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Rational design of high-performance stable metal–organic framework (MOF) membranes is challenging, especially for the sustainable treatment of hypersaline waters to address critical global environmental issues. Herein, a molecular-level intra-crystalline defect strategy combined with a selective layer thinning protocol is proposed to fabricate robust ultrathin missing-linker UiO-66 (ML-UiO-66) membrane to enable fast water permeation. Besides almost complete salt rejection, high and stable water flux is achieved even under long-term pervaporation operation in hash environments, which effectively addresses challenging stability issues. Then, detailed structural characterizations are employed to identify the type, chemical functionality, and density of intra-crystalline missing-linker defects. Moreover, molecular dynamics simulations shed light on the positive atomistic role of these defects, which are responsible for substantially enhancing structural hydrophilicity and enlarging pore window, consequently allowing ultra-fast water transport via a lower-energy-barrier pathway across three-dimensional sub-nanochannels during pervaporation. Unlike common unfavorable defect effects, the present positive intra-crystalline defect engineering concept at the molecular level is expected to pave a promising way toward not only rational design of next-generation MOF membranes with enhanced permeation performance, but additional water treatment applications. The development of highly water-permeable membranes is key for the treatment of high salinity waters. Here the authors enhance the water permeability of a metal-organic framework nanoporous membrane via an intra-crystalline defect engineering strategy.

The remarkable advantages of heterointerface and defect engineering and their unique electromagnetic characteristics inject infinite vitality into the design of advanced carbon-matrix electromagnetic wave absorbers. However, understanding the interface and dipole effects based on microscopic and macroscopic perspectives, rather than semi-empirical rules, can facilitate the design of heterointerfaces and defects to adjust the impedance matching and electromagnetic wave absorption of the material, which is currently lacking. Herein, CuCo 2 S 4 @Expanded Graphite heterostructure with multiple heterointerfaces and cation defects are reported, and the morphology, interfaces and defects of component are regulated by varying the concentration of metal ions. The results show that the 3D flower-honeycomb morphology, the crystal-crystal/amorphous heterointerfaces and the abundant cation defects can effectively adjust the conductive and polarization losses, achieve the impedance matching balance of carbon materials, and improve the absorption of electromagnetic wave. For the sample CEG-6, the effective absorption of Ku band with RL min of −72.28 dB and effective absorption bandwidth of 4.14 GHz is realized at 1.4 mm, while the filler loading is only 7.0 wt. %. This article reports on the establishment of potential relationship between crystal-crystal/amorphous heterointerfaces, cation defects, and the impedance matching of carbon materials. Heterointerface and defect promote the development of electromagnetic wave absorbers. Here, the authors show the 3D flower-honeycomb CuCo 2 S 4 @Expanded Graphite heterostructure, report the mechanism of crystal-crystal/amorphous heterointerfaces and cation defects on electromagnetic wave absorption.

With the high demand and sub-nanometer design for integrated circuits, surface defect complexity and frequency for semiconductor wafers have increased; subsequently emphasizing the need for highly accurate fault detection and root-cause analysis systems as manual defect diagnosis is more time-intensive, and expensive. As such, machine learning and deep learning methods have been integrated to automated inspection systems for wafer map defect recognition and classification to enhance performance, overall yield, and cost-efficiency. Concurrent with algorithm and hardware advances, in particular the onset of neural networks like the convolutional neural network, the literature for wafer map defect detection exploded with new developments to address the limitations of data preprocessing, feature representation and extraction, and model learning strategies. This article aims to provide a comprehensive review on the advancement of machine learning and deep learning applications for wafer map defect recognition and classification. The defect recognition and classification methods are introduced and analyzed for discussion on their respective advantages, limitations, and scalability. The future challenges and trends of wafer map detection research are also presented.

