scholarly journals Advanced Characterization and Modification of Nanoporous Metals

2021 ◽  
Author(s):  
Roger C. Newman ◽  
AmirHossein Foroozan Ebrahimy
Keyword(s):  
Advanced Characterization ◽  
Nanoporous Metals

Advanced characterization of Perovskite systems: Understanding and improving the performance and stability of photovoltaic devices

2017 ◽  
Author(s):  
Pia Dally ◽  
Noella Lemaitre ◽  
Stéphanie Pouget ◽  
Stéphane Cros ◽  
Serge Gambarelli ◽  
...  
Keyword(s):  
Advanced Characterization ◽  
Photovoltaic Devices

Nanoscale Capacitance and Capacitance-Voltage Curves for Advanced Characterization of Electrical Properties of Si and GaN Structures Using Scanning Microwave Impedance Microscopy

2016 ◽  
Author(s):  
Stuart Friedman ◽  
Oskar Amster ◽  
Yongliang Yang ◽  
Fred Stanke
Keyword(s):  
Process Development ◽  
Advanced Characterization ◽  
Electrical Measurement ◽  
Depletion Layer ◽  
Doped Semiconductors ◽  
Force Microscopy ◽  
Nano Scale ◽  
Capacitance Voltage ◽  
Systematic Response ◽  
Lock In

Abstract The use of Atomic Force Microscopy (AFM) electrical measurement modes is a critical tool for the study of semiconductor devices and process development. A relatively new electrical mode, scanning microwave impedance microscopy (sMIM), measures a material’s change in permittivity and conductivity at the scale of an AFM probe tip [1]. sMIM provides the real and imaginary impedance (Re(Z) and Im(Z)) of the probe-sample interface. By measuring the reflected microwave signal as a sample of interest is imaged with an AFM, we can in parallel capture the variations in permittivity and conductivity and, for doped semiconductors, variations in the depletion-layer geometry. An existing technique for characterizing doped semiconductors, scanning capacitance microscopy, modulates the tip-sample bias and detects the tip-sample capacitance with a lock-in amplifier. A previous study compares sMIM to SCM and highlights the additional capabilities of sMIM [2], including examples of nano-scale capacitance-voltage curves. In this paper we focus on the detailed mechanisms and capabilities of the nano-scale C-V curves and the ability to extract semiconductor properties from them. This study includes analytical and finite element modeling of tip bias dependent depletion-layer geometry and impedance. These are compared to experimental results on reference samples for both doped Si and GaN doped staircases to validate the systematic response of the sMIM-C (capacitive) channel to the doping concentration.

Physical - Chemical Issues of Cephalosporin Intercalated Nanoparticles for Life - Threatening Infections Treatment

2001 ◽  
Vol 71 (3) ◽  
pp. 342-349
Author(s):  
Lucian Eva ◽  
Letitia Doina Duceac ◽  
Liviu Stafie ◽  
Constantin Marcu ◽  
Geta Mitrea ◽  
...  
Keyword(s):  
Chemical Characterization ◽  
Advanced Characterization ◽  
Generation Cephalosporin ◽  
Fourth Generation ◽  
Exchange Method ◽  
Physico Chemical ◽  
Life Threatening ◽  
Double Hydroxide ◽  
Double Hydroxides

The fourth generation cephalosporin antibacterial agent, cefepime, was loaded into layered double hydroxides for enhancing antibiotic efficiency, reducing side effects, as well as achieving the sustained release property. The intercalation of antibiotic into the inter-gallery of ZnAl-layered double hydroxide (LDH) was carried out using ion exchange method, by this constituting a nano-sized organic-inorganic hybrid material for a controlled release novel formulation. Although cefepime is a broad spectrum antibiotic, it has various adverse effects and a significant degradation rate. Thus, the preparation and physico-chemical characterization of nanomaterials able to intercalate this drug is an important study for medical and pharmaceutical field. The antibiotic inclusion into LDHs nanostructure was confirmed by advanced characterization techniques and the release profile of cefepime was analysed with the respect to pH of the simulated media.

Dendrites in Solid‐State Batteries: Ion Transport Behavior, Advanced Characterization, and Interface Regulation

2021 ◽  
pp. 2003250
Author(s):  
Zhenjiang Yu ◽  
Xueyan Zhang ◽  
Chuankai Fu ◽  
Han Wang ◽  
Ming Chen ◽  
...  
Keyword(s):  
Solid State ◽  
Ion Transport ◽  
Advanced Characterization ◽  
Transport Behavior ◽  
Solid State Batteries

Metal–Organic Frameworks in Italy: From synthesis and advanced characterization to theoretical modeling and applications

2021 ◽  
Vol 437 ◽  
pp. 213861
Author(s):  
Giorgio Mercuri ◽  
Giuliano Giambastiani ◽  
Corrado Di Nicola ◽  
Claudio Pettinari ◽  
Simona Galli ◽  
...  
Keyword(s):  
Metal Organic Frameworks ◽  
Advanced Characterization ◽  
Theoretical Modeling ◽  
Metal Organic

scholarly journals Advanced Characterization of Additively Manufactured 316L Stainless Steel for Nuclear Applications

2021 ◽  
Vol 27 (S1) ◽  
pp. 2160-2161
Author(s):  
Lingfeng He ◽  
Laura Hawkins ◽  
Jingfan Yang ◽  
Xiang Liu ◽  
Miao Song ◽  
...  
Keyword(s):  
Stainless Steel ◽  
316L Stainless Steel ◽  
Advanced Characterization ◽  
Nuclear Applications

scholarly journals A Strategy for Dimensionality Reduction and Data Analysis Applied to Microstructure–Property Relationships of Nanoporous Metals

Materials ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 1822
Author(s):  
Norbert Huber
Keyword(s):  
Machine Learning ◽  
Dimensionality Reduction ◽  
Work Hardening ◽  
Large Range ◽  
Scaling Law ◽  
Principal Component ◽  
Underlying Structure ◽  
Structure Property ◽  
Work Hardening Rate ◽  
Nanoporous Metals

Nanoporous metals, with their complex microstructure, represent an ideal candidate for the development of methods that combine physics, data, and machine learning. The preparation of nanporous metals via dealloying allows for tuning of the microstructure and macroscopic mechanical properties within a large design space, dependent on the chosen dealloying conditions. Specifically, it is possible to define the solid fraction, ligament size, and connectivity density within a large range. These microstructural parameters have a large impact on the macroscopic mechanical behavior. This makes this class of materials an ideal science case for the development of strategies for dimensionality reduction, supporting the analysis and visualization of the underlying structure–property relationships. Efficient finite element beam modeling techniques were used to generate ~200 data sets for macroscopic compression and nanoindentation of open pore nanofoams. A strategy consisting of dimensional analysis, principal component analysis, and machine learning allowed for data mining of the microstructure–property relationships. It turned out that the scaling law of the work hardening rate has the same exponent as the Young’s modulus. Simple linear relationships are derived for the normalized work hardening rate and hardness. The hardness to yield stress ratio is not limited to 1, as commonly assumed for foams, but spreads over a large range of values from 0.5 to 3.

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