Complex Multilayer Structures Research Articles

Nonlinear Harmonics: A Gateway to Enhanced Image Contrast and Material Discrimination.

Recent advancements in atomic force microscopy (AFM) have enabled detailed exploration of materials at the molecular and atomic levels. These developments, however, pose a challenge: the data generated by microscopic and spectroscopic experiments are increasing rapidly in both size and complexity. Extracting meaningful physical insights from these datasets is challenging, particularly for multilayer heterogeneous nanoscale structures. In this paper, an unsupervised approach is presented to enhance AFM image contrast by analyzing the nonlinear response of a cantilever interacting with a material's surface using a wavelet-based AFM. This method simultaneously measures different frequencies and harmonics in a single scan, without the need for additional hardware and exciting multiple cantilevers' eigenmodes. This developed AFM image contrast enhancement (AFM-ICE) approach employs unsupervised learning, image processing, and image fusion techniques. The method is applied to interpret complex multilayer structures consist of defects, deposited nanoparticles and heterogeneities. Its substantial capability is demonstrated to improve image contrast and differentiate between various components. This methodology can pave the way for rapid and precise determination of material properties with enhancedresolution.

Accurate equivalent circuit design of an ultra-broadband composite absorber

The combination of circuit analog absorber (CAA) and honeycomb absorbing material (HAM) has the advantages of lower profile, wider absorption bandwidth, and strong absorption performance. However, the increase in the number of CAA interlaced with various dielectric spacers makes the design and optimization of this complex multi-layer structure more difficult. Here, an accurate equivalent circuit model (ECM) of the multi-layer lossy single-square loop (SSL) metal-grounded is developed, which can be used to quickly design and optimize absorbers with the aid of genetic algorithm (GA). Based on the guideline, a lightweight composite absorber consisting of a double-layer impedance-sheet CAA at the top and a HAM at the bottom is developed. It covers an ultra-wideband -10 dB reflection reduction in the frequency band of 0.83 to 18 GHz with a fractional bandwidth of 182% in a total thickness of 35 mm and only 4% over the minimum thickness calculated by the Rozanov limit. The CAA is responsible for the absorption at a lower frequency, while the HAM absorbs the incident electromagnetic waves at the higher end of the frequency spectrum. The agreement between the experimental and simulated results verifies the viability of our design approach.

Formation and snake-eating like solubilization mechanisms of rhamnolipid vesicles for oil components and amino acids

Rhamnolipid vesicles hold significant potential across a wide range of applications, yet their formation mechanisms and selective solubilization of organic molecules remain elusive. Employing dissipative particle dynamics (DPD) simulations, this study delves deeply into these aspects, uncovering a stepwise formation pathway from dispersed monomers to complex multi-layer vesicle structures. The fusion and growth of three-layer structures were identified as crucial steps in the development of stacked vesicles. Notably, double-chain rhamnolipids (Rh-C10-C10) exhibited enhanced stability in self-assembled structures compared to their single-chain counterparts (Rh-C10). Through a detailed analysis of parameters such as relative concentration distribution, radial distribution function, and density fields, the solubilization process of rhamnolipid vesicles was found to resemble a “snake-eating” mechanism. We also analyzed the solubilization sites, amounts, and vesicle sizes, elucidating the selective solubilization mechanisms of rhamnolipids for representative polar and non-polar compounds in crude oil, anisole and 1-hexene. The selectivity of rhamnolipid vesicles in solubilizing organic molecules was primarily influenced by polar attraction and steric hindrance, which together determined their solubilization sites within the vesicles. Additionally, the solubilization behavior and properties of five types of amino acids within rhamnolipid vesicles were explored, demonstrating analogous solubilization patterns that correlated with amino acid polarity. These results provide a foundation for optimizing the application of rhamnolipid vesicles, paving the way for potential advancements in drug delivery, environmental remediation, and oil recovery processes.

