Range Of Applications Research Articles

A fast actuated soft gripper based on shape memory alloy wires

The application of shape memory alloy (SMA) actuated soft grippers is limited by their slow recovery speed. In order to further expand their application range, as one of the solutions to address this limitation, this paper proposes a fast actuated soft gripper based on SMA wire active heat dissipation and elastic rib combination to meet the rapid actuation and recovery. The structure primarily consists of a heat dissipation module capable of winding SMA wire and a soft structure resembling a scorpion tail with embedded supper elastic SMA wire. The geometric structure model, dynamics and SMA constitutive model and finite element model of the soft gripper are established, and the lateral deformation of soft bionic scorpion tail end is analyzed through simulations and experiments. In addition, the force in designed soft gripper tip and its ability to grasp different objects are also studied through experiments. The results show that the addition of a cooling fan increased the recovery rate by about 25%, and the force in soft bionic scorpion tail end can reach about 0.12 N. The designed soft gripper can successfully grasp objects with different softness, shape, size and weight. It lays a theoretical foundation and technical support for the development of soft grippers actuated by SMA in the future.

Phyto-pharmacological Potential of Aegle marmelos (L.) for Neurological Disorders: Progress and Prospects.

Aegle marmelos, an Indian plant, has been extensively utilized by the people of the Indian subcontinent over about 5000 years. The leaves, bark, roots, and fruits, including seeds, are widely used to cure a variety of diseases in the Indian traditional system of medicine, Ayurveda, along with numerous folk medicines. By revealing the existence of significant bioactive chemicals, modern research has effectively substantiated the therapeutic effects of bael. The objective of this study was to review the literature regarding A. marmelos geographical distribution, morphology, therapeutic benefits, and phytochemicals found in the bael leaves, fruits, and other parts of the plant that offer a wide range of pharmacological applications in neurological disorders. A thorough literature search was conducted using five computerized databases, such as PubMed, Google Scholar, ScienceDirect, Elsevier, and Wiley Online Library (WOL), by using standard keywords "A. marmelos," "Geographical distribution," "Morphological description," "Ethnobotanical Uses," "Phytoconstituents" and "Neuroprotective activities" for review papers published between 1975 and 2023. A small number of earlier review articles focused on phyto-pharmacological potential of Aegle marmelos (L.) for neurological disorders. According to some research, Aegle marmelos extracts potentially have neuroprotective benefits. This is due to its capacity to alter cellular mechanisms that cause neuronal damage. Neurodegenerative illnesses usually induce permanent neuronal network loss overall the brain along with the spinal cord (CNS), resulting in chronic functional impairments. The review summarizes the multiple aspects and processes of A. marmelos extract and its components in several models of neurodegenerative diseases such as anxiety, epilepsy, depression, Parkinson's disease, Alzheimer's disease, and others. MDA, nitrite, TNF-, and IL-6 levels were dramatically elevated, whereas glutathione levels were significantly lowered in the hippocampus of STZ-treated rats. Furthermore, STZ-treated rats showed a substantial drop in catalase activity and an increase in AChE activity, indicating cholinergic hypofunction and neuronal injury. The neuroprotective ability of A. marmelos against STZ-induced oxidative stress and cognitive loss in rats suggests that it has therapeutic relevance in Alzheimer's disease (AD).

Poly(hydroxyalkanoates): Emerging Biopolymers in Biomedical Fields and Packaging Industries for a Circular Economy

AbstractPoly(hydroxyalkanoates) (PHAs) are a class of sustainable, bio-based thermoplastic polymers with attractive physiochemical properties, including non-toxicity, biocompatibility, elastomeric behavior by design, and piezoelectric characteristics. In the ongoing effort to reduce plastics waste, PHAs can play a substantial role due to their inherent biodegradability free of microplastics, customizable properties, and versatile applications. This includes their tremendous potential in a broad range of biomedical applications. Biomass-based materials have recently gained great interest in the health sector, given the vast amount of interdisciplinary research in bioengineering and medicine. Implantable biomaterials should not elicit any negative response at the implantation site, which differentiates them from general-purpose polymers. PHAs do not induce any thrombosis or antigenic response even after being in contact with blood in the human body during long-term use. The biocompatibility of PHAs is also a key factor in the rapid growth and proliferation of tissues onto and within these materials when served as tissue engineering scaffolds. By application, the biomedical field was estimated to be the second-largest market share for PHAs, in terms of volume, in 2022. While PHA-based materials bring forth a broad range of opportunities, they also present challenges that have limited their widespread use and a greater market share. A better understanding of their physiochemical properties and biodegradation rates, production challenges, and the need for cost-effective strategies are some of the hurdles that need to be addressed. This review paper provides an overview of the commonly used PHA homopolymers and copolymers in biomedical fields and packaging industries. The introduction of the manuscript presents the concept of bioplastics and their environmental significance, highlighting the urgent need for alternatives to conventional fossil-based plastics. The next sections briefly cover the synthesis, properties, as well as homopolymer and copolymer formulations, followed by the application of PHA-based materials in the biomedical field. Current opportunities and challenges, together with some insight into the future gathered from the published studies, have been brought in the concluding section of this paper.

