Solvent-Less Vapor-Phase Fabrication of Membranes for Sustainable Separation Processes

Sustainable processes for purifying water,capturing carbon,producing biofuels,operating fuel cells,and performing energy-efficient industrial separations will require next-generation membranes.Solvent-less fabrication for membranes not only eliminates potential environmental issues with organic solvents,but also solves the swelling problems that occur with delicate polymer substrates.Furthermore,the activation procedures often required for synthesizing microporous materials such as metal–organic frameworks(MOFs)can be reduced when solvent-less vapor-phase approaches are employed.This perspective covers several vacuum deposition processes,including initiated chemical vapor deposition(iCVD),initiated plasma-enhanced chemical vapor deposition(iPECVD),solvent-less vapor deposition followed by in situ polymerization(SLIP),atomic layer deposition(ALD),and molecular layer deposition(MLD).These solvent-less vapor-phase methods are powerful in creating ultrathin selective layers for thin-film composite membranes and advantageous in conformally coating nanoscale pores for the precise modification of pore size and internal functionalities.The resulting membranes have shown promising performance for gas separation,nanofiltration,desalination,and water/oil separation.Further development of novel membrane materials and the scaling up of high-throughput reactors for solvent-less vapor-phase processes are necessary in order to make a real impact on the chemical industry in the future.

Replacement of Process Scale Chromatography by Counterflow Membrane Cascades

Invention and innovation, always important, become ever more so in these fast changing and competitive times. They are in addition primarily dependent upon the dynamic behavior of the human mind. Our underlying purpose here is to examine these creative processes and to provide means to make them more effective. This is a timely effort because our understanding of perception and its interpretation by the human brain is very rapidly advancing. Even experimental insights into mental activity can be determined with rapidly increasing effectiveness. The framework of our discussion is that of evolution dynamics, and the scientific bases are rapidly developing neural sciences. However the bulk of our discussion deals with a specific example: the replacement of process scale chromatography by membrane-mediated steady counterflow in downstream processing. We do this because inventive activities must depend upon intimate knowledge of the systems available.

Double-stretching as an effective and generalizable strategy towards thinner nanofibers in solution blow spinning

Solution blow spinning(SBS)applies high-speed airflow to prepare fibers by generating a strong stretching force.It has the advantages of scalable production,tailorable morphologies,and wide applicability.Yet,the SBS strategy can hardly prepare fibers down to the sub-100 nanometers,which limits its performance in demanding applications.Herein,we overcome the limitation of SBS by introducing a second airflow.This novel strategy is termed double-stretching SBS(DS-SBS)because an extra stretching force is exerted on the fiber when it converges with the second airflow.Polyamide6 nanofibers with an average diameter of 80 nm are successfully prepared with the DS-SBS strategy,while the SBS strategy could only prepare submicron fibers with an average diameter of 120 nm.Further,the generality of the DS-SBS strategy to reduce fiber diameter is verified on numerous solute-solvent pairs.

Thermodynamics of multi-sublattice battery active materials: from an extended regular solution theory to a phase-field model of LiMn_(y)Fe_(1-y)PO_(4)

Phase separation during the lithiation of redox-active materials is a critical factor affecting battery performance,including energy density,charging rates,and cycle life.Accurate physical descriptions of these materials are necessary for understanding underlying lithiation mechanisms,performance limitations,and optimizing energy storage devices.This work presents an extended regular solution model that captures mutual interactions between sublattices of multi-sublattice battery materials,typically synthesized by metal substitution.We apply the model to phospho-olivine materials and demonstrate its quantitative accuracy in predicting the composition-dependent redox shift of the plateaus of LiMn_(y)Fe_(1-y)PO_(4)(LFMP),LiCo_(y)Fe_(1-y)PO_(4)(LFCP),LiCo_(x)Mn_(y)Fe_(1-y)PO_(4)(LFMCP),as well as their phase separation behavior.Furthermore,we develop a phase-field model of LFMP that consistently matches experimental data and identifies LiMn0.4Fe0.6PO4 as a superior composition that favors a solid solution phase transition,making it ideal for high-power applications.

Simple glycolipids of microbes:Chemistry,biological activity and metabolic engineering

Glycosylated lipids(GLs)are added-value lipid derivatives of great potential.Besides their interesting surface activities that qualify many of them to act as excellent ecological detergents,they have diverse biological activities with promising biomedical and cosmeceutical applications.Glycolipids,especially those of microbial origin,have interesting antimicrobial,anticancer,antiparasitic as well as immunomodulatory activities.Nonetheless,GLs are hardly accessing the market because of their high cost of production.We believe that experience of metabolic engineering(ME)of microbial lipids for biofuel production can now be harnessed towards a successful synthesis of microbial GLs for biomedical and other applications.This review presents chemical groups of bacterial and fungal GLs,their biological activities,their general biosynthetic pathways and an insight on ME strategies for their production.

