Information Processing Devices Research Articles

Static vector solitons in a topological mechanical lattice

Topological solitons, renowned for their stability and particle-like collision behaviors, have sparked interest in developing macroscopic-scale information processing devices. However, the exploration of interactions between multiple topological solitons in mechanical systems remains elusive. In this study, we construct a topological mechanical lattice supporting static vector solitons that represent quantized degrees of freedom and can freely propagate across the system. Drawing inspiration from coupled double atomic chains with sublattice symmetry breaking, we design a mechanical analogue featuring topologically protected boundary modes and induce independent modes to finite motions along branched motion pathways. Through a continuum theory, we describe the evolution of boundary modes with vector solitons composed of superposed kink solutions, identifying them as minimum energy pathways on the rugged effective potential surface with multiple degenerate ground states. Our results reveal the connection between transformable topological lattices and multistable systems, providing insight into nonlinear topological mechanics.

Vertically Integrated Monolithic Neuromorphic Nanowire Device for Physiological Information Processing.

This study demonstrates the conceptual design and fabrication of a vertically integrated monolithic (VIM) neuromorphic device. The device comprises an n-type SnO2 nanowire bottom channel connected by a shared gate to a p-type P3HT nanowire top channel. This architecture establishes two distinct neural pathways with different response behaviors. The device generates excitatory and inhibitory postsynaptic currents, mimicking the corelease mechanism of bilingual synapses. To enhance the signal processing efficiency, we employed a bipolar spike encoding strategy to convert fluctuating sensory signals to spike trains containing positive and negative pulses. Utilizing the neuromorphic platform for synaptic processing, physiological signals featuring bidirectional fluctuations, including electrocardiogram and breathing signals, can be classified with an accuracy of over 90%. The VIM device holds considerable promise as a solution for developing highly integrated neuromorphic hardware for healthcare and edge intelligence applications.

Spectrum of Gyrotropic Modes and Energy Transfer between Dipolar‐Coupled Magnetic Vortices in a Square Lattice via Triggered Vortex Gyration: A Promise for Spintronics Technology

AbstractThe atoms in a crystal lattice vibrate together and generate vibrational modes known as acoustic and optical phonon modes. Similarly, collective vortex gyration motion can be generated in artificial magnetic vortex lattices, created from periodically arranged nanodisks of specific dimensions and aspect ratios. This study uses micromagnetic simulations to characterize the spectra of gyrotropic modes in two‐dimensional magnetic vortex‐based, tailor‐made square lattice arrangements. The shifting of mode frequencies and mode splitting is witnessed depending on the vortex configurations in the lattice. The obtained gyrotropic modes are analogous to two‐dimensional square lattice structures exhibiting acoustic and optical phonon modes. The dynamics of magnetic vortices are also discussed in the transfer of magnetic energy at three points along the three high symmetry directions of the lattice when the central magnetic vortex is excited by a spin‐polarized current with an excitation frequency equal to the collective gyrotropic frequencies of the vortices. Similar to the higher contribution of acoustic phonon modes in the heat transmission process in a crystal lattice, acoustic‐like gyrotropic modes transfer more energy than optical‐like gyration modes in the vortex lattices. These magnetic metastructures hold promise for novel applications in magnetic waveguides and information processing devices, as well as for advancing spintronics.

Si/SiGe QuBus for single electron information-processing devices with memory and micron-scale connectivity function

The connectivity within single carrier information-processing devices requires transport and storage of single charge quanta. Single electrons have been adiabatically transported while confined to a moving quantum dot in short, all-electrical Si/SiGe shuttle device, called quantum bus (QuBus). Here we show a QuBus spanning a length of 10 μm and operated by only six simply-tunable voltage pulses. We introduce a characterization method, called shuttle-tomography, to benchmark the potential imperfections and local shuttle-fidelity of the QuBus. The fidelity of the single-electron shuttle across the full device and back (a total distance of 19 μm) is (99.7 ± 0.3) %. Using the QuBus, we position and detect up to 34 electrons and initialize a register of 34 quantum dots with arbitrarily chosen patterns of zero and single-electrons. The simple operation signals, compatibility with industry fabrication and low spin-environment-interaction in 28Si/SiGe, promises long-range spin-conserving transport of spin qubits for quantum connectivity in quantum computing architectures.

