Luminescence regulation of Sb^(3+)in 0D hybrid metal halides by hydrogen bond network for optical anti-counterfeiting

The Sb^(3+) doping strategy has been proven to be an effective way to regulate the band gap and improve the photophysical properties of organic-inorganic hybrid metal halides(OIHMHs).However,the emission of Sb^(3+) ions in OIHMHs is primarily confined to the low energy region,resulting in yellow or red emissions.To date,there are few reports about green emission of Sb^(3+)-doped OIHMHs.Here,we present a novel approach for regulating the luminescence of Sb^(3+) ions in 0D C_(10)H_(2)_(2)N_(6)InCl_(7)·H_(2)O via hydrogen bond network,in which water molecules act as agents for hydrogen bonding.Sb^(3+)-doped C_(10)H_(2)2N_(6)InCl_(7)·H_(2)O shows a broadband green emission peaking at 540 nm and a high photoluminescence quantum yield(PLQY)of 80%.It is found that the intense green emission stems from the radiative recombination of the self-trapped excitons(STEs).Upon removal of water molecules with heat,C_(10)H_(2)_(2)N_(6)In_(1-x)Sb_(x)Cl_(7) generates yellow emis-sion,attributed to the breaking of the hydrogen bond network and large structural distortions of excited state.Once water molecules are adsorbed by C_(10)H_(2)_(2)N_(6)In_(1-x)Sb_(x)Cl_(7),it can subsequently emit green light.This water-induced reversible emission switching is successfully used for optical security and information encryption.Our findings expand the under-standing of how the local coordination structure influences the photophysical mechanism in Sb^(3+)-doped metal halides and provide a novel method to control the STEs emission.

Research on Scheduling Strategy of Flexible Interconnection Distribution Network Considering Distributed Photovoltaic and Hydrogen Energy Storage

Distributed photovoltaic(PV)is one of the important power sources for building a new power system with new energy as the main body.The rapid development of distributed PV has brought new challenges to the operation of distribution networks.In order to improve the absorption ability of large-scale distributed PV access to the distribution network,the AC/DC hybrid distribution network is constructed based on flexible interconnection technology,and a coordinated scheduling strategy model of hydrogen energy storage(HS)and distributed PV is established.Firstly,the mathematical model of distributed PV and HS system is established,and a comprehensive energy storage system combining seasonal hydrogen energy storage(SHS)and battery(BT)is proposed.Then,a flexible interconnected distribution network scheduling optimization model is established to minimize the total active power loss,voltage deviation and system operating cost.Finally,simulation analysis is carried out on the improved IEEE33 node,the NSGA-II algorithm is used to solve specific examples,and the optimal scheduling results of the comprehensive economy and power quality of the distribution network are obtained.Compared with the method that does not consider HS and flexible interconnection technology,the network loss and voltage deviation of this method are lower,and the total system cost can be reduced by 3.55%,which verifies the effectiveness of the proposed method.

RuO_(2)-PdO nanowire networks with rich interfaces and defects supported on carbon toward the efficient alkaline hydrogen oxidation reaction

Interfacial engineering is a promising approach for enhancing electrochemical performance,but rich and efficient interfacial active sites remain a challenge in fabrication.Herein,RuO_(2)-PdO heterostructure nanowire networks(NWs) with rich interfaces and defects supported on carbon(RuO_(2)-PdO NWs/C) for alkaline hydrogen oxidation reaction(HOR) was formed by a seed induction-oriented attachment-thermal treatment method for the first time.As expected,the RuO_(2)-PdO NWs/C(72.8% Ru atomic content in metal) exhibits an excellent activity in alkaline HOR with a mass specific exchange current density(jo,m) of 1061 A gRuPd-1,which is 3.1 times of commercial Pt/C and better than most of the reported nonPt noble metal HOR electrocatalysts.Even at the high potential(~0.5 V vs.RHE) or the presence of CO(5 vol%),the RuO_(2)-PdO NWs/C still effectively catalyzes the alkaline HOR.Structure/electrochemical analysis and theoretical calculations reveal that the interfaces between RuO_(2) and PdO act as the active sites.The electronic interactions between the two species and the rich defects for the interfacial active sites weaken the adsorption of Had,also strengthen the adsorption of OHad,and accelerate the alkaline HOR process.Moreover,OHadon RuO_(2) can spillover to the interfaces,keeping the RuO_(2)-PdO NWs/C with the stable current density at higher potential and high resistance to CO poisoning.