AMENet is a monocular depth estimation network designed for automatic stereoscopic display.

Monocular depth estimation has a wide range of applications in the field of autostereoscopic displays, while accuracy and robustness in complex scenes are still a challenge. In this paper, we propose a depth estimation network for autostereoscopic displays, which aims at improving the accuracy of monocular depth estimation by fusing Vision Transformer (ViT) and Convolutional Neural Network (CNN). Our approach feeds the input image as a sequence of visual features into the ViT module and utilizes its global perception capability to extract high-level semantic features of the image. The relationship between the losses is quantified by adding a weight correction module to improve robustness of the model. Experimental evaluation results on several public datasets show that AMENet exhibits higher accuracy and robustness than existing methods in different scenarios and complex conditions. In addition, a detailed experimental analysis was conducted to verify the effectiveness and stability of our method. The accuracy improvement on the KITTI dataset compared to the baseline method is 4.4%. In summary, AMENet is a promising depth estimation method with sufficient high robustness and accuracy for monocular depth estimation tasks.

Forks in the road: decisions that have shaped and will shape the teaching and practice of geotechnical engineering

Geotechnical engineering spans a wide range of applications, including tunnels, foundations, dams, and retaining structures. It deals with a material known to be difficult to model: a particulate material whose mechanical response is affected by all three invariants of the stress tensor, by loading rate, by density and by fabric. New problems and greater complexity in old problems have come about with the effects of climate change. Progress in certain technologies—notably artificial intelligence—also defines the new landscape in which geotechnical engineers must operate. This paper focuses on mechanics-based geotechnical engineering applications. The paper reviews some of the major decisions that were made by the engineers and researchers who developed geotechnical engineering to the point at which it was an identifiable separate discipline and the consequences that these decisions have had on the development of the discipline and on its teaching. The paper identifies some key modelling choices that were made that have had an undeservedly disproportionate impact on the teaching and practice of geotechnical engineering. The focus of the paper is therefore on these decisions and choices, and what should be taught in their place today. Challenges that future geotechnical engineers may face, as well tools that will be available to them, are also discussed in the context of what should be taught in undergraduate and graduate courses.

Polar modification‐enhanced interfacial compatibility for high‐performance rubber blends

AbstractThe blending of different elastomers can greatly broaden the application range of rubber materials. However, due to the poor compatibility between polar elastomers and non‐polar elastomers, severe phase separation occurs during the blending process, which severely degrades their processing performance and mechanical properties. In this paper, we prepared SBR‐P/XNBR blends by emulsion blending polar modified styrene‐butadiene rubber (SBR‐P) latex with carboxylated nitrile rubber (XNBR) latex. The effects of the blending ratios on the vulcanization behavior, mechanical strength, dynamic mechanical properties, and oil resistance of the rubber compounds were studied. Experimental results showed that the mechanical strength and oil resistance of the modified SBR‐P/XNBR blends are significantly higher than the unmodified SBR and XNBR blends. The dynamic mechanical analysis curve results of the rubber compounds showed that SBR‐P has good compatibility with XNBR. With the increasing addition of XNBR, the oil resistance of the rubber compounds improves, and the solvent adsorption is reduced by over 60%.This study proposes a solution for utilizing non‐polar rubbers, which are typically not oil‐resistant, in oily environments. The proposed solution enables the preparation of composites with excellent mechanical properties in such environments.

