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A detailed study of the two-dimensional (2-D) Hofmann-like framework [Fe(furpy)

The use of an angular ligand drives the formation of an irregular Hofmann framework whereby 6-coordinate and rare 5-coordinate FeII species co-exist – the 6-coordinate species show a spin-crossover transition.

Nanoconfinement offers opportunities to tune physical properties of molecular entities by altering their assembled structures. This also applies to acene-based molecules with potentially rich π–π interactions. Unlike most of the previous cases with acene-based guests directly incorporated into hosts, we take a further step by oligomerizing a fluorescent anthryl monomer, 9-vinylanthracene, inside nanochannels of a metal–organic framework, which is a pillared three-dimensional kagome net of [Zn2(bdc)2(dabco)] (bdc2– = 1,4-benzenedicarboxylate; dabco = 1,4-diazabicyclo[2.2.2]octane). The fluorescence emission of the guest can be significantly enhanced after oligomerization, which is likely due to the suppressed nonemissive interaction between the oligomerized molecules in the nanospace and the MOF wall. The case we have demonstrated for fluorescence enhancement via confined oligomerization provides inspiration for the design of luminescent composites and is encouraging for further exploration of molecules in a nanoconfined space.

Two analogous 2-D Hofmann-type frameworks, which incorporate the novel ligand N-(pyridin-4-yl)benzamide (benpy) [FeII(benpy)2M(CN)4]·2H2O (M = Pd (Pd(benpy)) and Pt (Pt(benpy))) are reported. The benpy ligand was explored to facilitate spin-crossover (SCO) cooperativity via amide group hydrogen bonding. Structural analyses of the 2-D Hofmann frameworks revealed benpy-guest hydrogen bonding and benpy-benpy aromatic contacts. Both analogues exhibited single-step hysteretic spin-crossover (SCO) transitions, with the metal-cyanide linker (M = Pd or Pt) impacting the SCO spin-state transition temperature and hysteresis loop width (Pd(benpy): T½↓↑: 201, 218 K, ∆T: 17 K and Pt(benpy): T½↓↑: 206, 226 K, ∆T: 20 K). The parallel structural and SCO changes over the high-spin to low-spin transition were investigated using variable-temperature, single-crystal, and powder X-ray diffraction, Raman spectroscopy, and differential scanning calorimetry. These studies indicated that the ligand–guest interactions facilitated by the amide group acted to support the cooperative spin-state transitions displayed by these two Hofmann-type frameworks, providing further insight into cooperativity and structure–property relationships.

Foremost, practical applications of spin-crossover (SCO) materials require control of the nature of the spin-state coupling. In existing SCO materials, there is a single, well-defined dimensionality relevant to the switching behavior. A new material, consisting of 1,2,4-triazole-based trimers coordinated into 1D chains by [Au(CN)] and spaced by anions and exchangeable guests, underwent SCO defined by elastic coupling across multiple dimensional hierarchies. Detailed structural, vibrational, and theoretical studies conclusively confirmed that intra-trimer coupling was an order of magnitude greater than the intramolecular coupling, which was an order of magnitude greater than intermolecular coupling. As such, a clear hierarchy on the nature of elastic coupling in SCO materials was ascertained for the first time, which is a necessary step for the technological development of molecular switching materials.

A 3-D FeII Hofmann-type framework material has been prepared which contains a three-connecting pyridyl-donor ligand with amide functionality and [Au(CN)2]- metallo-ligands. The FeII sites display a rare FeII(py)3(N[triple bond, length as m-dash]C)3 coordination environment, which we show for the first time to be conducive to spin crossover (SCO).

Alkaline electrolyzed water, a kind of clean green water with excellent characteristics such as high activity, strong alkalinity, high ion penetrating ability, electrical charge, and good molecule adsorption, was significant to the resource utilization of industrial fly ash waste. This paper studies highly active potassium-based alkaline electrolyzed water’s impact, compared with ordinary water, on the cement hydration process using microstructural methods such as a hydration heat test, differential thermal analysis, X-ray diffraction (XRD) pattern, and Scanning electron microscope (SEM) image analysis. Fly ash cement-based materials were first prepared with alkaline electrolyzed water as the mixing water. The alkaline electrolyzed water’s influence on fly ash paste workability and the mechanical properties of fly ash mortar for varying fly ash proportions were ratified. Then alkaline electrolyzed water with the best pH value was selected to prepare fly ash concrete, and its durability was studied. The test results showed that it is feasible to increase the utilization rate of fly ash by using alkaline electrolyzed water. Furthermore, it promoted the process of cement hydration, increased the rate of the hydration reaction, and the promotion effect increased with the increase in pH value of the alkaline electrolyzed water, and also promoted the effective decomposition of the vitreous shell of fly ash to stimulate its early activity. Concurrent tests with ordinary water paste showed that the water requirement for normal consistency and setting time with alkaline electrolyzed water paste were significantly less. Alkaline electrolyzed water also solved the problem related to the low early strength of fly ash mortar. Furthermore, using alkaline electrolyzed water with an optimum pH value of 11.5 to prepare fly ash concrete effectively reduced concrete’s carbonation depth and carbonation rate and lessened the chloride ion migration coefficient.

