Intentional doping is important in semiconductors in order to tune the material property, yet the mechanism in metal halide perovskite is not well-understood. Here, the authors use silver, strontium, and cerium ions to showcase n-type doping on perovskite surface even up to metallic state.
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.
Strong excitonic effects and spin-orbit coupling in all-inorganic halide perovskite is promising for spintronic application, yet the spin-dependent phenomenon is not well understood. Here, the authors reveal that many-body interactions between spin-polarized excitons act like pseudo-magnetic field, lifting the degeneracy and resulting in circular dichroism.
Controlling the behavior of a complex network usually requires a knowledge of the network dynamics. Baggio et al. propose a data-driven framework to control a complex dynamical network, effective for non-complete or random datasets, which is of relevance for power grids and neural networks.
The requirement for external electric supplies has significantly limited the application of electrochromic devices in modulating light absorption as smart windows. Here, the authors report automatic switching perovskite solar cells-powered all-in-one gel electrochromic device in response to surrounding light intensity in real-time.
Infrastructure networks are characterized by fluctuations of flow demand between different points and temporal congestion or overload on flow pathways. Hamedmoghadam et al. identify congestion bottlenecks in networks relevant to communication, transportation, water supply, and power distribution.
Networks with higher order interactions, relevant to social groups, ecosystems and human brain, require new tools and instruments for their analysis. Gambuzza et al. propose an analytical approach which allows to find conditions for stable synchronization in many-body interaction networks.
Defects in perovskite affect the properties and performance in optoelectronic devices, yet the nature of ionic defects remains elusive. Here, the authors investigate the ionic defect landscape in perovskite introduced by varying precursor stoichiometry, and find the defects fulfill the Meyer-Neldel rule.
The emergent excitation dynamics of an ultracold gas of Rydberg atoms exhibits features analogous to epidemic spreading on networks. Wintermantel et al. propose a controllable experimental system for studying network dynamics at the interface of mathematical models and real-world complex systems.
Temporal networks in which interaction events are distributed heterogeneously in time are complex to model. Unicomb et al. propose an analytical framework for the analysis of cascading dynamics in such networks, relevant for spin interactions, epidemic spreading, and language dynamics.
Bicontinuous porous materials made by colloidal self-assemblies have many applications. Xi et al. utilize colloidal particles dispersed in a binary solvent to form thermo-reversible bicontinuous gel structures with good reproducibility and scalability, and tunable structural and optical properties.
A self-propelling agent at small Reynolds numbers usually requires a fore-aft asymmetry in order to circumvent the scallop theorem. Here Rogowski et al. show that this need not be true for motion in non-linear viscoelastic fluids, where an initial symmetry may be broken spontaneously.
Power grid frequencies mirror the state of the grid. Here, Rydin Gorjão et al. analyse measurements of power grid frequencies across areas and continents and uncover scaling laws of their fluctuations and spatio-temporal dynamics, which could aid the design, operation and control of power systems.
Designing effective covert security features is highly regarded to deter counterfeit of goods and currency in the global markets. Here, the authors present an electrohydrodynamically printed unicolour multifluorescent-lifetime security tag system based on perovskite to provide an alternative yet affordable solution.
A tracking-free approach by Gnesotto et al. is developed to distinguish active and thermal fluctuations in microscopy data of non-equilibrium systems such as cell membranes. The method relies on a dimensional reduction scheme revealing a hierarchy of the most dissipative dynamical components.
Vertically stacked graphene oxide sheets are promising structures for molecular sieving technologies. By folding large planar sheets in an accordion-like manner, Liu et al. fabricate a thin robust filter with near-vertically aligned nanochannels geared towards commercial separation membranes.
The intermittency of solar resources is one of the primary challenges for the large-scale integration of the renewable energy. Here Yin et al. used satellite data and climate model outputs to evaluate the geographic patterns of future solar power reliability, highlighting the tradeoff between the maximum potential power and the power reliability.
The commercialisation of organic photovoltaic technology calls for research on material degradation mechanisms. Ramirez et al. show that triplet excitons produced by back charge transfer can significantly impact the photo-stability of fullerene-based devices even in the absence of water and oxygen.
