low cost manufacturing
Recently Published Documents


TOTAL DOCUMENTS

152
(FIVE YEARS 40)

H-INDEX

12
(FIVE YEARS 3)

2021 ◽  
Vol 12 (1) ◽  
pp. 351
Author(s):  
Lilik Hasanah ◽  
Adryan Ashidiq ◽  
Roer Eka Pawinanto ◽  
Budi Mulyanti ◽  
Chandra Wulandari ◽  
...  

Perovskite solar cells (PSC) are currently exhibiting reproducible high efficiency, low-cost manufacturing, and scalable electron transport layers (ETL), which are becoming increasingly important. The application of photonic crystals (PC) on solar cells has been proven to enhance light harvesting and lead solar cells to adjust the propagation and distribution of photons. In this paper, the optimization of a two-dimensional nanodisk PC introduced in ETL with an organic-inorganic lead-iodide perovskite (methylammonium lead-iodide, MAPbI3) as the absorber layer was studied. A finite-difference time-domain (FDTD) simulation was used to evaluate the optical performance of PSC with various lattice constants and a radius of nanodisk photonic crystals. According to the simulation, the optimum lattice constant and PC radius applied to ETL are 500 nm and 225 nm, respectively. This optimum design enhances PSC absorption performance by more than 94% of incident light.


2021 ◽  
Vol 11 (23) ◽  
pp. 11290
Author(s):  
Bo Mi Lee ◽  
Ameen Eetemadi ◽  
Ilias Tagkopoulos

The objective of this study is to validate reduced graphene oxide (RGO)-based volatile organic compounds (VOC) sensors, assembled by simple and low-cost manufacturing, for the detection of disease-related VOCs in human breath using machine learning (ML) algorithms. RGO films were functionalized by four different metalloporphryins to assemble cross-sensitive chemiresistive sensors with different sensing properties. This work demonstrated how different ML algorithms affect the discrimination capabilities of RGO–based VOC sensors. In addition, an ML-based disease classifier was derived to discriminate healthy vs. unhealthy individuals based on breath sample data. The results show that our ML models could predict the presence of disease-related VOC compounds of interest with a minimum accuracy and F1-score of 91.7% and 83.3%, respectively, and discriminate chronic kidney disease breath with a high accuracy, 91.7%.


Author(s):  
Marco Vinicio Alban ◽  
Haechang Lee ◽  
Hanul Moon ◽  
Seunghyup Yoo

Abstract Thin dry electrodes are promising components in wearable healthcare devices. Assessing the condition of the human body by monitoring biopotentials facilitates the early diagnosis of diseases as well as their prevention, treatment, and therapy. Existing clinical-use electrodes have limited wearable-device usage because they use gels, require preparation steps, and are uncomfortable to wear. While dry electrodes can improve these issues and have demonstrated performance on par with gel-based electrodes, providing advantages in mobile and wearable applications; the materials and fabrication methods used are not yet at the level of disposable gel electrodes for low-cost mass manufacturing and wide adoption. Here, a low-cost manufacturing process for thin dry electrodes with a conductive micro-pyramidal array is presented for large-scale on-skin wearable applications. The electrode is fabricated using micromolding techniques in conjunction with solution processes in order to guarantee ease of fabrication, high device yield, and the possibility of mass production compatible with current semiconductor production processes. Fabricated using a conductive paste and an epoxy resin that are both biocompatible, the developed micro-pyramidal array electrode operates in a conformal, non-invasive manner, with low skin irritation, which ensures improved comfort for brief or extended use. The operation of the developed electrode was examined by analyzing electrode-skin-electrode impedance, electroencephalography, electrocardiography, and electromyography signals and comparing them with those measured simultaneously using gel electrodes.


2021 ◽  
Vol 12 ◽  
Author(s):  
SangJoon Lee ◽  
Jin-Hyeob Ryu

The innate immune system represents the first line of defense against influenza viruses, which cause severe inflammation of the respiratory tract and are responsible for more than 650,000 deaths annually worldwide. mRNA vaccines are promising alternatives to traditional vaccine approaches due to their safe dosing, low-cost manufacturing, rapid development capability, and high efficacy. In this review, we provide our current understanding of the innate immune response that uses pattern recognition receptors to detect and respond to mRNA vaccination. We also provide an overview of mRNA vaccines, and discuss the future directions and challenges in advancing this promising therapeutic approach.


2021 ◽  
Author(s):  
Caitlin Gamble ◽  
Drew Bryant ◽  
Damian Carrieri ◽  
Eli Bixby ◽  
Jason Dang ◽  
...  

