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This Special Issue covers solution synthesis, processing, and applications of non-metallic nanomaterials. Zhang et. al. and Jiang et. al. focus on synthesis of kesterite materials, and Wu et. al. and Zhang et. al. focus on synthesis of copper chromium oxide delafossite nanomaterials. Three of these papers discuss solar cell applications using these materials. Yun and Park’s review paper explores the self-assembly of complex nanostructures. Bhalothia et al. show enhanced catalytic activity for NiOx@Pt nanostructures and Wu et. al. report high-sensitivity ammonia sensors made from SnO nanoshells. On flexible electronics, Nakamura et. al. developed Cu nitride ink for rapid photonic processing of conducting lines, Liu et. al. made Au/HfO2/Pt resistive random access memory devices, and Moreira et al. fabricated solution combustion oxide thin film transistors.

Research & information: general --- copper --- copper nitride --- photo sintering --- ink --- paste --- printed electronics --- post-processing --- Cu2ZnSnS4 solar cell --- ball milling --- nano-ink --- annealing --- tin monoxide --- nanoshell --- ammonia sensor --- solution method --- CMZTSSe films --- sol–gel --- electrical properties --- optical properties --- selenization treatment --- solar cells --- oxygen reduction reaction --- nanocatalysts --- carbon nanotube --- wet-chemical reduction method --- Au-clusters --- mass activity --- resistance switching --- high/low resistance --- oxygen defect --- conduction mechanism --- BNSL --- superlattice --- self-assembly --- colloidal nanocrystal --- binary nanocrystal superlattice --- electrospinning --- CuCrO2 --- hollow nanotube --- Al2O3 template --- one-dimensional structures --- IGZO composition --- solution combustion synthesis --- transparent amorphous semiconductor oxides --- low voltage operation --- Mg doped CuCrO2 --- hole transport layer --- organic solar cells --- perovskite solar cells --- n/a --- sol-gel

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Artificial neural networks (ANNs) and evolutionary computation methods have been successfully applied in remote sensing applications since they offer unique advantages for the analysis of remotely-sensed images. ANNs are effective in finding underlying relationships and structures within multidimensional datasets. Thanks to new sensors, we have images with more spectral bands at higher spatial resolutions, which clearly recall big data problems. For this purpose, evolutionary algorithms become the best solution for analysis. This book includes eleven high-quality papers, selected after a careful reviewing process, addressing current remote sensing problems. In the chapters of the book, superstructural optimization was suggested for the optimal design of feedforward neural networks, CNN networks were deployed for a nanosatellite payload to select images eligible for transmission to ground, a new weight feature value convolutional neural network (WFCNN) was applied for fine remote sensing image segmentation and extracting improved land-use information, mask regional-convolutional neural networks (Mask R-CNN) was employed for extracting valley fill faces, state-of-the-art convolutional neural network (CNN)-based object detection models were applied to automatically detect airplanes and ships in VHR satellite images, a coarse-to-fine detection strategy was employed to detect ships at different sizes, and a deep quadruplet network (DQN) was proposed for hyperspectral image classification.

Research & information: general --- convolutional neural network --- image segmentation --- multi-scale feature fusion --- semantic features --- Gaofen 6 --- aerial images --- land-use --- Tai’an --- convolutional neural networks (CNNs) --- feature fusion --- ship detection --- optical remote sensing images --- end-to-end detection --- transfer learning --- remote sensing --- single shot multi-box detector (SSD) --- You Look Only Once-v3 (YOLO-v3) --- Faster RCNN --- statistical features --- Gaofen-2 imagery --- winter wheat --- post-processing --- spatial distribution --- Feicheng --- China --- light detection and ranging --- LiDAR --- deep learning --- convolutional neural networks --- CNNs --- mask regional-convolutional neural networks --- mask R-CNN --- digital terrain analysis --- resource extraction --- hyperspectral image classification --- few-shot learning --- quadruplet loss --- dense network --- dilated convolutional network --- artificial neural networks --- classification --- superstructure optimization --- mixed-inter nonlinear programming --- hyperspectral images --- super-resolution --- SRGAN --- model generalization --- image downscaling --- mixed forest --- multi-label segmentation --- semantic segmentation --- unmanned aerial vehicles --- classification ensemble --- machine learning --- Sentinel-2 --- geographic information system (GIS) --- earth observation --- on-board --- microsat --- mission --- nanosat --- AI on the edge --- CNN

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Open data and policy implications coming from data-aware planning entail collection and pre- and postprocessing as operations of primary interest. Before these steps, making data available to people and their decision-makers is a crucial point. Referring to the relationship between data and energy, public administrations, governments, and research bodies are promoting the construction of reliable and robust datasets to pursue policies coherent with the Sustainable Development Goals, as well as to allow citizens to make informed choices. Energy engineers and planners must provide the simplest and most robust tools to collect, process, and analyze data in order to offer solid data-based evidence for future projections in building, district, and regional systems planning. This Special Issue aims at providing the state-of-the-art on open-energy data analytics; its availability in the different contexts, i.e., country peculiarities; and its availability at different scales, i.e., building, district, and regional for data-aware planning and policy-making. For all the aforementioned reasons, we encourage researchers to share their original works on the field of open data and energy analytics. Topics of primary interest include but are not limited to the following: 1. Open data and energy sustainability; 2. Open data science and energy planning; 3. Open science and open governance for sustainable development goals; 4. Key performance indicators of data-aware energy modelling, planning, and policy; 5. Energy, water, and sustainability database for building, district, and regional systems; 6. Best practices and case studies.

