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We report a general route to decipher the apportionment of metal ions in bulk metal-organic frameworks (MOFs) by solid-state nuclear magnetic resonance spectroscopy. We demonstrate this route in Mg1-xNix-MOF-74, where we uncover all eight possible atomic-scale Mg/Ni arrangements through identification and quantification of the distinct chemical environments of 13C-labeled carboxylates as a function of the Ni content. Here, we use magnetic susceptibility, bond pathway, and density functional theory calculations to identify local metal bonding configurations. The results refute the notion of random apportionment from solution synthesis; rather, we reveal that only two of eight Mg/Ni arrangements are preferred in the Ni-incorporated MOFs. These preferred structural arrangements manifest themselves in macroscopic adsorption phenomena as illustrated by CO/CO2 breakthrough curves. We envision that this nondestructive methodology can be further applied to analyze bulk assembly of other mixed-metal MOFs, greatly extending the knowledge on structure-property relationships of MOFs and their derived materials.

Geological mapping involves the identification of elements such as rocks, soils, and surface water, which are fundamental tasks in Geological Environment Remote Sensing (GERS) interpretation. High-precision intelligent interpretation technology can not only reduce labor requirements and significantly improve the efficiency of geological mapping but also assist geological disaster prevention assessment and resource exploration. However, the high interclass similarity, high intraclass variability, gradational boundaries, and complex distributional characteristics of GERS elements coupled with the difficulty of manual labeling and the interference of imaging noise, all limit the accuracy of DL-based methods in wide-area GERS interpretation. We propose a Transformer-based multi-stage and multi-scale fusion network, RSWFormer (Rock–Soil–Water Network with Transformer), for geological mapping of spatially large areas. RSWFormer first uses a Multi-stage Geosemantic Hierarchical Sampling (MGHS) module to extract geological information and high-dimensional features at different scales from local to global, and then uses a Multi-scale Geological Context Enhancement (MGCE) module to fuse geological semantic information at different scales to enhance the understanding of contextual semantics. The cascade of the two modules is designed to enhance the interpretation and performance of GERS elements in geologically complex areas. The high mountainous and hilly areas located in western China were selected as the research area. A multi-source geological remote sensing dataset containing diverse GERS feature categories and complex lithological characteristics, Multi-GL9, is constructed to fill the significant gaps in the datasets required for extensive GERS. Using overall accuracy as the evaluation index, RSWFormer achieves 92.15% and 80.23% on the Gaofen-2 and Landsat-8 datasets, respectively, surpassing existing methods. Experiments show that RSWFormer has excellent performance and wide applicability in geological mapping tasks. [ABSTRACT FROM AUTHOR]

Reported here is the chelate effect as a design principle for tuning heterogeneous catalysts for electrochemical CO2 reduction. Palladium functionalized with a chelating tris-N-heterocyclic carbene (NHC) ligand (Pd-timtmbMe ) exhibits a 32-fold increase in activity for electrochemical reduction of CO2 to C1 products with high Faradaic efficiency (FEC1 =86 %) compared to the parent unfunctionalized Pd foil (FE=23 %), and with sustained activity relative to a monodentate NHC-ligated Pd electrode (Pd-mimtmbMe ). The results highlight the contributions of the chelate effect for tailoring and maintaining reactivity at molecular-materials interfaces enabled by surface organometallic chemistry.

Algebraic topology has proved to be a useful tool in the study of distributed computing. In this paper, we take a geometric realization problem that arises in distributed computing and formulate it as a more general problem in algebraic topology. We go on to give solutions in some initial cases, show that a modified problem has solutions in a wider range of cases, and relate the solutions back to distributed computing. [ABSTRACT FROM AUTHOR]

This paper investigates the three-stage assembly flow shop scheduling problem, provided that there is a fixed maintenance period (MP) imposed on one of the machines in the first stage, the objective is to minimize the makespan. The starting time and duration of MP are known in advance, during MP no job can be processed on the corresponding machine. Only the non-resumable scenario is considered, i.e., if a job fails to finish before MP, it must restart from the beginning after the machine becomes available again, rather than continuing its processing. The problem generalizes the three-stage assembly flow shop scheduling problem without MPs and is therefore strongly NP-hard. To the best of our knowledge, the problem has not been explored so far. We propose three approximation algorithms for the problem. [ABSTRACT FROM AUTHOR]

