Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Robust stability”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 865 records · Page 48

Robust natural nanocomposites realizing unprecedented ultrafast precise molecular separations

Synthetic polymer membranes can potentially reduce the large energy and carbon footprints that are typically associated with traditional chemical separation technologies. Unfortunately, current production protocols negate the green benefits of membrane separation. To address this bottleneck, here we report the use of natural materials monosaccharide – glucose and polydopamine and Zr-based metal organic frameworks (MOFs) to fabricate ultrathin nanocomposite membranes via interfacial polymerization reaction. The synergistic effect of these three materials on angstrom-scale molecular transport both in organic solvent and aqueous environment was elucidated using a series of complementary techniques. We demonstrate such nature-inspired nanocomposite membranes enable structural stability even in polar aprotic solvents, and unparalleled ultra-fast, low-pressure, precise separations in both nanofiltration modes, which easily surpass state-of-the-art membranes relying on unsustainable materials. Finally, the multi-functionality of saccharide nanocomposites was elegantly harnessed to impact separation applications that contribute towards a better living environment.

36 MATERIALS SCIENCE↗

Single Particle Cathodoluminescence Spectroscopy with Sub-20 nm, Electron-Stable Phosphors

Lanthanide-doped nanophosphors have emerged as promising optical labels for high-resolution, "multicolor"electron microscopy. Here, we develop a library of 11 unique lanthanide-doped nanophosphors with average edge lengths of 15.2 ± 2.0 nm (N = 4284). These nanophosphors consist of an electron-stable BaYF5 host lattice doped at 25% atomic concentration with the lanthanides Pr 3+ , Nd 3+ , Sm 3+ , Eu 3+ , Tb 3+ , Dy 3+ , Ce 3+ , Ho 3+ , Er 3+ , Tm 3+ , and Yb 3+ . Under ~100 pA/nm 2 beam beam current in a transmission electron microscope, each nanophosphor species exhibits strong cathodoluminescence spectra with sharp characteristic emission lines for each lanthanide. The bright emission and stability of these nanoparticles enable not only ensemble, but also single-particle cathodoluminescence spectroscopy, which we demonstrate with BaYF 5 :Ln 3+ , where Ln 3+ = Tb 3+ , Ho 3+ , Er 3+ , Sm 3+ , Eu 3+ , or Pr 3+ . Single-particle cathodoluminescence corresponds directly with HAADF intensity across nanoparticles, confirming high spatial localization of the measured cathodoluminescence signal of lanthanide-doped nanophosphors. Furthermore, our synthesis and characterization of sub-20 nm, electron-stable nanophosphors provides a robust material platform to achieve single-molecule labeled correlative cathodoluminescence electron microscopy, a critical foundation for high-resolution correlation of single molecules within the context of cellular ultrastructure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Challenges in Continuous In-Field Critical Current Testing of High-Temperature Superconducting Tapes: Thermal and Mechanical Perspectives

High-temperature superconductors (HTS) are essential for ultra-high-field applications requiring exceptional current-carrying capacity under extreme conditions. However, systematic characterization of critical current in long-length conductors remains challenging due to complex thermal, electromag netic, and mechanical interactions during continuous testing. This study reports the development of a continuous in-field magnetization testing system for position-dependent critical current measurement in HTS tapes at 20 K under 7.5 T fields applied normal to the tape plane, enabling identification of performance-limiting regions that could compromise magnet stability. Here, the system addresses two fundamental challenges inherent to cryogenic reel to-reel testing. First, thermal management requires continuous cooling of a moving conductor to 20 K, achieved through liquid nitrogen precooling combined with a 100 W@20 K Gifford McMahon cryocooler. Second, screening currents in high fields generate Lorentz forces that induce twisting, bowing, and potential delamination. To mitigate these risks, we propose mechanical reinforcement and active current density suppression strategies. Numerical simulations using the stream function formulation reveal four primary failure modes: frictional heating at guide interfaces, unstable equilibria causing deformation, transverse current-induced stresses at guide transitions, and unsupported forces in vertical spans. Our mitigation strategies include PTFE coated guides to minimize friction, spring-loaded stabilization mechanisms to maintain tape alignment, controlled pre-heating using the liquid nitrogen thermal jacket to suppress critical current at stress points, and optimized guide positioning to minimize force accumulation. The experimental system is nearing completion, with testing planned to commence within two months. Preliminary validation at 65 K under 0.5 T demonstrates strong correlation between simulation-predicted mechanical instabilities and observed critical current variations during conductor tran sitions through the measurement region. These findings establish a robust foundation for quality assurance protocols essential to next-generation superconducting magnet applications.