Designing hydrolysis-resistant Ti/Zn bimetallic catalyst based on the coordination activation mechanism to synthesize high molecular weight poly (1,5-pentene terephthalate) (PPeT)

The high molecular weight poly (1,5-pentene terephthalate) synthesis and its molecular weight distribution control are still challenging, and one of the critical problems is the lack of efficient catalysts. Based on the coordination activation mechanism, a heavy metal free, hydrolysis-resistant and 1,5-Pentanediol soluble Ti/Zn bimetallic catalyst has been synthesized and characterized. The Ti/Zn bimetallic active center increases electron-absorption effect in catalyst to promote the esterification process, and the diol-metal alkoxide structure increases the production of oligomer ligands, which can effectively improve transesterification efficiency. The optimal polycondensation reaction temperature for PPeT synthesized with Ti/Zn bimetallic catalyst can be reduced to 230 °C, with an average reaction rate of 90.33 g mol−1·min−1. The number average molecular weight of PPeT can be increased to 3.02 × 104 g mol−1, and the polymer dispersive index can be as low as 1.90. As the number average molecular weight increases, poly (1,5-pentene terephthalate) has a tensile strength of 29.80 MPa and an elongation at break of 16.39%. More importantly, Ti/Zn bimetallic catalyst retains excellent catalytic activity after treatment with boiling water and has significantly improved hydrolysis resistance and storage stability. Ti/Zn bimetallic catalyst can significantly increase the molecular weight and melt viscosity of poly (1,5-pentene terephthalate), giving it the potential for a wider range of applications in plastics and fiber fields.

Improved Regression Analysis with Ensemble Pipeline Approach for Applications across Multiple Domains

In this research, we introduce two new machine learning regression methods: the Ensemble Average and the Pipelined Model. These methods aim to enhance traditional regression analysis for predictive tasks and have undergone thorough evaluation across three datasets, Kaggle House Price, Boston House Price, and California Housing, using various performance metrics. The results consistently show that our models outperform existing methods in terms of accuracy and reliability across all three datasets. The Pipelined Model, in particular, is notable for its ability to combine predictions from multiple models, leading to higher accuracy and impressive scalability. This scalability allows for their application in diverse fields like technology, finance, and healthcare. Furthermore, these models can be adapted for real-time and streaming data analysis, making them valuable for applications such as fraud detection, stock market prediction, and IoT sensor data analysis. Enhancements to the models also make them suitable for big data applications, ensuring their relevance for large datasets and distributed computing environments. It is important to acknowledge some limitations of our models, including potential data biases, specific assumptions, increased complexity, and challenges related to interpretability when using them in practical scenarios. Nevertheless, these innovations advance predictive modeling, and our comprehensive evaluation underscores their potential to provide increased accuracy and reliability across a wide range of applications. The results indicate that the proposed models outperform existing models in terms of accuracy and robustness for all three datasets. The source code can be found at https://huggingface.co/DebajyotyBanik/Ensemble-Pipelined-Regression/tree/main

Electrical Characterization and Ammonia Gas Response of a p‐Si/n‐poly[benzimidazobenzophenanthroline] Thin‐Film Junction Diode

The electrical characterization and ammonia vapor (NH3) response of a p‐Si/n‐poly[benzimidazobenzophenanthroline] (n‐BBL) thin‐film junction diode are reported. The presence of a depletion layer at the n‐BBL/p‐Si interface is verified via capacitance–voltage measurements, and the built‐in potential is ≈1.8 V. Using the standard diode equation for data analysis, the turn‐on voltage, rectification ratio, and ideality parameter are found to be 2 V, 16, and 6, respectively. The diode is also tested in the presence of NH3 vapor where it retained its asymmetric J–V behavior with increased currents and an insignificant change in device parameters. NH3 is believed to interact with the adsorbed O2− species on the n‐BBL surface liberating electrons that enhance the diode current. The response time, recovery time, and sensitivity of the diode are 65 s, 121 s, and 52%, respectively. The removal of the gas restores the diode characteristics to their near original shape making it reusable. The diode is also electrically characterized as a function of temperature and is found to retain its rectifying behavior down to 150 K. The rectifying and gas‐sensing features make the diode multifunctional, which expands the range of applications of this ladder‐type conducting polymer.

Multimodality integrated microresonators using the Moiré speedup effect.

High-Q microresonators are indispensable components of photonic integrated circuits and offer several useful operational modes. However, these modes cannot be reconfigured after fabrication because they are fixed by the resonator's physical geometry. In this work, we propose a Moiré speedup dispersion tuning method that enables a microresonator device to operate in any of three modes. Electrical tuning of Vernier coupled rings switches operating modality to Brillouin laser, bright microcomb, and dark microcomb operation on demand using the same hybrid-integrated device. Brillouin phase matching and microcomb operation across the telecom C-band is demonstrated. Likewise, by using a single-pump wavelength, the operating mode can be switched. As a result, one universal design can be applied across a range of applications. The device brings flexible mixed-mode operation to integrated photonic circuits.