Research & information: general --- data envelopment analysis --- Kohonen self-organizing maps --- factor analysis --- multiple regression --- energy efficiency --- social media --- energy-consuming activities --- energy consumption --- machine learning --- ontology --- energy performance certificate --- heating energy demand --- buildings --- data mining --- classification --- regression --- decision tree --- support vector machine --- random forest --- artificial neural network --- open data --- electrification modelling --- Malawi --- OnSSET --- MESSAGEix --- reproducibility --- collaborative work --- open modelling and data --- data-handling --- integrated assessment modelling --- data pre- and post-processing --- space heating --- domestic hot water --- market assessment --- EU28 --- district heating --- data analytics --- big data --- forecasting --- energy --- polygeneration --- clustering --- kNN --- pattern recognition --- heating --- building stock --- heat map --- spatial analysis --- heat density map --- building performance simulation --- parametric modelling --- energy management --- model calibration --- Passive House --- energy planning --- energy potential mapping --- urban energy atlas --- urban energy transition --- energy data --- data-aware planning --- spatial planning --- open data analytics --- smart cities --- open energy governance --- urban database --- energy mapping --- building dataset --- energy modelling

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Additive Manufacturing (AM), more popularly known as 3D printing, is transforming the industry. AM of metal components with virtually no geometric limitations has enabled new product design options and opportunities, increased product performance, shorter cycle time in part production, total cost reduction, shortened lead time, improved material efficiency, more sustainable products and processes, full circularity in the economy, and new revenue streams. This Special Issue of Metals gives an up-to-date account of the state of the art in AM.

Technology: general issues --- additive manufacturing --- support structures --- electron beam melting --- support structure removability --- biological origin hydroxyapatite --- bioactive layers --- cranial mesh implants --- selective laser melting --- 3D printing --- radio-frequency magnetron sputtering --- powder bed fusion --- single crystal --- grain selection --- cavity resonators --- filters --- microwave --- plating --- stereolithography --- thermal expansion --- three-dimensional printing --- directed energy deposition --- EN AW-7075 --- porosity --- ultimate tensile strength --- wire arc additive manufacturing --- WAAM --- microstructure --- magnesium --- mechanical properties --- scanning electron microscopy --- electron backscattered diffraction method --- direct energy deposition --- cold metal transfer --- 5356-aluminum --- temperature distribution --- metal powder bed fusion --- Ti–6Al–4V --- residual stresses --- heat treatments --- electron beam melting (EBM) --- process window --- stainless steel --- 316LN --- powder methods --- additive manufacturing (AM) --- post-processing --- 316L stainless-steel --- electron microscopy --- rapid tooling --- laser-based powder bed fusion (L-PBF) --- production tools --- cold working --- hot working --- injection molding --- n/a --- Ti-6Al-4V

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Open data and policy implications coming from data-aware planning entail collection and pre- and postprocessing as operations of primary interest. Before these steps, making data available to people and their decision-makers is a crucial point. Referring to the relationship between data and energy, public administrations, governments, and research bodies are promoting the construction of reliable and robust datasets to pursue policies coherent with the Sustainable Development Goals, as well as to allow citizens to make informed choices. Energy engineers and planners must provide the simplest and most robust tools to collect, process, and analyze data in order to offer solid data-based evidence for future projections in building, district, and regional systems planning. This Special Issue aims at providing the state-of-the-art on open-energy data analytics; its availability in the different contexts, i.e., country peculiarities; and its availability at different scales, i.e., building, district, and regional for data-aware planning and policy-making. For all the aforementioned reasons, we encourage researchers to share their original works on the field of open data and energy analytics. Topics of primary interest include but are not limited to the following: 1. Open data and energy sustainability; 2. Open data science and energy planning; 3. Open science and open governance for sustainable development goals; 4. Key performance indicators of data-aware energy modelling, planning, and policy; 5. Energy, water, and sustainability database for building, district, and regional systems; 6. Best practices and case studies.

Research & information: general --- data envelopment analysis --- Kohonen self-organizing maps --- factor analysis --- multiple regression --- energy efficiency --- social media --- energy-consuming activities --- energy consumption --- machine learning --- ontology --- energy performance certificate --- heating energy demand --- buildings --- data mining --- classification --- regression --- decision tree --- support vector machine --- random forest --- artificial neural network --- open data --- electrification modelling --- Malawi --- OnSSET --- MESSAGEix --- reproducibility --- collaborative work --- open modelling and data --- data-handling --- integrated assessment modelling --- data pre- and post-processing --- space heating --- domestic hot water --- market assessment --- EU28 --- district heating --- data analytics --- big data --- forecasting --- energy --- polygeneration --- clustering --- kNN --- pattern recognition --- heating --- building stock --- heat map --- spatial analysis --- heat density map --- building performance simulation --- parametric modelling --- energy management --- model calibration --- Passive House --- energy planning --- energy potential mapping --- urban energy atlas --- urban energy transition --- energy data --- data-aware planning --- spatial planning --- open data analytics --- smart cities --- open energy governance --- urban database --- energy mapping --- building dataset --- energy modelling