Droplet morphology analysis of drop-on-demand inkjet printing

As an accurate 2D/3D fabrication tool,inkjet printing technology has great potential in preparation of micro electronic devices.The morphology of droplets produced by the inkjet printer has a great impact on the accuracy of deposition.In this study,the drop-on-demand(DoD)inkjet simulation model was established,and the accuracy of the simulation model was verified by corresponding experiments.The simulation result shows that the velocity of the droplet front and tail,as well as the time to disconnect from the nozzle is mainly affected by density(ρ),viscosity(μ)and surface tension(σ)of droplets.When the liquid filament is about to disconnect from the nozzle,the filament length and filament front velocity are found to have a linear correlation withσ/ρμand ln(ρ/(μσ1/2)).

Characterization of termetallic Pt-Ir-Au catalysts for NO decomposition

A termetallic catalyst of Pt-Ir-Au/Al2O3 for NOx decomposition was prepared by loading the metallic colloids in C2H5OH-H2O solution and a surfactant of polyvinyl pyrrolidone.Compared with an impregnated Pt/Al2O3 catalyst,the termetallic catalyst of PtIrAu811/Al2O3,with a Pt：Ir：Au atomic ratio of 8：1：1,exhibited higher NO decomposition and selectivity to N2.Transmission electron microscopy and X-ray diffraction were conducted to clarify the state of the supported metals and indicate three precious metals alloyed on the catalyst.In the study of NO-temperature programmed desorption,oxygen desorption on the PtIrAu811 catalyst shifted to the low temperature side compared to that on Pt/Al2O3,which correlated well with its higher catalytic performance in NO decomposition.

Surface Activities of Calix [4]resorcinarenes Bearing Four Hydrophobic Chains and Its Solubilization for Organic Compounds

Calix resorcinarenes bearing four hydrophobic side chains ( Ar-Rn, Ar-Ph, and Ar-N) orient stably on water oil interface and show high solubilization capacities for organic compounds, such as long chain alcohols, benzene, toluene and dyes. The capacities are high even near the cmc of polyalkylated calix resorcinarenes, but the solubilities of organic compounds(solubilizates) decrease with the increase of the size of the solubilizates. Ar-R 6, with a chain length of six carbons, is the most effective among Ar-R n , Ar-Ph, and Ar-N; 11 fold mol of hexanol is dissolved in 2×10 -3 mol/L Ar-R 6. Moreover, Ar-R n bearing four alkyl side chains solubilizes the chain alcohols of the same chain length mostly. The solubilization capacities are presumably brought by inclusion in a large cavity of the polyalkylated calix resorcinarenes and by an efficient orientation of the solubilizates.

Synthesis of Highly ordered Large Size Mesoporous Silica and Effect of Stabilization as Enzyme Supports in Organic Solvent

FSM 16, MCM 41 and SBA 15 types of hexagonal mesoporous silica with a highly ordered 2 dimensional structure were synthesized by using different silicon sources and surfactants. In the 2 dimensional silicate framework, pore size can be uniformly controlled by the combined use of the surfactants having different alkyl chain lengths and the swelling agents(triisopropyl benzene). The pore diameter of FSM 16 and MCM 41 can be expanded to be 10 nm, SBA 15 to be 15 nm. The crystal regularity was decreased with the increase of the pore diameter. In FSM 16 derived from kanemite(silicon source) and MCM 41 from water glass, their anionic characteristics on the pore wall may be stronger than those of SBA 15 derived from oligomeric tetramethoxysilane(TMOS). We have successfully used FSM 16 and MCM 41 to immobilize the enzyme having cationic residues below isoelectric point. The level of adsorption of enzymes in FSM 16 and MCM 41 was relatively high, but was low in SBA 15 support. The mechanism of enzyme to be adsorbed in mesoporous silica was suggested to be the ionic interactions. In aqueous solutions, horseradish peroxidase(HTP) was immobilized in FSM 16 with 8.9 nm mesopores and the highest loading amount(183 mg/mg FSM) was obtained, but for the FSM 16 of pore diameter 30 nm only an amount of 28 mg/mg FSM was obtained. The catalytic activity in the organic solvent was high when HRP was immobilized in FSM 16 and MCM 41, but it was low in case of SBA 15.