DNA Nanospheres Assisted Spatial Confinement Signal Amplification for MicroRNA Imaging in Live Cancer Cells.

DNA assemblies are commonly used in biosensing, particularly for the detection and imaging of microRNAs (miRNAs), which are biomarkers associated with tumor progression. However, the difficulty lies in the exploration of high-sensitivity analytical techniques for miRNA due to its limited presence in living cells. In this study, we introduced a DNA nanosphere (DS) enhanced catalytic hairpin assembly (CHA) system for the detection and imaging of intracellular miR-21. The single-stranded DNA with four palindromic portions and extending sequences at the terminal was annealed for assembling DS, which avoided the complex sequence design and high cost of long DNA strands. Benefiting from the multiple modification sites of DS, functional hairpins H1 (modified with Cy3 and BHQ2) and H2 were grafted onto the surface of DS for assembling DS-H1-H2 using a hybridization reaction. The DS-H1-H2 system utilized spatial confinement and the CHA reaction to amplify fluorescence signals of Cy3. This enabled highly sensitive and rapid detection of miR-21 in the range from 0.05 to 3.5 nM. The system achieved a limit of determination (LOD) of 2.0 pM, which was 56 times lower than that of the control CHA circuit with freedom hairpins. Additionally, the sensitivity was improved by 8 times. Moreover, DS-H1-H2 also showed an excellent imaging capability for endogenous miR-21 in tumor cells. This was due to enhanced cell internalization efficiency, accelerated reaction kinetics, and improved biostability. The imaging strategy was shown to effectively monitor the dynamic content of miR-21 in live cancer cells and differentiate various cells. In general, the simple nanostructure DS not only enhanced the detection and imaging capability of the conventional probe but also could be easily integrated with the reported DNA-free probe, indicating a wide range of potential applications.

Exosome Isolation Using Chitosan Oligosaccharide Lactate-1-Pyrenecarboxylic Acid-Based Self-Assembled Magnetic Nanoclusters.

Exosomes are small extracellular vesicles that play a crucial role in intercellular communication and offer significant potential for a wide range of biomedical applications. However, conventional methods for exosome isolation have limitations in terms of purity, scalability, and preservation of exosome structural integrity. To address these challenges, an exosome isolation platform using chitosan oligosaccharide lactate conjugated 1-pyrenecarboxylic acid (COL-Py) based self-assembled magnetic nanoclusters (CMNCs), is presented. CMNCs are characterized to optimize their size, stability, and interaction dynamics with exosomes. The efficiency of CMNCs in isolating exosomes is systematically evaluated using various analytical methods to demonstrate their ability to capture exosomes based on amphiphilic lipid bilayers. CMNC-based exosome isolation consistently yields exosomes with structural integrity and purity similar to those obtained using traditional methods. The reusability of CMNCs over multiple exosome isolation cycles underscores their scalability and offers an efficient solution for biomedical applications. These results are supported by western blot analysis, which demonstrated the superiority of CMNC-based isolation in terms of purity compared to conventional methods. By providing a scalable and efficient exosome isolation process that preserves both structural integrity and purity, CMNCs can constitute a new platform that can contribute to the field of exosome studies.

Performance simulation of the perovskite solar cells with Ti3C2 MXene in the SnO2 electron transport layer

MXenes, a class of two-dimensional (2D) transition metal carbides and nitrides, have a wide range of potential applications due to their unique electronic, optical, plasmonic, and other properties. SnO2–Ti3C2 MXene with different contents of Ti3C2 (0.5, 1.0, 2.0, 2.5 wt‰), experimentally, has been used as electron transport layers (ETLs) in Perovskite Solar Cells (PSCs). The SCAPS-1D simulation software could simulate a perovskite solar cell comprised of CH3NH3PbI3 absorber and SnO2 (or SnO2–Ti3C2) ETL. The simulation results like Power Conversion Efficiency (PCE), Open circuit voltage (VOC), Short circuit current density (JSC), Fill Factor (FF), and External Quantum Efficiency (EQE) have been compared within samples with different weight percentages of Ti3C2 MXene incorporated in ETL. Reportedly, the ETL of SnO2 with Ti3C2 (1.0 wt‰) effectively increases PCE from 17.32 to 18.32%. We simulate the role of MXene in changing the ideality factor (nid), photocurrent (JPh), built-in potential (Vbi), and recombination resistance (Rrec). The study of interface recombination currents and electric field shows that cells with 1.0 wt‰ of MXene in SnO2 ETL have higher values of ideality factor, built-in potential, and recombination resistance. The correlation between these values and cell performance allows one to conclude the best cell performance for the sample with 1.0 wt‰ of MXene in SnO2 ETL. With an optimization procedure for this cell, an efficiency of 27.81% is reachable.