Functional diversity and metabolic engineering of plantspecialized metabolites

Plants are talented biochemists that produce a broad diversity of small molecules.These so-called specialized metabolites(SMs)play critical roles in the adaptive evolution of plants to defend against biotic and abiotic stresses,attract pollinators,and modulate soil microbiota for their own benefits.Many plant SMs have been used as nutrition and flavor compounds in our daily food,as well as drugs for treatment of human diseases.Current multi-omics tools have significantly accelerated the process of biosynthetic pathway elucidation in plants through correlation analyses,genetic mapping,and de novo biosynthetic gene cluster predictions.Understanding the biosynthesis of plant SMs has enabled reconstitution of naturally occurring specialized metabolic pathways in microbial hosts,providing a sustainable supply of these high-value molecules.In this review,we illustrate the general functions of several typical plant SMs in natural ecosystems and for human societies.We then provide an overview of current methods elucidating the biosynthetic pathways of plant SMs,and synthetic biology strategies that optimize the efficiency of heterologous biosynthetic pathways in microbial hosts.Moving forward,dissection of the functions and application of plant SMs by using current multidiscipline approaches would be greatly benefit to the scientific community and human societies.

复杂反应流自适应化学理论计算的研究现状

麻省理工学院化工系的Green教授提出了自适应化学理论AdapChem的概念 ,它采用相容分割法将守恒方程划分为化学方程和流动方程两个有机的部分。根据反应条件的不同 ,这种方法分别使用多个简化化学反应模型 ,而非复杂的详细基元反应模型进行区域内的数值模拟 ,为我们提供了在保证化学精度条件下 ,避免效率浪费的一条有效途径。然而 ,为了完善AdapChem ,引入以往没有考虑过的辐射模型是有必要的 ,我们使用的是离散坐标法。针对CH4/空气火焰的模拟结果显示 :引入辐射模型后 ,计算结果的图形没有明显的变化 ,而且温度又合理的降低。

Layer-by-layer functionalized nanotube arrays:A versatile microfluidic platform for biodetection

We demonstrate the layer-by-layer(LbL)assembly of polyelectrolyte multilayers(PEM)on three-dimensional nanofiber scaffolds.High porosity(99%)aligned carbon nanotube(CNT)arrays are photolithographically patterned into elements that act as textured scaffolds for the creation of functionally coated(nano)porous materials.Nanometer-scale bilayers of poly(allylamine hydrochloride)/poly(styrene sulfonate)(PAH/SPS)are formed conformally on the individual nanotubes by repeated deposition from aqueous solution in microfluidic channels.Computational and experimental results show that the LbL deposition is dominated by the diffusive transport of the polymeric constituents,and we use this understanding to demonstrate spatial tailoring on the patterned nanoporous elements.A proof-of-principle application,microfluidic bioparticle capture using N-hydroxysuccinimide-biotin binding for the isolation of prostate-specific antigen(PSA),is demonstrated.

Quantifying Electronic Effects in QM and QM/MM Biomolecular Modeling with the Fukui Function

Multi-scale quantum-mechanical/molecular-mechanical(QM/MM) and large-scale QM simulation provide valuable insight into enzyme mechanism and structure-property relationships. Analysis of the electron density afforded through these methods can enhance our understanding of how the enzyme environment modulates reactivity at the enzyme active site. From this perspective, tools from conceptual density functional theory to interrogate electron densities can provide added insight into enzyme function. We recently introduced the highly parallelizable Fukui shift analysis(FSA) method, which identifies how frontier states of an active site are altered by the presence of an additional QM residue to identify when QM treatment of a residue is essential as a result of quantum-mechanically affecting the behavior of the active site. We now demonstrate and analyze distance and residue dependence of Fukui function shifts in pairs of residues representing different non-covalent interactions. We also show how the interpretation of the Fukui function as a measure of relative nucleophilicity provides insight into enzymes that carry out S_N2 methyl transfer. The FSA method represents a promising approach for the systematic, unbiased determination of quantum mechanical effects in enzymes and for other complex systems that necessitate multi-scale modeling.