The advance in single-cell RNA-sequencing (scRNA-seq) sheds light on cell-specific transcriptomic studies of cell developments, complex diseases and cancers. Nevertheless, scRNA-seq techniques suffer from 'dropout' events, and imputation tools are proposed to address the sparsity. Here, rather than imputation, we propose a tool, SMURF, to extract the low-dimensional embeddings from cells and genes utilizing matrix factorization with a mixture of Poisson-Gamma divergent as objective while preserving self-consistency. SMURF exhibits feasible cell subpopulation discovery efficacy with obtained cell embeddings on replicated in silico and eight web lab scRNA datasets with ground truth cell types. Furthermore, SMURF can reduce the cell embedding to a 1D-oval space to recover the time course of cell cycle. SMURF can also serve as an imputation tool; the in silico data assessment shows that SMURF parades the most robust gene expression recovery power with low root mean square error and high Pearson correlation. Moreover, SMURF recovers the gene distribution for the WM989 Drop-seq data. SMURF is available at https://github.com/deepomicslab/SMURF. [ABSTRACT FROM AUTHOR]

Lipid nanoparticles (LNPs) are the commonly used delivery tools for messenger RNA (mRNA) therapy and play an indispensable role in the success of COVID-19 mRNA vaccines. Ionizable cationic lipids are the most important component in LNPs. Herein, we developed a series of new ionizable lipids featuring bioreducible disulfide bonds, and constructed a library of lipids derived from dimercaprol. LNPs prepared from these ionizable lipids could be stored at 4 °C for a long term and are non-toxic toward HepG2 and 293T cells. In vivo experiments demonstrated that the best C4S18A formulations, which embody linoleoyl tails, show strong firefly luciferase (Fluc) mRNA expression in the liver and spleen via intravenous (IV) injection, or at the local injection site via intramuscular injection (IM). The newly designed ionizable lipids can be potentially safe and high-efficiency nanomaterials for mRNA therapy. [ABSTRACT FROM AUTHOR]

Elucidation of the intrinsic catalytic principle of iron carbides remains a substantial challenge in iron-catalyzed Fischer-Tropsch synthesis (FTS), due to possible interference from other Fe-containing species. Here, we propose a facile approach to synthesize single-phase θ-Fe3C via the pyrolysis of a molecularly defined Fe-C complex (Fe4[Fe(CN)6]3), thus affording close examination of its catalytic behavior during FTS. The crystal structure of prepared θ-Fe3C is unambiguously verified by combined XRD and MES measurement, demonstrating its single-phase nature. Strikingly, single-phase θ-Fe3C exhibited excellent selectivity to light olefins (77.8%) in the C2-C4 hydrocarbons with less than 10% CO2 formation in typical FTS conditions. This strategy further succeeds with promotion of Mn, evident for its wide-ranging compatibility for the promising industrial development of catalysts. This work offers a facile approach for oriented preparation of single-phase θ-Fe3C and provides an in-depth understanding of its intrinsic catalytic performance in FTS. [ABSTRACT FROM AUTHOR]

In this work, we extend the topology-based framework and method for the quantification and classification of general resilient asynchronous complexity. We present the arbitrary resilient asynchronous complexity theorem, applied to decision tasks in an iterated delayed model which is based on a series of communicating objects, each of which mainly consists of the delayed algorithm. In order to do this, we first introduce two topological structures, delayed complex and reduced delayed complex, and build the topological computability model, and then investigate some properties of those structures and the computing power of that model. Our theorem states that the time complexity of any arbitrary resilient asynchronous algorithm is proportional to the level of a reduced delayed complex necessary to allow a simplicial map from a task's input complex to its output complex. As an application, we use it to derive the bounds on time complexity to approximate agreement with n + 1 processes. [ABSTRACT FROM AUTHOR]

Hydrogen storage by means of catalytic hydrogenation of suitable organic substrates helps to elevate the volumetric density of hydrogen energy. In this regard, utilizing cheaper industrial crude hydrogen to fulfill the goal of hydrogen storage would show economic attraction. However, because CO impurities in crude hydrogen can easily deactivate metal active sites even in trace amounts such a process has not yet been realized. Here, we develop a robust RuNi/TiO2 catalyst that enables the efficient hydrogenation of toluene to methyl-cyclohexane under simulated crude hydrogen feeds with 1000–5000 ppm CO impurity at around 180 °C under atmospheric pressure. We show that the co-localization of Ru and Ni species during reduction facilitated the formation of tightly coupled metallic Ru-Ni clusters. During the catalytic hydrogenation process, due to the distinct bonding properties, Ru and Ni served as the active sites for CO methanation and toluene hydrogenation respectively. Our work provides fresh insight into the effective utilization and purification of crude hydrogen for the future hydrogen economy. Efficient storage of crude hydrogen, through toluene hydrogenation to methylcyclohexane, is often inhibited by CO impurities. Here, the authors develop a RuNi/TiO2 catalyst which avoids deactivation through promoting simultaneous CO methanation. [ABSTRACT FROM AUTHOR]

