June 17, 2024 UMD Home FabLab AIMLab
Hot Papers logo

Issue 3

Sustainable high-strength macrofibres extracted from natural bamboo

Nature Sustainability

Zhihan Li, Chaoji Chen, Hua Xie, Yuan Yao, Xin Zhang, Alexandra Brozena, Jianguo Li, Yu Ding, Xinpeng Zhao, Min Hong, Haiyu Qiao, Lee M. Smith, Xuejun Pan, Robert Briber, Sheldon Q. Shi & Liangbing Hu

Synthetic fibres such as polyester and carbon are used in a broad variety of industries. However, as they derive from petrochemicals that are neither renewable nor biodegradable, the development of natural alternatives has gained increasing momentum in recent years. Here, we report a top-down approach for scalable production of cellulose macrofibres from bamboo stems involving a mild delignification process followed by water-assisted air-drying. Consisting of aligned and densely packed cellulose nanofibrils that possess strong hydrogen bonds and van der Walls forces, the extracted fibres exhibit a tensile strength of 1.90 ± 0.32 GPa, a Young’s modulus of 91.3 ± 29.7 GPa and a toughness of 25.4 ± 4.5 MJ m−3, which exceed those of wood-derived fibres and are comparable to synthetic carbon analogues. As a result of the low density, the specific strength is as high as 1.26 ± 0.21 GPa cm−3 g−1, surpassing most reinforcing components such as steel wire, synthetic polymers and vitreous fibres. The life-cycle assessment reveals that replacing polymer and carbon fibres in structural composites with the current natural fibres leads to substantial reduction in carbon emissions. Our work suggests a pathway towards sustainability in wider areas of application, including automobiles, aeronautics and construction.


van der Waals SWCNT@BN Heterostructures Synthesized from Solution-Processed Chirality-Pure Single-Wall Carbon Nanotubes

ACS Nano

Chiyu Zhang, Jacob Fortner, Peng Wang, Jeffrey A. Fagan, Shuhui Wang, Ming Liu, Shigeo Maruyama, and YuHuang Wang

Single-wall carbon nanotubes in boron nitride (SWCNT@BN) are one-dimensional van der Waals heterostructures that exhibit intriguing physical and chemical properties. As with their carbon nanotube counterparts, these heterostructures can form from different combinations of chiralities, providing rich structures but also posing a significant synthetic challenge to controlling their structure. Enabled by advances in nanotube chirality sorting, clean removal of the surfactant used for solution processing, and a simple method to fabricate free-standing submonolayer films of chirality pure SWCNTs as templates for the BN growth, we show it is possible to directly grow BN on chirality enriched SWCNTs from solution processing to form van der Waals heterostructures. We further report factors affecting the heterostructure formation, including an accelerated growth rate in the presence of H2, and significantly improved crystallization of the grown BN, with the BN thickness controlled down to one single BN layer, through the presence of a Cu foil in the reactor. Transmission electron microscopy and electron energy-loss spectroscopic mapping confirm the synthesis of SWCNT@BN from the solution purified nanotubes. The photoluminescence peaks of both (7,5)- and (8,4)-SWCNT@BN heterostructures are found to redshift (by ∼10 nm) relative to the bare SWCNTs. Raman scattering suggests that the grown BN shells pose a confinement effect on the SWCNT core.


Neural network in food analytics

Critical Reviews in Food Science and Nutrition

Peihua Ma, Zhikun Zhang, Xiaoxue Jia, Xiaoke Peng, Zhi Zhang, Kevin Tarwa, Cheng-I Wei, Fuguo Liu, Qin Wang

Neural network (i.e. deep learning, NN)-based data analysis techniques have been listed as a pivotal opportunity to protect the integrity and safety of the global food supply chain and forecast $11.2 billion in agriculture markets. As a general-purpose data analytic tool, NN has been applied in several areas of food science, such as food recognition, food supply chain security and omics analysis, and so on. Therefore, given the rapid emergence of NN applications in food safety, this review aims to provide a comprehensive overview of the NN application in food analysis for the first time, focusing on domain-specific applications in food analysis by introducing fundamental methodology, reviewing recent and notable progress, and discussing challenges and potential pitfalls. NN demonstrated that it has a bright future through effective collaboration between food specialist and the broader community in the food field, for example, superiority in food recognition, sensory evaluation, pattern recognition of spectroscopy and chromatography. However, major challenges impeded NN extension including void in the food scientist-friendly interface software package, incomprehensible model behavior, multi-source heterogeneous data, and so on. The breakthrough from other fields proved NN has the potential to offer a revolution in the immediate future.


Agarose hydrogel composite supports microgreen cultivation with enhanced porosity and continuous water supply under terrestrial and microgravitational conditions

International Journal of Biological Macromolecules

Zi Teng, Yaguang Luo, Daniel J. Pearlstein, Bin Zhou, Christina M. Johnson, Joseph Mowery, Qin Wang, Jorge M. Fonseca

Hydrogels are attractive soilless media for plant cultivation with strong water and nutrient retention. However, pristine hydrogels contain mostly ultra-micro pores and lack air-filled porosity for root zone aeration. Herein we report a porous hydrogel composite comprising an agarose network and porous growing mix particle (GMP) fillers. The agarose backbone allowed the composite to sustain a 12-d growth cycle for red cabbage microgreens without the need for watering or crew interaction. Moreover, the GMP induced greater total pore volume and increased the prevalence of pores >30 μm by 8-fold. Further investigation suggested that the nutrients from GMP accounted for a 54 % increase in microgreen yield over pristine hydrogel, while the porous structure introduced by GMP improved the yield by another 44 %. Increased air-filled porosity accelerated the water transport and loss of hydrogel but maintained favorable water potential levels for plant extraction. Finally, the hydrogel composite supported microgreen growth satisfyingly under simulated microgravity despite some morphological changes. Results of this study reveal a novel growth substrate that is lightweight, convenient, and water-efficient, while effectively sustaining plant growth for multiple applications including indoor farming and space farming.


Achieving Scalable Near-Zero-Index Materials

Advanced Photonics Research

Kevin J. Palm, Tao Gong, Calum Shelden, Ece Deniz, Lisa J. Krayer, Marina S. Leite, Jeremy N. Munday

Near-zero-index (NZI) materials are becoming increasingly important for photonic designs because they enable new ways to control light–matter interactions at the nanoscale. Many device prototypes that utilize NZI layers are created under conditions that are tool and laboratory specific, making widespread utilization and scalability of NZI materials difficult. Herein, this limitation is circumvented by using transparent conducting oxides (TCOs) produced from scalable commercial sources. The optical response of 49 distinct TCOs with NZI behavior from 12 different suppliers is quantified, including indium tin oxide (ITO), aluminum-doped zinc oxide (AZO), and fluorine-doped tin oxide (FTO). The measurements reveal that the ITO samples have the strongest NZI resonances with many samples exhibiting |n| < 0.6 with resonances occurring between 1150 and 1350 nm. Conversely, the FTO and AZO films present higher values of |n| (ranging from 0.6 to 0.9) at 1500–1900 nm. The optical properties, resistivities, and roughness values for all thin films are reported, creating a useful database for device design. Finally, novel NZI phenomena, such as the strong suppression of non-normal incidence illumination using the data collected from these samples, are demonstrated, opening the door to new opportunities for both research-grade and mass-produced NZI devices.


Read all NanoCenter papers >>

Colleges A. James Clark School of Engineering
The College of Computer, Mathematical, and Natural Sciences

Communicate Join Email List
Contact Us
Follow us on TwitterTwitter logo

Links Privacy Policy

Copyright The University of Maryland University of Maryland