Devising a method for the virtual clustering of the Internet of Things edge environment

The object of research is the process of load distribution in the edge environment of the Internet of Things. The task to improve the efficiency of the functioning of the network of computing devices in the Internet of Things edge environment has been solved. Free resources of heterogeneous single-board computers were used to this end. In the process of conducting research, an approach to the construction of an architecture for a virtual cluster of computers with limited resources was devised. The design took into account specific features of the edge environment on the Internet of Things. This has made it possible to propose a four-layer architecture instead of the standard seven-layer architecture of IoT sensor information processing device networks. Stages in the virtual cluster construction in the edge environment on the Internet of Things were also defined. A three-stage procedure to form a virtual cluster was justified. This procedure made it possible to devise a method for the virtual clustering in the Internet of Things edge environment based on the proposed virtual cluster architecture. The proposed method for building a virtual cluster in the Internet of Things edge environment was investigated. With a small network load, a virtual cluster has no advantage over a classic cluster. But with the growth of the network load, the virtual cluster prevails over the classic cluster in total performance; the advantage in total performance can exceed 10 %. It was also proven that for a heterogeneous environment, performance changes at full network load significantly depend on the number of virtual node groups. The research results on the method for building a virtual cluster in the Internet of Things edge environment can be explained by improving the balance of the network load at virtual clustering

Engineering Ferroelectric‐/Ion‐Modulated Conductance in 2D vdW CuInP2S6 for Non‐Volatile Digital Memory and Artificial Synapse

AbstractTwo‐dimensional (2D) ferroionics is appealing in performing complex artificial intelligence tasks due to the interesting property of coexistence of ferroelectricity and ionic activities. CuInP2S6 (CIPS), as a typical 2D ferroionic material, is highly conducive to rich functions of information devices due to the displacement of Cu+ inducing both ferroelectricity and ionic conductivity. However, the coupling and modulation of polarization and ion migration in CIPS for multifunctional information devices has not been fully explored. Here, this study demonstrates that digital memory and synaptic simulations are realized in Au/CIPS/Au device via engineering ferroelectric polarization reversal and the long‐distance migration of the Cu+ to change conductive modes. Steep resistive switching behavior based on ion‐migration is observed with a high on/off ratio of over 108, long retention time (>2 × 104 s), and current compliance engineered multilevel resistance states, demonstrating reliable nonvolatile high‐density memory characteristics. Based on the continuous modulation of polar order, the key synaptic behaviors are successfully simulated. Moreover, by the co‐modulation of polarization state and ions migration, the paired‐pulse facilitation, paired‐pulse depression, and potentiation following depression are achieved. These results suggest that CIPS is a promising candidate for constructing high‐performance, function‐enriched devices for data storage, information processing, and neuromorphic computing.

Silicon-Compatible Ferroelectric Tunnel Junctions with a SiO2/Hf0.5Zr0.5O2 Composite Barrier as Low-Voltage and Ultra-High-Speed Memristors.

The big data era requires ultrafast, low-power, and silicon-compatible materials and devices for information storage and processing. Here, ferroelectric tunnel junctions (FTJs) based on SiO2/Hf0.5Zr0.5O2 composite barrier and both conducting electrodes are designed and fabricated on Si substrates. The FTJ achieves the fastest write speed of 500ps under 5V (2 orders of magnitude faster than reported silicon-compatible FTJs) or 10ns speed at a low voltage of 1.5V (the lowest voltage among FTJs at similar speeds), low write current density of 1.3 × 104 A cm-2, 8 discrete states, good retention >105 s at 85°C, and endurance >107. In addition, it provides a large read current (88 A cm-2) at 0.1V, 2 orders of magnitude larger than reported FTJs. Interestingly, in FTJ-based synapses, gradually tunable conductance states (128 states) with high linearity (<1) are obtained by 10ns pulses of <1.2V, and a high accuracy of 91.8% in recognizing fashion product images is achieved by online neural network simulations. These results highlight that silicon-compatible HfO2-based FTJs are promising for high-performance nonvolatile memories and electrical synapses.