Polyethylene terephthalate (PET) and CO2, two chemical wastes that urgently need to be transformed in the environment, are converted simultaneously in a one‐pot catalytic process through the synergistic coupling of three reactions: CO2 hydrogenation, PET methanolysis and dimethyl terephthalate (DMT) hydrogenation. More interestingly, the chemical equilibria of both reactions were shifted forward due to a revealed dual‐promotion effect, leading to significantly enhanced PET depolymerization. The overall methanol yield from CO2 hydrogenation exceeded the original thermodynamic equilibrium limit since the methanol was in situ consumed in the PET methanolysis. The degradation of PET by a stoichiometric ratio of methanol was significantly enhanced because the primary product, DMT was hydrogenated to dimethyl cyclohexanedicarboxylate (DMCD) or p‐xylene (PX). This synergistic catalytic process provides an effective way to simultaneously recycle two wastes, polyesters and CO2, for producing high‐value chemicals. [ABSTRACT FROM AUTHOR]

Deuterium (D) labeling is of great value in organic synthesis, pharmaceutical industry, and materials science. However, the state‐of‐the‐art deuteration methods generally require noble metal catalysts, expensive deuterium sources, or harsh reaction conditions. Herein, noble metal‐free and ultrathin ZnIn2S4 (ZIS) is reported as an effective photocatalyst for visible light‐driven reductive deuteration of carbonyls to produce deuterated alcohols using heavy water (D2O) as the sole deuterium source. Defective two‐dimensional ZIS nanosheets (D‐ZIS) are prepared in a surfactant assisted bottom‐up route exhibited much enhanced performance than the pristine ZIS counterpart. A systematic study is carried out to elucidate the contributing factors and it is found that the in situ surfactant modification enabled D‐ZIS to expose more defect sites for charge carrier separation and active D‐species generation, as well as high specific surface area, all of which are beneficial for the desirable deuteration reaction. This work highlights the great potential in developing low‐cost semiconductor‐based photocatalysts for organic deuteration in D2O, circumventing expensive deuterium reagents and harsh conditions. [ABSTRACT FROM AUTHOR]

Efficient synthesis of higher alcohols from syngas over a single‐metal catalyst remains challenging because both active sites for CO dissociation and molecular CO adsorption are required. We report herein that iron nitrides can directly catalyze syngas to higher alcohols with high selectivity. Three iron nitride catalysts (Fe2N, Fe3N, and Fe4N) were fabricated via the nitriding of α‐Fe and their structures were confirmed by X‐ray diffraction (XRD) and Mössbauer spectroscopy (MES). Moreover, no carbides were detected even after syngas conversion for Fe2N and Fe3N catalysts, in which the N content was higher than that in Fe4N (iron nitrides transformed to Fe2C partly). The catalytic performance indicated that higher alcohols could be directly produced from syngas with remarkable selectivity (>51 % for C2+OH selectivity in total alcohols) over iron nitrides, which was tentatively ascribed to the unique electronic structure of iron nitrides, as evidenced by DFT calculation. This study proposed a novel method for the selective one‐step synthesis of higher alcohols from syngas. [ABSTRACT FROM AUTHOR]

• H 2 reduction behaviors of Fe 2 O 3 based catalysts are investigated by in situ XRD. • Potassium promoter notably inhibits the reduction from α-Fe 2 O 3 to Fe 3 O 4. • The formation of α-Fe crystallite is accelerated or unchanged during reduction. • Potassium effect on FTS performance of the Fe 2 O 3 based catalysts is studied. Effect of potassium promoter on phase transformation during the isothermal and temperature programmed reduction of the α-Fe 2 O 3 catalyst were systematically investigated by in situ XRD. The reduction pathway of Fe 2 O 3 based catalysts follows the same sequence of α-Fe 2 O 3 → Fe 3 O 4 → α-Fe during the isothermal reduction, in contrast to that of α-Fe 2 O 3 → Fe 3 O 4 → FeO/ α-Fe→ α-Fe during the temperature programmed reduction. The potassium promoter notably inhibits the reduction from α-Fe 2 O 3 to Fe 3 O 4 due to the enhanced strength of Fe-O bonds, whereas it either accelerates or has no effect on the formation rate of α-Fe crystallites during reduction. The potassium promoter increases the CO conversion during FTS, while enhances C 5 +, olefins, CO 2 selectivity, and decreases CH 4 selectivity. [ABSTRACT FROM AUTHOR]