Creation of crystal structure reproducing X-ray diffraction pattern without using database

When a sample’s X-ray diffraction pattern(XRD)is measured,the corresponding crystal structure is usually determined by searching for similar XRD patterns in the database.However,if a similar XRD pattern is not found,it is tremendously laborious to identify the crystal structure even for experts.This case commonly happens when researchers develop novel and complex materials.In this study,we propose a crystal structure creation scheme that reproduces a given XRD pattern.We employed a combinatorial inverse design method using an evolutionary algorithm and crystal morphing(Evolv&Morph)supported by Bayesian optimization,which maximizes the similarity of the XRD patterns between target one and those of the created crystal structures.For sixteen different crystal structure systems with twelve simulated and four powder target XRD patterns,Evolv&Morph successfully created crystal structures with the same XRD pattern as the target(cosine similarity 99%for the simulated ones and>96%the experimentally measured ones).Furthermore,the present method has merits in that it is an automated crystal structure creation scheme,not dependent on a database.We believe that Evolv&Morph can be applied not only to determine crystal structures but also to design materials for specific properties.

Artificial-intelligence-assisted mass fabrication of nanocantilevers from randomly positioned single carbon nanotubes

Nanoscale cantilevers(nanocantilevers)made from carbon nanotubes(CNTs)provide tremendous benefits in sensing and electromagnetic applications.This nanoscale structure is generally fabricated using chemical vapor deposition and/or dielectrophoresis,which contain manual,time-consuming processes such as the placing of additional electrodes and careful observation of single-grown CNTs.Here,we demonstrate a simple and Artificial Intelligence(Al)-assisted method for the effcient fabrication of a massive CNT-based nanocantilever.We used randomly positioned single CNTs on the substrate.The trained deep neural network recognizes the CNTs,measures their positions,and determines the edge of the CNT on which an electrode should be clamped to form a nanocantilever.Our experiments demonstrate that the recognition and measurement processes are automatically completed in 2 s,whereas comparable manual processing requires 12 h.Notwithstanding the small measurement error by the trained network(within 200 nm for 90%of the recognized CNTs),more than 34 nanocantilevers were successfully fabricated in one process.Such high accuracy contributes to the development of a massive field emitter using the CNT-based nanocantilever,in which the output current is obtained with a low applied voltage.We further showed the benefit of fabricating massive CNT-nanocantilever-based field emitters for neuromorphic computing.The activation function,which is a key function in a neural network,was physically realized using an individual CNT-based field emitter.The introduced neural network with the CNT-based field emitters recognized handwritten images successfully.We believe that our method can accelerate the research and development of CNT-based nanocantilevers for realizing promising future applications.

Efects of amine, amine salt and amide on the behaviour of carbon dioxide absorption into calcium hydroxide suspension to precipitate calcium carbonate

The amount of carbon dioxide （CO2） absorption and calcium ion （Ca^2＋） concentration besides the pH of aqueous solution were observed during the COz absorption to precipitate calcium carbonate （CaCO3） from calcium hydroxide （Ca（OH）2）. A reaction rate-limiting effect of an amount of CO2 absorption without any organic additives in the early stage of the precipitation was observed, which was attributed to an interruption effect of bicarbonate ion （HCO3） on the precipitation of CaCO3. The improvement for the reaction rate was achieved not only by amine additives but also by neutral additives such as ε-caprolactam or amine salt. When the hexamethylene diamine was dissolved in the solution, successive change of crystal forms of CaCO3 aragonite to calcite in aqueous suspensions, confirmed by Ca^2＋ concentration change and X-ray diffraction, was concluded that a local environment around the amine group in aqueous solution and an interaction of the diamine with precipitated CaCO3 particles were important factors for these reactions.

