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Three-Dimensional Electronic Microfliers With Designs Inspired by Wind-Dispersed Seeds

Authors:
  • Daegu Gyeongbuk Institute of Science and Technology (DGIST)

Abstract

Large, distributed collections of miniaturized, wireless electronic devices may form the basis of future systems for environmental monitoring, population surveillance, disease management and other applications that demand coverage over expansive spatial scales. In this paper, we show that wind-dispersed seeds can serve as the bio-inspiration for unusual aerial schemes to distribute components for such networks via controlled, unpowered flight across natural environments or city settings. Techniques in mechanically guided assembly of three-dimensional (3D) mesostructures provide access to miniature, 3D fliers optimized for such purposes, in processes that align with the most sophisticated production techniques for electronic, optoelectronic, microfluidic and microelectromechanical technologies. We demonstrate a range of 3D macro-, meso- and microscale fliers produced in this manner, including those that incorporate active electronic payloads. Analytical, computational and experimental studies of the aerodynamics of high-performance structures of this type establish a set of fundamental considerations in bio-inspired design, with a focus on 3D fliers that exhibit controlled rotational kinematics and low terminal velocities. Battery-free, wireless devices for atmospheric measurements provide simple examples of a wide spectrum of applications of these unusual concepts.
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Three-Dimensional Electronic Microfliers With Designs
Inspired by Wind-Dispersed Seeds
Bong Hoon Kim1, Kan Li2, Jin-Tae Kim3, Yoonseok Park3†, Hokyung Jang4, Xueju Wang5,
Zhaoqian Xie6, Sang Min Won7, Woo Jin Jang8, Kun Hyuk Lee3, Ted S. Chung3, Yei Hwan Jung9,
Seung Yun Heo3, Yechan Lee10, Juyun Kim8, Tengfei Cai11, Yeonha Kim8, Poom Prasopsukh11,
Yongjoon Yu3, Xinge Yu12, Haiwen Luan3,13, Honglie Song14, Feng Zhu15, Ying Zhao16, Lin Chen17,
Seung Ho Han18, Jiwoong Kim1, Soong Ju Oh19, Heon Lee19, Chi Hwan Lee20, Yonggang Huang13*,
Leonardo P. Chamorro11*, Yihui Zhang14*, John A. Rogers3,21*
1 Department of Organic Materials and Fiber Engineering
Department of Smart Wearable Engineering
Soongsil University, Seoul 06978, Republic of Korea
2 Department of Engineering
University of Cambridge, Cambridge CB2 1PZ, United Kingdom
3 Querrey Simpson Institute for Bioelectronics
Northwestern University, Evanston, Illinois 60208, United States
4 Department of Electrical and Computer Engineering
University of Wisconsin Madison, Madison, Wisconsin 53706, United States
5 Department of Materials Science and Engineering, Institute of Materials Science
University of Connecticut, Storrs, Connecticut 06269, United States
6 State Key Laboratory of Structural Analysis for Industrial Equipment
Department of Engineering Mechanics
Dalian University of Technology, Dalian 116024, People’s Republic of China
Ningbo Institute of Dalian University of Technology, Ningbo, 315016, People’s Republic of China
7 Department of Electrical and Computer Engineering
Sungkyunkwan University, Suwon 16419, Republic of Korea
8 Department of Chemical and Biomolecular Engineering
University of Illinois, Urbana, Illinois 61801, United States
9Department of Electronic Engineering
Hanyang University, Seoul 04763, Republic of Korea
10 Department of Chemical and Biomolecular Engineering
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Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea
11 Department of Mechanical Science and Engineering
University of Illinois, Urbana, Illinois 61801, United States
12 Department of Biomedical Engineering
City University of Hong Kong, Hong Kong 999077, China
13 Departments of Civil and Environmental Engineering, Mechanical Engineering, and Materials
Science and Engineering
Northwestern University, Evanston, Illinois 60208, United States
14 Applied Mechanics Laboratory, Department of Engineering Mechanics
Center for Flexible Electronics Technology
Tsinghua University, Beijing 100084, People's Republic of China
15 School of Logistics Engineering
Wuhan University of Technology, Wuhan 430063, People’s Republic of China
16 School of Aerospace Engineering and Applied Mechanics
Tongji University, 200092 Shanghai, People’s Republic of China
17 State Key Laboratory for Mechanical Behavior of Meterials,
School of Material Science and Engineering,
Xi’an Jiaotong University, Xi’an 710000, People’s Republic of China
18 Electronic Convergence Materials and Device Research Center
Korea Electronics Technology Institute, Seongnam 13509, Republic of Korea
19 Department of Materials Science and Engineering
Korea University, Seoul 02841, Republic of Korea
20 Weldon School of Biomedical Engineering
School of Mechanical Engineering
School of Materials Engineering
Purdue University, West Lafayette, Indiana 47907, United States
21 Department of Materials Science and Engineering, Biomedical Engineering, Neurological Surgery,
Chemistry, Mechanical Engineering, Electrical Engineering and Computer Science
Northwestern University, Evanston, Illinois 60208, United States
E-mail: y-huang@northwestern.edu; lpchamo@illinois.edu; yihuizhang@tsinghua.edu.cn;
jrogers@northwestern.edu
Keywords: Bio-inspired design, three-dimensional fabrication, fluid dynamics, aerodynamics,
wireless electronics, air pollution sensors
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Large, distributed collections of miniaturized, wireless electronic devices may form the
basis of future systems for environmental monitoring, population surveillance, disease
management and other applications that demand coverage over expansive spatial scales. In this
paper, we show that wind-dispersed seeds can serve as the bio-inspiration for unusual aerial
schemes to distribute components for such networks via controlled, unpowered flight across
natural environments or city settings. Techniques in mechanically guided assembly of three-
dimensional (3D) mesostructures provide access to miniature, 3D fliers optimized for such
purposes, in processes that align with the most sophisticated production techniques for
electronic, optoelectronic, microfluidic and microelectromechanical technologies. We
demonstrate a range of 3D macro-, meso- and microscale fliers produced in this manner,
including those that incorporate active electronic payloads. Analytical, computational and
experimental studies of the aerodynamics of high-performance structures of this type establish
a set of fundamental considerations in bio-inspired design, with a focus on 3D fliers that exhibit
controlled rotational kinematics and low terminal velocities. Battery-free, wireless devices for
atmospheric measurements provide simple examples of a wide spectrum of applications of these
unusual concepts.
