Porous anodic aluminum oxide: anodization and templated synthesis of functional nanostructures.

The upcoming fifth generation (5G) of wireless networks is expected to lay a foundation of intelligent networks with the provision of some isolated artificial intelligence (AI) operations. However, fully intelligent network orchestration and management for providing innovative services will only be realized in Beyond 5G (B5G) networks. To this end, we envisage that the sixth generation (6G) of wireless networks will be driven by on-demand self-reconfiguration to ensure a many-fold increase in the network performance and service types. The increasingly stringent performance requirements of emerging networks may finally trigger the deployment of some interesting new technologies, such as large intelligent surfaces, electromagnetic–orbital angular momentum, visible light communications, and cell-free communications, to name a few. Our vision for 6G is a massively connected complex network capable of rapidly responding to the users’ service calls through real-time learning of the network state as described by the network edge (e.g., base-station locations and cache contents), air interface (e.g., radio spectrum and propagation channel), and the user-side (e.g., battery-life and locations). The multi-state, multi-dimensional nature of the network state, requiring the real-time knowledge, can be viewed as a quantum uncertainty problem. In this regard, the emerging paradigms of machine learning (ML), quantum computing (QC), and quantum ML (QML) and their synergies with communication networks can be considered as core 6G enablers. Considering these potentials, starting with the 5G target services and enabling technologies, we provide a comprehensive review of the related state of the art in the domains of ML (including deep learning), QC, and QML and identify their potential benefits, issues, and use cases for their applications in the B5G networks. Subsequently, we propose a novel QC-assisted and QML-based framework for 6G communication networks while articulating its challenges and potential enabling technologies at the network infrastructure, network edge, air interface, and user end. Finally, some promising future research directions for the quantum- and QML-assisted B5G networks are identified and discussed.

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Quantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future

Highly ordered nanostructures with tunable size, shape and properties : A new way to surface nano-patterning using ultra-thin alumina masks

Multifunctional nanoparticles: analytical prospects.

A new chemosensor RF1 that combines a ferrocene unit and a rhodamine block via the linkage of a carbohydrazone binding unit was designed and prepared for the highly selective detection of Hg2+ in natural water. This chemosensor displays great brightness and fluorescence enhancement following Hg2+ coordination within the limit of detection for Hg2+ at 1 parts per billion (ppb). The fluorescence intensities are nearly proportional to the amount of Hg2+ at the ppb level. It is capable of distinguishing between the safe and the toxic levels of inorganic mercury in drinking water. Hg2+-binding also arouses the absorption of the rhodamine moiety in RF1 significantly with the chromogenic detection limit for Hg2+ at 50 ppb. The conventional UV-vis spectroscopic method thus has the potential to provide the critical information about the mercury hazard assessment for industrial wastewater discharging. The obvious and characteristic color change of the titration solution from colorless to pink upon the addition of H...

Highly sensitive multiresponsive chemosensor for selective detection of Hg2+ in natural water and different monitoring environments.

A nanoporous alumina template made from a multilayer metal film structure has been developed that allows for the in situ removal of the electrically insulating alumina barrier layer, exposing a Pt electrode at the pore bases. This barrier-free nanoporous system is of great use for dc electrodeposition of a wide variety of materials in the alumina pores. This work in particular describes the development of a multilayer thin film precursor consisting of a Si substrate with thin Pt and Ti and a thicker Al layer in that order. After the Al is anodized, producing the porous alumina, the resulting TiO 2 is selectively removed at the base of the alumina pores exposing the Pt electrode. The metals in the precursor perform different roles in the fabrication and allow the alumina template to be fabricated directly on the final substrate with no film transfer technique involved. This allows Si to be used as the substrate, which could then include electronic circuitry. Several techniques are used to analyze the resulting template.

Nanoporous Alumina Template with In Situ Barrier Oxide Removal, Synthesized from a Multilayer Thin Film Precursor

As the term IoT is expanding there is a huge increase in the number of development boards being introduced in the market ranging in size from a quarter to a credit card. Apart from the major hardware manufacturers like Intel, IBM, Atmel, etc. many of these boards are also being produced by crowdfunded companies. Cost effectiveness, Power efficiency and Easy Deployment make these boards a suitable candidate for IoT applications. The aim and objective of this paper is to provide a comprehensive insight on the technical specifications of these boards which will enable developers, hobbyists and industry professionals to choose a board suitable for their application.

A review of low cost and power efficient development boards for IoT applications

State of the Art Routing Protocols in VANETs: A Review

Mobile ad hoc networks (MANETs) are self-organized networks without any fixed infrastructure. The topology changes are very frequent in MANETs due to nodes’ mobility. The topology maintenance creates an extra overhead, as the mobility information of a single node is shared with all nodes in the network. To address the topology maintenance overhead problem in MANETs, the researchers proposed different cluster-based algorithms to reduce the size of a routing table. The clusters are formed to locally adjust the topology changes within the cluster. If a node wants to communicate with a node outside the cluster, it only communicates with its cluster head (CH). The CH communicates with other CHs to transmit data toward the destination. To efficiently utilize the clustering mechanism in MANETs, stable and balanced clusters are required. To form good quality and optimized clusters, some metrics, such as relative mobility (node speed and direction), node degree, residual energy, communication workload, and neighbor’s behavior, are required. In this paper, we present a comprehensive survey of recent CAs in MANETs. We also present the objectives, goals, and contributions of recent research. Similarly, the findings, challenges, and future directions are stated. The validation of each proposed work is analyzed critically in terms of the mobility model, the simulation tool used during simulation, simulation metrics, and the performance metrics used in the validation process.

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Ataul Aziz Ikram

Papers

Nanoporous Alumina Template with In Situ Barrier Oxide Removal, Synthesized from a Multilayer Thin Film Precursor

A review of low cost and power efficient development boards for IoT applications

State of the Art Routing Protocols in VANETs: A Review

State-of-the-Art Clustering Schemes in Mobile Ad Hoc Networks: Objectives, Challenges, and Future Directions

SeqCompress: an algorithm for biological sequence compression.