Gaussian Process Based Model to Optimize Additively Manufactured Powder Microstructures From Phase Field Modeling

A persistent problem in the selective laser sintering process is to maintain the quality of additively manufactured parts, which can be attributed to the various sources of uncertainty. In this work, a two-particle phase-field microstructure model has been analyzed. The sources of uncertainty as the two input parameters were surface diffusivity and inter-particle distance. The response quantity of interest (QOI) was selected as the size of the neck region that develops between the two particles. Two different cases with equal and unequal sized particles were studied. It was observed that the neck size increased with increasing surface diffusivity and decreased with increasing inter-particle distance irrespective of particle size. Sensitivity analysis found that the inter-particle distance has more influence on variation in neck size than that of surface diffusivity. The machine learning algorithm Gaussian Process Regression was used to create the surrogate model of the QOI. Bayesian Optimization method was used to find optimal values of the input parameters. For equal-sized particles, optimization using Probability of Improvement provided optimal values of surface diffusivity and inter-particle distance as 23.8268 and 40.0001, respectively. The Expected Improvement as an acquisition function gave optimal values 23.9874 and 40.7428, respectively. For unequal sized particles, optimal design values from Probability of Improvement were 23.9700 and 33.3005, respectively, while those from Expected Improvement were 23.9893 and 33.9627, respectively. The optimization results from the two different acquisition functions seemed to be in good agreement.

A Deep Water Dispersion Experiment in the Gulf of Mexico

<p>The Deep Water Horizon oil spill has dramatically impacted the Gulf of Mexico from the seafloor to the surface. While dispersion of contaminants at the surface has been extensively studied, little is known about deep water dispersion properties. This study describes the results of the Deep Water Dispersion Experiment (DWDE), which consisted in the release of surface drifters and RAFOS floats drifting at 300 and 1500 dbar in the Gulf of Mexico. We show that surface diffusivity is elevated, and decreases with depth. The separation dependence of relative diffusivity follows a Richardson law at all depths. Time dependence of dispersion suggests a Richardson regime near the surface and a mixed Richardson/ballistic regime in depth at scales of [10-100 km]. Finite Scale Lyapunov Exponents and pair separation Kurtosis suggest the existence of a Lundgren regime at scales smaller than the Rossby radius near the surface, and at smaller scales in depth.</p>

High-Selectivity Growth of GaN Nanorod Arrays by Liquid-Target Magnetron Sputter Epitaxy

Selective-area grown, catalyst-free GaN nanorod (NR) arrays grown on Si substrates have been realized using liquid-target reactive magnetron sputter epitaxy (MSE). Focused ion beam lithography (FIBL) was applied to pattern Si substrates with TiNx masks. A liquid Ga target was sputtered in a mixture gas of Ar and N2, ranging the N2 partial pressure (PN₂) ratio from 100% to 50%. The growth of NRs shows a strong correlation with PN₂ on the selectivity, coalescence, and growth rate of NRs in both radial and axial directions. The growth rate of NRs formed inside the nanoholes increases monotonically with PN₂. The PN₂ ratio between 80% and 90% was found to render both a high growth rate and high selectivity. When the PN₂ ratio was below 80%, multiple NRs were formed in the nanoholes. For a PN₂ ratio higher than 90%, parasitic NRs were grown on the mask. An observed dependence of growth behavior upon the PN₂ ratio is attributed to a change in the effective Ga/N ratio on the substrate surface, as an effect of impinging reactive species, surface diffusivity, and residence time of adatoms. The mechanism of NR growth control was further investigated by studying the effect of nanoholes array pitch and growth temperature. The surface diffusion and the direct impingement of adatoms were found to be the dominant factors affecting the lateral and axial growth rates of NR, respectively, which were well elucidated by the collection area model.

A Fractal-Based Correlation for Time-Dependent Surface Diffusivity in Porous Adsorbents

Fluid–solid adsorption processes are mostly governed by the adsorbate transport in the solid phase and surface diffusion is often the limiting step of the overall process in microporous materials such as zeolites. This work starts from a concise review of concepts and models for surface transport and variable surface diffusivity. It emerges that the phenomenon of hindered surface diffusion for monolayer adsorption, which is common in zeolites, and models able to fit a non-monotonic trend of surface diffusivity against adsorbate solid phase concentration, have received limited attention. This work contributes to the literature of hindered diffusion by formulating a time-dependent equation for surface diffusivity based on fractal dynamics concepts. The proposed equation takes into account the contributions of both fractal-like diffusion (a time-decreasing term) and hopping diffusion (a time-increasing term). The equation is discussed and numerically analyzed to testify its ability to reproduce the possible different patterns of surface diffusivity vs. time.