Subwavelength broadband light-harvesting metacoating for infrared camouflage and anti-counterfeiting empowered by inverse design

Broadband mid-infrared (MIR) light harvesting is critical for a wide range of applications, including thermophotovoltaic conversion, thermal sensing and imaging, infrared camouflage and anti-counterfeiting technologies. In this study, we present the design and experimental validation of a deep-subwavelength broadband MIR light-harvesting metacoating (MMC), optimized through a genetic algorithm (GA)-based inverse design approach. The strength of this approach lies in its ability to automate and optimize the complex multilayer structure, encompassing both material selection and structural thickness, thereby achieving unparalleled performance in broadband MIR light absorption, with an average absorbance of approximately 0.85 across the 3–13 μm spectral range and nearly perfect absorption within the 4–12 μm range. This exceptional performance is attributed to strong electromagnetic localization within its multilayer configuration, facilitating efficient energy dissipation via high-loss materials such as bismuth and titanium. Notably, the MMC exhibits robust performance with respect to angle and polarization variations, maintaining high absorbance even at incident angles up to 70°. Its large-area fabrication capabilities and compatibility with various substrates further enhance its practical applicability. Two specific applications, long-wavelength infrared camouflage and anti-counterfeiting, highlight its potential for real-world deployment. In these applications, the MMC seamlessly integrates into high-emission environments and enables the modulation of patterned infrared emission, providing a lithography-free, cost-effective solution compared to conventional methods relying on artificially engineered structures. This work underscores the versatility of the developed MMC for a diverse array of MIR applications, ranging from camouflage technologies to advanced security measures.

Recent Advances in the Fabrication and Application of Electrochemical Paper-Based Analytical Devices.

In response to growing environmental concerns, the scientific community is increasingly incorporating green chemistry principles into modern analytical techniques. Electrochemical paper-based analytical devices (ePADs) have emerged as a sustainable and efficient alternative to conventional analytical devices, offering robust applications in point-of-care testing, personalized healthcare, environmental monitoring, and food safety. ePADs align with green chemistry by minimizing reagent use, reducing energy consumption, and being disposable, making them ideal for eco-friendly and cost-effective analyses. Their user-friendly interface, alongside sensitive and selective detection capabilities, has driven their popularity in recent years. This review traces the evolution of ePADs from simple designs to complex multilayered structures that optimize analyte flow and improve detection. It also delves into innovative electrode fabrication methods, assessing key advantages, limitations, and modification strategies for enhanced sensitivity. Application-focused sections explore recent advancements in using ePADs for detecting diseases, monitoring environmental hazards like heavy metals and bacterial contamination, and screening contaminants in food. The integration of cutting-edge technologies, such as wearable wireless devices and the Internet of Things (IoT), further positions ePADs at the forefront of point-of-care testing (POCT). Finally, the review identifies key research gaps and proposes future directions for the field.

A Bottom-Up Approach to Assemble Cell-Laden Biomineralized Nanofiber Mats into 3D Multilayer Periosteum Mimics for Bone Regeneration.

The creation of complex multilayer periosteal graft structures is challenging. This study introduced a novel bottom-up approach to assemble cell-laden nanofiber mats into a three-dimensional (3D) multilayer periosteum mimic, successfully replicating the hierarchical complexity of the natural periosteum. These nanofiber mats, which were fabricated by electrospinning, surface modification, and stimulated body fluid (SBF) immersion, are composed of nanoscale polycaprolactone (PCL) fibers coated with a mineralized collagen layer along the fiber orientation. They closely resembled the natural periosteal matrix, thereby promoting osteogenic differentiation of rat bone marrow mesenchymal stem cells (rBMSCs) in vitro. The biomimetic periosteum, constructed via layer-by-layer assembly, offered advantages such as a multilayer nanofibrous structure, controlled cell distribution, a reservoir for osteoprogenitors, and enhanced pro-osteogenic potential. The rat calvarial bone defect model confirmed its potent bone repair capacity. This study presents an efficient approach to construct tissue-engineered periosteum mimics, holding promise for serving as periosteal grafts in orthopedic applications.

A Two-Step Dry Etching Model for Non-Uniform Etching Profile in Gate-All-Around Field-Effect Transistor Manufacturing.

The Gate-All-Around Field-Effect Transistor (GAAFET) is proposed as a successor to Fin Field-Effect Transistor (FinFET) technology to increase channel length and improve the device performance. The GAAFET features a complex multilayer structure, which complicates the manufacturing process. One of the most critical steps in GAAFET fabrication is the selective lateral etching of the SiGe layers, essential for forming the inner-spacer. Industry commonly encounters a non-uniform etching profile during this step. In this paper, a continuous two-step dry etching model is proposed to investigate the mechanism behind the formation of the non-uniform profiles. The model consists of four modules: anisotropic etching simulation, Ge atom diffusion simulation, Si/SiGe etch selectivity calculation and SiGe selective etching simulation. By calibrating and verifying this model with experimental data, the edge rounding and gradient etching rates along the sidewall surface are successfully simulated. Based on further examination of the influence of chamber pressure on the profile using this model, the inner-spacer shape is improved experimentally by appropriately reducing the chamber pressure. This work aims to provide valuable insights for etching process recipes in advanced GAAFETs manufacturing.

