Graphene and related two-dimensional materials provide an ideal platform for next generation disruptive technologies and applications. Exploiting these solution-processed two-dimensional materials in printing can accelerate this development by allowing additive patterning on both rigid and conformable substrates for flexible device design and large-scale, high-speed, cost-effective manufacturing. In this review, we summarise the current progress on ink formulation of two-dimensional materials and the printable applications enabled by them. We also present our perspectives on their research and technological future prospects.

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Functional inks and printing of two-dimensional materials.

Metal-oxide-semiconductor (MOS) based gas sensors have been considered a promising candidate for gas detection over the past few years. However, the sensing properties of MOS-based gas sensors also need to be further enhanced to satisfy the higher requirements for specific applications, such as medical diagnosis based on human breath, gas detection in harsh environments, etc. In these fields, excellent selectivity, low power consumption, a fast response/recovery rate, low humidity dependence and a low limit of detection concentration should be fulfilled simultaneously, which pose great challenges to the MOS-based gas sensors. Recently, in order to improve the sensing performances of MOS-based gas sensors, more and more researchers have carried out extensive research from theory to practice. For a similar purpose, on the basis of the whole fabrication process of gas sensors, this review gives a presentation of the important role of screening and the recent developments in high throughput screening. Subsequently, together with the sensing mechanism, the factors influencing the sensing properties of MOSs involved in material preparation processes were also discussed in detail. It was concluded that the sensing properties of MOSs not only depend on the morphological structure (particle size, morphology, pore size, etc.), but also rely on the defect structure and heterointerface structure (grain boundaries, heterointerfaces, defect concentrations, etc.). Therefore, the material-sensor integration was also introduced to maintain the structural stability in the sensor fabrication process, ensuring the sensing stability of MOS-based gas sensors. Finally, the perspectives of the MOS-based gas sensors in the aspects of fundamental research and the improvements in the sensing properties are pointed out.

Metal-oxide-semiconductor based gas sensors: screening, preparation, and integration

Terahertz (THz) science and technology have greatly progressed over the past two decades to a point where the THz region of the electromagnetic spectrum is now a mature research area with many fundamental and practical applications. Furthermore, THz imaging is positioned to play a key role in many industrial applications, as THz technology is steadily shifting from university-grade instrumentation to commercial systems. In this context, the objective of this review is to discuss recent advances in THz imaging with an emphasis on the modalities that could enable real-time high-resolution imaging. To this end, we first discuss several key imaging modalities developed over the years: THz transmission, reflection, and conductivity imaging; THz pulsed imaging; THz computed tomography; and THz near-field imaging. Then, we discuss several enabling technologies for real-time THz imaging within the time-domain spectroscopy paradigm: fast optical delay lines, photoconductive antenna arrays, and electro-optic sampling with cameras. Next, we discuss the advances in THz cameras, particularly THz thermal cameras and THz field-effect transistor cameras. Finally, we overview the most recent techniques that enable fast THz imaging with single-pixel detectors: mechanical beam-steering, compressive sensing, spectral encoding, and fast Fourier optics. We believe that this critical and comprehensive review of enabling hardware, instrumentation, algorithms, and potential applications in real-time high-resolution THz imaging can serve a diverse community of fundamental and applied scientists.

Toward real-time terahertz imaging

Due to its excellent performance, aerogel is considered to be an especially promising new material. Cellulose is a renewable and biodegradable natural polymer. Aerogel prepared using cellulose has the renewability, biocompatibility, and biodegradability of cellulose, while also having other advantages, such as low density, high porosity, and a large specific surface area. Thus, it can be applied for many purposes in the areas of adsorption and oil/water separation, thermal insulation, and biomedical applications, as well as many other fields. There are three types of cellulose aerogels: natural cellulose aerogels (nanocellulose aerogels and bacterial cellulose aerogels), regenerated cellulose aerogels, and aerogels made from cellulose derivatives. In this paper, more than 200 articles were reviewed to summarize the properties of these three types of cellulose aerogels, as well as the technologies used in their preparation, such as the sol–gel process and gel drying. In addition, the applications of different types of cellulose aerogels were also introduced.

Cellulose Aerogels: Synthesis, Applications, and Prospects.

Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions

There is sufficient evidence proving the impact that negative lifestyle choices have on people’s health and wellness. Changing unhealthy behaviours requires raising people’s self-awareness and also providing healthcare experts with a thorough and continuous description of the user’s conduct. Several monitoring techniques have been proposed in the past to track users’ behaviour; however, these approaches are either subjective and prone to misreporting, such as questionnaires, or only focus on a specific component of context, such as activity counters. This work presents an innovative multimodal context mining framework to inspect and infer human behaviour in a more holistic fashion. The proposed approach extends beyond the state-of-the-art, since it not only explores a sole type of context, but also combines diverse levels of context in an integral manner. Namely, low-level contexts, including activities, emotions and locations, are identified from heterogeneous sensory data through machine learning techniques. Low-level contexts are combined using ontological mechanisms to derive a more abstract representation of the user’s context, here referred to as high-level context. An initial implementation of the proposed framework supporting real-time context identification is also presented. The developed system is evaluated for various realistic scenarios making use of a novel multimodal context open dataset and data on-the-go, demonstrating prominent context-aware capabilities at both low and high levels.

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Human Behavior Analysis by Means of Multimodal Context Mining.

Customized wellness care is a progressing area to promote self-care management, utilizing the state of the art techniques and technologies to monitor user daily life activities. Mining Minds Platform is one such effort that lies in customized wellness care domain with objective to support personalized health and wellness. This paper focuses on the one year journey of Mining Minds, its evolution into different versions with the challenges and limitations faced while design and development of the platform. We developed two versions (MM V1.0 and MM V1.5) in the first year and are moving towards MM V2.0 in the next year. We will discuss about the experience of building the core technology in these versions on top of the defined service scenario of physical activities.

Wahajat Ali Khan

Papers

Human Behavior Analysis by Means of Multimodal Context Mining.

Mining minds: journey of evolutionary platform for ubiquitous wellness