Chen, Siwei [Princeton Plasma Physics Laboratory (↗

Thermal Stability and Outgassing Behaviors of High‐nickel Cathodes in Lithium‐ion Batteries

Abstract LiNiO 2 ‐based high‐nickel layered oxide cathodes are regarded as promising cathode materials for high‐energy‐density automotive lithium batteries. Most of the attention thus far has been paid towards addressing their surface and structural instability issues brought by the increase of Ni content (>90 %) with an aim to enhance the cycle stability. However, the poor safety performance remains an intractable problem for their commercialization in the market, yet it has not received appropriate attention. In this review, we focus on the gas generation and thermal degradation behaviors of high‐Ni cathodes, which are critical factors in determining their overall safety performance. A comprehensive overview of the mechanisms of outgassing and thermal runaway reactions is presented and analyzed from a chemistry perspective. Finally, we discuss the challenges and the insights into developing robust, safe high‐Ni cathodes.

Cui, Zehao↗

Synthetic-domain computing and neural networks using lithium niobate integrated nonlinear phononics

Analogue computing uses the physical behaviours of devices to provide energy-efficient arithmetic operations. However, scaling up analogue computing platforms by simply increasing the number of devices leads to challenges such as device-to-device variation. Here, in this study, we report scalable analogue computing and neural networks in the synthetic frequency domain using an integrated nonlinear phononic platform on lithium niobate. This synthetic-domain computing is robust to device variations, as vectors and matrices are concurrently encoded at different frequencies within a single device, achieving a high throughput per area. Leveraging inherent nonlinearities, our device-aware neural network can perform a four-class classification task with an accuracy of 98.2%. The nonlinear phononic computing hardware also maintains consistent performance over a wide operational temperature range (characterized up to 192 °C). Our synthetic-domain computing combines single-device parallelism, inherent nonlinearity and environmental stability, and could be of use in edge computing applications in which power efficiency and environmental resilience are crucial.

Ji, Jun [Virginia Polytechnic Inst. and State Univ↗

Programming Amphiphilic Peptoid Oligomers for Hierarchical Assembly and Inorganic Crystallization

Natural organisms make a wide variety of exquisitely complex, nano-, micro-, and macroscale structured materials in an energy-efficient and highly reproducible manner. During these processes, the information-carrying biomolecules (e.g., proteins, peptides, and carbohydrates) enable (1) hierarchical organization to assemble scaffold materials and execute high-level functions and (2) exquisite control over inorganic materials synthesis, generating biominerals whose properties are optimized for their functions. Inspired by nature, significant efforts have been devoted to developing functional materials that can rival those natural molecules by mimicking in vivo functions using engineered proteins, peptides, DNAs, sequence-defined synthetic molecules (e.g., peptoids), and other biomimetic polymers. Among them, peptoids, a new type of synthetic mimetics of peptides and proteins, have received particular attention because they combine the merits of both synthetic polymers (e.g., high chemical stability and efficient synthesis) and biomolecules (e.g., sequence programmability and biocompatibility). The lack of both chirality and hydrogen bonds in their backbone results in a highly designable peptoid-based system with reduced structural complexity and side chain-chemistry-dominated properties. Here in this Account, we present our recent efforts in this field by programming amphiphilic peptoid sequences for (1) the controlled self-assembly into different hierarchically structured nanomaterials with favorable properties and (2) manipulating inorganic (nano)crystal nucleation, growth, and assembly into superstructures. First, we designed a series of amphiphilic peptoids with controlled side chain chemistries that self-assembled into 1D highly stiff and dynamic nanotubes, 2D membrane-mimetic nanosheets, hexagonally patterned nanoribbons, and 3D nanoflowers. These crystalline nanostructures exhibited sequence-dependent properties and showed promise for different applications. The corresponding peptoid self-assembly pathways and mechanisms were also investigated by leveraging in situ atomic force microscopy studies and molecular dynamics simulations, which showed precise sequence dependency. Second, inspired by peptide- and protein-controlled formation of hierarchical inorganic nanostructures in nature, we developed peptoid-based biomimetic approaches for controlled synthesis of inorganic materials (e.g., noble metals and calcite), in which we took advantage of the substantial side chain chemistry of peptoids and investigated the relationship between the peptoid sequences and the morphology and growth kinetics of inorganic materials. For example, to overcome the challenges (e.g., complexity of protein- and peptide-folding, poor thermal and chemical stabilities) facing the area of protein- and peptide-controlled synthesis of inorganic materials, we recently reported the design of sequence-defined peptoids for controlled synthesis of highly branched plasmonic gold particles. Moreover, we developed a rule of thumb for designing peptoids that predictively enabled the morphological evolution from spherical to coral-shaped gold nanoparticles (NPs). With this Account, we hope to stimulate the research interest of chemists and materials scientists and promote the predictive synthesis of functional and robust materials through the design of sequence-defined synthetic molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