Metallic and highly conducting two-dimensional atomic arrays of sulfur enabled by molybdenum disulfide nanotemplate

Element sulfur in nature is an insulating solid.While it has been tested that one-dimensional sulfur chain is metallic and conducting,the investigation on two-dimensional sulfur remains elusive.We report that molybdenum disulfide layers are able to serve as the nanotemplate to facilitate the formation of two-dimensional sulfur.Density functional theory calculations suggest that confined inbetween layers of molybdenum disulfide,sulfur atoms are able to form two-dimensional triangular arrays that are highly metallic.As a result,these arrays contribute to the high conductivity and metallic phase of the hybrid structures of molybdenum disulfide layers and two-dimensional sulfur arrays.The experimentally measured conductivity of such hybrid structures reaches up to 223 S/m.Multiple experimental results,including X-ray photoelectron spectroscopy(XPS),transition electron microscope(TEM),selected area electron diffraction(SAED),agree with the computational insights.Due to the excellent conductivity,the current density is linearly proportional to the scan rate until 30,000 mV s^(−1) without the attendance of conductive additives.Using such hybrid structures as electrode,the two-electrode supercapacitor cells yield a power density of 10^(6) Wh kg^(−1) and energy density ~47.5 Wh kg^(−1) in ionic liquid electrolytes.Our findings offer new insights into using two-dimensional materials and their Van der Waals heterostructures as nanotemplates to pattern foreign atoms for unprecedented material properties.

Additive manufacturing of high aspect-ratio structures with self-focusing photopolymerization

Photocrosslinkable polymers have been exploited to attain impressive advantages in printing freestanding,micrometer-scale,mechanically compliant features.However,a more integrated understanding of both the polymer photochemistry and the microfabrication processes could enable new strategic design avenues,unlocking far-reaching applications of the light-based modality of additive manufacturing.One promising approach for achieving high-aspect-ratio structures is to leverage the phenomenon of light self-trapping during the photopolymerization process.In this review,we discuss the design of materials that facilitate this optical behavior,the computational modeling and practical processing considerations to achieve high aspect-ratio structures,and the range of applications that can benefit from architectures fabricated using light self-trapping-especially those demanding free-standing structures and materials of stiffnesses relevant in biological applications.Coupled interactions exist among material attributes,including polymer composition,and processing parameters such as light intensity.We identify strong opportunities for predictive design of both the material and the process.Overall,this perspective describes the wide range of existing polymers and additive manufacturing approaches,and highlights various future directions to enable constructs with new complexities and functionalities through the development of next-generation photocrosslinkable materials and micromanufacturing methods.

Engineering Covalent Organic Framework Membranes

CONSPECTUS:Membrane technology plays an increasingly important role for sustainable development of our society owing to its huge capability to tackle the energy crisis,water scarcity,environmental pollution,and carbon neutrality.To fully unlock the potential of membranes,it is in high demand to develop advanced membrane materials that significantly outperform conventional polymer membrane materials in separation performance and longterm stability.The emergent covalent organic frameworks(COFs)have been deemed as potent membrane materials because of their unique structure and properties in comparison with polymers,zeolites,and metal organic frameworks(MOFs).(i)First,the highly tunable and ordered crystalline pore structure,high porosity,and excellent stability render COFs an ideal membrane material.COFs are more stable than MOFs and,in some cases,are even more stable than zeolite.Moreover,it is easier to introduce functional groups into the COF nanochannels compared with zeolite and MOFs.Further,COFs are ideally suitable for constructing ordered nanochannels with size in the range of 0.6−3 nm which is difficult to be realized by other materials.(ii)Second,along with the unremitting discovery of diverse platform chemistries such as reticular chemistry,the in-depth understanding of nucleation/growth mechanisms of COFs as well as the rapid progress of manufacturing technologies and various routes to fabricating COF membranes with favorable physical and chemical structures inside the nanochannels are being actively exploited.COFs generally show better membrane-formation ability owing to their abundant 2D structures,which make it easier to fabricate ultrathin membranes compared with zeolite and MOFs.(iii)Last,a great number of COF membranes exhibit exceptionally high separation performance and stability,establishing their position as the next-generation membranes.In this Account,we discuss three types of engineering toward COF membranes based on Schiff base reaction for high-efficiency molecules/ion separations,i.e.,reticular engineering,crystal engineering,and nanochannel engineering.First,we discuss the reticular engineering of COF membranes with a focus on the bond types,chemical structure,and architecture design.The membraneformation ability and methods of COFs are also analyzed.Second,we discuss the crystal engineering of COF membranes with a focus on the key thermodynamical and kinetic factors to drive the disorder-to-order transition where we attempt to dig deeper into the crystallization habit of COF membranes.Third,we discuss nanochannel engineering of COF membranes with a focus on the construction and modulation of the physical and chemical microenvironments of nanochannels for efficient and selective transport of molecules/ions.Last,we conclude with a perspective on the opportunities and major challenges in the R&D of COF membranes,targeting at identifying the future directions.

