Mini Mental State

Graphene and other two-dimensional materials offer a new approach to controlling mass transport at the nanoscale. These materials can sustain nanoscale pores in their rigid lattices and due to their minimum possible material thickness, high mechanical strength and chemical robustness, they could be used to address persistent challenges in membrane separations. Here we discuss theoretical and experimental developments in the emerging field of nanoporous atomically thin membranes, focusing on the fundamental mechanisms of gas- and liquid-phase transport, membrane fabrication techniques and advances towards practical application. We highlight potential functional characteristics of the membranes and discuss applications where they are expected to offer advantages. Finally, we outline the major scientific questions and technological challenges that need to be addressed to bridge the gap from theoretical simulations and proof-of-concept experiments to real-world applications.

Fundamental transport mechanisms, fabrication and potential applications of nanoporous atomically thin membranes

This paper presents a low power boost converter for thermoelectric energy harvesting that demonstrates an efficiency that is 15% higher than the state-of-the-art for voltage conversion ratios above 20. This is achieved by utilizing a technique allowing synchronous rectification in the discontinuous conduction mode. A low-power method for input voltage monitoring is presented. The low input voltage requirements allow operation from a thermoelectric generator powered by body heat. The converter, fabricated in a 0.13 μm CMOS process, operates from input voltages ranging from 20 mV to 250 mV while supplying a regulated 1 V output. The converter consumes 1.6 (1.1) μW of quiescent power, delivers up to 25 (175) μW of output power, and is 46 (75)% efficient for a 20 mV and 100 mV input, respectively.

A 20 mV Input Boost Converter With Efficient Digital Control for Thermoelectric Energy Harvesting

A review on inorganic membranes for desalination and wastewater treatment

Extensive environmental pollution caused by worldwide industrialization and population growth has led to a water shortage. This problem lowers the quality of human life and wastes a large amount of money worldwide each year due to the related consequences. One main solution for this challenge is water purification. State-of-the-art water purification necessitates the implementation of novel materials and technologies that are cost and energy efficient. In this regard, graphene nanomaterials, with their unique physicochemical properties, are an optimum choice. These materials offer extraordinarily high surface area, mechanical durability, atomic thickness, nanosized pores and reactivity toward polar and non-polar water pollutants. These characteristics impart high selectivity and water permeability, and thus provide excellent water purification efficiency. This review introduces the potential of graphene membranes for water desalination. Although literature reviews have mostly concerned graphene’s capability for the adsorption and photocatalysis of water pollutants, updated knowledge related to its sieving properties is quite limited. Water desalination plants stand to markedly reduce their energy consumption once nanoporous graphene-based membranes are optimized. Purifying brackish water with reverse osmosis works most efficiently when membranes are as thin, selective and strong as possible. Mady Elbahri from Aalto University in Finland reviews efforts to achieve these goals using graphene monolayers perforated with nanoscale pores. Recent roll-to-roll fabrications of graphene onto polymer supports show that inexpensive, large-scale production of these ultrathin membranes is feasible. It remains challenging, however, to tailor the nanochannels and selectivity of single-atom-thick material. An alternative may be to switch to multilayered graphene oxide membranes. These substances can be engineered with different molecular cross-linking agents between each carbon layer, opening room to insert negatively charged functional groups that target and electrostatically repel sodium ions. Graphene nanomaterials hold great promise for the development of advanced water purification membranes, especially for water desalination. Their atomic thickness, extraordinary mechanical stability and potential for size-selective transport are ideal features, encouraging the membrane scientist across the world to investigate their applicability for water desalination. Graphene can potentially desalinate water either as monolayer or as multilayer membranes. In this review, we discuss these different classes of graphene membranes and highlight their merits and shortcomings. In addition, the theory behind their performance is presented in detail.