ALD-Derived WO 3– x Leads to Nearly Wake-Up-Free Ferroelectric Hf 0.5 Zr 0.5 O 2 at Elevated Temperatures

Breaking the memory wall in advanced computing architectures will require complex 3D integration of emerging memory materials such as ferroelectrics─either within the back-end-of-line (BEOL) of CMOS front-end processes or through advanced 3D packaging technologies. Achieving this integration demands that memory materials exhibit high thermal resilience, with the capability to operate reliably at elevated temperatures, such as 125°C, due to the substantial heat generated by front-end transistors. However, silicon-compatible HfO 2 -based ferroelectrics tend to exhibit antiferroelectric-like behavior in this temperature range, accompanied by a more pronounced wake-up effect, posing significant challenges to their thermal reliability. Here, we report that by introducing a thin tungsten oxide (WO 3–x ) layer─known as an oxygen reservoir─and carefully tuning its oxygen content, ultrathin Hf 0.5 Zr 0.5 O 2 (5 nm) films can be made robust against the ferroelectric-to-antiferroelectric transition at elevated temperatures. This approach not only minimizes polarization loss in the pristine state but also effectively suppresses the wake-up effect, reducing the required wake-up cycles from 10 5 to only 10 at 125°C, a qualifying temperature for back-end memory integrated with front-end logic, as defined by the JEDEC standard. First-principles density functional theory (DFT) calculations reveal that WO 3 enhances the stability of the ferroelectric orthorhombic phase (o-phase) at elevated temperatures by increasing the tetragonal-to-orthorhombic phase energy gap and promoting favorable phonon mode evolution, thereby supporting o-phase formation under both thermodynamic and kinetic constraints.

36 MATERIALS SCIENCE↗

Non-autoregressive time-series methods for stable parametric reduced-order models

Advection-dominated dynamical systems, characterized by partial differential equations, are found in applications ranging from weather forecasting to engineering design where accuracy and robustness are crucial. There has been significant interest in the use of techniques borrowed from machine learning to reduce the computational expense and/or improve the accuracy of predictions for these systems. These rely on the identification of a basis that reduces the dimensionality of the problem and the subsequent use of time series and sequential learning methods to forecast the evolution of the reduced state. Often, however, machine-learned predictions after reduced-basis projection are plagued by issues of stability stemming from incomplete capture of multiscale processes as well as due to error growth for long forecast durations. To address these issues, we have developed a non-autoregressive time series approach for predicting linear reduced-basis time histories of forward models. In particular, we demonstrate that non-autoregressive counterparts of sequential learning methods such as long short-term memory (LSTM) considerably improve the stability of machine-learned reduced-order models. Further, we evaluate our approach on the inviscid shallow water equations and show that a non-autoregressive variant of the standard LSTM approach that is bidirectional in the principal component directions obtains the best accuracy for recreating the nonlinear dynamics of partial observations. Moreover-and critical for many applications of these surrogates-inference times are reduced by three orders of magnitude using our approach, compared with both the equation-based Galerkin projection method and the standard LSTM approach.