Plants spread their seeds through a remarkable variety of passive strategies, each the result of
sustained processes of natural selection. Botanists classify these strategies according to their vectors
for dispersal, the main types of which are gravity, ballistic, wind, water, and animals. Among these,
wind is one of the most powerful and widely applicable. The 3D shapes of seeds optimized to exploit
air flow in such contexts can support stable dynamics in controlled free-fall and/or facilitate transport
over distances of up to hundreds of kilometers1-3. Although certain interactions between airborne
seeds and the ambient air are well known, few research studies quantitatively define the essential
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aerodynamics and none considers the potential relevance in microsystems technologies 4-6. Just as
plants use seeds and passive mechanisms for dispersal of genetic material to propagate the species,
interesting opportunities might follow from use of similar approaches to distribute miniature
electronic sensors, wireless communication nodes, energy harvesting components and/or various
internet-of-things (IoT) technologies as monitors to track environmental processes, as aids to guide
remediation efforts or as components to support distributed surveillance. This paper introduces the
foundational engineering science for practical realization of these ideas7-11.
Wind-dispersed seeds adopt geometries that are shaped by forces of evolution to maximize
dynamic stability and/or transport distance during passive free-fall. The character of motions induced
by air flow defines three broad categories of seeds: (i) gliders such as those of the box elder (Acer
negundo) and the big-leaf maple (Acer macrophyllum), (ii) parachuters such as those of the evergreen
ash (Fraxinus uhdei) and the tipu tree (Tipuana tipu) and (iii) flutterers/spinners such as those of the
empress tree (Paulownia tomentosa), the tree of heaven (Ailanthus altissima) and the jacaranda
(Facaranda mimosifolia) (Fig. 1a). These designs serve as inspiration for man-made passive flier
structures built using approaches introduced here and engineered to optimize aerial dispersal of
functional payloads, including a range of electronic, optoelectronic, microfluidic and
microelectromechanical systems technologies. The overall sizes span the microscale (half widths of
wings mm; microfliers), mesoscale (half widths  mm; mesofliers), and macroscale (half
widths mm; macrofliers) with the capacity to integrate material elements and devices with critical
feature sizes that extend into the nanometer regime. Fig. 1b compares the dimensions and the
geometries of a representative 3D microflier to those of various seeds with elaborate designs.
The fabrication scheme exploits controlled mechanical buckling to convert planar precursor
structures formed with state-of-the-art planar processing and lithographic techniques into desired 3D
layouts. Specifically, releasing the strain in a prestretched elastomer substrate generates compressive
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forces on these precursors through a collection of bonding sites. The result affects geometrical
transformation through a continuous sequence of in- and out-of-plane displacements and rotational
motions (Figs. 1c~e). When implemented with shape memory polymers (SMPs; a mixture of epoxy
monomer (E44; China Petrochemical Corporation) and curing agent (D230; Sigma-Aldrich)) and
sacrificial thin layers (Mg ~ 50 nm) at the bonding sites, the resulting 3D objects can be released as
free-standing passive fliers (Fig. 1f)11. The designs and choices of bonding sites define the overall 3D
architectures; the magnitude of strain release determines the extent of three dimensionality,
qualitatively defined by the ratio of the height of the structures to their lateral dimensions (small, 3D;
large, 3D+), as in Fig. 1c. This scheme provides access to systems that behave in any of the three
bio-inspired modalities mentioned previously, with flat and/or curved wings, solid and/or perforated
structural elements, and various numbers of articulations. A simple identifying nomenclature includes
(i) a number to indicate the number of wings, (ii) a letter to describe the shape of wings (R = ribbons,
M = membranes, PM = porous membranes, and H = Hybrid, as a combination of ribbons and
membranes), and (iii) a number to define the 3D aspect ratio (e.g., height divided by the width). Fig.
1d shows pictures of three 3D microfliers (widths µm) placed on a fingertip. Fig. 1e highlights
a 10 x 10 array of micro-, and mesofliers in various sizes (widths 0.5~2 mm; Fig. S1) and
geometries, formed via a single assembly process on a common substrate. Mass quantities of fliers
can be formed at high throughput, as illustrated in Fig. 1f.
The terminal velocity (vT) associated with free-fall in still air serves as a simple metric to
compare the aerodynamics of these fliers to seeds and other objects in nature. As described in the
following, microfliers can exhibit values of vT that are 10 to 15 times small than other objects with
similar sizes (~1 mm) and weights (~ 10 mg), including brown rice, sesame seeds, and snow (Fig.
1g)12. 3D microfliers with features (diameter ~ 1 mm, mass 12.2 mg, type [3, M, 0.4]) inspired by
those of tristellateia seeds (diameter ~ 19.8 mm, mass 18.2 mg, density ~ 0.11 mg/mm3; Fig. S2)
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exhibit vT ~28 cm/s, which is a factor of 3 smaller than that of the seeds (vT ~100 cm/s; Supplementary
Video 1).
Computational Fluid Dynamics (CFD) simulations (see Methods and Fig. S3) and analytical
approaches (Supplementary Notes 1-4) reveal the underlying aerodynamic mechanisms. The essence
of the physics can be examined by decomposing complex flier configurations into discrete numbers
of tilted blades, as in Fig. 2a. The drag coefficient, 
, is a dimensionless parameter
that characterizes the relationship between the terminal velocity () and the weight (), where is
the density of air and is the area of the 2D membrane of the flier, excluding the area of perforations
(i.e., voids). Fig. 2b summarizes values of computed by CFD at different Reynolds numbers (Re),
where , is the dynamic viscosity of air and  is the diameter of the flier. The results
can be described empirically as , where the first () and second () terms
correspond to behaviors where inertial and viscous effects dominate, at high and low Re, respectively.