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Graphene membranes for water desalination

Recent advances in utilization of graphene for filtration and desalination of water: A review

The early detection and classification of dementia are important clinical support tasks for medical practitioners in customizing patient treatment programs to better manage the development and progression of these diseases. Efforts are being made to diagnose these neurodegenerative disorders in the early stages. Indeed, early diagnosis helps patients to obtain the maximum treatment benefit before significant mental decline occurs. The use of electroencephalogram as a tool for the detection of changes in brain activities and clinical diagnosis is becoming increasingly popular for its capabilities in quantifying changes in brain degeneration in dementia. This paper reviews the role of electroencephalogram as a biomarker based on signal processing to detect dementia in early stages and classify its severity. The review starts with a discussion of dementia types and cognitive spectrum followed by the presentation of the effective preprocessing denoising to eliminate possible artifacts. It continues with a description of feature extraction by using linear and nonlinear techniques, and it ends with a brief explanation of vast variety of separation techniques to classify EEG signals. This paper also provides an idea from the most popular studies that may help in diagnosing dementia in early stages and classifying through electroencephalogram signal processing and analysis.

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Role of EEG as Biomarker in the Early Detection and Classification of Dementia

This paper focuses on the recent advances on radiolysis-assisted shape-controlled synthesis of noble metal nanostructures. The techniques and protocols for producing desirable shapes of noble metal nanoparticles are discussed through introducing the critical parameters which can influence the nucleation and growth mechanisms. Nucleation rate plays a vital role on the crystallinity of seeds while growth rate of different seeds’ facets determines the final shape of resultant nanoparticles. Nucleation and growth rate both can be altered with factors such as absorbed dose, capping agents, and experimental environment condition to control the final shape. Remarkable physical and chemical properties of synthesized noble metal nanoparticles by controlled morphology have been systematically evaluated to fully explore their applications.

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Recent Advances in Shape-Controlled Synthesis of Noble Metal Nanoparticles by Radiolysis Route

The aim of this pilot study was to select the most similar mother wavelet function and the most efficient threshold in order to use with wavelet basis function for the human brain electrical activity during working memory task. A 60 seconds was recorded from the scalp using the Electroencephalography (EEG). 19 electrodes were placed over different sites on the scalp where analyzed for one control subject and one post-stroke patients in the first week of his stroke onset. In this study, forty-five mother wavelet basis functions from orthogonal families with four thresholding methods were used. The selection of mother wavelet functions like Daubechies (db), symlet (sym) and coiflet (coif) and the thresholding methods these are sqtwolog, rigrsure, heursure and minimax are to check mother wavelet functions similarity with the recorded EEG signals during working memory task. The test have been done using four evaluating criteria, namely signal to noise ratio (SNR), peak signal to noise ratio (PSNR) mean square error (MSE) and crosscorelation method (xcorr). Symlet mother wavelet of order 9 (sym9) is the most compatible for all the 19 channels for both EEG datasets that selected to be examined and the best results have been obtained by using the rigrsure thresholding method.

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Selection of mother wavelets thresholding methods in denoising multi-channel EEG signals during working memory task

In this work mass loading sensitivity of a Sezawa wave mode based surface acoustic wave (SAW) device is investigated through finite element method (FEM) simulation and the prospects of these devices to function as highly sensitive SAW sensors is reported. A ZnO/Si layered SAW resonator is considered for the simulation study. Initially the occurrence of Sezawa wave mode and displacement amplitude of the Rayleigh and Sezawa wave mode is studied for lower ZnO film thickness. Further, a thin film made of an arbitrary material is coated over the ZnO surface and the resonance frequency shift caused by mass loading of the film is estimated. It was observed that Sezawa wave mode shows significant sensitivity to change in mass loading and has higher sensitivity (eight times higher) than Rayleigh wave mode for the same device configuration. Further, the mass loading sensitivity was observed to be greater for a low ZnO film thickness to wavelength ratio. Accordingly, highly sensitive SAW sensors can be developed by coating a sensing medium over a layered SAW device and operating at Sezawa mode resonance frequency. The sensitivity can be increased by tuning the ZnO film thickness to wavelength ratio.

https://www.mdpi.com/1424-8220/13/2/2164/pdf

Md. Shabiul Islam

Papers

Recent advances in utilization of graphene for filtration and desalination of water: A review

Role of EEG as Biomarker in the Early Detection and Classification of Dementia

Recent Advances in Shape-Controlled Synthesis of Noble Metal Nanoparticles by Radiolysis Route

Selection of mother wavelets thresholding methods in denoising multi-channel EEG signals during working memory task

Investigation into Mass Loading Sensitivity of Sezawa Wave Mode-Based Surface Acoustic Wave Sensors