Infrared nonlinear optical (IR-NLO) materials are the key components in solid-state lasers for military and civilian applications. The development of IR-NLO materials remains urgent because the existing commercial materials AgGaS2 (AGS), AgGaSe2, and ZnGeP2 are limited for their own intrinsic shortcomings, for example, the lower laser damage thresholds (LDTs), the non-phase-matchable feature, and the strong two-photon absorption, respectively, exhibited in AgGaSe2 and ZnGeP2 at a conventional laser of 1 μm. Chalcogenides, halides, and iodates are known to be common sources of potential IR-NLO materials with good properties, of which the most in-depth studied is usually constructed by single anions. Recently, mixed-anion inorganic compounds are thought to be promising IR-NLO materials which can optimize comprehensive performances, especially balance the incompatibility between a large NLO coefficient and a high LDT in one material. This review focuses on the syntheses and crystal structures of mixed-anion inorganic IR-NLO materials, as well as the relationships of structure–property. Examples include four kinds of such compounds, i.e., mixed-anion chalcogenides, mixed-anion halides, mixed-anion chalcohalides, and other miscellaneous mixed-anion compounds including adducts, oxychalcogenides, oxyhalides, iodate fluorides, selenite fluorides, and halide borates. This work gives some exploring directions for novel IR-NLO materials, including how to optimize the NLO performances of the existing materials, from the inferred structure–property relationships of the potential mixed-anion inorganic NLO compounds.

Shortfalls and mismatches between the supply and demand of ecosystem services (ES) can be detrimental to human wellbeing. Studies focused on these problems have increased in recent decades, but few have applied land use optimization to reduce such spatial mismatches. This study developed a methodology to identify ES mismatches and then use these mismatches as objectives for land use optimization. The methodology was applied to the Guangdong-Hong Kong-Macao “Greater Bay Area” (GBA), a megacity of over 70 million people and one of the world’s largest urban agglomerations. Considering the demand for a healthy and secure living environment among city-dwellers, we focused on three ES: heat mitigation, flood mitigation, and recreational services. The results showed large spatial heterogeneity in supply and demand for these three ES. However, compared to current conditions in the GBA, our model showed that optimized land use allocation could better match the supply and demand for heat mitigation (number of beneficiaries increased by 15%), flood mitigation (amount of population exposed to flood damage decreased by 37%), and recreation (number of beneficiaries increased by 14%). By integrating land use allocation and spatial mismatch analysis, this methodology provides a feasible way to align ES supply and demand to advance urban and regional sustainability.

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