Use of information redundancy to increase the reliability of devices for storing, processing and transmitting information

In modern information transmission systems, a special place is occupied by telecommunication systems (TS), which include digital data transmission systems (DSTS) containing specialized computers (SEVMs). The systems under consideration must ensure fast and reliable transmission of discrete data over communication lines. In this case, the loss of even one transmitted character is unacceptable; therefore, the main indicator of the reliability of a computer is the probability of failure-free operation. To increase the probability of failure-free operation of a storage device (MS), corrective codes and duplication are used, and to increase the probability of failure-free operation of the arithmetic-logical unit (ALU) of a computer, majority redundancy is used. The disadvantage of the majority method is the high hardware costs for redundancy, which reduces the efficiency of its use. The disadvantages of using correction codes include: as a rule, they are used for separate redundancy (detection and correction of errors that occur in storage devices; majority redundancy is used to detect and correct errors in the ALU); not all arithmetic and logical operations can be controlled based on existing correcting codes; a sharp increase in hardware costs when using algebraic linear codes to detect and correct multiple errors. Detection of errors in the ALU of a computer processor can be achieved on the basis of duplication in a loaded mode with replacement, however, this is associated with solving the main problem of computer duplication: - selection of monitoring tools for determining a failed channel (detection of errors in storage and information processing devices). The purpose of the research is to develop a scientific and methodological apparatus for computer backup using the duplication method with error detection in backup channels based on the use of an algebraic linear code, which makes it possible to detect errors not only in storage devices, but also adapted for detecting errors when performing arithmetic and logical operations. Results. An analysis of operation and selection of reliability indicators for specialized computers (SEVMs) of telecommunication systems was carried out. Requirements for computer backup methods are formulated. A comparative assessment of the detecting ability and hardware costs was carried out when implementing the majority redundancy method, the duplication method and the use of correcting codes. The expediency of using the duplication method is substantiated to increase the probability of failure-free operation and survivability of self-healing digital computers, using algebraic linear codes to determine the faulty channel, which allows to significantly reduce hardware costs for constructing monitoring equipment and use 10-30% of backup equipment for these purposes. It is proposed to use an algebraic linear code, in which, unlike well-known codes, the values of the check bits correspond to the direct and inverse values of the information bits, which makes it possible to detect errors when reading information from the inverse outputs of the memory, correct single errors, detect double errors and control the logical inversion operation , necessary to represent a negative number in two's complement code, which makes it possible to adapt the code to control arithmetic and logical operations of the computer processor. An assessment was made of the probability of failure-free operation of a duplicated computer, with its general redundancy, with detection and correction of single errors in the backup memory channels and detection of errors in the backup channels of the processor ALU based on the proposed code, and an assessment of the probability of failure-free operation of the computer, with its separate redundancy, with error detection in the backup channels of the duplicated memory based on the Hamming code and error correction in the backup channels of the processor ALU based on the majority method. A comparative assessment of the probabilities of failure-free operation allows us to conclude that the general redundancy of the computer based on the proposed code, in comparison with the separate redundancy of the memory and ALU of the computer processor, allows for a gain in the probability of failure-free operation of the computer and its functional devices throughout the entire period of operation. The practical significance lies in the fact that the proposed scientific and methodological apparatus provides: reduction of hardware costs for identifying a faulty channel when organizing duplication; detection of errors in the memory and ALU of the computer processor with time costs not exceeding the time of error detection when using standard methods of monitoring the computer system.

Brain-Inspired Reservoir Computing Using Memristors with Tunable Dynamics and Short-Term Plasticity.

Recent advancements in reservoir computing (RC) research have created a demand for analogue devices with dynamics that can facilitate the physical implementation of reservoirs, promising faster information processing while consuming less energy and occupying a smaller area footprint. Studies have demonstrated that dynamic memristors, with nonlinear and short-term memory dynamics, are excellent candidates as information-processing devices or reservoirs for temporal classification and prediction tasks. Previous implementations relied on nominally identical memristors that applied the same nonlinear transformation to the input data, which is not enough to achieve a rich state space. To address this limitation, researchers either diversified the data encoding across multiple memristors or harnessed the stochastic device-to-device variability among the memristors. However, this approach requires additional preprocessing steps and leads to synchronization issues. Instead, it is preferable to encode the data once and pass them through a reservoir layer consisting of memristors with distinct dynamics. Here, we demonstrate that ion-channel-based memristors with voltage-dependent dynamics can be controllably and predictively tuned through the voltage or adjustment of the ion channel concentration to exhibit diverse dynamic properties. We show, through experiments and simulations, that reservoir layers constructed with a small number of distinct memristors exhibit significantly higher predictive and classification accuracies with a single data encoding. We found that for a second-order nonlinear dynamical system prediction task, the varied memristor reservoir experimentally achieved an impressive normalized mean square error of 1.5 × 10-3, using only five distinct memristors. Moreover, in a neural activity classification task, a reservoir of just three distinct memristors experimentally attained an accuracy of 96.5%. This work lays the foundation for next-generation physical RC systems that can exploit the complex dynamics of their diverse building blocks to achieve increased signal processing capabilities.