Data-driven structural descriptor for predicting platinum-based alloys as oxygen reduction electrocatalysts

Owing to increasing global demand for carbon neutral and fossil-free energy systems,extensive research is being conducted on efficient and inexpensive electrocatalysts for catalyzing the kinetically sluggish oxygen reduction reaction(ORR)at the cathode of fuel cells.Platinum(Pt)-based alloys are considered promising candidates for replacing expensive Pt catalysts.However,the current screening process of Pt-based alloys is time-consuming and labor-intensive,and the descriptor for predicting the activity of Pt-based catalysts is generally inaccurate.This study proposed a strategy by combining high-throughput first-principles calculations and machine learning to explore the descriptor used for screening Pt-based alloy catalysts with high Pt utilization and low Pt consump-tion.Among the 77 prescreened candidates,we identified 5 potential candidates for catalyzing ORR with low overpotential.Furthermore,during the second and third rounds of active learning,more Pt-based alloys ORR candidates are identi-fied based on the relationship between structural features of Pt-based alloys and their activity.In addition,we highlighted the role of structural features in Pt-based alloys and found that the difference between the electronegativity of Pt and heteroatom,the valence electrons number of the heteroatom,and the ratio of heteroatoms around Pt are the main factors that affect the activity of ORR.More importantly,the combination of those structural features can be used as structural descriptor for predicting the activity of Pt-based alloys.We believe the findings of this study will provide new insight for predicting ORR activ-ity and contribute to exploring Pt-based electrocatalysts with high Pt utiliza-tion and low Pt consumption experimentally.

Is bitter actually better?Targeting a soyasaponin acetyltransferase affects soybean seed germination

Soyasaponins are a class of triterpenoid saponins that accumulate in soybean(Glycine max)seeds and give a bitter flavor to some soybean products(Berhow et al.,2006).Acetylated sugars at C22 in type-A soyasaponins are largely responsible for the undesirable bitterness in soybean-derived foods.

基于多功能纳米磁珠的DNA制备与基因分型

为了构建DNA样品制备芯片, 研发了一种以羧基修饰的磁性纳米粒子作为固相载体, 从全血、唾液和细菌培养基中快速提取基因组DNA并扩增靶基因的通用方法. 这种羧基修饰磁性纳米粒子不但可以从样品中富集靶细胞和从细胞裂解液中吸附DNA, 而且吸附在纳米磁珠表面的DNA可以不用洗脱而直接作为目标基因PCR扩增的模板, 从而通过功能集成简化了从靶细胞富集到靶基因扩增的全过程. 利用该方法实现了微量唾液样品中HLA基因的快速制备与扩增, 扩增产物与固定于寡核苷酸基因芯片上的16条探针杂交进行HLA基因分型, 取得了良好的效果. 由于该方法快速简便, 不使用有毒试剂和离心操作, 便于用以构建快速高通量的核酸制备微芯片.

Heterogeneous molecular catalysts for electrocatalytic CO2 reduction

This review provides an overview of the literature regarding heterogeneous molecular catalysts for electrochemical CO2 reduction (ECR).Fundamental aspects of the science,including aggregation,electrochemical rate laws,and electrode-catalyst electronic coupling,are discussed to provide a solid foundation on which to design experiments and interpret results.Mechanistic aspects of ECR are presented based on electrokinetic and spectroscopic measurements as well as density functional theory (DFT) calculations.Consensus is improving for electrokinetic measurements,but the redox state of the metal center under reaction conditions and DFT reaction pathways lack agreement in the literature.Concerning the tunable aspects of the molecular catalyst,the impacts of the metal center,ligand substituents,and electrode support on the activity and selectivity toward ECR are presented with an emphasis on those studies that controlled for aggregation and minimized mass-transport limitations.Extended three-dimensional (3D) structures such as polymers,metal-organic frameworks (MOFs),and covalent-organic frameworks (COFs) are discussed as highly tunable architectures that begin to mimic the catalytic pockets of enzyme active sites.To achieve the full potential of these catalysts,design principles must emerge based on a combination of deconvoluting measurements to extract intrinsic catalyst properties and more reliable theoretical calculations to predict reaction pathways.