Semi-Interpenetrating Novolac-Epoxy Thermoset Polymer Networks Derived from Plant Biomass

Bio-based phenol-formaldehyde polymer (BioNovolac) was developed by reacting molar excess of bio-oil/phenolwith formaldehyde in acidic medium. Glycidyl 3,5-diglycidoxybenzoate (GDGB), was prepared by directglycidylation of α-resorcylic acid (RA), a naturally occurring phenolic monomer. GDGB was crosslinked in thepresence of BioNovolac by anionic polymerization. Fourier transform infrared spectroscopy (FTIR) confirmedthe formation of semi-interpenetrating polymer networks. The glass transition temperature and moduli of biobasedcrosslinked systems were observed to increase with increasing GDGB content. Active chain density andmass retention measured by dynamic mechanical analysis (DMA) and Soxhlet extraction, respectively, indicated ahigh crosslink density of the cured networks. Scanning electron microscopy (SEM) images depicted thehomogeneity of the bulk phase. The preparation of bio-based epoxy-novolac thermoset network resulted inreduced consumption of petroleum-based chemicals.

Semi-interpenetrating network anion exchange membranes based on quaternized polyvinyl alcohol/poly(diallyldimethylammonium chloride)

The semi-interpenetrating network anion exchange membranes(AEMs)based on quaternized polyvinyl alcohol(QPVA)and poly(-diallyldimethylammonium chloride)(PDDA)are synthesized.The chemical cross-linking structure is formed between hydroxyl groups of QPVA and aldehyde groups of glutaraldehyde(GA),which makes PDDA more stable embed in the QPVA matrix and also improves the mechanical properties and dimensional stability of AEMs.Due to the phase separation phenomenon of AEMs swelling in water,a microporous structure may be formed in the membrane,which reduces the transmission resistance of hydroxide ions and provides a larger space for the transfer of hydroxide ions,thus improving the conductivity.The ring structure of PDDA is introduced as a cationic group to transfer hydroxide ions,and shields the nucleophilic attack of the hydroxide ions through the steric hindrance effect,which improves alkaline stability.The hydroxide conductivity of semi-interpenetrating network membrane(QPVA/PDDA0.5-GA)is 36.5 mS cm^(-1) at 60℃.And the membrane of QPVA/PDDA0.5-GA exhibits excellent mechanical property with maximum tensile strength of 19.6 MPa.After immersing into hot 3 mol L^(-1) NaOH solutions at 60℃ for 300 h,the OHconductivity remains 78%of its initial value.The semi-interpenetrating network AEMs with microporous structure exhibit good ionic conductivity,mechanical strength and alkaline durability.

Tough Semi-interpenetrating Polyvinylpyrrolidone/Polyacrylamide Hydrogels Enabled by Bioinspired Hydrogen-bonding Induced Phase Separation

Semi-interpenetrating(semi-IPN)hydrogels formed by the continuous interpenetration of cross-linked polymer network and linear non-crosslinked polymer with multifunctionality are widely used in biomedical and other fields.However,the negative impact of linear polymer on the homogeneity of the cross-linked network often leads to a decrease in the mechanical properties of semi-IPN hydrogels and severely limits their applications.Herein,a bioinspired hydrogen-bonding induced phase separation strategy is presented to construct the tough semi-IPN polyvinylpyrrolidone/polyacrylamide hydrogels(named PVP/PAM hydrogels),including the linear polymer polyvinylpyrrolidone(PVP)and cross-linked polyacrylamide(PAM)network.The resultant PVPx/PAM hydrogels exhibit unique phase separation induced by the hydrogen bonding between PVP and PAM and affected by the amount of substance of PVP.Meanwhile,the phase separation of PVPx/PAM hydrogels results in excellent mechanical properties with a strain of 2590%,tensile strength of 0.28 MPa and toughness of 2.17 MJ/m^(3).More importantly,the hydrogen bonding between PVP and PAM firstly disrupts to dissipate energy under external forces,so the PVPx/PAM hydrogels exhibit good self-recovery properties and outperform chemically cross-linked PAM hydrogels in impact resistance and damping applications.It is believed that the PVPx/PAM hydrogels with hydrogen-bonding induced phase separation possess more potential application prospects.