Integrated Manipulation and Addressing of Spin Defect in Diamond.

Scalable and addressable integrated manipulation of qubits is crucial for practical quantum information applications. Different waveguides have been used to transport the optical and electrical driving pulses, which are usually required for qubit manipulation. However, the separated multifields may limit the compactness and efficiency of manipulation and introduce unwanted perturbation. Here, we develop a tapered fiber-nanowire-electrode hybrid structure to realize integrated optical and microwave manipulation of solid-state spins at nanoscale. Visible light and microwave driving pulses are simultaneously transported and concentrated along an Ag nanowire. Studied with spin defects in diamond, the results show that the different driving fields are aligned with high accuracy. The spatially selective spin manipulation is realized. And the frequency-scanning optically detected magnetic resonance (ODMR) of spin qubits is measured, illustrating the potential for portable quantum sensing. Our work provides a new scheme for developing compact, miniaturized quantum sensors and quantum information processing devices.

Enhancing plasticity in optoelectronic artificial synapses: A pathway to efficient neuromorphic computing

The continuous growth in artificial intelligence and high-performance computing has necessitated the development of efficient optoelectronic artificial synapses crucial for neuromorphic computing (NC). Ga2O3 is an emerging wide-bandgap semiconductor with high deep ultraviolet absorption, tunable persistent photoconductivity, and excellent stability toward electric fields, making it a promising component for optoelectronic artificial synapses. Currently reported Ga2O3 optoelectronic artificial synapses often suffer from complex fabrication processes and potential room for improvement due to plasticity. To address the issue of low device plasticity and practical application scenarios, we present an amorphous Ga2O3 (α-GaOx) flexible optoelectronic artificial synapse. This synapse modulates light stimulus signals using electron/oxygen vacancies and optical stimulation and operates as a visual storage device for information processing. We investigate the improvement of the optoelectronic synapses' plasticity by controlling the number of oxygen vacancies via a plasma treatment method and demonstrate its effective application in a three-layer backpropagation neural network for handwritten digit classification. Under the same stimulus conditions, the synaptic weight of samples treated with Ar plasma exhibits a higher rate of change, with the current levels increasing by 2–3 orders of magnitude, achieving greater plasticity. The improved optoelectronic synapses achieved an accuracy of 93.34%/94%, demonstrating their potential as efficient computing solutions and insights for future applications in NC chips.

Magnetic skyrmions and their manipulations in a 2D multiferroic CuCrP2Te6 monolayer.

Magnetic skyrmions and their effective manipulations are promising for the design of next-generation information storage and processing devices, due to their topologically protected chiral spin textures and low energy cost. They, therefore, have attracted significant interest from the communities of condensed matter physics and materials science. Herein, based on density functional theory (DFT) calculations and micromagnetic simulations, we report the spontaneous 2 nm-diameter magnetic skyrmions in the monolayer CuCrP2Te6 originating from the synergistic effect of broken inversion symmetry and strong Dzyaloshinskii-Moriya interactions (DMIs). The creation and annihilation of magnetic skyrmions can be achieved via the ferroelectric to anti-ferroelectric (FE-to-AFE) transition, due to the variation of the magnetic parameter D2/|KJ|. Moreover, we also found that the DMIs and Heisenberg isotropic exchange can be manipulated by bi-axial strain, to effectively enhance skyrmion stability. Our findings provide feasible approaches to manipulate the skyrmions, which can be used for the design of next-generation information storage devices.

A 2D Heterostructure-Based Multifunctional Floating Gate Memory Device for Multimodal Reservoir Computing.

The demand for economical and efficient data processing has led to a surge of interest in neuromorphic computing based on emerging two-dimensional (2D) materials in recent years. As a rising van der Waals (vdW) p-type Weyl semiconductor with many intriguing properties, tellurium (Te) has been widely used in advanced electronics/optoelectronics. However, its application in floating gate (FG) memory devices for information processing has never been explored. Herein, an electronic/optoelectronic FG memory device enabled by Te-based 2D vdW heterostructure for multimodal reservoir computing (RC) is reported. When subjected to intense electrical/optical stimuli, the device exhibits impressive nonvolatile electronic memory behaviors including ≈108 extinction ratio, ≈100 ns switching speed, >4000 cycles, >4000-s retention stability, and nonvolatile multibit optoelectronic programmable characteristics. When the input stimuli weaken, the nonvolatile memory degrades into volatile memory. Leveraging these rich nonlinear dynamics, a multimodal RC system with high recognition accuracy of 90.77% for event-type multimodal handwritten digit-recognition is demonstrated.