Research on the impact mechanism and parameter optimization of RTP structure layer fusion process

Fiber-reinforced thermoplastic composite pipes (RTP) possess a complex multilayer structure. Apart from the melting process of the reinforced layer, the melting process between the inner and outer layers and the reinforced layer is equally crucial. Factors such as heating time, heating temperature, and pipe diameter significantly influence the degree of tight bonding between these layers. The purpose of this study is to investigate the influence mechanism of the fusion process between the three main layers of RTP and to perform parameter optimization analysis. First, Box-Behnken response surface method and finite element analysis were used to obtain the softened layer thickness under different parameters and to couple the influence mechanism of process parameters on the softened layer thickness. Then, single parameter sensitivity analysis was used to reveal the influence mechanism of each parameter change on the softened layer thickness of the pipe, and then the coupling analysis of the process parameters was carried out. The analysis results show that the softened layer thickness is most sensitive to the change of heating temperature, followed by heating time and pipe diameter. Finally, the optimal parameter combination was obtained through the expected function method, and experiments were conducted on finished pipes.

Computational ultrasound testing for non-destructive evaluation of multilayered structures: 3D modeling of longitudinal wave propagation signal responses

Non-destructive evaluation (NDE) using ultrasonic imaging (UI) is essential for detecting defects in complex multilayered structures, which are commonly encountered in aerospace, automotive, and medical fields. A thorough understanding of material properties, wave propagation, and dispersion behavior is crucial for accurate defect detection. The Transfer Matrix Method (TMM) provides a comprehensive approach by modeling the entire UI process, including the control system, ultrasonic transmitter, wave propagation (both bulk and guided modes), and receiver response. This study focuses on predicting the backscattered ultrasonic signal during longitudinal wave propagation in a multilayer structure immersed in water, considering normal incidence and specific frequencies. TMM, employing a quadrupole formalism, integrates stress and velocities at layer boundaries and models the multilayer structure as a transfer matrix derived from individual layer matrices. This approach allows for the calculation of reflection coefficients across a wide frequency spectrum. TMM generates detailed distance-time and distance-frequency representations that illustrate the propagation of various longitudinal modes in configurations, such as plexiglass/water/glass under direct (PWG) and reverse (GWP) insonation. Comparisons between PWG and GWP distance-time planes may be affected by layer arrangement and properties, which influence the reflection coefficient, highlighting the system's sensitivity to layer order even with similar thicknesses and materials.

Diamine-surfactant adsorption at the air–water interface: The impact of the diamine structure, surfactant structure and solution pH

The biogenic amines, polyamines, such as putrescine and cadavarine, are small flexible polycations. They interact with charged biological species and have a range of important biological functions. Their strong interaction with anionic surfactants results in enhanced adsorption at interfaces. Aspects of the impact of the polyamine molecular weight and structure on the pattern of surfactant adsorption at the air–water interface have been explored previously using neutron reflectivity, NR, and surface tension, ST. However there is limited evidence for the extent to which surfactant adsorption can be manipulated and the impact of the diamine structure and surfactant headgroup structure on surfactant adsorption at the air–water interface is reported here.The addition of putrescine [1,4 diaminobutane or butanediamine] over the pH range 3 to 10 enhances significantly the adsorption of sodium dodecyl sulfate, SDS, sodium dodecyl diethylene sulfate, SLES, and sodium tetradecyl methyl ester sulfonate, MES. For SDS and to a lesser extent MES there are regions where surface multilayer adsorption occurs at both pH 3 and 10, and this extends significantly the range of polyamine structures for which this is observed. Modifying the diamine spacer with ethylene oxide groups of varying length still results in enhanced adsorption for SDS and MES, but the enhancement is less pronounced and depends upon the size of the ethylene oxide group. However the incorporation of the ethylene oxide group does suppresses the formation of the more complex surface multilayered structures.