The terminal velocity can be then expressed as



 (1)
where and depend on critical geometric parameters of the fliers, such as the areal fill factor
(, where is the void-free membrane area), porosity (, where  is the
total area of voids) and the tilt angle of the blades () in the rotational direction. In particular, for
macrofliers, Eq. (1) becomes

; (2)
while for meso- and micro- fliers,

, (3)
consistent with CFD simulations (Fig. S4). As might be expected, the behaviors of microfliers and
macrofliers depend mainly on and , respectively; both parameters are important for mesofliers.
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The vT of microfliers and macrofliers depend mainly on and , respectively (Fig. S5). The results
of CFD (Fig. 2c) show that the flow fields associated with microfliers (, Re; near the
Stokes regime) and mesofliers ( , Re ) are laminar, while those of macrofliers
(, Re) are turbulent.
Mesofliers with different 3D configurations exhibit a common dependence of vT on fill factor
(Fig. 2d, Fig. S6, and Supplementary Note 1),

, as obtained from Eq
(3), which is dominated by the viscous term, where  is the weight of the payload, is the
density of the structural material, is the thickness, and is the gravity acceleration. This equation
indicates the existence of an optimal fill factor, i.e.,  , that minimizes the
terminal velocity for a given .
Parachute type seeds incorporate bundles of filaments with high effective porosity .
Such configurations can be mimicked to a certain degree by introducing arrays of perforating holes
(i.e., voids) in the structural components of the fliers. The result enhances and reduces vT 4, with
different effects on and (Fig. 2b, Figs. S7-S9, and Supplementary Note 2). For example,
porosity (e.g., ) has a smaller effect on (by ~ 10%) for macrofliers than for microfliers
(by ~ 20%), as shown in Fig. S10. By contrast, the effects of curvature and tilt angle () in the blades
of macrofliers (Fig. S11, S12) are more significant than those of microfliers (Supplementary Note 3).
Factors related to the properties of air, i.e., altitude, humidity, temperature or molecular
makeup, influence the behaviors mainly through and . For example, increasing the altitude from
0 to 80 km decreases by a factor of 5, but the value of decreases by less than 25% (Fig. S13).
Therefore, as shown by the CFD simulation results in Fig. 2e, mesofliers exhibit small vT even at high
altitudes (e.g.,  at  altitude for ). By comparison, macrofliers have large
vT at such altitudes (e.g.,  at  altitude for ). In a similar way, the
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temperature and molecular makeup of the air can lead to opposite effects for micro- and macrofliers
(Figs. S14 and S15).
Rotational behaviors (e.g., rotational speed ) that follow from the 3D configuration
(characterized by ) can confer kinematic stability. Analytical modeling (Supplementary Note 2),
validated by CFD (Fig. S16), shows that . With , rotation does not occur (Fig. S17).
Stability can be analyzed by considering the microflier as a rotating rigid body driven by forces
associated with air flow and subjected to small perturbations to its angular speed ( in
direction 1) from an initial balanced state (Fig. 2f and Supplementary Note 4), where and
denote the perturbation angles with respect to directions 1 and 2, respectively. Studies of three
representative structures (i.e., a 2D precursor; a 3D mesoflier without rotation, i.e., , see Fig.
S7; and a 3D mesoflier with rotation, all with the same size () and fill factor ())
reveal the essential effects. Fig. 2g shows the perturbed angles ( and ) as a function of
time () after perturbation. The 2D precursor structure does not return to the balanced state. The 3D
microflier without rotation returns to the balanced state quickly, but the maximum perturbed angle
(
) is much larger than that of the 3D microflier with rotation
(
). A normalized stability factor, , as defined by



, (4)
can characterize the stability, in which  and 
account for the influences of material
parameters, geometrical parameters and air properties (Fig. 2h, Supplementary Note 4), as given by



, 
, 
, (5)
where  are the moment of inertias with respect to directions 1, 2 and 3, and is the distance
between the center of gravity and the center of pressure. A large positive value of suggests that the
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structure can quickly recover to its balanced, stable state; a negative value of indicates that the
structure is unstable. Additionally, the overall maximum perturbed angle, i.e., 
,
decreases monotonically with  (Fig. S18), consistent with rotational improvements in stability.
Substitution of Eq. (1) into  suggests that reducing increases . As a result, increasing
and/or decreasing can improve the stability through increases in 
and .
Experimental studies and results of additional computational modeling reveal detailed features
of these and related behaviors. One set of measurements involves 3D Particle Tracking Velocimetry
(3D-PTV), with a focus on (i) characterizing the 3D trajectories, terminal velocities and the
characteristics of aerodynamic stability, and (ii) capturing 3D patterns of flow in a still ambient
environment (see Methods, Fig. S19a and Supplementary Video 2 and 3). Another set focuses on
quantifying the wake produced by various fliers placed at the exit of a vertical wind tunnel by high-
speed Particle Image Velocimetry (PIV) (see Methods, Fig. S19b, S20, S21 and Supplementary Video
4 and 5).
Data show that a 2D precursor for a 3D mesoflier [3,M,0.4], Y2, (diameter ,
weight ) exhibits nonrotating, random tumbling behaviors with vT (  m/s)
larger than that of stable, rotational behaviors of a 3D mesoflier [3,M,0.4], Y, (Fig. 3a and
Supplementary Video 2 and 3), vT (  m/s). Introducing porosity into the same
structure, YP, promotes further reductions in vT (  m/s; ; Fig. 3b).
These results agree with theoretical predictions and simulations, as in Fig. 2c. Across this same
set of samples, the 3D shapes reduce the standard deviation of vT by ~40% due to the enhanced
aerodynamic stability (  m/s,   m/s,   m/s), consistent with
the measured trajectories (Fig. 3c). Specifically, the 3D mesofliers travel in a straight downward
direction, while the 2D precursors exhibit abnormal, chaotic falling behaviors with a time-
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dependent combination of fluttering and gliding13-15. These latter processes lead to large
variations in vT and in settling location.
