Graphene-based composite membranes for isotope separation: challenges and opportunities

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Faisal Rehman ◽  
Fida Hussain Memon ◽  
Zubeda Bhatti ◽  
Muzaffar Iqbal ◽  
Faheeda Soomro ◽  
...  

Abstract Graphene-based membranes have got significant attention in wastewater treatment, desalination, gas separation, pervaporation, fuel cell, energy storage applications due to their supreme properties. Recently, studies have confirmed that graphene based membranes can also use for separation of isotope due to their ideal thickness, large surface area, good affinity, 2D structure etc. Herein, we review the latest groundbreaking progresses in both theoretically and experimentally chemical science and engineering of both nanoporous and lamellar graphene-based membrane for separation of different isotopes. Especially focus will be given on the current issues, engineering hurdles, and limitations of membranes designed for isotope separation. Finally, we offer our experiences on how to overcome these issues, and present an ideas for future improvement and research directions. We hope, this article is provide a timely knowledge and information to scientific communities, and those who are already working in this direction.

2021 ◽  
Vol 127 (1) ◽  
pp. 119-134
Author(s):  
Jay Szpilka

While the subject of women’s activity in historical and contemporary punk scenes has attracted significant attention, the presence of trans women in punk has received comparatively little research, in spite of their increasing visibility and long history in punk. This article examines the conditions for trans women’s entrance in punk and the challenges and opportunities that it offers for their self-assertion. By linking Michel Foucault’s notion of parrhesia with the way trans women in punk do their gender, an attempt is made at showing how the embodied experience of a trans woman making herself heard from the punk stage can serve as a site of ‘gender pluralism’.


2022 ◽  
Vol 8 ◽  
Author(s):  
Zhongkui Wang ◽  
Shinichi Hirai ◽  
Sadao Kawamura

Despite developments in robotics and automation technologies, several challenges need to be addressed to fulfill the high demand for automating various manufacturing processes in the food industry. In our opinion, these challenges can be classified as: the development of robotic end-effectors to cope with large variations of food products with high practicality and low cost, recognition of food products and materials in 3D scenario, better understanding of fundamental information of food products including food categorization and physical properties from the viewpoint of robotic handling. In this review, we first introduce the challenges in robotic food handling and then highlight the advances in robotic end-effectors, food recognition, and fundamental information of food products related to robotic food handling. Finally, future research directions and opportunities are discussed based on an analysis of the challenges and state-of-the-art developments.


2018 ◽  
Vol 2 (3) ◽  
pp. 228-267 ◽  
Author(s):  
Zaidi ◽  
Chandola ◽  
Allen ◽  
Sanyal ◽  
Stewart ◽  
...  

Modeling the interactions of water and energy systems is important to the enforcement of infrastructure security and system sustainability. To this end, recent technological advancement has allowed the production of large volumes of data associated with functioning of these sectors. We are beginning to see that statistical and machine learning techniques can help elucidate characteristic patterns across these systems from water availability, transport, and use to energy generation, fuel supply, and customer demand, and in the interdependencies among these systems that can leave these systems vulnerable to cascading impacts from single disruptions. In this paper, we discuss ways in which data and machine learning can be applied to the challenges facing the energy-water nexus along with the potential issues associated with the machine learning techniques themselves. We then survey machine learning techniques that have found application to date in energy-water nexus problems. We conclude by outlining future research directions and opportunities for collaboration among the energy-water nexus and machine learning communities that can lead to mutual synergistic advantage.


2019 ◽  
Vol 43 (3) ◽  
pp. 187-207
Author(s):  
Klodian Gradeci ◽  
Umberto Berardi

Probabilistic-based approaches for the performance evaluation of building envelopes to withstand mould growth have gained significant attention in recent years. In this article, a scoping review is performed to identify some current challenges and opportunities in probabilistic-based approaches. Therefore, the performance of a highly insulated wall is evaluated by applying a probabilistic-based methodology that accounts for several uncertainties and investigates their significance. A sensitivity analysis is performed according to the Morris method to understand the influence of each parameter and simplify the system representation of this case study. Deficiencies in terms of rain penetration and air leakage are accounted for. The mould growth risk is evaluated by integrating different mould models and assessment criteria. Overall, the performance of the investigated wall is found satisfactory in most of the cases, except when wind-driven rain penetration occurs. The study demonstrates that a probabilistic-based methodology enables a systematic approach to evaluate the performance of building constructions as it accounts for the involved uncertainties, provides a clear association of the microbial growth to its probability of occurrence and enables the identification of the dominant parameters, delivering more comprehensive conclusions.


Author(s):  
Matilda K ◽  
Charlotte G

Ethosomes are noninvasive release carriers that facilitate drugs to attain the deep skin layers and the universal movement. Though ethosomal systems are theoretically complicated, they are effortless in their training, safe for use an arrangement that can highly enlarge their relevance. Ethosomes are soft, compliant vesicles tailored for improved liberation of vigorous agents. Because of their exclusive organization, ethosomes are able to encapsulate and deliver during the skin highly lipophilic molecules such as cannabinoids, testosterone, and minoxidil, as well as cationic drugs such as propranolol, trihexaphenidyl, Cyclosporine, insulin, salbutamol etc. Improved release of bioactive molecules during the skin and cellular membranes by means of an ethosomal delivery service opens numerous challenges and opportunities for the research and future improvement of novel improved therapies. Ethosomes are gaining reputation in designing drug delivery systems for topical and transdermal use for their ability to reach deep skin layers and universal circulation. Although ethosomes are theoretically complicated, they are simple in training and safe for use. Although with their high efficiency, the ethosomes show possible for development of their applications. The aim of the review to make a inclusive description on properties and training of ethosomes followed by the classification and the list of drugs encapsulated in ethosomes.


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