Retina‐Like Neuromorphic Visual Sensor for Sensing Broad‐Spectrum Ultraviolet Light

AbstractThe rapidly developing Artificial Intelligence era has an increasing demand for high‐performance organ‐on‐a‐chip systems, especially the vision system, which is the most essential perceptual system for human beings. However, traditional artificial vision systems require multiple functional components, which are not favorable for integration. Neuromorphic visual sensors (NVSs) inspired by the human retina combine visual sensing and multiple preprocessing functions. However, most NVSs require complex structures to achieve both photo sensing and memory, and are difficult to be large‐scale fabricated. Here, a novel In2O3‐Ga2O3 (InGaO) thin‐film‐based NVS with both high photosensitivity and superior photomemory performance is proposed, which can avoid the complex multilayer structure. The device possesses high accuracy optical communication and multiple retina‐like functions. Notably, this InGaO NVS achieves sensing of most UV light, and it has been experimentally confirmed to have excellent photoelectric synaptic performance under both 254 nm and 365 nm UV illumination. This work provides a feasible strategy to assist the human eye in sensing invisible UV light.

Analysis of micro-defect-induced cracking in the IPyC layer of TRISO particle with the XFEM

PurposeWe use the extended finite element method (XFEM) to model the whole process of initiation and propagation of cracks in the inner dense pyrolytic carbon (IPyC) layer of tri-structural isotropic (TRISO) particle induced by the microdefect in an irradiation-induced thermomechanical coupling environment and study the effect of microdefect sizes on the propagation path.Design/methodology/approachThe irradiation-induced thermal–mechanical coupling analysis is first conducted for the representative volume element (RVE) of the TRISO particle by using the conventional finite element method (CFEM) so that the stress distribution is obtained. The stress results are then restored for the enriched elements, and the simulation of crack initiation and propagation is eventually carried out by using the XFEM.Findings1. As a crack initiates in the IPyC layer, it will terminate at the free edge of the RVE TRISO particle in the end. 2. The size of the microdefect has a significant impact on the propagation path.Originality/valueThe ceramic dispersion microencapsulated (CDM) fuel is a good accident-resistant fuel whose safe operation is crucial to the safety and reliability of the whole nuclear reactor. It is of great scientific significance and practical value to study the irradiation-induced thermomechanical coupling stress distribution and cracking behavior in the IPyC layer of TRISO particles for the CDM fuel. Crack initiation and propagation analysis is challengeable for this complex multi-layer structure. This can help understand the failure mechanism of TRISO particles and evaluate the operation safety of the reactor.

Considerations for extracting moiré-level strain from dark field intensities in transmission electron microscopy

Bragg interferometry (BI) is an imaging technique based on four-dimensional scanning transmission electron microscopy (4D-STEM) wherein the intensities of select overlapping Bragg disks are fit or more qualitatively analyzed in the context of simple trigonometric equations to determine local stacking order. In 4D-STEM based approaches, the collection of full diffraction patterns at each real-space position of the scanning probe allows the use of precise virtual apertures much smaller and more variable in shape than those used in conventional dark field imaging such that even buried interfaces marginally twisted from other layers can be targeted. With a coarse-grained form of dark field ptychography, BI uses simple physically derived fitting functions to extract the average structure within the illumination region and is, therefore, viable over large fields of view. BI has shown a particular advantage for selectively investigating the interlayer stacking and associated moiré reconstruction of bilayer interfaces within complex multi-layered structures. This has enabled investigation of reconstruction and substrate effects in bilayers through encapsulating hexagonal boron nitride and of select bilayer interfaces within trilayer stacks. However, the technique can be improved to provide a greater spatial resolution and probe a wider range of twisted structures, for which current limitations on acquisition parameters can lead to large illumination regions and the computationally involved post-processing can fail. Here, we analyze these limitations and the computational processing in greater depth, presenting a few methods for improvement over previous works, discussing potential areas for further expansion, and illustrating the current capabilities of this approach for extracting moiré-scale strain.