Silver SERS Adenine Sensors with a Very Low Detection Limit

The detection of adenine molecules at very low concentrations is important for biological and medical research and applications. This paper reports a silver-based surface-enhanced Raman scattering (SERS) sensor with a very low detection limit for adenine molecules. Clusters of closely packed silver nanoparticles on surfaces of discrete ball-like copper bumps partially covered with graphene are deposited by immersion in silver nitrate. These clusters of silver nanoparticles exhibit abundant nanogaps between nanoparticles, where plasmonic coupling induces very high local electromagnetic fields. Silver nanoparticles growing perpendicularly on ball-like copper bumps exhibit surfaces of large curvature, where electromagnetic field enhancement is high. Between discrete ball-like copper bumps, the local electromagnetic field is low. Silver is not deposited on the low-field surface area. Adenine molecules interact with silver by both electrostatic and functional groups and exhibit low surface diffusivity on silver surface. Adenine molecules are less likely to adsorb on low-field sensor surface without silver. Therefore, adenine molecules have a high probability of adsorbing on silver surface of high local electric fields and contribute to the measured Raman scattering signal strength. We demonstrated SERS sensors made of clusters of silver nanoparticles deposited on discrete ball-like copper bumps with very a low detection limit for detecting adenine water solution of a concentration as low as 10−11 M.

Estimating and leveraging protein diffusion on ion-exchange resin surfaces

Protein mobility at solid–liquid interfaces can affect the performance of applications such as bioseparations and biosensors by facilitating reorganization of adsorbed protein, accelerating molecular recognition, and informing the fundamentals of adsorption. In the case of ion-exchange chromatographic beads with small, tortuous pores, where the existence of surface diffusion is often not recognized, slow mass transfer can result in lower resin capacity utilization. We demonstrate that accounting for and exploiting protein surface diffusion can alleviate the mass-transfer limitations on multiple significant length scales. Although the surface diffusivity has previously been shown to correlate with ionic strength (IS) and binding affinity, we show that the dependence is solely on the binding affinity, irrespective of pH, IS, and resin ligand density. Different surface diffusivities give rise to different protein distributions within the resin, as characterized using confocal microscopy and small-angle neutron scattering (length scales of micrometer and nanometer, respectively). The binding dependence of surface diffusion inspired a protein-loading approach in which the binding affinity, and hence the surface diffusivity, is modulated by varying IS. Such gradient loading increased the protein uptake efficiency by up to 43%, corroborating the importance of protein surface diffusion in protein transport in ion-exchange chromatography.

THE KINETICS OF CaO ASSISTED PATTUKKU CHARCOAL STEAM GASIFICATION

Coal is a solid fuel that can be converted into syngas through gasification process. To obtain optimum gasification process design and operation, in-depth understanding of the influential parameters is required. This study aims to investigate the effect of temperature on the gasification process and to obtain its kinetics parameters. The study was carried out in a tubular reactor equipped with a heater and a condenser. Steam was used as gasifying agent, while CaO was employed as a CO2 adsorbent. The charcoal from coal was subjected to gasification at temperatures of 600°C, 700°C, and 800°C. The ratio of charcoal and CaO was 1:1. The gasification process lasted for 60 minutes with gas sample was taken every 15 minutes for composition analysis. The results showed that a temperature increase of 100°C caused a proportional increase of conversion of about 75% higher. The value of activation energy (Ea) and exponential factor (ko) were 46.645kJ/mole and 328.3894/min, respectively. For mass transfer parameters, values of activation energy for surface diffusion (Es) and surface diffusivity factor (as) were 81.126 kJ/mole and 0.138/min, respectively. Keywords: gasification; mathematical model; Pattukku coal char; steam; Thin Reaction Zone Model

Nanoporous Copper Fabricated by Dealloying Mn–Cu Precursors with Minor Nickel Element Addition and Heat Treatment Coarsening

Nanoporous copper (NPC) and nanoporous copper-nickel (NPC-Ni) can be prepared by free corrosion dealloying Mn[Formula: see text]Cu[Formula: see text]Nix ([Formula: see text], 1, 3[Formula: see text]at.% Ni) precursor alloys. Microscopic morphology characterization by scanning electron microscopy exhibited a three-dimensional bicontinuous porous structure with nanoscale ligaments and pores. NPC with a pore size of 48.7[Formula: see text]nm was obtained in 0.1[Formula: see text]M hydrochloric acid solution for 3.5[Formula: see text]h dealloyed at 25[Formula: see text]C. Under the same free corrosion dealloying condition, NPC-Ni1 and NPC-Ni3 were obtained with the pore size of 36.6[Formula: see text]nm and 28.1[Formula: see text]nm, respectively. The results indicate that minor Ni atoms addition to the precursor greatly refined the dealloyed nanoporous structure. This effect could be attributed to the lower Ni surface diffusivity than that of Cu and resulted in slow down of the diffusion and rearrangement of Cu atoms during dealloying process. Post-dealloying heat treatment at 300[Formula: see text]C, 450[Formula: see text]C and 600[Formula: see text]C made the ligaments coarsen in NPC and NPC-Ni.