The 3D wake structures measured with 3D-PTV highlight additional features. Two
representative instants in time (Figs. 3d and Fig. S22) show flow separations, as highlighted by the
blue isosurface (flow structures in the opposite direction of the fall) and momentum deficits noted by
the red isosurface (flow structures in the direction of the fall). The wake for the 2D flier exhibits
comparatively large flow structures against the motion, with small flow structures along the motion
at this instant and at other times throughout the fall. The 3D mesoflier induces comparatively small
and rotating flow structures oriented against the motion, with large following structures. Large flow
structures against the fall in the 2D precursor indicate early flow separation, which promotes
comparatively high pressure gradients and aerodynamic instabilities. Small structures in the direction
of the fall indicate small momentum deficits and, consequently, low drag and correspondingly large
vT. The rotational dynamics of the 3D mesofliers minimize flow separation and induce large
momentum deficits, resulting in stable and slow falling behaviors (Supplementary Video 6).
Complementary insights follow from high-speed PIV measurements of instantaneous velocity
fields (Fig. S23), mean velocity fields (Fig. 3e), velocity profiles (Fig. 3f) and velocity fluctuation
profiles (Fig. 3g and h). The 3D mesoflier (Fig. 3e and f, Fig. S23) produces a larger wake and higher
vertical velocity fluctuations, , than the 2D precursor (Fig. 3g). Notably, the fluctuations for the
2D case show asymmetrical distributions due to its planar geometry and nonrotating behavior (Fig.
3h), as additional sources of instability. Symmetry in velocity fluctuations and large momentum
deficits are consistent with the enhanced aerodynamics of 3D mesofliers.
Like seeds, these 3D platforms can transport payloads with passive or active functionality.
The fabrication scheme affords many possibilities in functional integration, spanning nearly all forms
of planar microsystems and semiconductor technologies. Fig. 4a shows an exploded view illustration
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of 3D mesofliers, i.e. [3, M, 0.4] and [3, H, 0.75], that support semiconductor devices based on silicon
nanomembranes (Si NMs; thickness 200 nm) as the active material, i) n-channel Si NM metal oxide
semiconductor field effect transistors (nMOSFETs; channel lengths/widths of 20/80 μm) with SiO2
gate dielectrics (thickness ~ 50 nm) and metal electrodes for gate, source and drain (Cr/Au, thickness
~ 5/50 nm), and ii) Si NM diodes formed with similar materials, respectively. The 3D structures are
similar to those featured in the CFD simulations (Figs. S24 ~ S28). Layers of polyimide on the bottom
and the top enhance the structural integrity of the SMP and improve the rigidity of the overall device.
They also place the Si NM near the neutral mechanical plane to minimize the potential for fracture
during assembly and use16,17. The electrical properties of the devices are consistent with those
expected for monocrystalline silicon devices formed in the usual way on planar wafer substrates (Fig.
S29). Optical micrographs in Fig. 4b highlight the geometries of the 2D precursors and the locations
of the bonding sites. Fig. 4c&d show pictures of a 3 x 3 array of 3D mesofliers [3, M, 0.4] with Si
NM nMOSFETs and corresponding 3D surface profiles determined using a laser scanning confocal
microscope (Keyence VK-X1000).
As a simple application example, these types of electronic 3D microfliers can be released into
the atmosphere from aircraft to track relevant environmental characteristics from positions at high
altitudes to the ground, in large-area, dispersed configurations, as a complement to conventional
gravimetric and optical particle counting methods18,19 performed at stationary, localized positions.
Fliers for such purposes support wireless, miniaturized battery-free light dosimeters designed for
operation in the ultraviolet-A (UVA) band of the solar spectrum, according to recently reported
schemes20. A photodiode (PD) generates photocurrent with a magnitude proportional to the UVA
intensity. This current continuously charges a supercapacitor (SC) as a continuous, accumulation
mode of detection during and after free fall. The electronics include a system-on-a-chip (SoC) with
near field communication (NFC) capabilities and an analog-to-digital converter (ADC; Specification)
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with a general-purpose-input/output (GPIO). An external reader device activates the SoC to measure
the voltage across the SC, retrieve the corresponding digital data and to discharge the SC, all in a
single operation (Fig. 4e, Fig. S30, S31, and Table S1). The measured dose depends on atmospheric
conditions, including the pollution levels across altitudes, solar activity and other factors. Fig. 4f
demonstrates the quantitative effect of air-born particles (Fig. S32).
The aerodynamics of these 3D IoT macrofliers (Figs. 4g~i and Fig. S33 ~ S36) are consistent
with preceding discussions of the physics. The wakes exhibit oscillating tip vortices in the vicinity
of the wings and a secondary vortex behind the center (Fig. 4g and Supplementary Video 7). Mean
streamwise velocity fields (Fig. 4h) are similar to those of mesofliers with similar designs. Figure 4i
shows that across a range of centimeter scale dimensions, the normalized transverse velocity profiles
exhibit self-similarity, allowing for efficient dimensional analysis and modeling; inferred drag
coefficients are shown in Fig. S33c and d).
The bio-inspired ideas and engineering foundations for mesoscale 3D fliers introduced here
establish a set of unusual capabilities in aerial dispersal of advanced device technologies. Although
not explicitly studied in this research, the effects of wind, thermal air currents and fluctuating air
flows represent important practical considerations that tend to increase in significance as the sizes
and the masses of the fliers decrease. The low terminal velocities of flutterers/spinners are of interest
partly because they maximize the time for engagement with these flows, to increase the net transport
distance. Gliders and parachuters represent alternative platforms that can be realized using similar
constituent materials, fabrication processes, experimental methods and computational techniques.
Layouts that combine these various design strategies may offer enhanced levels of performance,
beyond those observed in nature. In addition to payloads that support active semiconductor
functionality, responsive materials structures that change in color, shape or radio frequency signature
according to environmental cues may serve as simple, complementary options for remote monitoring.
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For many applications of distributed sensors and electronic components, efficient methods for
recovery and disposal must be carefully considered. One solution is in devices constructed from
materials that naturally resorb into the environment via a chemical reaction and/or physical
disintegration to benign end products21-23. In these and other cases, eco-resorbable piezoelectric
actuators or alternative active mechanical components may enhance control over flight dynamics.
