petter Holme
- Xiangyi Meng
ArticleOpen Access3 Nov 2023 Nature Communications
Grasping extreme aerodynamics on a low-dimensional manifold

In adverse weather, small-scale modern aircraft can encounter severe turbulence in urban canyons and mountainous areas hindering stable flight. The authors use machine learning to reveal the low-dimensional manifold that captures the extreme aerodynamics of gust-airfoil interactions.
- Kai Fukami
- Kunihiko Taira
ArticleOpen Access14 Oct 2023 Nature Communications
A nanoscale view of the origin of boiling and its dynamics

Boiling, despite being a well-known phenomenon still lacks an understanding of its multiscale and non-equilibrium nature. Using the stochastic mesoscale model based on fluctuating hydrodynamics and diffuse interface approach Gallo et al. describe the process of boiling from nucleation to macroscopic bubble dynamics.
- Mirko Gallo
- Francesco Magaletti
- Carlo Massimo Casciola
ArticleOpen Access13 Oct 2023 Nature Communications
Golden section criterion to achieve droplet trampoline effect on metal-based superhydrophobic surface

The relation between the rebound behavior of droplets and surface structure is crucial to regulating the surface dynamic wettability based on structure design. Zhao et al. explore droplet rebound numbers when the droplet impacts laser-ablated microstructures with different structure spaces and report that droplets can consecutively rebound 17 times.
- Shengteng Zhao
- Zhichao Ma
- Luquan Ren
ArticleOpen Access18 Oct 2023 Nature Communications
Minimum entropy production by microswimmers with internal dissipation

What is the physical limit on entropy production in a suspension of active microswimmers? In answer to this question, the authors derive a general theorem that provides an exact lower bound on the total, external and internal dissipation by a microswimmer and apply it to optimize swimmer shapes.
- Abdallah Daddi-Moussa-Ider
- Ramin Golestanian
- Andrej Vilfan
ArticleOpen Access28 Sep 2023 Nature Communications
Liquid–liquid phase separation within fibrillar networks

Liquid–liquid phase separation is known in cell biology as an underlying mechanism of intracellular organization. The authors study a complex interplay between phase separation, network mechanics, and condensate capillarity, providing explanation for the phenomena in complex environments like the cellular interior.
- Jason X. Liu
- Mikko P. Haataja
- Rodney D. Priestley
ArticleOpen Access29 Sep 2023 Nature Communications
Hyper-cores promote localization and efficient seeding in higher-order processes

Networks with higher-order interactions provide better description of social and biological systems, however tools to analyze their function still need to be developed. The authors introduce here a decomposition of network in hyper-cores, that gives better understanding of spreading processes and can be applied to fingerprint real-world datasets.
- Marco Mancastroppa
- Iacopo Iacopini
- Alain Barrat
ArticleOpen Access6 Oct 2023 Nature Communications
Predicting discrete-time bifurcations with deep learning

Critical transitions and qualitative changes of dynamics in cardiac, ecological, and economical systems, can be characterized by discrete-time bifurcations. The authors propose a deep learning framework that provides early warning signals for critical transitions in discrete-time experimental data.
- Thomas M. Bury
- Daniel Dylewsky
- Gil Bub
ArticleOpen Access10 Oct 2023 Nature Communications
Versatile bubble maneuvering on photopyroelectric slippery surfaces

Light-induced bubble maneuvering remains challenging in terms of response and functional adaptability due to the single driving mechanism including the Marangoni effect or asymmetrical deformation. Using a photopyroelectric slippery surface (PESS), Liu et al. demonstrate the splitting, merging, and detachment of underwater bubbles with high flexibility and precision.
- Haiyang Zhan
- Zichao Yuan
- Yahua Liu
ArticleOpen Access3 Oct 2023 Nature Communications
Electro-capillary peeling of thin films

Current methods for thin film peeling suffer from limitations because of complicated preparations and the limitations of applied films. Li et al. present a peeling method for the thin film’s detachment that is achieved by driving liquid to percolate and spread into the bonding layer under electric fields.
- Peiliu Li
- Xianfu Huang
- Ya-Pu Zhao
ArticleOpen Access3 Oct 2023 Nature Communications
Reactive wetting enabled anchoring of non-wettable iron oxide in liquid metal for miniature soft robot

Interfacial non-wettability between biocompatible iron oxide and liquid metal caused by the substantial mismatch in surface energy remains an issue. Here, the authors introduce a silver intermediate layer to reduce compositional mismatch and improve the wetting ability between iron oxide and liquid metal.
- Yifeng Shen
- Dongdong Jin
- Xing Ma
ArticleOpen Access7 Oct 2023 Nature Communications
Microrobots powered by concentration polarization electrophoresis (CPEP)

Concentration polarization electroosmosis (CPEO) has recently been found to produce similar flow patterns around spheres in an AC electric field as induced charge electroosmosis. Katzmeier and Simmel study the flow around the asymmetric particle dimers caused by CPEO and design a microrobot that can be steered with a joystick and facilitates the transport of cargo particles.
- Florian Katzmeier
- Friedrich C. Simmel
ArticleOpen Access6 Oct 2023 Nature Communications
Model-free tracking control of complex dynamical trajectories with machine learning

In nonlinear tracking control, relevant to robotic applications, the knowledge on the system model may be not available and there is current need in model-free approaches to track a desired trajectory, regular or chaotic. The authors introduce here a framework that employs machine learning to control a two-arm robotic manipulator using only partially observed states.
- Zheng-Meng Zhai
- Mohammadamin Moradi
- Ying-Cheng Lai
ArticleOpen Access14 Sep 2023 Nature Communications

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