Recent advancements in manufacturing, finite element analysis (FEA), and optimization techniques have expanded the design possibilities for metamaterials, including isotropic and auxetic structures, known for applications like energy absorption due to their unique deformation mechanism and consistent behavior under varying loads. However, achieving simultaneous control of multiple properties, such as optimal isotropic and auxetic characteristics, remains challenging. This paper introduces a systematic design approach that combines modeling, FEA, genetic algorithm, and optimization to create tailored mechanical behavior in metamaterials. Through strategically arranging 8 distinct neither isotropic nor auxetic unit cell states, the stiffness tensor in a 5 × 5 × 5 cubic symmetric lattice structure is controlled. Employing the NSGA-II genetic algorithm and automated modeling, we yield metamaterial lattice structures possessing both desired isotropic and auxetic properties. Multiphoton lithography fabrication and experimental characterization of the optimized metamaterial highlights a practical real-world use and confirms the close correlation between theoretical and experimental data.
This content will become publicly available on June 1, 2024
- Award ID(s):
- 2134534
- NSF-PAR ID:
- 10474763
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Extreme Mechanics Letters
- Volume:
- 61
- Issue:
- C
- ISSN:
- 2352-4316
- Page Range / eLocation ID:
- 102013
- Subject(s) / Keyword(s):
- ["Hierarchical mechanical behavior","Bioinspired design","In situ SEM microindentation","Atomic force microscopy","FEA modeling"]
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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null (Ed.)Purpose To develop a novel model composed solely of Col I and Col III with the lower and upper limits set to include the ratios of Col I and Col III at 3:1 and 9:1 in which the structural and mechanical behavior of the resident CM can be studied. Further, the progression of fibrosis due to change in ratios of Col I:Col III was tested. Methods Collagen gels with varying Col I:Col III ratios to represent a healthy (3:1) and diseased myocardial tissue were prepared by manually casting them in wells. Absorbance assay was performed to confirm the gelation of the gels. Rheometric analysis was performed on each of the collagen gels prepared to determine the varying stiffnesses and rheological parameters of the gels made with varying ratios of Col I:Col III. Second Harmonic Generation (SHG) was performed to observe the 3D characterization of the collagen samples. Scanning Electron microscopy was used for acquiring cross sectional images of the lyophilized collagen gels. AC16 CM (human) cell lines were cultured in the prepared gels to study cell morphology and behavior as a result of the varying collagen ratios. Cellular proliferation was studied by performing a Cell Trace Violet Assay and the applied force on each cell was measured by means of Finite Element Analysis (FEA) on CM from each sample. Results Second harmonic generation microscopy used to image Col I, displayed a decrease in acquired image intensity with an increase in the non-second harmonic Col III in 3:1 gels. SEM showed a fiber-rich structure in the 3:1 gels with well-distributed pores unlike the 9:1 gels or the 1:0 controls. Rheological analysis showed a decrease in substrate stiffness with an increase of Col III, in comparison with other cases. CM cultured within 3:1 gels exhibited an elongated rod-like morphology with an average end-to-end length of 86 ± 28.8 µm characteristic of healthy CM, accompanied by higher cell growth in comparison with other cases. Finite element analysis used to estimate the forces exerted on CM cultured in the 3:1 gels, showed that the forces were well dispersed, and not concentrated within the center of cells, in comparison with other cases. Conclusion This study model can be adopted to simulate various biomechanical environments in which cells crosstalk with the Collagen-matrix in diseased pathologies to generate insights on strategies for prevention of fibrosis.more » « less
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By mimicking biomimetic synaptic processes, the success of artificial intelligence (AI) has been astounding with various applications such as driving automation, big data analysis, and natural-language processing.[1-4] Due to a large quantity of data transmission between the separated memory unit and the logic unit, the classical computing system with von Neumann architecture consumes excessive energy and has a significant processing delay.[5] Furthermore, the speed difference between the two units also causes extra delay, which is referred to as the memory wall.[6, 7] To keep pace with the rapid growth of AI applications, enhanced hardware systems that particularly feature an energy-efficient and high-speed hardware system need to be secured. The novel neuromorphic computing system, an in-memory architecture with low power consumption, has been suggested as an alternative to the conventional system. Memristors with analog-type resistive switching behavior are a promising candidate for implementing the neuromorphic computing system since the devices can modulate the conductance with cycles that act as synaptic weights to process input signals and store information.[8, 9]
The memristor has sparked tremendous interest due to its simple two-terminal structure, including top electrode (TE), bottom electrode (BE), and an intermediate resistive switching (RS) layer. Many oxide materials, including HfO2, Ta2O5, and IGZO, have extensively been studied as an RS layer of memristors. Silicon dioxide (SiO2) features 3D structural conformity with the conventional CMOS technology and high wafer-scale homogeneity, which has benefited modern microelectronic devices as dielectric and/or passivation layers. Therefore, the use of SiO2as a memristor RS layer for neuromorphic computing is expected to be compatible with current Si technology with minimal processing and material-related complexities.
In this work, we proposed SiO2-based memristor and investigated switching behaviors metallized with different reduction potentials by applying pure Cu and Ag, and their alloys with varied ratios. Heavily doped p-type silicon was chosen as BE in order to exclude any effects of the BE ions on the memristor performance. We previously reported that the selection of TE is crucial for achieving a high memory window and stable switching performance. According to the study which compares the roles of Cu (switching stabilizer) and Ag (large switching window performer) TEs for oxide memristors, we have selected the TE materials and their alloys to engineer the SiO2-based memristor characteristics. The Ag TE leads to a larger memory window of the SiO2memristor, but the device shows relatively large variation and less reliability. On the other hand, the Cu TE device presents uniform gradual switching behavior which is in line with our previous report that Cu can be served as a stabilizer, but with small on/off ratio.[9] These distinct performances with Cu and Ag metallization leads us to utilize a Cu/Ag alloy as the TE. Various compositions of Cu/Ag were examined for the optimization of the memristor TEs. With a Cu/Ag alloying TE with optimized ratio, our SiO2based memristor demonstrates uniform switching behavior and memory window for analog switching applications. Also, it shows ideal potentiation and depression synaptic behavior under the positive/negative spikes (pulse train).
In conclusion, the SiO2memristors with different metallization were established. To tune the property of RS layer, the sputtering conditions of RS were varied. To investigate the influence of TE selections on switching performance of memristor, we integrated Cu, Ag and Cu/Ag alloy as TEs and compared the switch characteristics. Our encouraging results clearly demonstrate that SiO2with Cu/Ag is a promising memristor device with synaptic switching behavior in neuromorphic computing applications.
Acknowledgement This work was supported by the U.S. National Science Foundation (NSF) Award No. ECCS-1931088. S.L. and H.W.S. acknowledge the support from the Improvement of Measurement Standards and Technology for Mechanical Metrology (Grant No. 22011044) by KRISS.
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