N-level complex helical structure modeling method

This paper primarily explores the modeling method of n-level complex helical structures with coal mining machine cables as the research object. The paper first elaborately introduces the modeling method of n-level helix curves based on parametric equations and coordinate transformations, and compensates for the n-level helix curves with corrected pitch, which can obtain more accurate n-level helix curves and improve the accuracy of n-level helix curves modeling. Subsequently, based on this high-precision n-level helix curves modeling method, the paper elaborates on the method of solving pitch and twisting radius of multi-layer helical structure. Calculation scripts were written based on the above methods, which can be used to batch calculate the twisting radius and pitch of each layer structure in multi-layer structures when satisfying the conditions of in-layer tangency, inter-layer tangency, and extrusion deformation, and retain the actual results through logical judgment. Then, based on the above two methods, the paper developed a modeling method for braided structures based on piecewise functions containing fifth-order polynomials, which can effectively avoid the problem of insufficiently dense arrangement of braided lines and easy interference in traditional methods. Finally, a set of modeling tools was developed using C# and Python in Grasshopper to implement the modeling algorithm. Taking the MCPT-1.9/3.3 3120 + 170 + 4 * 10 coal mining machine cable as an example. The cable was modeled using both the method proposed in this paper and the traditional method. Comparative data shows that the method proposed in this paper can reduce errors by 3.31E6 times in the second-level and above helical structures. In addition this paper compares the standard line length, measured line length, and the line length established by the proposed model, showing that the relative errors are both less than 0.1941%. This paper provides a new, systematic, high-precision, and full-process cable modeling method, in which all parameters except the process parameters are accurately solved by equations. It lays a theoretical foundation for the high-precision simulation and intelligent sensing cables, which is of great significance for improving the safety, stability, and efficient development of the coal mining industry. The research results of the paper can not only be applied to the modeling of coal mining machine cables but also can be extended to the modeling of other complex multi-layer helical structures.

Numerical modeling of fiber orientation in multi-layer, isothermal material-extrusion big area additive manufacturing

Fiber orientation is a critical factor in determining the mechanical, electrical, and thermal properties of 3D-printed short-fiber polymer composites. However, the current numerical studies on predicting fiber orientation are limited to straight single-strand configurations, while the actual printed parts are often composed of complex multi-layer structures. To address this issue, we conducted numerical simulations of material extrusion in multi-layer big-area additive manufacturing without any post-deposition strand morphology modification mechanism. By examining the effects of material properties and printing conditions when extruding and depositing strands on a fixed substrate as well as previously deposited layers, it was possible to observe the complex interplay between multiple layers and its impact on fiber orientation. The work and methodology presented in this paper can be used to identify optimal extrusion-to-nozzle speed ratios, material rheology, fiber content, and fiber aspect ratio to achieve the desired performance and thermo/mechanical properties of additively manufactured parts. This work is an important contribution towards the manufacture of high-performance, short-fiber polymer composites as the presented methodology can enable engineers to precisely predict and tailor the fiber orientation in 3D printed parts.

Effects of surface and subsurface water/ice on spatial distributions of impact crater ejecta on Mars

Ejecta blankets around craters on a km-scale show stark differences in the ejecta mobility (maximal extent of ejecta divided by the crater radius) with latitude and types of plains on Mars, which has been known for a long time (Barlow and Pollak, 2002; Li et al., 2015) but is not well-understood. Our main goal is to explore the idea that the subsurface rheology drives ejecta dynamics and leaves characteristic, observable imprints in the spatial distributions of ejecta. We conduct numerical simulations of impact cratering into a variety of subsurface models and study the impact of varied subsurface material (porous basalt, water ice, water), as well as structure and layering on impact sites and properties of impact ejecta. Our models consider variations in the depth of water or ice covering basalt; the thickness of buried ice; and the depth of burial of ice. We find that ejection angles and velocities depend on these quantities and configurations, e.g. velocities decrease and angles of ejection increase with increasing water layer thickness, buried ice thickness, or thickness of basaltic debris over an ice sheet. As a result, several ejecta characteristics derived from ejecta thickness profiles carry information about the underlying rheology. Specifically, the ejecta mobility, as well as the radial position of the maximum and the slope of the ejecta thickness profiles are diagnostic. The power-law function of the thickness profile of the ejecta blanket right after formation is a good indicator of ejecta from water- or ice-covered targets but not from more complex multi-layered structures, hence we caution against using scaling relations to describe ejecta from such targets. As any surface water/ice volatile mass is unstable on Mars, we also consider the geomorphology of craters and ejecta after the loss of volatiles. Our main findings include the observation that after the loss of surface volatiles, craters which formed in water-covered targets would appear shallower than those formed in basalt. The ejecta mobilities observed today would also be smaller if craters formed in volatile-covered targets than in basalt. Our findings can aid the interpretation of data returned from cameras onboard multiple spacecraft orbiting Mars such as HiRISE, CaSSIS, or CTX, and constitute a proof of concept of the hypothesis that information on the subsurface, including where ice is or was present, is encoded in the ejecta profile and spatial distribution.