With the increasing circuit complexity of chip design, wafers are prone to defects in the production process. Since different defects have their causes, post-analysis is important to wafer production. However, the sample size is not balanced, and the effect of classical residual networks is limited. This article uses a Split-Attention network (ResNeSt) with which feature maps will be input into k-base groups, each consisting of r groups. Thanks to the large receptive field, image features can be obtained better. We add channel attention and give higher weight to the effective feature channels to improve network performance. Compared with the classical residual network, the new network has an improvement of 43.06%, 32.73%, and 10.86% in handling Scratch, Near-full, and Local defects, respectively.

Rational design of single atom catalyst is critical for efficient sustainable energy conversion. However, the atomic-level control of active sites is essential for electrocatalytic materials in alkaline electrolyte. Moreover, well-defined surface structures lead to in-depth understanding of catalytic mechanisms. Herein, we report a single-atomic-site ruthenium stabilized on defective nickel-iron layered double hydroxide nanosheets (Ru 1 /D-NiFe LDH). Under precise regulation of local coordination environments of catalytically active sites and the existence of the defects, Ru 1 /D-NiFe LDH delivers an ultralow overpotential of 18 mV at 10 mA cm −2 for hydrogen evolution reaction, surpassing the commercial Pt/C catalyst. Density functional theory calculations reveal that Ru 1 /D-NiFe LDH optimizes the adsorption energies of intermediates for hydrogen evolution reaction and promotes the O–O coupling at a Ru–O active site for oxygen evolution reaction. The Ru 1 /D-NiFe LDH as an ideal model reveals superior water splitting performance with potential for the development of promising water-alkali electrocatalysts. Rational design of single atom catalyst is critical for efficient sustainable energy conversion. Single-atomic-site ruthenium stabilized on defective nickel-iron layered double hydroxide nanosheets achieve superior HER and OER performance in alkaline media.

The size and defects in crystalline inorganic materials are of importance in many applications, particularly catalysis, as it often results in enhanced/emerging properties. So far, applying the strategy of modulation chemistry has been unable to afford high-quality functional Metal–Organic Frameworks (MOFs) nanocrystals with minimized size while exhibiting maximized defects. We report here a general sustainable strategy for the design of highly defective and ultra-small tetravalent MOFs (Zr, Hf) crystals (ca. 35% missing linker, 4–6 nm). Advanced characterizations have been performed to shed light on the main factors governing the crystallization mechanism and to identify the nature of the defects. The ultra-small nanoMOFs showed exceptional performance in peptide hydrolysis reaction, including high reactivity, selectivity, diffusion, stability, and show emerging tailorable reactivity and selectivity towards peptide bond formation simply by changing the reaction solvent. Therefore, these highly defective ultra-small M(IV)-MOFs particles open new perspectives for the development of heterogeneous MOF catalysts with dual functions. Crystalline materials’ properties are highly dependent on their size. Here authors report a general synthesis of ultrasmall (4–6 nm) and highly defective Zr/Hf-Metal Organic Frameworks nanoparticles that present enhanced peptide hydrolysis performance.

Molecular passivation is a prominent approach for improving the performance and operation stability of halide perovskite solar cells (HPSCs). Herein, we reveal discernible effects of diammonium molecules with either an aryl or alkyl core onto Methylammonium-free perovskites. Piperazine dihydriodide (PZDI), characterized by an alkyl core-electron cloud-rich-NH terminal, proves effective in mitigating surface and bulk defects and modifying surface chemistry or interfacial energy band, ultimately leading to improved carrier extraction. Benefiting from superior PZDI passivation, the device achieves an impressive efficiency of 23.17% (area ~1 cm 2 ) (low open circuit voltage deficit ~0.327 V) along with superior operational stability. We achieve a certified efficiency of ~21.47% (area ~1.024 cm 2 ) for inverted HPSC. PZDI strengthens adhesion to the perovskite via -NH 2 I and Mulliken charge distribution. Device analysis corroborates that stronger bonding interaction attenuates the defect densities and suppresses ion migration. This work underscores the crucial role of bifunctional molecules with stronger surface adsorption in defect mitigation, setting the stage for the design of charge-regulated molecular passivation to enhance the performance and stability of HPSC. Molecular passivation is promising for improving the performance and operation stability of perovskite solar cells. Here, authors employ piperazine dihydriodide to strengthen adhesion to MA-free perovskite via −NH 2 I and Mulliken charge distribution, realizing charge-regulated molecular passivation.