Such possibilities represent promising directions for future work.
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Methods
Three-Dimensional (3D) Micro-, Meso- and Macrofliers. Fabrication of 2D precursors in thin films
of SMP (thickness ~ 5 μm) began with a mixture (a mass ratio of 7:3) of epoxy monomer (E44,
molecular weight 450 g mol1, China Petrochemical Corporation) and curing agent (D230,
poly(propylene glycol) bis(2-aminopropyl)ether, Sigma-Aldrich). Spin coating and thermally curing
(100 °C, 3 h) this mixture onto a sacrificial layer of a water-soluble polymer (spin cast; poly(4-
styrenesulfonic acid, 500 nm), PSA; Sigma-Aldrich) on a silicon wafer defined a thin film of SMP.
Electron beam evaporation of gold (Au, thickness ~ 10/50 nm) followed by photolithography and wet
etching formed a metal hard mask for patterned removal of exposed regions of the SMP by oxygen
plasma reactive ion etching (O2 RIE). Removing the Au and the underlying PSA facilitated the
retrieval of the patterned SMP onto a water-soluble tape (polyvinyl alcohol, 3M Corporation). A
multilayer of Ti/Mg/Ti/SiO2 (thickness ~ 5/50/5/50 nm) deposited through a shadow mask by electron
beam evaporation defined sites for chemical bonding, activated by exposure to ozone to create surface
hydroxyl termination on the SiO2. Transfer onto a pre-strained silicone elastomer substrate (Ecoflex,
Smooth-On) led to strong covalent bonding only at these locations, with weak van der Waals adhesion
forces at all other regions. Releasing the prestrain led to mechanical buckling and a corresponding 2D
to 3D geometric transformation. Heating to 70 °C for 1 min in an oven followed by cooling to room
temperature fixed the 3D shape via shape memory effects. Immersing the structure in water eliminated
the Mg layer and released the structures as free-standing objects.
3D Electronic Mesofliers. Fabrication of the silicon (Si) nanomembranes (NM) nMOS transistors
began by defining regions of phosphorus doping using spin-on-dopants (950 °C, 8 min) on a silicon
on insulator (SOI, top silicon thickness ~ 200 nm, SOITEC, France) wafer for source and drain
contacts. For Si NM diodes, the doping involved both phosphorus (1050 °C, 15 min) and boron
(1100 °C, 30 min) to define p-n junctions. Removing the buried silicon dioxide (SiO2) by wet etching
released the top device silicon from the SOI wafer, and enabled transfer printing of the resulting Si
NMs onto spin-cast films of polyimide (PI, thickness ~ 3 μm, HD microsystems INC) on a sacrificial
layer of polymethylmethacrylate (PMMA, thickness ~ 100 nm, MicroChem INC) on a silicon wafer.
Photolithography and reactive ion etching (RIE, Plasma Therm, Inc., USA) with sulfur hexafluoride
gas (SF6, 100 mTorr, 50 W, 40 sccm, 200 s) left the top silicon only in the active regions of the device.
A thin layer of SiO2 (thickness ~ 50 nm) formed by PECVD served as the gate dielectric for Si NM
15
nMOS transistors. A bilayer of Cr/Au (thickness ~ 5/100 nm) deposited by electron beam evaporation
and patterned by photolithography served as electrodes and interconnects. Spin casting a thin layer of
PI (thickness ~ 3 μm) and etching by RIE (O2 gas, 150 mTorr, 100 W, 20 sccm) completed the
formation of an ultra-thin active device layer composed of Si NM devices and metal interconnects.
Dissolving the PMMA layer with acetone released the devices from the silicon wafer. Lastly, the Si
NMs device layer encapsulated by a film of PI was transfer printed onto a thin film of SMP (thickness
~ 5 μm) using a PDMS stamp. Additional steps to create 3D electronic mesofliers from these 2D
precursors followed those outlined above.
3D Internet of Things (IoT) Macrofliers. Fabricating the 2D precursors began with spin-coating
films of SMP (thickness ~ 12 μm) onto thick Cu foils (thickness ~ 18 μm). A pattern of photoresist
served as a mask for wet etching (CE-100 etchant, Transene) the copper foil to define a metal
interconnect structure for the electronic components. After using a laser cutting process to pattern the
film of SMP, mounting an NFC chip (Texas Instruments, RF430FRL152HCRGER), a collection of
photodiodes (Advanced Photonix, PDB-CD160SM), a set of MOSFETs (Texas Instruments,
CSD17381F4), super-capacitors (Seiko Instruments, CPH3225A) and capacitors (Murata Electronics
North America / TDK, GRM033R60J225ME47D / C0603X7R1A103K030BA &
C0603X5R1A104K030BC) at defined locations on the 2D precursor with conductive epoxy (Allied
Electronics) yielded a digital sensing system. Additional steps to create 3D IoT macrofliers from these
2D precursors followed those outlined above.
Optical experiments with particulate matter (PM) pollution. The 3D IoT macroflier uses a
millimeter-scale, wireless, and battery-free NFC platform with an electronic circuit for accumulation
mode dosimetry in the UVA region of the solar spectrum, where the flux depends, in part, on airborne
particulates. The photodiodes generate a photocurrent with a magnitude that correlates with the
instantaneous exposure intensity. This current continuously charges the SC such that the accumulated
charge, measured by the voltage, defines the exposure dose20. A dust generation chamber operated
with incense sticks, smoke cakes, corn starch, and kitchen blenders served as a platform to investigate
the influence of fine particulate pollution on the measured response (Fig. S30).