Wide-incident-angle, polarization-independent broadband-absorption metastructure without external resistive elements by using a trapezoidal structure

The absorption of electromagnetic waves in a broadband frequency range with polarization insensitivity and incidence-angle independence is greatly needed in modern technology applications. Many structures based on metamaterials have been suggested for addressing these requirements; these structures were complex multilayer structures or used special materials or external electric components, such as resistive ones. In this paper, we present a metasurface structure that was fabricated simply by employing the standard printed-circuit-board technique but provides a high absorption above 90% in a broadband frequency range from 12.35 to 14.65 GHz. The metasurface consisted of structural unit cells of 4 symmetric substructures assembled with a metallic bar pattern, which induced broadband absorption by using a planar resistive interaction in the pattern without a real resistive component. The analysis, simulation, and measurement results showed that the metasurface was also polarization insensitive and still maintained an absorption above 90% at incident angles up to 45°. The suggested metasurface plays a role in the fundamental design and can also be used to design absorbers at different frequency ranges. Furthermore, further enhancement of the absorption performance is achieved by improved design and fabrication.

AI-driven design of customized 3D-printed multi-layer capsules with controlled drug release profiles for personalized medicine

Personalized medicine aims to effectively and efficiently provide customized drugs that cater to diverse populations, which is a significant yet challenging task. Recently, the integration of artificial intelligence (AI) and three-dimensional (3D) printing technology has transformed the medical field, and was expected to facilitate the efficient design and development of customized drugs through the synergy of their respective advantages. In this study, we present an innovative method that combines AI and 3D printing technology to design and fabricate customized capsules. Initially, we discretized and encoded the geometry of the capsule, simulated the dissolution process of the capsule with classical drug dissolution model, and verified it by experiments. Subsequently, we employed a genetic algorithm to explore the capsule geometric structure space and generate a complex multi-layer structure that satisfies the target drug release profiles, including stepwise release and zero-order release. Finally, Two model drugs, isoniazid and acetaminophen, were selected and fused deposition modeling (FDM) 3D printing technology was utilized to precisely print the AI-designed capsule. The reliability of the method was verified by comparing the in vitro release curve of the printed capsules with the target curve, and the f2 value was more than 50. Notably, accurate and autonomous design of the drug release curve was achieved mainly by changing the geometry of the capsule. This approach is expected to be applied to different drug needs and facilitate the development of customized oral dosage forms.

Optimizing the management, control, and computation of skin depth in laminated structures considering reflection effects

This study introduces an alternative method for calculating multilayered skin depth in laminated structures. It concentrates on locating the layer where the skin effect occurs and developing a novel formula for skin depth. This method involves attenuating the electric field as it traverses the layers of the structure until it reaches the 1/e point. The equation's resolution considers the reflection that occurs when electromagnetic wave transitions between layers. To execute computations with precision and efficiency, a numerical algorithm is implemented. An in-depth examination will be conducted to identify materials in the first, second, and third positions within the multilayer structure, where the skin effect may manifest in specific frequency ranges, including those defined by the IEEE. The approach provides a reliable mean to precisely control the skin effect's location in complex multilayered structures and select materials to minimize or maximize its impact as needed.

Future Thread: Printing Electronics on Fibers.

This article introduces a methodology to increase the integration density of functional electronic features on fibers/threads/wires through additive deposition of functional materials via printed electronics. It opens the possibility to create a multifunctional intelligent system on a single fiber/thread/wire while combining the advantages of existing approaches, i.e., the scalability of coating techniques and the microfeatures of semiconductor-based fabrication. By directly printing on threads (of diameters ranging from 90 to 1000 μm), micropatterned electronic devices and multifunctional electronic systems could be formed. Contact and noncontact printing methods were utilized to create various shapes from serpentines and meanders to planar coils and interdigitated electrodes, as well as complex multilayer structures for thermal and light actuators, humidity, and temperature sensors. We demonstrate the practicality of the method by integrating a multifunctional thread into a FFP mask for breath monitoring. Printing technologies provide virtually unrestricted choices for the types of threads, materials, and devices used. They are scalable via roll-to-roll processes and offer a resource-efficient way to democratize electronics across textile products.