As the main limiting step of overall water splitting, oxygen evolution reaction (OER) is urgent to be enhanced by developing efficient catalysts to promote the process of electrolytic water. Based on theoretical analysis, the Ni-metal-organic framework (Ni-MOF) and NiFe-layered double hydroxide (NiFe-LDH) (NiFe-LDH/MOF) heterostructure can optimize the energy barrier of the OER process and decrease the adsorption energy of oxygen-containing intermediates, effectively accelerating the OER kinetics. Accordingly, layered NiFe-LDH/MOF heterostructures are in situ constructed through a facile two-step reaction process, with substantial oxygen defects and lattice defects that further improve the catalytic performance. As a result, only 208 and 275 mV OER overpotentials are needed for NiFe-LDH/MOF to drive the current densities of 20 and 100 mA·cm −2 in 1 M KOH solutions, and even maintain catalytic stability of 100 h at 20 mA·cm −2 . When applied to seawater oxidation, only 235 and 307 mV OER overpotentials are required to achieve the current densities of 20 and 100 mA·cm −2 , respectively, with almost no attenuation for 100 h stability test at 20 mA·cm −2 , all better than commercial RuO 2 . This work provides the theoretical and experimental basis and a new idea for efficiently driving fresh water and seawater cracking by heterostructure and defect coupling design toward catalysts.

Understanding how the bulk structure of a material affects catalysis on its surface is critical to the development of actionable catalyst design principles. Bulk defects have been shown to affect electrocatalytic materials that are important for energy conversion systems, but the structural origins of these effects have not been fully elucidated. Here we use a combination of high-resolution scanning electrochemical cell microscopy and electron backscatter diffraction to visualize the potential-dependent electrocatalytic carbon dioxide ( C O 2 ) electroreduction and hydrogen ( H 2 ) evolution activity on Au electrodes and probe the effects of bulk defects. Comparing colocated activity maps and videos to the underlying microstructure and lattice deformation supports a model in which CO 2 electroreduction is selectively enhanced by surface-terminating dislocations, which can accumulate at grain boundaries and slip bands. Our results suggest that the deliberate introduction of dislocations into materials is a promising strategy for improving catalytic properties. Although bulk defects can influence the performance of electrocatalysts used for energy conversion, their structural origins are still unclear. The effects of bulk defects on CO 2 electroreduction and H 2 evolution activity on Au electrodes are now elucidated.

Engineering of defects in semiconductors provides an effective protocol for improving photocatalytic N 2 conversion efficiency. This review focuses on the state-of-the-art progress in defect engineering of photocatalysts for the N 2 reduction toward ammonia. The basic principles and mechanisms of thermal catalyzed and photon-induced N 2 reduction are first concisely recapped, including relevant properties of the N 2 molecule, reaction pathways, and NH 3 quantification methods. Subsequently, defect classification, synthesis strategies, and identification techniques are compendiously summarized. Advances of in situ characterization techniques for monitoring defect state during the N 2 reduction process are also described. Especially, various surface defect strategies and their critical roles in improving the N 2 photoreduction performance are highlighted, including surface vacancies (i.e., anionic vacancies and cationic vacancies), heteroatom doping (i.e., metal element doping and nonmetal element doping), and atomically defined surface sites. Finally, future opportunities and challenges as well as perspectives on further development of defect-engineered photocatalysts for the nitrogen reduction to ammonia are presented. It is expected that this review can provide a profound guidance for more specialized design of defect-engineered catalysts with high activity and stability for nitrogen photochemical fixation.