Designing energy efficient and fast optoelectric neuromorphic systems remains a challenge. Long et al. report that the combined optical-electric stimulus enables switching the ferroelectric polarization and cycling the resistance state of BaTiO3 tunnel barriers, showing that the optical control of resistance is non-volatile.
Multiplayer games can be used as testbeds for the development of learning algorithms for artificial intelligence. Omidshafiei et al. show how to characterize and compare such games using a graph-based approach, generating new games that could potentially be interesting for training in a curriculum.
Supply networks with optimal structure do not contain loops but these can arise as a result of damages or fluctuations. Here Kaiser et al. uncover the mechanisms of loop formation, predict their location and draw analogies with loop formation in biological networks such as plants and animal vasculature.
The degree of irreversibility of a dynamical system is commonly characterized by the total rate of entropy production. Seara et al. introduce a measure that quantifies irreversibility from data in broad classes of spatiotemporal non-equilibrium systems.
The design principles underlying biomolecular phase separation of membrane-less organelles remain poorly understood. Using model homopolymers, Fisher et al. show that the formation kinetics of coexisting liquid phases can be tuned by exploiting differences between arginine and lysine residues.
Conformational disorder of organic cations tunes the charge carrier mobility in two-dimensional organic-inorganic perovskites
Understanding the correlation between molecular structure and properties of 2D hybrid perovskites is crucial for material design and device performance. Here, the authors reveal that conformation of organic cations in the inorganic cages has strong effects on charge mobility and broadband emission behaviour.
Integration of III-V semiconductor microlasers into modern Si or Si3N4 based photonic integrated circuits remains a challenge. Here, the authors demonstrate a perovskite vortex microlaser with highly directional outputs and well-controlled topological charges that is highly compatible with most materials.
Effects of social distancing and isolation on epidemic spreading modeled via dynamical density functional theory
Existing models describing epidemic spreading need an update to capture effects of social distancing and isolation. An extended model is proposed by te Vrugt et al. by drawing an analogy between persons and diffusing particles with repulsive interactions that correspond to social distancing.
Learning molecular dynamics with simple language model built upon long short-term memory neural network
Artificial neural networks have been successfully used for language recognition. Tsai et al. use the same techniques to link between language processing and prediction of molecular trajectories and show capability to predict complex thermodynamics and kinetics arising in chemical or biological physics.
Bellec et al. present a mathematically founded approximation for gradient descent training of recurrent neural networks without backwards propagation in time. This enables biologically plausible training of spike-based neural network models with working memory and supports on-chip training of neuromorphic hardware.
Detailed control over motions of colloidal particles holds promise for many applications such as lab-on-chip devices. Mirzaee-Kakhki et al. show transport of self-assembled colloidal rods with different lengths into different directions simultaneously on a checkerboard pattern under a magnetic field.
Ultra-conformal drawn-on-skin electronics for multifunctional motion artifact-free sensing and point-of-care treatment
Designing efficient wearable bioelectronics for health monitoring, disease prevention, and treatment, remains a challenge. Here, the authors demonstrate an ultra-conformal, customizable and deformable drawn-on-skin electronics which is robust to motion artifacts and resistant to physical damage.
Spiking neurons with spatiotemporal dynamics and gain modulation for monolithically integrated memristive neural networks
Designing energy efficient and scalable artificial networks for neuromorphic computing remains a challenge. Here, the authors demonstrate online learning in a monolithically integrated 4 × 4 fully memristive neural network consisting of volatile NbOx memristor neurons and nonvolatile TaOx memristor synapses.
Whether a turbulent flow would inevitably develop singular behavior at the smallest length scales is an ongoing intriguing debate. Using large-scale numerical simulations, Buaria et al. find an unexpected non-linear mechanism which counteracts local vorticity growth instead of enabling it.
The navigation of catheters through blood vessels requires flexible guiding wires that are pushable and tractable at the same time. Pancaldi et al. rely on hydrodynamic forces and magnetic torque in order to access even rather small capillaries with an ultraflexible magnetomechanical probe.