97 MATHEMATICS AND COMPUTING↗

A Model-Reference Adaptive Direct-Power Control Scheme for Grid-Interactive Inverters

This paper develops an adaptive direct power control scheme for grid-interactive inverters while the control parameters are adaptively adjusted as the grid and filter parameters vary under different conditions. To demonstrate the efficacy and robustness of the adaptive operation, the performance of the adaptive controller is compared with a typical direct power controller by estimating the filter and grid impedances using a model reference parameter estimation technique with small signal injection. The simulation results verify that the developed methodology can track the reference power setpoints under output circuit parameter uncertainties while the typical design leads to instability. To improve the performance of the adaptive technique and eliminate the need for filter parameter estimation, a Lyapunov stability criterion-based model-reference adaptive direct power controller is designed to track the filter impedance. The developed method was tested using MATLAB/Simulink software to demonstrate the effectiveness of the proposed method. The results verify that adaptively tuning the control parameter can still maintain stable operation if the control gains are poorly selected while applying the classical method leads to abnormal operation or instability.

Gursoy, Mehmetcan↗

Fast Solution of Fully Implicit Runge--Kutta and Discontinuous Galerkin in Time for Numerical PDEs, Part II: Nonlinearities and DAEs

Fully implicit Runge--Kutta (IRK) methods have many desirable accuracy and stability properties as time integration schemes, but high-order IRK methods are not commonly used in practice with large-scale numerical PDEs because of the difficulty of solving the stage equations. This paper introduces a theoretical and algorithmic framework for solving the nonlinear equations that arise from IRK methods (and discontinuous Galerkin discretizations in time) applied to nonlinear numerical PDEs, including PDEs with algebraic constraints. Several new linearizations of the nonlinear IRK equations are developed, offering faster and more robust convergence than the often-considered simplified Newton, as well as an effective preconditioner for the true Jacobian if exact Newton iterations are desired. Inverting these linearizations requires solving a set of block 2 x 2 systems. Under quite general assumptions, it is proven that the preconditioned 2 x 2 operator's condition number is bounded by a small constant close to one, independent of the spatial discretization, spatial mesh, and time step, and with only weak dependence on the number of stages or integration accuracy. Moreover, the new method is built using the same preconditioners needed for backward Euler-type time stepping schemes, so can be readily added to existing codes. The new methods are applied to several challenging fluid flow problems, including the compressible Euler and Navier--Stokes equations, and the vorticity-streamfunction formulation of the incompressible Euler and Navier--Stokes equations. Up to 10th-order accuracy is demonstrated using Gauss IRK, while in all cases fourth-order Gauss IRK requires roughly half the number of preconditioner applications as required by standard Singly diagonally implicit Runge--Kutta methods.

97 MATHEMATICS AND COMPUTING↗

Design & Assembly of Atomically-Precise Quantum Materials & Devices (Final Report)

Atomic-layer honeycomb materials (Xene, where “X” may stand for a number of different elements) are a promising platform for new quantum states. When X is a heavier element such as tin (Sn) or bismuth (Bi), the edges of the honeycomb may conduct electron charge or spin without resistance - an effect that could persist up to room temperature in some cases. The type of edge states, and their robustness at room temperature, depend sensitively on (a) the substrate material that the Xene is sitting on; (b) out-of-plane buckling of the honeycomb structure; (c) the pattern of atoms or molecules sitting atop the honeycomb. This sensitivity suggests that Xene edge states could be tuned and rearranged to construct nanoscale electronic or spintronic devices. We report on theoretical progress in modeling the assembly and structure of Xenes, and their underlying substrates and overlaying atoms. Specifically, we model the stability of Sn atoms forming a single atomic layer (“stanene”), the stability and phase transitions

36 MATERIALS SCIENCE↗

Advanced Transmission Technologies – GETs and HPCs Session 2: Advanced Power Flow Control and Transmission Topology Optimization

