High-resolution remote thermography using luminescent low-dimensional tin-halide perovskites

While metal-halide perovskites have recently revolutionized research in optoelectronics through a unique combination of performance and synthetic simplicity, their low-dimensional counterparts can further expand the field with hitherto unknown and practically useful optical functionalities. In this context, we present the strong temperature dependence of the photoluminescence (PL) lifetime of low-dimensional, perovskite-like tin-halides, and apply this property to thermal imaging with a high precision of 0.05 {\deg}C. The PL lifetimes are governed by the heat-assisted de-trapping of self-trapped excitons, and their values can be varied over several orders of magnitude by adjusting the temperature (up to 20 ns {\deg}C-1). Typically, this sensitive range spans up to one hundred centigrade, and it is both compound-specific and shown to be compositionally and structurally tunable from -100 to 110 {\deg} C going from [C(NH2)3]2SnBr4 to Cs4SnBr6 and (C4N2H14I)4SnI6. Finally, through the innovative implementation of cost-effective hardware for fluorescence lifetime imaging (FLI), based on time-of-flight (ToF) technology, these novel thermoluminophores have been used to record thermographic videos with high spatial and thermal resolution.Comment: 25 pages, 4 figure

Spatiotemporal Mapping of Photocurrent in a Monolayer Semiconductor Using a Diamond Quantum Sensor

The detection of photocurrents is central to understanding and harnessing the interaction of light with matter. Although widely used, transport-based detection averages over spatial distributions and can suffer from low photocarrier collection efficiency. Here, we introduce a contact-free method to spatially resolve local photocurrent densities using a proximal quantum magnetometer. We interface monolayer MoS2 with a near-surface ensemble of nitrogen-vacancy centers in diamond and map the generated photothermal current distribution through its magnetic field profile. By synchronizing the photoexcitation with dynamical decoupling of the sensor spin, we extend the sensor's quantum coherence and achieve sensitivities to alternating current densities as small as 20 nA per micron. Our spatiotemporal measurements reveal that the photocurrent circulates as vortices, manifesting the Nernst effect, and rises with a timescale indicative of the system's thermal properties. Our method establishes an unprecedented probe for optoelectronic phenomena, ideally suited to the emerging class of two-dimensional materials, and stimulates applications towards large-area photodetectors and stick-on sources of magnetic fields for quantum control.Comment: 19 pages, 4 figure

Review on carbon-derived, solid-state, micro and nano sensors for electrochemical sensing applications

The aim of this review is to summarize the most relevant contributions in the development of electrochemical sensors based on carbon materials in the recent years. There have been increasing numbers of reports on the first application of carbon derived materials for the preparation of an electrochemical sensor. These include carbon nanotubes, diamond like carbon films and diamond film-based sensors demonstrating that the particular structure of these carbon material and their unique properties make them a very attractive material for the design of electrochemical biosensors and gas sensors. Carbon nanotubes (CNT) have become one of the most extensively studied nanostructures because of their unique properties. CNT can enhance the electrochemical reactivity of important biomolecules and can promote the electron-transfer reactions of proteins (including those where the redox center is embedded deep within the glycoprotein shell). In addition to enhanced electrochemical reactivity, CNT-modified electrodes have been shown useful to be coated with biomolecules (e.g., nucleic acids) and to alleviate surface fouling effects (such as those involved in the NADH oxidation process). The remarkable sensitivity of CNT conductivity with the surface adsorbates permits the use of CNT as highly sensitive nanoscale sensors. These properties make CNT extremely attractive for a wide range of electrochemical sensors ranging from amperometric enzyme electrodes to DNA hybridization biosensors. Recently, a CNT sensor based fast diagnosis method using non-treated blood assay has been developed for specific detection of hepatitis B virus (HBV) (human liver diseases, such as chronic hepatitis, cirrhosis, and hepatocellular carcinoma caused by hepatitis B virus). The linear detection limits for HBV plasma is in the range 0.5–3.0 μL−1 and for anti- HBVs 0.035–0.242 mg/mL in a 0.1 M NH4H2PO4 electrolyte solution. These detection limits enables early detection of HBV infection in suspected serum samples. Therefore, non-treated blood serum can be directly applied for real-time sensitive detection in medical diagnosis as well as in direct in vivo monitoring. Synthetic diamond has been recognized as an extremely attractive material for both (bio-) chemical sensing and as an interface to biological systems. Synthetic diamond have outstanding electrochemical properties, superior chemical inertness and biocompatibility. Recent advances in the synthesis of highly conducting nanocrystalline-diamond thin films and nano wires have lead to an entirely new class of electrochemical biosensors and bio-inorganic interfaces. In addition, it also combines with development of new chemical approaches to covalently attach biomolecules on the diamond surface also contributed to the advancement of diamond-based biosensors. The feasibility of a capacitive field-effect EDIS (electrolyte-diamond-insulatorsemiconductor) platform for multi-parameter sensing is demonstrated with an O-terminated nanocrystalline-diamond (NCD) film as transducer material for the detection of pH and penicillin concentration. This has also been extended for the label-free electrical monitoring of adsorption and binding of charged macromolecules. One more recent study demonstrated a novel bio-sensing platform, which is introduced by combination of a) geometrically controlled DNA bonding using vertically aligned diamond nano-wires and b) the superior electrochemical sensing properties of diamond as transducer material. Diamond nanowires can be a new approach towards next generation electrochemical gene sensor platforms. This review highlights the advantages of these carbon materials to promote different electron transfer reactions specially those related to biomolecules. Different strategies have been applied for constructing carbon material-based electrochemical sensors, their analytical performance and future prospects are discussed