Experiments using 3D-Particle Tracking Velocimetry (3D-PTV). The studies involved two types
of measurements, both performed using 3D-PTV in a customized channel (Fig. S19a): (1) 3D
16
trajectories of free-falling microfliers with 2D, 3D and 3D porous designs and (2) associated 3D
induced flows. The upper part of the test chamber consisted of a 1.5m-long glass tube with an inner
diameter of 0.01 m to (i) minimize anomalous behaviors such as tumbling and (ii) ensure steady-state
behavior. The lower part included an acrylic glass enclosure with inner dimensions of 0.1 × 0.1 × 0.2
m3 (L × W × H), sufficiently large to minimize boundary effects. The investigation volume for the
fliers had dimensions of 4 × 4 × 6 cm3, illuminated by an LED light source. The volume for visualizing
3D induced flows was 0.8 × 0.8 × 1.2 cm3, illuminated by a synchronized dual-cavity YLF laser with
pulse energies of 50 mJ at repetition rates of 1 kHz (527-80-M, Terra). Oil droplets with diameters of
O(100) µm served as tracers. Recordings for 3D-PTV experiments used three digital cameras (2560
× 1600 pixels CMOS Phantom Miro 340 with 12 GB on-board memory and frame rates of 1,000 fps).
A series of lenses (60 mm, focal ratio f/2.8, Nikon AF Micro-Nikkor) focused the images on the
corresponding investigation volumes. Pre-processing, calibration, 3D reconstruction, tracking and
post-processing exploited 3D-PTV codes described previously24. Tracking of the 3D reconstructed
positions of fliers relied on the Hungarian algorithm linked by performing a three-frame gap closing
to produce long trajectories. Associated temporal derivatives were filtered and estimated using fourth-
order B splines. Additional details of the PTV system can be found elsewhere25. The free-falling
experiments involved 10 repetitions for each sample to obtain statistically significant measurements
of the stability and kinematics of the falling behaviors (Fig. 3c). Tracer particles were tracked in 3D
and converted into inferred 3D Eulerian velocity vector fields that defined the 3D induced flows.
Interpolating scattered Lagrangian flow particles at each frame based on the natural neighbor
interpolation method yielded the 3D vector fields.
Experiments using High-Speed Particle Image Velocimetry (PIV) and a vertical wind tunnel.
Two sets of experiments used high-speed PIV above a vertical wind tunnel (Fig. S19b) to define the
wake dynamics of (1) fixed 2D precursors and 3D fliers exposed to flow velocities of U≈0.4 m/s,
similar to those associated with terminal velocities in free fall and (2) working 3D fliers with five
different diameters d=1, 2, 3, 4 and 5 cm at U≈1.2, 2.4 and 3.6 m/s. For the latter, a 200 µm diameter
and 4 cm long wire with an adhesive on the tip fixed the positions of the fliers (Fig. S20). The wire
attached to a thin rectangular acrylic plate to minimize boundary effects on incoming flows. A
customized vertical wind tunnel enabled measurements of wake dynamics around the fliers. A series
of four fans (Mechatronics G8015X12B-AGR-EM) placed on the bottom of the tunnel produced air
flows in the wind tunnel. A tunable power supply (Tekpower TP3005N Regulated DC Variable Power
17
Supply) calibrated by quantifying the background flow using PIV set the fan speed. The channel
consisted of flow straighteners above the fans to smoothen the flows and an aluminum honeycomb
grid above the contraction section. A 1/8" acrylic sheet machined by laser cutting defined the frame
of the tunnel. A high-speed PIV system (TSI, Inc.) characterized the wake induced by meso- and
macrofliers. Olive oil droplets served as tracers in the air. A 1 mm thick laser sheet produced by a
synchronized dual-cavity YLF laser with pulse energies of 50 mJ at repetition rates of 100 Hz (527-
80-M, Terra) illuminated the resulting flows. The field of view covered a 24.48 mm × 15.3 mm region
above the fliers, with 950 image pairs collected for each case at a frequency of 100 Hz using a digital
camera (2560× 1600 pixels CMOS Phantom Miro 340.) A recursive cross-correlation method (Insight
4G software, TSI Image) processed pairs of images. The first pass used a 64 × 64-pixel interrogation
window. The final window had a size of 8 × 8-pixels with 50% overlap, resulting in a vector spacing
 mm. For fifteen sets of PIV measurements on working fliers (three speed and five
diameters), the field of view covered a 128 mm × 80 mm region with a vector spacing of 
 mm. Overall, more than 97% of the vectors were resolved in all measurements.
Finite Element Analysis. Three-dimensional FEA techniques quantitatively captured the mechanical
deformations and the associated 3D configurations of the fliers in different scales, during processes
of compressive buckling and bending under the flow of air. Eight-node shell elements were employed
using commercial software (ABAQUS), with refined meshes to ensure computational accuracy.
Linear elastic responses were used to model the SMP, with material parameters   and
 . Parameters for the other materials were  ,   and 
as a perfect elastic-plastic model for copper,   and   as an elastic model for
silicon.
Computational Fluid Dynamics. Three-dimensional CFD simulations defined the rotational falling
behaviors of the fliers in a static state, using the 3D rotating machinery, laminar flow module in
commercial software (COMSOL 5.2). First-order discretization (P1-P1) with a refined mesh ensured
computational accuracy. Fliers with 3D configurations defined by FEA resided in the centered
rotating region inside a large tube. The inflow velocities set at the bottom surface of the outer tube
matched values equivalent to the terminal velocities of the fliers. The flier was set as the rotating
interior wallin the rotating domain, as shown in Fig. S3, where the local velocity of air equals to the
velocity of flier. The rotating speed of the rotating domain, which represents the rotating velocity of
18
the flier, corresponded to the value for which the torque of the air acting on the microflier equals zero.
For a given terminal velocity, the force of air acting on the flier in the inflow direction matched its
weight. The air was modeled as compressible flow, with properties at sea-level 
and . At large Reynolds numbers, the k- model captured the effects of turbulence.
Two-dimensional CFD simulations captured the aerodynamic behaviors of the 2D airfoils in a similar
manner.
Electromagnetic Simulations. The commercial software ANSYS HFSS was used to perform
electromagnetic finite element analysis and to determine the inductance, Q factor for the 2D and 3D
antennas. Lumped ports yielded the port impedance Z of the antennas. An adaptive mesh (tetrahedron
elements) and a spherical radiation boundary (radius of 1000 mm) ensured computational accuracy.