The INL TADA GETs Cohort Session 2, held on November 7, 2025, conducted in collaboration with ScottMadden, focused on two core Advanced Transmission Technologies (ATTs): Advanced Power Flow Control (APFC) and Transmission Topology Optimization (TTO). These technologies are pivotal in enhancing grid flexibility, reliability, and cybersecurity resilience. APFC, particularly through modular FACTS devices like Modular Static Synchronous Series Compensators (M-SSSCs), enables dynamic voltage injection to reroute power flows. The session highlighted the deployment benefits of APFC, such as rapid installation, minimal civil works, and re-deployability. Regulatory drivers like FERC Order 2023 mandate the inclusion of Grid-Enhancing Technologies (GETs) in interconnection studies. Case studies from Central Hudson, CAISO, and National Grid (UK) demonstrated APFC’s effectiveness in congestion relief and cost savings. The session also addressed cybersecurity concerns, including firmware vulnerabilities, SCADA integration risks, and supply chain dependencies. Participants engaged in interactive exercises to rank cybersecurity and supply chain risks, emphasizing the need for robust digital assurance strategies. TTO involves software-based reconfiguration of transmission networks to optimize power flow without new infrastructure. The session showcased its operational value, with examples from SPP, PJM, and MISO showing significant congestion cost reductions. Cybersecurity vulnerabilities were discussed, particularly in API security and software supply chains, referencing incidents like SolarWinds and attacks on Danish utilities. Digital assurance exercises explored worst-case scenarios, attack paths, and mitigation responsibilities between vendors and utilities. Reliability challenges such as algorithm stability, vendor dependency, and operator trust were also examined. Cross-cutting themes emphasized the importance of digital assurance tools, including Software Bills of Materials (SBOMs) and hardware-in-loop testing. Human performance, training, and operational confidence were identified as critical enablers of technology adoption. The session concluded with a preview of Session 3, which will focus on High Performance Conductors (HPCs) and risk-based cybersecurity tools. Session 2 of 3.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

A Bioinspired Artificial Injury Response System Based on a Robust Polymer Memristor to Mimic a Sense of Pain, Sign of Injury, and Healing

Abstract Flexible electronic skin with features that include sensing, processing, and responding to stimuli have transformed human–robot interactions. However, more advanced capabilities, such as human‐like self‐protection modalities with a sense of pain, sign of injury, and healing, are more challenging. Herein, a novel, flexible, and robust diffusive memristor based on a copolymer of chlorotrifluoroethylene and vinylidene fluoride (FK‐800) as an artificial nociceptor (pain sensor) is reported. Devices composed of Ag/FK‐800/Pt have outstanding switching endurance >10 6 cycles, orders of magnitude higher than any other two‐terminal polymer/organic memristors in literature (typically 10 2 –10 3 cycles). In situ conductive atomic force microscopy is employed to dynamically switch individual filaments, which demonstrates that conductive filaments correlate with polymer grain boundaries and FK‐800 has superior morphological stability under repeated switching cycles. It is hypothesized that the high thermal stability and high elasticity of FK‐800 contribute to the stability under local Joule heating associated with electrical switching. To mimic biological nociceptors, four signature nociceptive characteristics are demonstrated: threshold triggering, no adaptation, relaxation, and sensitization. Lastly, by integrating a triboelectric generator (artificial mechanoreceptor), memristor (artificial nociceptor), and light emitting diode (artificial bruise), the first bioinspired injury response system capable of sensing pain, showing signs of injury, and healing, is demonstrated.

36 MATERIALS SCIENCE↗

Cluster expansion by transfer learning for phase stability predictions

Recent progress towards universal machine-learned interatomic potentials holds considerable promise for materials discovery. Yet the accuracy of these potentials for predicting phase stability may still be limited. In contrast, cluster expansions provide accurate phase stability predictions but are computationally demanding to parameterize from first principles, especially for structures of low dimension or with a large number of components, such as interfaces or multimetal catalysts. We overcome this trade-off via transfer learning. Using Bayesian inference, we incorporate prior statistical knowledge from machine-learned and physics-based potentials, enabling us to sample the most informative configurations and to efficiently fit first-principles cluster expansions. Furthermore, this algorithm is tested on Pt:Ni, showing robust convergence of the mixing energies as a function of sample size with reduced statistical fluctuations.