Terahertz spin currents resolved with nanometer spatial resolution

The development of coherent terahertz (THz) spin currents with femtosecond temporal resolution has been extensively studied due to its significant implications for advancing high-speed information processing devices. However, the precise spatial resolution of THz spin currents, which is crucial for increasing storage density, is still unknown. In this study, we employ spintronic THz emission nanoscopy (STEN) to achieve efficient injection and accurate detection of femtosecond THz spin currents with nanoscale lateral spatial resolution (∼60 nm). The occurrence of emission signals at the fifth harmonic order indicates a substantial signal-to-noise ratio. Additionally, STEN proves to be an effective method for characterizing and etching nanoscale spintronic heterostructures. The integration of nanophotonics, nanospintronics, and THz-nanotechnology into a unified platform is poised to enable the characterization of spin states at micro-to-nanoscale densities, accelerate the development of high-frequency spintronic optoelectronic nanodevices, and catalyze other revolutionary technical applications.

All-Optical Switches for Optical Soliton Interactions in a Birefringent Fiber

Interactions among optical solitons can be used to develop photonic information processing devices such as all-optical switches and all-optical logic gates. It is the key to achieve high-speed, high-capacity all-optical networks and optical computers, which is also important in academy. We study the properties of all-optical switches of optical solitons in birefringent fibers, based on the coupled nonlinear Schrödinger equations. It is found that under different initial conditions we can achieve all-optical switching functions. We also study the influence of different physical parameters of birefringent fibers on all-optical soliton switching. The relevant conclusions are conducive to achieving the all-optical switching function of optical solitons in birefringent fibers, providing useful guidance for widespread applications of optical soliton all-optical switches in birefringent fibers of communications.

A Topological Valley Stamping Plate for Low-Frequency-Vibration Isolation and Wave Manipulation in Helicopters

Vibration isolation and wave manipulation play a significant role in helicopter applications, from small elastic devices for information processing to large solid structures for vibration control. The emergence of topological elastic metamaterials has opened up new possibilities for modulating vibrations and waves in solids. However, most designs are limited to laboratory settings due to complex manufacturing or low structural strength. In this study, we propose a topological elastic metamaterial with a stamping triangle whose orientation θ can be rotated to achieve topological phase transitions between −30° and 30°. Unlike traditional manufacturing methods, the utilization of stamping technology provides a cost-effective means of production, allowing for wider application across diverse industries. Moreover, the metamaterial has the capability to manipulate elastic waves along specific trajectories and effectively decrease common vibrations (more than 50 dB), typically occurring at a frequency of 24 Hz in helicopters. Our approach also enables the control of elastic wave propagation along interfaces through the emergence of topological edge states. The practical implementation of this design will enhance the confidence in using topological elastic metamaterials for vibration isolation and wave manipulation in helicopters.

Giant Nonvolatile Electric Field Control of Proximity‐Induced Magnetism in the Spin–Orbit Semimetal SrIrO3

AbstractWith its potential for drastically reduced operation power of information processing devices, electric field control of magnetism has generated huge research interest. Recently, novel perspectives offered by the inherently large spin–orbit coupling of 5d transition metals have emerged. Here, nonvolatile electrical control of the proximity‐induced magnetism in SrIrO3 based back‐gated heterostructures is demonstrated. Up to a 700% variation of the anomalous Hall conductivity (σAHE) and Hall angle (ΘAHE) as function of the applied gate voltage Vg is reported. In contrast, the Curie temperature TC ≈ 100 K and magnetic anisotropy of the system remain essentially unaffected by Vg indicating a robust ferromagnetic state in SrIrO3 which strongly hints to gating‐induced changes of the anomalous Berry curvature. The electric‐field induced ferroelectric‐like state of SrTiO3 enables nonvolatile switching behavior of σAHE and ΘAHE below 60 K. The large tunability of this system, opens new avenues toward efficient electric‐field manipulation of magnetism.