Background: Arthrospira platensis (commonly known as spirulina) is a promising new platform for low-cost manufacturing of biopharmaceuticals. However, full realization of the platform's potential will depend on achieving both high growth rates of spirulina and high expression of therapeutic proteins. Objective: We aimed to optimize culture conditions for the spirulina-based production of therapeutic proteins. Methods: We used a machine learning approach called Bayesian black-box optimization to iteratively guide experiments in 96 photobioreactors that explored the relationship between production outcomes and 17 environmental variables such as pH, temperature, and light intensity. Results: Over 16 rounds of experiments, we identified key variable adjustments that approximately doubled spirulina-based production of heterologous proteins, improving volumetric productivity between 70% to 100% in multiple bioreactor setting configurations. Conclusion: An adaptive, machine learning-based approach to optimize heterologous protein production can improve outcomes based on complex, multivariate experiments, identifying beneficial variable combinations and adjustments that might not otherwise be discoverable within high-dimensional data.


Author(s):  
Parth Kotak ◽  
Jason Wilken ◽  
Kirsten Anderson ◽  
Caterina Lamuta

Abstract Ankle foot orthoses (AFOs) control the position and motion of the ankle, compensate for weakness, and correct deformities. AFOs can be classified as passive or powered. Powered AFOs overcome the limitations of passive AFOs by adapting their performance to meet a variety of requirements. However, the actuators currently used to power AFOs are typically heavy, bulky, expensive, or limited to laboratory settings. Thus, there is a strong need for lightweight, inexpensive, and flexible actuators for powering AFOs. In this technical brief, Carbon Fiber/Silicone Rubber (CF/SR) Twisted and Coiled Artificial Muscles (TCAMs) are proposed as novel actuators for powered AFOs. CF/SR TCAMs can lift up to 12,600 times their weight with an input power of only 0.025 W cm-1 and are fabricated from inexpensive materials through a low-cost manufacturing process. Additionally, they can provide a specific work of 758 J kg-1 when an input voltage of 1.64 V cm-1 is applied. A mechanical characterization of CF/SR TCAMs in terms of length/tension, tension/velocity, and active-passive length/tension is presented, and results are compared with the performance of skeletal muscles. A gait analysis demonstrates that CF/SR TCAMs can provide the performance required to supplement lower limb musculature and replicate the gait cycle of a healthy subject. Therefore, the preliminary results provided in this brief are a stepping stone for a dynamic AFO powered by CF/SR TCAMs.


2021 ◽  
Author(s):  
Cengiz Akkale ◽  
Donna Marie Cassidy-Hanley ◽  
Theodore G Clark

The requirement for low cost manufacturing makes bacterial cells a logical platform for the production of recombinant subunit vaccines for malaria. However, protein solubility has been a major stumbling block with prokaryotic expression systems. Notable examples include the transmission blocking vaccine candidates, Pfs25 and Pfs48/45, which are almost entirely insoluble when expressed as recombinant proteins in Escherichia coli. Various solubility tags have been used with limited success in improving solubility, although recent studies with granule lattice protein 1 (Grl1p) from the ciliated protozoan, Tetrahymena thermophila, have shown promise. Here, we examine a related solubility tag, granule lattice protein 3 (Grl3p) from T. thermophila, and compare it to both Grl1p and the well-studied maltose binding protein (MBP) used to improve the solubility of multiple protein targets. We find that Grl3p performs comparably to Grl1p when linked to Pfs25 but significantly improves solubility when paired with Pfs48/45.


2021 ◽  
Vol 4 (2) ◽  
pp. 27
Author(s):  
Prafulla Kumar Padhi ◽  
Feranando Charrua-Santos

Quantumization, the process of converting information into quantum (qubit) format, is a key enabler for propelling a new and distinct infrastructure in the pharmaceutical space. Quantum messenger RNA (QmRNA) technology, an indispensable constituent of quantum biotech (QB), is a compelling alternative to conventional vaccine methods because of its capacity for rapid development, high efficacy, and low-cost manufacturing to combat infectious diseases. Internet of Virus Things (IoVT), a biological version of Internet of Things (IoT), comprises applications to fight against pandemics and provides effective vaccine administration. The integration of QB and IoVT constitutes the QBIoVT system to advance the prospect of QmRNA vaccine discovery within a few days. This research disseminates the QBIoVT system paradigm, including architectural aspects, priority areas, challenges, applications, and QmRNA research engine design to accelerate QmRNA vaccines discovery. A comprehensive review of the literature was accomplished, and a context-centered methodology was applied to the QBIoVT paradigm forensic investigations to impel QmRNA vaccine discovery. Based on the above rumination, the principal motive for this study was to develop a novel QBIoVT theoretical framework which has not been produced through earlier theories. The proposed framework shall inspire future QBIoVT system research activities to improve pandemics detection and protection.


Sign in / Sign up

Export Citation Format

Share Document