The inductance (L) and Q factor (Q) (shown in Fig. S28) were obtained from L = Im4/(2πf) and Q =
|Im4/Re4|, where Re4, Im4 and f represent the real and imaginary part of the Z and the frequency,
respectively. The default material properties included in the HFSS material library were used in the
simulation.
Acknowledgements
This work was supported by the Querrey Simpson Institute for Bioelectronics at Northwestern
University. B.H.K. acknowledges the support from the National Research Foundation of Korea (NRF)
grant funded by the Korea government (MSIT) (No.2020R1C1C1014980), Creative Materials
Discovery Program through the National Research Foundation of Korea (NRF) funded by Ministry
of Science and ICT (NRF-2018M3D1A1058972), and Korea Institute for Advancement of
Technology (KIAT) grant funded by the Korea Government (MOTIE) (P0012770). Y.Z.
acknowledges the support from the National Natural Science Foundation of China (Grant Nos.
11722217 and 12050004), the Institute for Guo Qiang, Tsinghua University (Grant No.
2019GQG1012), and the Tsinghua National Laboratory for Information Science and Technology.
H.L. acknowledge the support from Nanomaterial Technology Development Program (NRF-
2016M3A7B4905613) through the National Research Foundation of Korea (NRF) funded by the
Ministry of Science, ICT and Future Planning. Z.X. acknowledges the support from the National
Natural Science Foundation of China (Grant No. 12072057) and Fundamental Research Funds for the
Central Universities (Grant No. DUT20RC(3)032).
19
Author Contributions
B.H.K., K.L., J.-T.K. and Y.P. contributed equally to this work. Y.H., L.P.C., Y.Z. and J.A.R.
conceived the ideas and supervised the project. B.H.K., K.L., J.-T.K., Y.P., Y.H., L.P.C., Y.Z. and
J.A.R. wrote the manuscript. H.J., X.W., S.M.W., W.J.J., K.H.L., Y.H.J., S.Y.H., Y.L., J.K., Y.K.,
Y.Y. and X.Y. performed microelectromechanical experiments. J.-T.K., T.C., and P.P. performed
fluid dynamics experiments. Z.X., T.S.C., H.L., H.S., F.Z., Y.Z. and L.C. performed mechanical and
electromagnetic simulation. S.H.H., J.K., S.J.O., H.L. and C.H.L. provided scientific and
experimental advice. All authors commented on the manuscript.
Figure captions
Fig. 1 | 3D microfliers inspired by wind-dispersed seeds. a, Glider types: (1) the box elder (Acer
negundo) and (2) the big-leaf maple (Acer macrophyllum); parachuter types: (3) the evergreen ash
(Fraxinus uhdei) and (4) the tipu tree (Tipuana tipu); flutterers/spinner types: (5) the empress tree
(Paulownia tomentosa), (6) the tree of heaven (Ailanthus altissima), and (7) the jacaranda (Facaranda
mimosifolia). b, Schematic illustration that compares the sizes and morphologies of a Diptocarpus
alatus seed, dandelion seed, and a representative 3D microflier. c, Mechanical simulation results for
the geometrical transformation of ten different 2D precursors (grey; 2D, bottom row) into
corresponding 3D structures with modest (green; 3D, middle row) and large (green; 3D+, top row)
aspect ratios. The identifying terminology indicating beneath each case includes (i) a number to
indicate the number of wings, (ii) a letter to describe the shape of wings (R = ribbons, M = membranes,
PM = porous membranes, and H = Hybrid), and (iii) a number to define the 3D aspect ratio (e.g.
height divided by the width). d-f, Photographs and optical micrographs of three different 3D
microfliers [2,H,1.2], [3,H,0.6] (left), and [3,M,0.4], resting on the tip of a finger (right) (d), a 10 x
10 array (e), and a large collection of 3D microfliers (f). g, The terminal velocity of several small
objects and a 3D microflier [3,M,0.4].
Fig. 2 | Theoretical analysis and numerical simulation of the aerodynamics associated with
representative 3D micro-, meso- and macrofliers. a, Schematic diagram of a rotating 3D microflier
[3,M,0.4] (top) and a simplified model (bottom) for purposes of theoretical analysis, with key
variables indicated. b, Drag coefficient versus Reynolds number of various structures (i.e. 2D disk,
and 3D microfliers [3,M,0.4] and [3,PM,0.4]). c, Terminal velocities of four different 3D microfliers
X = [3,H,0.75], Y = [3,M,0.4], Z = [3,H,0.6], and W = [2,H,1.2] with various fill factors. d,
20
Instantaneous flow fields for 3D micro-, meso- and macrofliers. e, CFD prediction of the terminal
velocity for 3D microfliers [3,M,0.4] at different size scales at different altitudes in the atmosphere,
from sea level to 80 km. f, Schematic diagram of the stability analysis of a rotating 3D microflier
[3,M,0.4] during free-fall. g, Behaviors of different 3D microfliers (a 2D precursor for a 3D microflier
[3,M,0.4], and 3D microfliers [3,H,0.75] and [3,M,0.4]) with small perturbations of angular speed. h,
Stability phase plot of 3D microfliers X = [3,H,0.75] and Y = [3,M,0.4] and a 2D precursor for a 3D
microflier Y2 = [3,M,0.4].
