The ubiquitous function of nitric oxide (NO) guided the biological discovery of the natural dinitrosyliron unit (DNIU) [Fe-(NO) 2 ] as an intermediate/end product after Fe nitrosylation of nonheme cofactors. Because of the natural utilization of this cofactor for the biological storage and delivery of NO, a bioinorganic study of synthetic dinitrosyliron complexes (DNICs) has been extensively explored in the last 2 decades. The bioinorganic study of DNICs involved the development of synthetic methodology, spectroscopic discrimination, biological application of NO-delivery reactivity, and translational application to the (catalytic) transformation of small molecules. In this Forum Article, we aim to provide a systematic review of spectroscopic and computational insights into the bonding nature within the DNIU [Fe(NO) 2 ] and the electronic structure of different types of DNICs, which highlights the synchronized advance in synthetic methodology and spectroscopic tools. With regard to the noninnocent nature of a NO ligand, spectroscopic and computational tools were utilized to provide qualitative/quantitative assignment of oxidation states of Fe and NO in DNICs with different redox levels and ligation modes as well as to probe the Fe−NO bonding interaction modulated by supporting ligands. Besides the strong antiferromagnetic coupling between high-spin Fe and paramagnetic NO ligands within the covalent DNIU [Fe(NO) 2 ], in polynuclear DNICs, the effects of the Fe•••Fe distance, nature of the bridging ligands, and type of bridging modes on the regulation of the magnetic coupling among paramagnetic DNIU [Fe(NO) 2 ] are further reviewed. In the last part of this Forum Article, the sequential reaction of {Fe(NO) 2 } 10 DNIC [(NO) 2 Fe(AMP)] (1-red) with NO (g) , HBF 4 , and KC 8 establishes a synthetic cycle, {Fe(NO) 2 } 9 -{Fe(NO) 2 } 9 DNIC [(NO) 2 Fe(μ-dAMP) 2 Fe(NO) 2 ] (1) → {Fe(NO) 2 } 9 DNIC [(NO 2 )Fe(AMP)][BF 4 ] (1-H) → {Fe(NO) 2 } 10 DNIC 1-red → DNIC 1, for the transformation of NO into HNO/N 2 O. Of importance, the NO-induced transformation of {Fe(NO) 2 } 10 DNIC 1-red and [(NO) 2 Fe(DTA)] (2-red; DTA = diethylenetriamine) unravels a synthetic strategy for preparation of the {Fe(NO) 2 } 9 -{Fe(NO) 2 } 9 DNICs [(NO) 2 Fe(μ-NHR) 2 Fe(NO) 2 ] containing amido-bridging ligands, which hold the potential to feature distinctive physical properties, chemical reactivities, and biological applications.

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A new method using reinforcement learning for designing bioinspired composite materials is proposed. While bioinspired design of materials is a promising avenue, the possible combination of building blocks in a composite is usually intractable. In this work, a new method is proposed based on reinforcement learning applied as an autonomous agent for arranging the microstructure that is composed of brittle and soft material. The resolution of the design space is enhanced in a progressive fashion, reaching increasingly higher resolution. The results show that the resulting high-resolution designs can significantly reduce stress concentrations at crack tips and enhance mechanical resilience. Complementing the experimental results with manufactured optimal composites shows excellent agreement with the optimal results obtained using the AI method. The framework reported in this work may serve as an alternative to conventional composite optimization techniques, which often suffer from the curse of high dimensionality and are also unable to effectively predict high-resolution designs, due to limitations of the algorithms to escape low-resolution local minima. The new approach discussed in this work can be widely applied in multiple areas of engineering and design, and the progressive multiresolution approach may also be critical for the de novo autonomous reinforcement engineering solutions.