As a prerequisite elementary step, carburization of iron oxides to form iron carbides is critically important to display activity for iron‐based Fischer–Tropsch synthesis catalysts. The positive role of the Cu promoter to advocate the reduction of the iron oxides has long been known. Nevertheless, its complex influence along the carburization of catalyst precursors remains controversial. Here, we resolve this decades‐long question by using a state‐of‐the‐art in situ X‐ray diffraction (XRD) method to elucidate the multi‐role of Cu promoter in modulation of carburization rate, composition of post‐carburization samples, and morphology evolution of prepared iron carbide particles under CO/He (v/v=2 %/98 %) and H2/CO/He (v/v/v=8 %/2 %/90 %) gaseous environment, by excluding the possible interference from promoter components other than Cu. We anticipate that this study enriches current tool box in the research of a specific promoter of the Fischer‐Tropsch synthesis catalysts. In situ seeing is believing: The complex influence of Cu promoter along the carburization of iron catalyst precursors has been elucidated by using a state‐of‐the‐art in situ X‐ray diffraction (XRD) method. Particularly, the multi‐role of Cu promoter in modulation of carburization rate, composition of post‐carburization samples, and morphology evolution of prepared iron carbide particles under CO/He (v/v=2 %/98 %) and H2/CO/He (v/v/v=8 %/2 %/90 %) gaseous environment, by excluding the possible interference from promoter components other than Cu. [ABSTRACT FROM AUTHOR]

Abstract: Capped chelating organic molecules are presented as a design principle for tuning heterogeneous nanoparticles for electrochemical catalysis. Gold nanoparticles (AuNPs) functionalized with a chelating tetradentate porphyrin ligand show a 110‐fold enhancement compared to the oleylamine‐coated AuNP in current density for electrochemical reduction of CO2 to CO in water at an overpotential of 340 mV with Faradaic efficiencies (FEs) of 93 %. These catalysts also show excellent stability without deactivation (<5 % productivity loss) within 72 hours of electrolysis. DFT calculation results further confirm the chelation effect in stabilizing molecule/NP interface and tailoring catalytic activity. This general approach is thus anticipated to be complementary to current NP catalyst design approaches. [ABSTRACT FROM AUTHOR]

Reported here is the chelate effect as a design principle for tuning heterogeneous catalysts for electrochemical CO2 reduction. Palladium functionalized with a chelating tris‐N‐heterocyclic carbene (NHC) ligand (Pd‐timtmbMe) exhibits a 32‐fold increase in activity for electrochemical reduction of CO2 to C1 products with high Faradaic efficiency (FEC1=86 %) compared to the parent unfunctionalized Pd foil (FE=23 %), and with sustained activity relative to a monodentate NHC‐ligated Pd electrode (Pd‐mimtmbMe). The results highlight the contributions of the chelate effect for tailoring and maintaining reactivity at molecular‐materials interfaces enabled by surface organometallic chemistry. [ABSTRACT FROM AUTHOR]

A study of the promotional effect of potassium on the carburization behavior of a series of spray-dried precipitated Fe2O3 catalysts (100 Fe, 100 Fe/0.52 K, 100 Fe/1.54 K, and 100 Fe/2.4 K) has been performed by using in situ XRD. The average crystallite size evolution for species such as α-Fe2O3, Fe3O4, χ-Fe5C2, and θ-Fe3C were followed. The potassium promoter clearly inhibits the reduction of α-Fe2O3 to Fe3O4, where the decreasing binding energy in the Fe 2p3/2, O 1s and K 2p3/2 spectra from X-ray photoelectron spectroscopy (XPS) suggests an electron density increase in Fe and O upon potassium promotion, leading to the enhanced covalency in the Fe−O bond. In terms of crystallite size during carburization, an optimum potassium loading exists in catalyst 100 Fe/0.52 K, which shows the fastest reduction to Fe3O4 with minimum crystallite sizes of around 7 to 15 nm. Potassium has no clear effect in determining the final crystallite size of χ-Fe5C2. An arch-shaped curve in the evolution of crystallite size of the Fe3O4 intermediate was observed, which can be explained by the activation energy difference between the bidirectional steps of the outward oxygen diffusion and the inward carbon diffusion. [ABSTRACT FROM AUTHOR]