Anisotropic Morphing in Bistable Kirigami through Symmetry Breaking and Geometric Frustration.

Shape morphing in bistable kirigami enables remarkable functionalities appealing to a diverse range of applications across the spectrum of length scale. At the core of their shape shifting lies the architecture of their repeating unit, where highly deformable slits and quasi-rigid rotating units often exhibit multiple symmetries that confer isotropic deployment obeying uniform scaling transformation. In this work, symmetry breaking in bistable kirigami is investigated to access geometric frustration and anisotropic morphing, enabling arbitrarily scaled deployment in planar and spatial bistable domains. With an analysis on their symmetry properties complemented by a systematic investigation integrating semi-analytical derivations, numerical simulations, and experiments on elastic kirigami sheets, this work unveils the fundamental relations between slit symmetry, geometric frustration, and anisotropic bistable deployment. Furthermore, asymmetric kirigami units are leveraged in planar and flat-to-3D demonstrations to showcase the pivotal role of shear deformation in achieving target shapes and functions so far unattainable with uniformly stretchable kirigami. The insights provided in this work unveil the role of slit symmetry breaking in controlling the anisotropic bistable deployment of soft kirigami metamaterials, enriching the range of achievable functionalities for applications spanning deployable space structures, wearable technologies, and soft machines.

Coarse-Grained Crystal Graph Neural Networks for Reticular Materials Design.

Reticular materials, including metal-organic frameworks and covalent organic frameworks, combine the relative ease of synthesis and an impressive range of applications in various fields from gas storage to biomedicine. Diverse properties arise from the variation of building units─metal centers and organic linkers─in almost infinite chemical space. Such variation substantially complicates the experimental design and promotes the use of computational methods. In particular, the most successful artificial intelligence algorithms for predicting the properties of reticular materials are atomic-level graph neural networks, which optionally incorporate domain knowledge. Nonetheless, the data-driven inverse design involving these models suffers from the incorporation of irrelevant and redundant features such as a full atomistic graph and network topology. In this study, we propose a new way of representing materials, aiming to overcome the limitations of existing methods; the message passing is performed on a coarse-grained crystal graph that comprises molecular building units. To highlight the merits of our approach, we assessed the predictive performance and energy efficiency of neural networks built on different materials representations, including composition-based and crystal-structure-aware models. Coarse-grained crystal graph neural networks showed decent accuracy at low computational costs, making them a valuable alternative to omnipresent atomic-level algorithms. Moreover, the presented models can be successfully integrated into an inverse materials design pipeline as estimators of the objective function. Overall, the coarse-grained crystal graph framework is aimed at challenging the prevailing atom-centric perspective on reticular materials design.

An improved optical length research on the physical boundary of particle-dispersed fuel

The Volumetric Homogenization Method (VHM) is one of the most commonly used methods for neutronics calculation in reactors or components. However, the use of VHM for the Double-Heterogeneous (DH) System may lead to a large deviation in reactivity calculation. The deviation of DH System using the VHM can be expressed by the theoretically modified optical length. When the theoretically modified optical length is less than 10−4, the deviation caused by the VHM will be less than 100 pcm. This paper points out that the existing theoretically modified optical length for some cases of DH systems is not accurate, and this method is only for pin cell. In this paper, by calculating a series of DH models and their corresponding VHM models, it is found that the water-uranium ratio and the shape of fuel region seriously affects the reactivity calculation deviation of particle-dispersed fuel, the original modified optical length does not take this into account, resulting in unacceptable errors. On this basis, the application of optical length to physical boundaries for DH system is further discussed and the shape correction factor is taken into consideration. Therefore, an improved optical length is proposed, which greatly expands the range of application of the physical boundary judgment methods for the double heterogeneity of dispersed particle fuel. The numerical results show that the accuracy of the improved optical length in defining the physical boundary of double heterogeneous system is higher than the theoretically modified optical length.