Thermal transport and phase transitions of zirconia by on-the-fly machine-learned interatomic potentials

Machine-learned interatomic potentials enable realistic finite temperature calculations of complex materials properties with firstprinciples accuracy.It is not yet clear,however,how accurately they describe anharmonic properties,which are crucial for predicting the lattice thermal conductivity and phase transitions in solids and,thus,shape their technological applications.Here we employ a recently developed on-the-fly learning technique based on molecular dynamics and Bayesian inference in order to generate an interatomic potential capable to describe the thermodynamic properties of zirconia,an important transition metal oxide.This machine-learned potential accurately captures the temperature-induced phase transitions below the melting point.We further showcase the predictive power of the potential by calculating the heat transport on the basis of Green–Kubo theory,which allows to account for anharmonic effects to all orders.This study indicates that machine-learned potentials trained on the fly offer a routine solution for accurate and efficient simulations of the thermodynamic properties of a vast class of anharmonic materials.

Dynamic microstructure evolution and mechanical properties of dilute Mg-Al-Ca-Mn alloy during hot rolling

The dynamic microstructure and texture of dilute Mg-0.50Al-0.71Ca-0.33Mn(wt.%) during hot rolling at two slab temperatures were investigated by electron backscattered diffraction(EBSD) and high resolution transmission electron microscopy(HRTEM). The results show that the development of the rolling microstructures is to first form {10–12} extension twins in the original grains, thereby forming the extension-twinned regions, and then to further form {10–11}-{10–12} double twins and kinks in the extension-twinned regions, and finally to form continuous dynamic recrystallized(continuous DRXed)grains in the double twins and the cross parts of the shear-deformed coarse extension-twinned regions.These extension twins, double twins and kinks show a decisive effect on the formation of rolling texture.The number of {10–11}-{10–12} double twins and resultant the continuous DRX process are strongly affected by the rolling slab temperature and the reduction thickness per pass. By optimizing the rolling conditions, texture and microstructures of the multi-pass rolled Mg-Al-Ca-Mn alloy sheets are successfully modified. Although the total alloy content is only 1.5 wt.%, these Mg-Al-Ca-Mn alloy sheets show much higher strength than the commercial Mg-3Al-1 Zn(wt.%)(AZ31B) sheet.

Topology optimization based on reduction methods with applications to multiscale design and additive manufacturing

Advanced manufacturing processes such as additive manufacturing offer now the capability to control material placement at unprecedented length scales and thereby dramatically open up the design space.This includes the considerations of new component topologies as well as the architecture of material within a topology offering new paths to creating lighter and more efficient structures.Topology optimization is an ideal tool for navigating this multiscale design problem and leveraging the capabilities of advanced manufacturing technologies.However,the resulting design problem is computationally challenging as very fine discretizations are needed to capture all micro-structural details.In this paper,a method based on reduction techniques is proposed to perform efficiently topology optimization at multiple scales.This method solves the design problem without length scale separation,i.e.,without iterating between the two scales.Ergo,connectivity between space-varying micro-structures is naturally ensured.Several design problems for various types of micro-structural periodicity are performed to illustrate the method,including applications to infill patterns in additive manufacturing.

Structure of polyelectrolyte brushes studied by coarse grain simulations

As an example of a very low friction system,Monte Carlo Brownian dynamics simulations have been used to calculate equilibrium structures of a polyelectrolyte brush grafted onto planes.The polymers were calculated in a semi-flexible coarse-grain model that is appropriate to treat the charge density of the polyion.The effect of linear charge density on the polyionx,the surface negative charge,and added salts were studied.In salt-free solution,scaling theories predicted the structure well in the lowxregion.In the highxregion,additional shrinkage was found from the theories due to counterion condensation.The effect of surface charge showed not only the repulsion of the polyion from the surface but also the shrinkage in the highxregion due to the additional counterions required for electrical neutrality.The addition of salts led to the shrinkage of the brush heights,and in the highxregion,additional extension was found.The computational strategy for calculating the friction dynamics of the system is also discussed.

Gas Transport Properties in Gas Diffusion Layers:A Lattice Boltzmann Study

The lattice Boltzmann method is applied to the investigations of the diffusivity and the permeability in the gas diffusion layer(GDL)of the polymer electrolyte fuel cell(PEFC).The effects of the configuration of water droplets,the porosity of the GDL,the viscosity ratio of water to air,and the surface wettability of the GDL are investigated.From the simulations under the PEFC operating conditions,it is found that the heterogeneous water network and the high porosity improve the diffusivity and the permeability,and the hydrophobic surface decreases the permeability.