Studies on Hydrogen Bonding Network Structures of Konjac Glucomannan

In this paper, the hydrogen bonding network models of konjac glucomannan （KGM） are predicted in the approach of molecular dynamics （MD）. These models have been proved by experiments whose results are consistent with those from simulation. The results show that the hydrogen bonding network structures of KGM are stable and the key linking points of hydrogen bonding network are at the O（6） and O（2） positions on KGM ring. Moreover, acety has significant influence on hydrogen bonding network and hydrogen bonding network structures are more stable after deacetylation.

Radial Basis Function Neural Networks-Based Modeling of the Membrane Separation Process: Hydrogen Recovery from Refinery Gases

Membrane technology has found wide applications in the petrochemical industry, mainly in the purification and recovery of the hydrogen resources. Accurate prediction of the membrane separation performance plays an important role in carrying out advanced process control （APC）. For the first time, a soft-sensor model for the membrane separation process has been established based on the radial basis function （RBF） neural networks. The main performance parameters, i.e, permeate hydrogen concentration, permeate gas flux, and residue hydrogen concentration, are estimated quantitatively by measuring the operating temperature, feed-side pressure, permeate-side pressure, residue-side pressure, feed-gas flux, and feed-hydrogen concentration excluding flow structure, membrane parameters, and other compositions. The predicted results can gain the desired effects. The effectiveness of this novel approach lays a foundation for integrating control technology and optimizing the operation of the gas membrane separation process.

Hydrogen Bond Networks' QSAR and Topologica Analysis of Konjac Glucomannan Chains

Based on the knot theory and researching of network structures of glucomannan molecules, the polysaccharides were analyzed. The link prediction analysis is to further reveal the interactions between polysaccharides, to elaborate QSAR of polysaccharides, and to analyze the network conformation relationships among polysaccharides. We made a classification for glucomannan molecules based on the related domestic and international theories, and investigated their network structures and application prospects. The knot theory and the link predictions not only simplify the glucomannan microscopic descriptions but also play a guiding role in predicting and regulating the structures.

Self-assembly of three-dimensional CdS nanosphere/graphene networks for efficient photocatalytic hydrogen evolution

In this work, we report the construction of three-dimensional(3D) CdS nanosphere/graphene networks by a one-step hydrothermal self-assembly route. The 3D graphene networks not only enhance the light scattering, thanks to the interconnected 3D architecture, but also improve the crystallinity of deposited CdS nanospheres, and at the same time provide a direct electron pathway to quickly separate the photogenerated electron-hole pairs from CdS, which thus dramatically improve the photocatalytic activity.The optimized 3D CdS nanosphere/graphene networks with 2 wt% of graphene could produce molecular hydrogen at a rate of 2310 μmol gcatalyst^(-1) h^(-1) under visible-light illumination(λ > 400 nm).

Pinch Location of the Hydrogen Network with Purification Reuse

In the hydrogen network with the minimum hydrogen utility flow rate,the pinch appears at the point with zero hydrogen surplus,while the hydrogen surpluses of all the other points are positive.In the hydrogen purity profiles,the pinch can only lie at the sink-tie-line intersecting the source purity profile.According to the alternative distribution of the negative and positive regions,the effect of the purification to the hydrogen surplus is analyzed.The results show that when the purification is applied,the pinch point will appear neither above the purification feed nor between the initial pinch point and the purification feed,no matter the purification feed lies above or below the initial pinch point.This is validated by two case studies.