Two-Photon Absorbing Dendrimers and Their Properties-An Overview.

This review describes the two-photon absorption properties of dendrimers, which are arborescent three-dimensional macromolecules differing from polymers by their perfectly defined structure. The two-photon absorption process is a third order non-linear optical property that is attractive because it can be used in a wide range of applications. In this review, dendrimers that were studied for their two-photon absorption properties are first described. Then, the use of dendritic TPA chromophores for light harvesting, photopolymerization, optical power limitation, cell imaging, singlet oxygen generation, and photodynamic therapy is described. This review thus proposes an overview of the properties and possible applications of two-photon absorbing dendrimers.

Current progress and future perspectives in total‐body positron emission tomography/computed tomography. Part II: Clinical applications

AbstractTotal‐body positron emission tomography (TB‐PET) has significantly advanced from initial conception to global commercial availability. The high sensitivity of TB‐PET has led to superior lesion detection, thereby expanding the range of clinical applications. TB‐PET technology offers several advantages: (a) It enables the detection of small lesions, facilitating precise cancer staging and targeted cancer formulation. (b) The technology shortens the acquisition time while maintaining the quality of diagnostic images. (c) TB‐PET allows for a reduction in the amount of administered radiotracer, which minimizes image noise, reduces the effective radiation dose to patients, and enhances staff safety. (d) The scanner supports the development of new tracers and the dynamic imaging of these tracers throughout the entire body. (e) TB‐PET accommodates delayed scanning, which has been shown to improve the detection of small and previously undetected malignant lesions by enhancing the clearance in areas of significant background activity. (f) Owing to its high‐quality images, TB‐PET is suitable for parametric imaging, which offers several advantages over conventional standardized uptake value imaging. However, TB‐PET still faces several challenges. There is a lack of consensus on the optimal dose and scan duration for clinical diagnosis using TB‐PET. Additionally, unified standards for parametric imaging via TB‐PET are yet to be established, and the full clinical significance of this technology remains under‐explored. The accompanying review (Part 1) covers TB‐PET data manipulation and analysis.

Microstructure of dendrimers functionalized with folic acid as studied by molecular dynamics simulations

Poly(amidoamine) dendrimers (PAMAM), due to their unique properties such as nanometric size and shape, monodispersity, and numerous modifiable surface groups, are promising nanocarriers in a wide range of biomedical applications. However, amine-terminated PAMAM dendrimers have been proven to be toxic at physiological pH, which limits their biomedical application. It has been approved that the binding of folic acid (FA) to dendrimer reduces nanocarrier toxicity. Also, it can selectively target cancer cells with folate receptors (FR-α) overexpression. In this study, we have explored the structural features of FA-functionalized PAMAM dendrimers using all-atom molecular dynamics (MD) simulations. To this end, third and fourth generations of PAMAM dendrimers were functionalized with FA, and MD simulations were performed for 100 ns at 310 K and 1 bar at neutral pH. We have examined the effect of FA functionalization on the molecular size, solvent accessible surface area, structural changes of amidoamine monomers, and the solvation of investigated dendrimers. Our results reveal that G4FA is the most suitable drug delivery system for cancer therapy among others.

Amino-Acid-Encoded Bioinspired Supramolecular Self-Assembly of Multimorphological Nanocarriers.

Supramolecular self-assembly has emerged as an efficient tool to construct well-organized nanostructures for biomedical applications by small organic molecules. However, the physicochemical properties of self-assembled nanoarchitectures are greatly influenced by their morphologies, mechanical properties, and working mechanisms, making it challenging to design and screen ideal building blocks. Herein, using a biocompatible firefly-sourced click reaction between the cyano group of 2-cyano-benzothiazole (CBT) and the 1,2-aminothiol group of cysteine (Cys), an amino-acid-encoded supramolecular self-assembly platform Cys(SEt)-X-CBT (X represents any amino acid) is developed to incorporate both covalent and noncovalent interactions for building diverse morphologies of nanostructures with bioinspired response mechanism, providing a convenient and rapid strategy to construct site-specific nanocarriers for drug delivery, cell imaging, and enzyme encapsulation. Additionally, it is worth noting that the biodegradation of Cys(SEt)-X-CBT generated nanocarriers can be easily tracked via bioluminescence imaging. By caging either the thiol or amino groups in Cys with other stimulus-responsive sites and modifying X with probes or drugs, a variety of multi-morphological and multifunctional nanomedicines can be readily prepared for a wide range of biomedical applications.