Modeling the Reflectance Changes Induced by Vapor Condensation in Lycaenid Butterfly Wing Scales Colored by Photonic Nanoarchitectures

Butterfly wing architectures inspire sensor and energy applications

Natural biological systems are constantly developing efficient mechanisms to counter adverse effects of increasing human population and depleting energy resources. Their intelligent mechanisms are characterized by the ability to detect changes in the environment, store and evaluate information, and respond to external stimuli. Bio-inspired replication into man-made functional materials guarantees enhancement of characteristics and performance. Specifically, butterfly architectures have inspired the fabrication of sensor and energy materials by replicating their unique micro/nanostructures, light-trapping mechanisms and selective responses to external stimuli. These bio-inspired sensor and energy materials have shown improved performance in harnessing renewable energy, environmental remediation and health monitoring. Therefore, this review highlights recent progress reported on the classification of butterfly wing scale architectures and explores several bio-inspired sensor and energy applications.

Progress in Bioinspired Dry and Wet Gradient Materials from Design Principles to Engineering Applications

Nature does nothing in vain. Through millions of years of revolution, living organisms have evolved hierarchical and anisotropic structures to maximize their survival in complex and dynamic environments. Many of these structures are intrinsically heterogeneous and often with functional gradient distributions. Understanding the convergent and divergent gradient designs in the natural material systems may lead to a new paradigm shift in the development of next-generation high-performance bio-/nano-materials and devices that are critically needed in energy, environmental remediation, and biomedical fields. Herein, we review the basic design principles and highlight some of the prominent examples of gradient biological materials/structures discovered over the past few decades. Interestingly, despite the anisotropic features in one direction (i.e., in terms of gradient compositions and properties), these natural structures retain certain levels of symmetry, including point symmetry, axial symmetry, mirror symmetry, and 3D symmetry. We further demonstrate the state-of-the-art fabrication techniques and procedures in making the biomimetic counterparts. Some prototypes showcase optimized properties surpassing those seen in the biological model systems. Finally, we summarize the latest applications of these synthetic functional gradient materials and structures in robotics, biomedical, energy, and environmental fields, along with their future perspectives. This review may stimulate scientists, engineers, and inventors to explore this emerging and disruptive research methodology and endeavors.

Bio-inspired gas sensing: boosting performance with sensor optimization guided by "machine learning"

The performance of existing gas sensors often degrades in field conditions because of the loss of measurement accuracy in the presence of interferences. Thus, new sensing approaches are required with improved sensor selectivity. We are developing a new generation of gas sensors, known as multivariable sensors, that have several independent responses for multi-gas detection with a single sensor. In this study, we analyze the capabilities of natural and fabricated photonic three-dimensional (3-D) nanostructures as sensors for the detection of different gaseous species, such as vapors and non-condensable gases. We employed bare Morpho butterfly wing scales to control their gas selectivity with different illumination angles. Next, we chemically functionalized Morpho butterfly wing scales with a fluorinated silane to boost the response of these nanostructures to the vapors of interest and to suppress the response to ambient humidity. Further, we followed our previously developed design rules for sensing nanostructures and fabricated bioinspired inorganic 3-D nanostructures to achieve functionality beyond natural Morpho scales. These fabricated nanostructures have embedded catalytically active gold nanoparticles to operate at high temperatures of ≈300 °C for the detection of gases for solid oxide fuel cell (SOFC) applications. Our performance advances in the detection of multiple gaseous species with specific nanostructure designs were achieved by coupling the spectral responses of these nanostructures with machine learning (a.k.a. multivariate analysis, chemometrics) tools. Our newly acquired knowledge from studies of these natural and fabricated inorganic nanostructures coupled with machine learning data analytics allowed us to advance our design rules for sensing nanostructures toward the required gas selectivity for numerous gas monitoring scenarios at room and high temperatures for industrial, environmental, and other applications.

Stability and Selective Vapor Sensing of Structurally Colored Lepidopteran Wings Under Humid Conditions

Biological photonic nanoarchitectures are capable of rapidly and chemically selectively sensing volatile organic compounds due to changing color when exposed to such vapors. Here, stability and the vapor sensing properties of butterfly and moth wings were investigated by optical spectroscopy in the presence of water vapor. It was shown that repeated 30 s vapor exposures over 50 min did not change the resulting optical response signal in a time-dependent manner, and after 5-min exposures the sensor preserved its initial properties. Time-dependent response signals were shown to be species-specific, and by using five test substances they were also shown to be substance-specific. The latter was also evaluated using principal component analysis, which showed that the time-dependent optical responses can be used for real-time analysis of the vapors. It was demonstrated that the capability to detect volatile organic compounds was preserved in the presence of water vapor: high-intensity color change signals with short response times were measured in 25% relative humidity, similar to the one-component case; therefore, our results can contribute to the development of biological photonic nanoarchitecture-based vapor detectors for real-world applications, like living and working environments.

Vapor Selectivity of a Natural Photonic Crystal to Binary and Tertiary Mixtures Containing Chemical Warfare Agent Simulants

Vapor sensing via light reflected from photonic crystals has been increasingly studied as a means to rapidly identify analytes, though few studies have characterized vapor mixtures or chemical warfare agent simulants via this technique. In this work, light reflected from the natural photonic crystals found within the wing scales of the Morpho didius butterfly was analyzed after exposure to binary and tertiary mixtures containing dimethyl methylphosphonate, a nerve agent simulant, and dichloropentane, a mustard gas simulant. Distinguishable spectra were generated with concentrations tested as low as 30 ppm and 60 ppm for dimethyl methylphosphonate and dichloropentane, respectively. Individual vapors, as well as mixtures, yielded unique responses over a range of concentrations, though the response of binary and tertiary mixtures was not always found to be additive. Thus, while selective and sensitive to vapor mixtures containing chemical warfare agent simulants, this technique presents challenges to identifying these simulants at a sensitivity level appropriate for their toxicity.

Humidity-dependent colour change in the green forester moth, Adscita statices

The colours of insects serve important visual functions in aiding mate recognition, camouflage and warning. The display of insects is usually static, as cuticle coloration does not (or hardly) change during the lifespan of a mature imago form. Here, we describe a case of humidity-dependent, brilliant coloration in the green forester moth, Adscita statices. We show, by employing spectroscopic and ultrastructural methods, that the moth's colour results from the interference of incident light with an unusual hydrophilic melanized-chitin multilayer present in the wing scales. Humidity changes in the environment affect the multilayer properties, causing a significant shift of the green-peaking reflectance in the dry state to a rusty colour when damp, resulting in the strong colour change between day and dusk or dawn.