Foremost, practical applications of spin-crossover (SCO) materials require control of the nature of the spin-state coupling. In existing SCO materials, there is a single, well-defined dimensionality relevant to the switching behavior. A new material, consisting of 1,2,4-triazole-based trimers coordinated into 1D chains by [Au(CN)

A 3-D FeII Hofmann-type framework material has been prepared which contains a three-connecting pyridyl-donor ligand with amide functionality and [Au(CN)2]- metallo-ligands. The FeII sites display a rare FeII(py)3(N[triple bond, length as m-dash]C)3 coordination environment, which we show for the first time to be conducive to spin crossover (SCO).

Wildfires are one of the major serious disasters all over the world. The technology of satellite remote sensing provides useful data for post-fire assessment. This study aimed to investigate the optimal spectral indices for mapping post-fire-burned area. We acquired the post-fire data of Moderate Resolution Imaging Spectroradiometer (MODIS) sensor over several wildfires in boreal forest in western America, 2016. Then, we adopted empirical formula and multi-threshold method to extract the sample sets of five types (burned area, vegetation, cloud, bare soil, and shadow). The separability of spectral indices between burned area and other four types was analyzed by separability index M. Based on the spectral characteristic analysis of burned area, the value of separability index M of the six spectral indices (VI, CSI, MIRBI, NBR, NSEv1, and NSTv1) is larger than 1.0, which indicates that these indices perform well in discriminating burned area and unburned types, and NIR (0.841–0.876 μm), SWIR (2.105–2.155 μm) spectral domain, emissivity of thermal infrared band and land surface temperature are also proved to be sensitive to burned area. The optimal spectral indices obtained in this paper can be integrated into the burned area detection algorithm in further research.

Since wildfires have occurred frequently in recent years, accurate burned area mapping is required for wildfire severity assessment and burned land reconstruction. Satellite remote sensing is an effective technology that can provide valuable information for wildfire assessment. However, the common approaches based on using a single satellite image to promptly detect the burned areas have low accuracy and limited applicability. This paper develops a new burned area mapping method that surpasses the detection accuracy of previous methods, while still using a single Moderate Resolution Imaging Spectroradiometer (MODIS) sensor image. The key innovation is integrating optimal spectral indices and a neural network algorithm. We used the traditional empirical formula method, multi-threshold method and visual interpretation method to extract the sample sets of five typical types (burned area, vegetation, cloud, bare soil, and cloud shadow) from the MODIS data of several wildfires in the American states of Nevada, Washington and California in 2016. Afterward, the separability index M was adopted to assess the capacity of seven spectral bands and 13 spectral indices to distinguish the burned area from four unburned land cover types. Based on the separability analysis between the burned area and unburned areas, the spectral indices with an M value higher than 1.0 were employed to generate the training sample sets that were assessed to have an overall accuracy of 98.68% and Kappa coefficient of 97.46%. Finally, we utilized a back-propagation neural network (BPNN) to learn the spectral differences of different types from the training sample sets and obtain the output burned area map. The proposed method was applied to three wildfire cases in the American states of Idaho, Nevada and Oregon in 2017. A comparison of detection results between the new MODIS-based burned area map and the reference burned area map compiled from Landsat-8 Operational Land Imager (OLI) data indicates that the proposed method can effectively exploit the spectral characteristics of various land cover types. Also, this new method can achieve higher accuracy with the reduction of commission error (CE, >10%) and omission error (OE, >6%) compared to the traditional empirical formula method. The new burned area mapping method could help managers and the public perform more effective wildfire assessments and emergency management.

Two of the main remote sensing data resources for forest fire detection have significant drawbacks: geostationary Earth Observation (EO) satellites have high temporal resolution but low spatial resolution, whereas Polar-orbiting systems have high spatial resolution but low temporal resolution. Therefore, the existing forest fire detection algorithms that are based on a single one of these two systems have only exploited temporal or spatial information independently. There are no approaches yet that have effectively merged spatial and temporal characteristics to detect forest fires. This paper fills this gap by presenting a spatiotemporal contextual model (STCM) that fully exploits geostationary data’s spatial and temporal dimensions based on the data from Himawari-8 Satellite. We used an improved robust fitting algorithm to model each pixel’s diurnal temperature cycles (DTC) in the middle and long infrared bands. For each pixel, a Kalman filter was used to blend the DTC to estimate the true background brightness temperature. Subsequently, we utilized the Otsu method to identify the fire after using an MVC (maximum value month composite of NDVI) threshold to test which areas have enough fuel to support such events. Finally, we used a continuous timeslot test to correct the fire detection results. The proposed algorithm was applied to four fire cases in East Asia and Australia in 2016. A comparison of detection results between MODIS Terra and Aqua active fire products (MOD14 and MYD14) demonstrated that the proposed algorithm from this paper effectively analyzed the spatiotemporal information contained in multi-temporal remotely sensed data. In addition, this new forest fire detection method can lead to higher detection accuracy than the traditional contextual and temporal algorithms. By developing algorithms that are based on AHI measurements to meet the requirement to detect forest fires promptly and accurately, this paper assists both emergency responders and the general public to mitigate the damage of forest fires.