Simulation of site-specific irrigation control strategies with sparse input data

Crop and irrigation water use efficiencies may be improved by managing irrigation application timing and volumes using physical and agronomic principles. However, the crop water requirement may be spatially variable due to different soil properties and genetic variations in the crop across the field. Adaptive control strategies can be used to locally control water applications in response to in-field temporal and spatial variability with the aim of maximising both crop development and water use efficiency. A simulation framework ‘VARIwise’ has been created to aid the development, evaluation and management of spatially and temporally varied adaptive irrigation control strategies (McCarthy et al., 2010). VARIwise enables alternative control strategies to be simulated with different crop and environmental conditions and at a range of spatial resolutions. An iterative learning controller and model predictive controller have been implemented in VARIwise to improve the irrigation of cotton. The iterative learning control strategy involves using the soil moisture response to the previous irrigation volume to adjust the applied irrigation volume applied at the next irrigation event. For field implementation this controller has low data requirements as only soil moisture data is required after each irrigation event. In contrast, a model predictive controller has high data requirements as measured soil and plant data are required at a high spatial resolution in a field implementation. Model predictive control involves using a calibrated model to determine the irrigation application and/or timing which results in the highest predicted yield or water use efficiency. The implementation of these strategies is described and a case study is presented to demonstrate the operation of the strategies with various levels of data availability. It is concluded that in situations of sparse data, the iterative learning controller performs significantly better than a model predictive controller

Air pollution and livestock production

The air in a livestock farming environment contains high concentrations of dust particles and gaseous pollutants. The total inhalable dust can enter the nose and mouth during normal breathing and the thoracic dust can reach into the lungs. However, it is the respirable dust particles that can penetrate further into the gas-exchange region, making it the most hazardous dust component. Prolonged exposure to high concentrations of dust particles can lead to respiratory health issues for both livestock and farming staff. Ammonia, an example of a gaseous pollutant, is derived from the decomposition of nitrous compounds. Increased exposure to ammonia may also have an effect on the health of humans and livestock. There are a number of technologies available to ensure exposure to these pollutants is minimised. Through proactive means, (the optimal design and management of livestock buildings) air quality can be improved to reduce the likelihood of risks associated with sub-optimal air quality. Once air problems have taken hold, other reduction methods need to be applied utilising a more reactive approach. A key requirement for the control of concentration and exposure of airborne pollutants to an acceptable level is to be able to conduct real-time measurements of these pollutants. This paper provides a review of airborne pollution including methods to both measure and control the concentration of pollutants in livestock buildings

A review of mechanoluminescence in inorganic solids : compounds, mechanisms, models and applications

Mechanoluminescence (ML) is the non-thermal emission of light as a response to mechanical stimuli on a solid material. While this phenomenon has been observed for a long time when breaking certain materials, it is now being extensively explored, especially since the discovery of non-destructive ML upon elastic deformation. A great number of materials have already been identified as mechanoluminescent, but novel ones with colour tunability and improved sensitivity are still urgently needed. The physical origin of the phenomenon, which mainly involves the release of trapped carriers at defects with the help of stress, still remains unclear. This in turn hinders a deeper research, either theoretically or application oriented. In this review paper, we have tabulated the known ML compounds according to their structure prototypes based on the connectivity of anion polyhedra, highlighting structural features, such as framework distortion, layered structure, elastic anisotropy and microstructures, which are very relevant to the ML process. We then review the various proposed mechanisms and corresponding mathematical models. We comment on their contribution to a clearer understanding of the ML phenomenon and on the derived guidelines for improving properties of ML phosphors. Proven and potential applications of ML in various fields, such as stress field sensing, light sources, and sensing electric (magnetic) fields, are summarized. Finally, we point out the challenges and future directions in this active and emerging field of luminescence research

Scalable processing and integration of 2D materials and devices

Due to its truly two dimensional (2D) character and its particular lattice, single layer graphene (SLG) possesses exceptional properties: it is semimetallic, transparent, strong yet flexible... Complementary features such as the insulating character of hexagonal boron nitride (h-BN) and semiconducting properties of transition metal dichalcogenides (TMDs) enable the whole spectrum of electronic devices to be built with combinations of these 2D materials. Due to this and the ease of exfoliation with a sticky tape, a vast amount of research was sparked. The mechanical exfoliation method, however, is only suitable for novel or proof-of-concept devices. The trend nowadays in electronics is towards transparent, lightweight, flexible, embedded smart devices and sensors in everyday objects such as windows and mirrors, garments, windshields, car seats, parachutes...These demands are already met inherently by these new materials, thus the challenges remaining are within their synthesis, deposition and processing, where more scalable ways of production and device fabrication need to be developed. This thesis explores innovative approaches using established techniques that aim to bridge the gap between proof-of-concept devices and real applications of 2D materials in future commercial level technologies. Methods to create graphene and engineer its properties are employed with a special focus on scalability and adaptability towards the industry. These graphene materials have been processed using pioneering schemes to create different optoelectronic devices and sensors. The techniques employed here for synthesis, transfer and deposition, device processing and characterization of graphene and derivatives, are suitable for their use in large manufacturing and mass-production. Depending on the application envisaged, different materials are used and optimize in order to balance good performance, cost-effectiveness and suitability/scalability of the process for the specific target the device was designed for