36 MATERIALS SCIENCE↗

Pseudoknot length modulates the folding, conformational dynamics, and robustness of Xrn1 resistance of flaviviral xrRNAs

To understand how RNA dynamics is regulated and connected to its function, we investigate the folding, conformational dynamics and robustness of Xrn1 resistance of a set of flaviviral xrRNAs using SAXS, smFRET and in vitro enzymatic assay. Flaviviral xrRNAs form discrete ring-like 3D structures, in which the length of a conserved longrange pseudoknot (PK2) ranges from 2 bp to 7 bp. We find that xrRNAs’ folding, conformational dynamics and Xrn1 resistance are strongly correlated and highly Mg 2+ - dependent, furthermore, the Mg 2+ -dependence is modulated by PK2 length variations. xrRNAs with long PK2 require less Mg 2+ to stabilize its folding, exhibits reduced conformational dynamics and strong Xrn1 resistance even at low Mg 2+ , and tolerates mutations at key tertiary motifs at high Mg 2+ , which generally are destructive to xrRNAs with short PK2. These results demonstrate an unusual regulatory mechanism of RNA dynamics providing insights into the functions and future biomedical applications of xrRNAs.

59 BASIC BIOLOGICAL SCIENCES↗

Resilience of the slow component in timescale separated synchronized oscillators

Physiological networks are usually made of a large number of biological oscillators evolving on a multitude of different timescales. Phase oscillators are particularly useful in the modelling of the synchronization dynamics of such systems. If the coupling is strong enough compared to the heterogeneity of the internal parameters, synchronized states might emerge where phase oscillators start to behave coherently. Here, we focus on the case where synchronized oscillators are divided into a fast and a slow component so that the two subsets evolve on separated timescales. We assess the resilience of the slow component by, first, reducing the dynamics of the fast one using Mori-Zwanzig formalism. Second, we evaluate the variance of the phase deviations when the oscillators in the two components are subject to noise with possibly distinct correlation times. From the general expression for the variance, we consider specific network structures and show how the noise transmission between the fast and slow components is affected. Interestingly, we find that oscillators that are among the most robust when there is only a single timescale, might become the most vulnerable when the system undergoes a timescale separation. We also find that layered networks seem to be insensitive to such timescale separations.

97 MATHEMATICS AND COMPUTING↗

Transformation of Highly Stable Pt Single Sites on Defect Engineered Ceria into Robust Pt Clusters for Vehicle Emission Control

Engineering surface defects on metal oxide supports could help promote the dispersion of active sites and catalytic performance of supported catalysts. Herein, a strategy of ZrO 2 doping was proposed to create rich surface defects on CeO 2 (CZO) and, with these defects, to improve Pt dispersion and enhance its affinity as single sites to the CZO support (Pt/CZO). The strongly anchored Pt single sites on CZO support were initially not efficient for catalytic oxidation of CO/C 3 H 6 . However, after a simple activation by H 2 reduction, the catalytic oxidation performance over Pt/CZO catalyst was significantly boosted and better than Pt/CeO 2 . Pt/CZO catalyst also exhibited much higher thermal stability. The structural evolution of Pt active sites by H 2 treatment was systematically investigated on aged Pt/CZO and Pt/CeO 2 catalysts. With H 2 reduction, ionic Pt single sites were transformed into active Pt clusters. Much smaller Pt clusters were created on CZO (ca. 1.2 nm) than on CeO 2 (ca. 1.8 nm) due to stronger Pt-CeO 2 interaction on aged Pt/CZO. Consequently, more exposed active Pt sites were obtained on the smaller clusters surrounded by more oxygen defects and Ce 3+ species, which directly translated to the higher catalytic oxidation performance of activated Pt/CZO catalyst in vehicle emission control applications.

36 MATERIALS SCIENCE↗

Geometrically stabilized skyrmionic vortex in FeGe tetrahedral nanoparticles

The concept of topology has dramatically expanded the research landscape of magnetism, leading to the discovery of numerous magnetic textures with intriguing topological properties. A magnetic skyrmion is an emergent topological magnetic texture with a string-like structure in three dimensions and a disk-like structure in one and two dimensions. Skyrmions in zero dimensions have remained elusive due to challenges from many competing orders. Here, by combining electron holography and micromagnetic simulations, we uncover the real-space magnetic configurations of a skyrmionic vortex structure confined in a B20-type FeGe tetrahedral nanoparticle. An isolated skyrmionic vortex forms at the ground state and this texture shows excellent robustness against temperature without applying a magnetic field. Furthermore, our findings shed light on zero-dimensional geometrical confinement as a route to engineer and manipulate individual skyrmionic metastructures.

36 MATERIALS SCIENCE↗