Spatially resolved and multiplexed MicroRNA quantification from tissue using nanoliter well arrays

Spatially resolved gene expression patterns are emerging as a key component of medical studies,including companion diagnostics,but technologies for quantification and multiplexing are limited.We present a method to perform spatially resolved and multiplexed microRNA(miRNA)measurements from formalin-fixed,paraffin-embedded(FFPE)tissue.Using nanoliter well arrays to pixelate the tissue section and photopatterned hydrogels to quantify miRNA,we identified differentially expressed miRNAs in tumors from a genetically engineered mouse model for non-small cell lung cancer(K-ras&(LSL-G12D/+);p53^(fl/fl)).This technology could be used to quantify heterogeneities in tissue samples and lead to informed,biomarker-based diagnostics.

Tailoring Distinct Reactive Environments in Lewis Acid Zeolites for Liquid Phase Catalysis

CONSPECTUS:Lewis acidic zeolites are microporous crystalline materials that offer promise as catalysts for the activation and conversion of biomassderived precursors in the liquid phase due to their unique water tolerance and synthetic versatility.The active site environment in zeolite catalysts is multifaceted in nature and is composed of a primary catalytic binding site,the secondary pore structure that confines such binding sites,and occluded solvent and reactant molecules that interact with adsorbed species.Moreover,Lewis acidic heteroatoms can adopt structurally diverse coordination that selectively catalyze different classes of chemical transformations and can be difficult to control synthetically or characterize spectroscopically.Thus,precise mechanistic interpretation of liquid-phase zeolite catalysis necessitates the development of synthetic,spectroscopic,and kinetic methods that can decouple such complex active site structures and probe the interactions that occur between confined active sites,solvent and reactant molecules,and adsorbed intermediates and transition states.

Electrospinning in membrane contactor:manufacturing Elec-PVDF/SiO2 superhydrophobic surface for efficient flue gas desulphurization applications

In membrane contactors,maintaining a high SO_(2)absorption flux and an excellent wetting resistance are crucial for hazardous gas removal.In this study,we adopted an electrospinning strategy to fabricate highly robust superhydrophobic dual-layer Elec-PVDF/SiO_(2)composite membrane contactors used for flue gas desulfurization.The composite membrane contactor consisted of a durable and ultrathin three-dimensional(3D)superhydrophobic surface and a porous supporting layer,where the formulation was optimized by regulating the PVDF concentration,solvent ratio and SiO_(2)particles content in electrospinning solution.The scanning electronic microscopy(SEM),EDS-mapping,water contact angle(WCA)and surface roughness of as-prepared Elec-PVDF/SiO_(2)composite membrane contactors were conducted to explore the physical and chemical structure.The SiO_(2)nanoparticles were uniformly loaded in ElecPVDF/SiO_(2)composite membrane contactor,and constructed micro-nano dual-coarse lotus-leaf-like morphology,which noticeably elevated surface roughness(Ra).The SiO_(2)nanoparticles also functioned as hydrophobic modifiers,which boosted the WAC up to 155.The SO_(2)absorption fluxes and SO_(2)removal efficiencies were investigated.In particular,the membrane contactor doped with 20 wt%SiO_(2)nanoparticles significantly elevated the stability of desulfurization performance.Besides,the membrane mass transfer coefficient(Km)and corresponding membrane mass transfer resistance(H/Km)were explored.

Evolving simple-to-use method to determine watereoil relative permeability in petroleum reservoirs

In the current research,a new approach constructed based on artificial intelligence concept is introduced to determine water/oil relative permeability at various conditions.To attain an effective tool,various artificial intelligence approaches such as artificial neural network(ANN),hybrid of genetic algorithm and particle swarm optimization(HGAPSO)are examined.Intrinsic potential of feed-forward artificial neural network(ANN)optimized by different optimization algorithms are composed to estimate water/oil relative permeability.The optimization methods such as genetic algorithm,particle swarm optimization and hybrid approach of them are implemented to obtain optimal connection weights involved in the developed smart technique.The constructed intelligent models are evaluated by utilizing extensive experimental data reported in open literature.Results obtained from the proposed intelligent tools were compared with the corresponding experimental relative permeability data.The average absolute deviation between the model predictions and the relevant experimental data was found to be less than 0.1%for hybrid genetic algorithm and particle swarm optimization technique.It is expected that implication of HGAPSO-ANN in relative permeability of water/oil estimation leads to more reliable water/oil relative permeability predictions,resulting in design of more comprehensive simulation and further plans for reservoir production and management.