Integration strategies of hydrogen network in a refinery based on operational optimization of hydrotreating units

Inferior crude oil and fuel oil upgrading lead to escalating increase of hydrogen consumption in refineries.It is imperative to reduce the hydrogen consumption for energy-saving operations of refineries.An integration strategy of hydrogen network and an operational optimization model of hydrotreating(HDT)units are proposed based on the characteristics of reaction kinetics of HDT units.By solving the proposed model,the operating conditions of HDT units are optimized,and the parameters of hydrogen sinks are determined by coupling hydrodesulfurization(HDS),hydrodenitrification(HDN)and aromatic hydrogenation(HDA)kinetics.An example case of a refinery with annual processing capacity of eight million tons is adopted to demonstrate the feasibility of the proposed optimization strategies and the model.Results show that HDS,HDN and HDA reactions are the major source of hydrogen consumption in the refinery.The total hydrogen consumption can be reduced by 18.9%by applying conventional hydrogen network optimization model.When the hydrogen network is optimized after the operational optimization of HDT units is performed,the hydrogen consumption is reduced by28.2%.When the benefit of the fuel gas recovery is further considered,the total annual cost of hydrogen network can be reduced by 3.21×10~7CNY·a^(-1),decreased by 11.9%.Therefore,the operational optimization of the HDT units in refineries should be imposed to determine the parameters of hydrogen sinks base on the characteristics of reaction kinetics of the hydrogenation processes before the optimization of the hydrogen network is performed through the source-sink matching methods.

Modeling and Multi-objective Optimization of Refinery Hydrogen Network

在炼油厂的氢的需求作为市场力量和环境立法正在增加，因此氢网络管理在精炼厂正在变得日益重要。大多数研究集中了于单身者 -- 为氢网络的客观优化问题，而是为多客观的优化问题的很少报道。这份报纸为在精炼厂为氢网络当模特儿和多客观的优化论述一条新奇途径。一个改进多客观的优化模型基于上层建筑的概念被建议。优化包括操作费用的最小化和设备的投资费用的最小化。为氢网络的多客观的优化的建议方法论考虑流动率限制，压力限制，纯净限制，杂质限制，回报时期，等等。方法认为所有可行连接和题目是这到混合整数非线性的编程(MINLP ) 。一个确定的优化方法被使用解决这个多客观的优化问题。最后，真实案例研究被介绍说明途径的适用性。

Optimization of hydrogen networks with multiple impurities and impurity removal

To explore the effect of removing different impurities to hydrogen networks, an MINLP model is proposed with all matching possibilities and the trade-off between operation cost and capital cost is considered. Furthermore,the impurity remover, hydrogen distribution, compressor and pipe setting are included in the model. Based on this model, the impurity and source(s) that are in higher priority for impurity removal, the optimal targeted concentration, and the hydrogen network with the minimum annual cost can be identified. The efficiency of the proposed model is verified by a case study.

Improving Refinery Profits via Fine Management of Hydrogen Networks

氢网络管理对 refineries.Various 重要系统的管理技术被开发了改进精炼厂氢 networks.However 的效率，所有对待在处理的氢网络费用和油之间的氢网络 separately.The 折衷的存在方法联网利益没在氢网络管理 yet.A 小说敏感分析计划被探索被介绍拿把网络处理成处理统一哪个是 sensi 的 consideration.Oil

A New Three-dimensional Network Constructed by Heptamolybdate, Sodium Ions and Hexamethylene Tetramine Cations via Hydrogen Bonds

The crystal structure of the title compound [Na2(OH2)5]2+[C6H12N4H2]2-2+ [Mo7O24]6 ?4H2O, prepared from an aqueous solution of Na2MoO4 ?2H2O in the presence of MoCl3 and hexamethylene tetramine, has been determined by single-crystal X-ray diffraction. The crystal is of orthorhombic, space group Pnma with a = 14.6113(2), b = 18.6833(1), c = 15.3712(2), V = 4196.14(8)3, Z = 4, Mr = 1548.13, F(000) = 3016, = 2.157 mm-1 and Dc = 2.451 g/cm3. The final R factor is 0.0526 for 3818 unique observed reflections (I > 2(I)). The structural analysis reveals that heptamolybdate anions in the title compound consist of seven edge-sharing MoO6 octahedra, and are linked into a three-dimensional framework by sodium ions and hydrogen bonds.