Fig. 3 | Experimental measurements of the flow characteristics of representative 3D mesofliers.
a, Optical images of Y2 = a 2D precursor for a 3D mesoflier [3,M,0.4] and a corresponding 3D
mesoflier Y = [3,M,0.4] at various times during free fall. The former shows nonrotating and random
tumbling behaviors; the latter exhibits strong rotational dynamics and a straight path trajectory. b,
Mean terminal velocity and its standard deviation for Y2 = a 2D precursor for a 3D mesoflier [3,M,0.4]
and 3D mesoflier Y = [3,M,0.4], and YP = a porous 3D mesoflier for [3,PM,0.4]. c, Falling trajectories
upon release at an angle of 900, where 00 corresponds to the flat side parallel to the ground. Y2 = a
2D precursor for a 3D mesoflier [3,M,0.4] and 3D mesoflier Y = [3,M,0.4]. d, Instantaneous 3D flow
velocity fields induced by a free-falling 2D precursor for a 3D mesoflier [3,M,0.4] (left) and a 3D
mesoflier [3,M,0.4] (right) determined via 3D-PTV. Red and blue iso-surfaces indicate iso-values of
15 and -5 mm/s, respectively. The color denotes correlated CFD results of the in-plane 2D vertical
velocity along the center plane of the flier. PIV measurements of instantaneous flow fields induced
by a physically constrained a 2D precursor for a 3D mesoflier [3,M,0.4] and a 3D mesoflier [3,M,0.4]
in a wind tunnel. e, Mean velocity fields of a 2D precursor for a 3D mesoflier [3,M,0.4] (left) and a
3D mesoflier [3,M,0.4] (right) in these conditions, with a wind velocity  m/s. f, g, Velocity
profiles (f) and vertical velocity fluctuation profiles (g) at mm downstream. h, Vertical velocity
fluctuation for a 2D precursor for a 3D mesoflier [3,M,0.4] (left) and a 3D mesoflier [3,M,0.4]
(right).
Fig. 4 | 3D electronic mesofliers and IoT macrofliers. a,b, Schematic illustration (a) and optical
micrographs (b) of 2D precursors for 3D electronic mesofliers [3,M,0.4] and [3,H,0.75] with silicon
nanomembrane (NM) nMOS transistors and diodes as payloads. c, Photograph of a 3 x 3 array of 3D
electronic mesofliers [3, M, 0.4] with these payloads. d, 3D surface profile of a 3D mesoflier
[3,M,0.4]. e, Mechanical simulation results and photograph of a 3D IoT macroflier with a circuit to
21
measure fine dust pollution through the light dosimetry method. f, Energy stored on the SC as a
function of exposure time in the presence of 3 types of fine dust. High-speed PIV flow measurements
for 3D IoT macrofliers (d=2 cm) with various diameters and air velocities. g, Instantaneous velocity
field. h, Mean velocity field  
. i, Normalized spanwise velocity profiles at 1.2 diameter
downstream for 3D IoT macrofliers with diameters between 1 and 5 cm.
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On the dynamics of air bubbles in Rayleigh–Bénard convection - Volume 891 - Jin-Tae Kim, Jaewook Nam, Shikun Shen, Changhoon Lee, Leonardo P. Chamorro
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Plant dispersal mechanisms rely on anatomical and morphological adaptations for the use of physical or biological dispersal vectors. Recently, studies of interactions between the dispersal unit and physical environment have uncovered fluid dynamic mechanisms of seed flight, protective measures against fire, and release mechanisms of explosive dispersers. Although environmental conditions generally dictate dispersal distances, plants are not purely passive players in these processes. Evidence suggests that some plants may enact informed dispersal, where dispersal‐related traits are modified according to the environment. This can occur via developmental regulation, but also on shorter timescales via structural remodelling in relation to water availability and temperature. Linking interactions between dispersal mechanisms and environmental conditions will be essential to fully understand population dynamics and distributions.
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Wind dispersal of seeds is an essential mechanism for plants to proliferate and to invade new territories. In this paper we present a methodology used in our recent work [Rabault, Fauli, and Carlson, Phys. Rev. Lett. 122, 024501 (2019)] that combines 3D printing, a minimal theoretical model, and experiments to determine how the curvature along the length of the wings of autorotating seeds, fruits, and other diaspores provides them with an optimal wind dispersion potential, i.e., minimal terminal descent velocity. Experiments are performed on 3D-printed double-winged synthetic fruits for a wide range of wing fold angles (obtained from normalized curvature along the wing length), base wing angles, and wing loadings to determine how these affect the flight. Our experimental and theoretical models find an optimal wing fold angle that minimizes the descent velocity, where the curved wings must be sufficiently long to have horizontal segments, but also sufficiently short to ensure that their tip segments are primarily aligned along the horizontal direction. The curved shape of the wings of double winged autorotating diaspores may be an important parameter that improves the fitness of these plants in an ecological strategy.
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Lagrangian statistics and pair dispersion induced by an isolated pulse of a small jellyfish, Aurelia aurita, were quantified and characterized using 3D particle tracking velocimetry (3D-PTV). Probability density functions (PDF) of the Lagrangian velocity components indicated more intense mixing in the radial direction and revealed three stages dominated by flow acceleration, mixing, and dissipation. Time evolution of the Lagrangian acceleration variance further illustrates each phase. During the mixing phase, the flow shares characteristics of homogeneous isotropic turbulence. In addition, we show that a single pulse may induce rich wake dynamics characterized by pair dispersion with a super-diffusive t 3 regime due to large-scale flow inhomogeneity, followed by a coherent t 2-Batchelor scaling and then t 1-Brownian motions. The first trend occurred in the accelerated flow, whereas the second dynamic was observed in the mixed wake and depended on the initial separation. The Brownian motion was present in the late stage dominated by flow dissipation. Kolmogorov microscales during the fully mixed phase were obtained with three distinct approaches, namely, Heisenberg-Yaglom relation of the Lagrangian acceleration variance, the fluctuating rate of the strain tensor in the Eulerian frame of reference as well as the Batchelor scaling in pair dispersion, which showed good agreement.
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Sensors that reproduce the complex characteristics of cutaneous receptors in the skin have important potential in the context of artificial systems for controlled interactions with the physical environment. Multimodal responses with high sensitivity and wide dynamic range are essential for many such applications. This report introduces a simple, three-dimensional type of microelectromechanical sensor that incorporates monocrystalline silicon nanomembranes as piezoresistive elements in a configuration that enables separate, simultaneous measurements of multiple mechanical stimuli, such as normal force, shear force, and bending, along with temperature. The technology provides high sensitivity measurements with millisecond response times, as supported by quantitative simulations. The fabrication and assembly processes allow scalable production of interconnected arrays of such devices with capabilities in spatiotemporal mapping. Integration with wireless data recording and transmission electronics allows operation with standard consumer devices.