Geometric phase and photonic spin Hall effect in thin films with architected columnar morphology

We have detected spin-dependent splitting of light, the signature of the photonic spin Hall effect (PSHE), via quantum weak measurements on two types of thin films with architected columnar morphology. Specifically, we fabricated columnar thin films comprising parallel tilted nanocolumns and chiral sculptured thin films comprising parallel upright nanohelices by resistively heating zinc selenide (ZnSe) in a low-pressure chamber and collecting the collimated vapor flux of ZnSe on planar substrates with dynamically varying orientation. The architected columnar morphology creates a spin-dependent geometric Pancharatnam–Berry (PB) phase corresponding to the evolution of polarization states on the Poincaré sphere. Morphology-controlled anisotropy and spatial inhomogeneity result in the depolarization and optical rotation of incident plane-polarized light, and intrinsic spin-precession coupling with the propagation vector, contributing to the efficient generation and two-dimensional manipulation of both in-plane and out-of-plane spin splitting and steering the PB phase in the propagation process. The first experimental observations of widely tailorable PSHE and PB phase in thin films with architected columnar morphology may lead to new applications ranging from spin-controlled nanophotonics to optoelectronic devices for quantum information processing and optical communication.

Near-field observation of mid-infrared edge modes in topological photonic crystals

Topological photonic crystals inherit the unique properties of topological insulators, including topologically protected energy transfer and unidirectional propagation, which offer an excellent platform for exploring exotic physics and developing photonic devices. However, topological photonic crystals possessing mid-infrared edge modes that have potential applications in infrared imaging, biosensing, thermal radiation energy transfer, etc., are seldom brought into focus. In this work, we study the topological properties of a photonic crystal slab (PCS) consisting of silicon square veins in the mid-infrared, which is intended to mimic the two-dimensional Su–Schrieffer–Heeger model. By interfacing topologically trivial and nontrivial PCSs, mid-infrared edge modes can appear at domain wall, according to the principle of bulk-edge correspondence. It is also demonstrated high-efficiency mid-infrared light transport can be achieved by these edge modes. In addition, adjusting the vertical offset near the interface can manipulate the bandwidth for various applications and turns the connected PCS structure to a photonic realization of Rice–Mele model. We further fabricate the PCS and provide an experimental observation of transverse-electric-like edge modes in mid-infrared by using the scattering-type scanning near-field optical microscope. Additionally, we integrate it with phase change material of nanoscale thickness, Ge2Sb2Te5, to realize an ultrafast and switchable topological waveguide with zero static power. This work not only enriches the fundamental understanding of topological physics in mid-infrared optical settings, but also shows promising prospects in compact devices for energy transfer and information processing for light sources in these wavelengths, for instance, thermal radiation.

Comparative Density Functional Theory Study of Magnetic Exchange Couplings in Dinuclear Transition-Metal Complexes.

Multicenter transition-metal complexes (MCTMs) with magnetically interacting ions have been proposed as components for information-processing devices and storage units. For any practical application of MCTMs as magnetic units, it is crucial to characterize their magnetic behavior, and in particular, the isotropic magnetic exchange coupling, J, between its magnetic centers. Due to the large size of typical MCTMs, density functional theory is the only practical electronic structure method for evaluating the J coupling. Here, we assess the accuracy of different density functional approximations for predicting the magnetic couplings of eight dinuclear transition-metal complexes, including five dimanganese, two dicopper, and one divanadium with known reliable experimental J couplings spanning from ferromagnetic to strong antiferromagnetic. The density functionals considered include global hybrid functionals which mix semilocal density functional approximations and exact exchange with a fixed admixing parameter, six local hybrid functionals where the admixing parameters are extended to be spatially dependent, the SCAN and r2SCAN meta-generalized gradient approximations (GGAs), and two widely used GGAs. We found that global hybrids tested in this work have a tendency to over-correct the error in magnetic coupling parameters from the Perdew-Burke-Ernzerhof (PBE) GGA as seen for manganese complexes. The performance of local hybrid density functionals shows no improvement in terms of bias and is scattered without a clear trend, suggesting that more efforts are needed for the extension from global to local hybrid density functionals for this particular property. The SCAN and r2SCAN meta-GGAs are found to perform as well as benchmark global hybrids on most tested complexes. We further analyze the charge density redistribution of meta-GGAs as well as global and local hybrid density functionals with respect to that of PBE, in connection to the self-interaction error or delocalization error.