Institution
Missouri University of Science and Technology
Education•Rolla, Missouri, United States•
About: Missouri University of Science and Technology is a education organization based out in Rolla, Missouri, United States. It is known for research contribution in the topics: Artificial neural network & Control theory. The organization has 9380 authors who have published 21161 publications receiving 462544 citations. The organization is also known as: Missouri S&T & University of Missouri–Rolla.
Topics: Artificial neural network, Control theory, Nonlinear system, Ionization, Finite element method
Papers published on a yearly basis
Papers
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19 Jan 2017TL;DR: 3D bioprinting of human adipose stem cells with a polycaprolactone (PCL)/bioactive borate glass composite shows a high potential to create a bioactive, highly angiogenic three-dimensional environment required for complex and dynamic interactions that govern the cell’s behavior in vivo.
Abstract: A major limitation of using synthetic scaffolds in tissue engineering applications is insufficient angiogenesis in scaffold interior. Bioactive borate glasses have been shown to promote angiogenesis. There is a need to investigate the biofabrication of polymer composites by incorporating borate glass to increase the angiogenic capacity of the fabricated scaffolds. In this study, we investigated the bioprinting of human adipose stem cells (ASCs) with a polycaprolactone (PCL)/bioactive borate glass composite. Borate glass at the concentration of 10 to 50 weight %, was added to a mixture of PCL and organic solvent to make an extrudable paste. ASCs suspended in Matrigel were ejected as droplets using a second syringe. Scaffolds measuring 10 x 10 x 1 mm3 in overall dimensions with pore sizes ranging from 100 - 300 μm were fabricated. Degradation of the scaffolds in cell culture medium showed a controlled release of bioactive glass for up to two weeks. The viability of ASCs printed on the scaffold was investigated during the same time period. This 3D bioprinting method shows a high potential to create a bioactive, highly angiogenic three-dimensional environment required for complex and dynamic interactions that govern the cell's behavior in vivo.
112 citations
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TL;DR: In this article, the structures of phosphourus oxynitride glasses have been determined using a combination of solid-state 31P, 15N, and 23Na nuclear magnetic resonance and Raman spectroscopies.
Abstract: The structures of phosphourus oxynitride glasses have been determined using a combination of solid-state 31P, 15N, and 23Na nuclear magnetic resonance and Raman spectroscopies. Raman spectra of model phosphazene compounds with different types of P–N bonding have been used to confirm spectral assignments. Results indicate that nitrogen replaces oxygen in the phosphrus atoms (via one double bond and one single bond) and as nitrogen bonded to three phosphorus atoms via three single bonds. The observed structural features are consistent with data which show that nitrogen influences the chemical durability, thermal expansion, and other properties of phosphate glasses by cross-linking ploymeric phosphate chain to gether in the glass network.
112 citations
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TL;DR: In this paper, the geometry and distribution of droplets for water/polymer ratios from 1 1 to 9 1 1 were investigated using scanning electron microscope techniques, and electron micrographs confirm those models which predicts polyhedral droplet formation at high internal phase ratios.
112 citations
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TL;DR: In this article, the behavior of reinforced concrete (RC) beams strengthened in shear with externally bonded composites was investigated, and two different types of composites were studied: fiber reinforced polymer (FRP) and fiber reinforced cementitious matrix (FRCM) composites.
112 citations
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TL;DR: Two new techniques for microwave imaging of layered structures are introduced to address the limiting issues associated with classical synthetic aperture radar (SAR) imaging techniques in generating focused and properly-positioned images of embedded objects in generally layered dielectric structures.
Abstract: In this paper, two new techniques for microwave imaging of layered structures are introduced. These techniques were developed to address the limiting issues associated with classical synthetic aperture radar (SAR) imaging techniques in generating focused and properly-positioned images of embedded objects in generally layered dielectric structures. The first method, referred to as piecewise SAR (PW-SAR), is a natural extension of the classical SAR technique, and considers physical and electrical properties of each individual layer and the discontinuity among them. Although this method works well with low loss dielectric media, its applicability to lossy media is limited. This is due to the fact that this method does not consider signal attenuation. Moreover, multiple reflections within each layer are not incorporated. To improve imaging performance in which these important phenomena are included, a second method was developed that utilizes the Green's function of the layered structure and casts the imaging approach into a deconvolution procedure. Subsequently, a Wiener filter-based deconvolution technique is used to solve the problem. The technique is referred to as Wiener filter-based layered SAR (WL-SAR). The performance and efficacy of these SAR based imaging techniques are demonstrated using simulations and corresponding measurements of several different layered media.
112 citations
Authors
Showing all 9433 results
Name | H-index | Papers | Citations |
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Robert Stone | 160 | 1756 | 167901 |
Tobin J. Marks | 159 | 1621 | 111604 |
Jeffrey R. Long | 118 | 425 | 68415 |
Xiao-Ming Chen | 108 | 596 | 42229 |
Mark C. Hersam | 107 | 659 | 46813 |
Michael Schulz | 100 | 759 | 50719 |
Christopher J. Chang | 98 | 307 | 36101 |
Marco Cavaglia | 93 | 372 | 60157 |
Daniel W. Armstrong | 93 | 759 | 35819 |
Sajal K. Das | 85 | 1124 | 29785 |
Ming-Liang Tong | 79 | 364 | 23537 |
Ludwig J. Gauckler | 78 | 517 | 25926 |
Rodolphe Clérac | 78 | 506 | 22604 |
David W. Fahey | 77 | 315 | 30176 |
Kai Wang | 75 | 519 | 22819 |