A Perfect Three-dimensional Hydrogen Bonding Network within Hydroxonium Hexa-aqua-magnesium(Ⅱ) Trichloride

Hydrothermal reaction of MgCl2 and ethyl tetrazolate-5-carboxylate at 160 ℃unexpectedly yielded compound {（H3O）[Mg（H2O）6]Cl3} （1）. The result of X-ray diffraction analysis indicates that 1 crystallizes in the monoclinic system, space group C2/c with a = 9.2896（3）, b = 9.5570（4）, c = 13.3169（5） A, β = 90.1221（12）°, V= 1182.28（8） A3, Z = 4, Mr = 257.78, Dc = 1.448 g/cm3, μ = 0.824 mm^-1, F（000） = 536, R = 0.0265 and wR - 0.0706. 1 is composed of one hexa-aqua-magnesium（Ⅱ） ion, one hydroxonium ion, and three chlorine anions. These three components weave a perfect three-dimensional （3D） （4,4,6,12）-connected hydrogen bonding network within 1.

Fuzzy optimization design of multicomponent refinery hydrogen network

Hydrogen and light hydrocarbon components are essential resources of the refinery.The optimization of the refinery hydrogen system and recovery of the light hydrocarbon components contained in the gas streams are key strategies to reduce the operating costs for sustainable development.Many research efforts have been focused on the optimization of single impurity hydrogen network,and the flowrates of the hydrogen sources and sinks are assumed to be constant.However,their flowrates vary along with the quality of crude oil and refinery processing plans.A general superstructure of multicomponent refinery hydrogen network is proposed,which considers four components,namely H_(2),H_(2)S,CH_(4) and C_(2+),as well as the flowrate variations of hydrogen source and hydrogen sink.The mathematical model based on the superstructure is developed with objective functions,including the minimization of total annualized cost and the maximization of overall satisfaction of the hydrogen network.Moreover,the model considers the removal of hydrogen sulfide and the recovery of light hydrocarbon components(i.e.,C_(2+))in the optimization.To verify the applicability of the proposed mathematical model,a simplified industrial case study with four scenarios is solved.The optimization results show that the economic benefit can be maximized by considering both the direct reuse of gas streams from high-pressure separator(HP gas stream)and from low-pressure separator(LP gas stream)and the recovery of the light hydrocarbon streams.The fuzzy optimization method can be used to guide the optimal design of the refinery hydrogen system with multi-period variable flowrates.

A Novel Hydrogen-bonded Three-dimensional Network Complex Containing Nickel

A novel complex, (H 3O) 2[Ni(2,6-pydc) 2]·2H 2O was synthesized in an aqueous solution and characterized by means of single-crystal X-ray diffraction, elemental analyses and IR spectra. The X-ray structural analysis revealed that the novel compound forms three-dimensional(3D) networks by both π-π stacking and hydrogen-bonding interactions. The crystal data for the complex are a=13.853(3) nm, b=9.6892(19) nm, c=13.732(3) nm, α=90.00°, β=115.52(3)°, γ=90.00°, Z=3, R 1=0.0786, wR 2=0.1522.

Deep Learning Accelerates the Discovery of Two- Dimensional Catalysts for Hydrogen Evolution Reaction

Two-dimensional materials with active sites are expected to replace platinum as large-scale hydrogen production catalysts.However,the rapid discovery of excellent two-dimensional hydrogen evolution reaction catalysts is seriously hindered due to the long experiment cycle and the huge cost of high-throughput calculations of adsorption energies.Considering that the traditional regression models cannot consider all the potential sites on the surface of catalysts,we use a deep learning method with crystal graph convolutional neural networks to accelerate the discovery of high-performance two-dimensional hydrogen evolution reaction catalysts from two-dimensional materials database,with the prediction accuracy as high as 95.2%.The proposed method considers all active sites,screens out 38 high performance catalysts from 6,531 two-dimensional materials,predicts their adsorption energies at different active sites,and determines the potential strongest adsorption sites.The prediction accuracy of the two-dimensional hydrogen evolution reaction catalysts screening strategy proposed in this work is at the density-functional-theory level,but the prediction speed is 10.19 years ahead of the high-throughput screening,demonstrating the capability of crystal graph convolutional neural networks-deep learning method for efficiently discovering high-performance new structures over a wide catalytic materials space.