| 1. |
- Maryam, A., et al.
(författare)
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Preparation and application of LiSiC-oxide for low temperature solid oxide fuel cells
- 2021
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Ingår i: Digest Journal of Nanomaterials and Biostructures. - : VIRTUAL CO PHYSICS SRL. - 1842-3582. ; 16:2, s. 501-508
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Tidskriftsartikel (refereegranskat)abstract
- Semiconductors are well known as excellent materials in the field of exploring novel avenues which combine various fields in electronics, electrochemistry, etc for new functional device concepts. Lithium silicon carbide (LiSiC) is a well-known electrode material for Lithium ion batteries but relatively new for solid oxide fuel cells (SOFCs) and electrolyte-layer free fuel cells (EFFCs). In the present work, we have explored three categories of fuel cells based on mixed LiSiC-SDC (samarium doped ceria) in SOFC and LiSiC as a single component material with type (I) and without coating of a layer of 3C-SiC as EFFC type (II). All of three cells are sandwiched between Ni foams coated with NCAL (Ni0.8Co0.15Al0.05Li-oxide). The electrochemical performances of as prepared fuel cells are tested at 550 degrees C, which is substantially lower than in conventional fuel cell materials. The LiSiC based EFFC type (II) demonstrates better performance because of less ohmic resistance as compared to type (I) have more layers. This indicates that the LiSiC-SDC system has potential for fuel cell development in accordance with energy band structure and alignment.
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| 2. |
- Al-Ansari, Nadhir, 1947-, et al.
(författare)
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Mosul Dam Problem and Stability
- 2021
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Ingår i: Engineering. - USA : Scientific Research Publishing. - 1947-3931 .- 1947-394X. ; 13:3, s. 105-124
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Tidskriftsartikel (refereegranskat)abstract
- Mosul Dam is located on the River Tigris about 60 km northwest Mosul in Iraq. It is the biggest dam where its storage capacity reaches 11.11 billion cubic meters at normal operational level (330 m. above sea level). The dam was constructed on alternating beds of karistified limestone, gypsum and marl. This dam suffered from water seepage under its foundation since its operation in 1986. Grouting operations were implemented since that time to overcome this problem. This seepage is believed to be due to dissolution of gypsum beds under the foundation, which was not carefully considered by the designers. It was recommended by the international board of experts that the water level should be kept at or below 319 m.a.s.l. to minimize damages in case of the failure of the dam. ISIS occupied the dam site on 8 August 2014 and it was seized back from the hands of ISIS on the 16th of the same month. They did plenty of damage despite the short period they occupied the area. After that, the Iraqi Ministry of Water Resources rebuilt the damaged parts and used new grouting and maintenance program. Now, the dam looks very safe at 319 m water level at its reservoir. In addition, the impounding was raised 325 m.a.s.l. for few days and nothing abnormal was noticed.
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| 3. |
- Rasheed, M. N., et al.
(författare)
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Enhanced electrical properties of nonstructural cubic silicon carbide with graphene contact for photovoltaic applications
- 2020
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Ingår i: Digest Journal of Nanomaterials and Biostructures. - Bucharest, Romania : S.C. Virtual Company of Phisics S.R.L. - 1842-3582. ; 15:3, s. 963-972
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Tidskriftsartikel (refereegranskat)abstract
- Cubic silicon carbide (3C-SiC) is successfully synthesized through a simple solid-state reaction technique at a comparatively low temperature without using any catalyst. The XRD data is also used to study other structural parameters of synthesized sample by using different method. Raman peak at 796 cm(-1) supports the XRD results. Si-C vibrational mode observed at 788 cm-1 in the FTIR spectrum further confirms the growth of 3C-SiC. UV-Vis spectroscopy is used to measure optical bandgap energy (E-g = 2.36 eV). Other optical parameters such as dielectric constant and refractive index of grown sample are also studied. Electrical performance is analyzed by using graphene contact with further evaluation of dark and light IV-measurements. The use of graphene contact establishes the enhancement of electrical conductivity of as-grown samples particularly when they are exposed to light. These findings indicate that the grown sample has comparatively better transport properties than conventional metal contacts under the illuminated conditions.
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| 4. |
- Safdar, A., et al.
(författare)
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MoDLF-A Model-Driven Deep Learning Framework for Autonomous Vehicle Perception (AVP)
- 2022
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Ingår i: Proceedings - 25th ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS 2022. - New York, NY, USA : Association for Computing Machinery, Inc. - 9781450394666 ; , s. 187-198
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Konferensbidrag (refereegranskat)abstract
- Modern vehicles are extremely complex embedded systems that integrate software and hardware from a large set of contributors. Modeling standards like EAST-ADL have shown promising results to reduce complexity and expedite system development. However, such standards are unable to cope with the growing demands of the automotive industry. A typical example of this phenomenon is autonomous vehicle perception (AVP) where deep learning architectures (DLA) are required for computer vision (CV) tasks like real-time object recognition and detection. However, existing modeling standards in the automotive industry are unable to manage such CV tasks at a higher abstraction level. Consequently, system development is currently accomplished through modeling approaches like EAST-ADL while DLA-based CV features for AVP are implemented in isolation at a lower abstraction level. This significantly compromises productivity due to integration challenges. In this article, we introduce MoDLF-A Model-Driven Deep learning Framework to design deep convolutional neural network (DCNN) architectures for AVP tasks. Particularly, Model Driven Architecture (MDA) is leveraged to propose a metamodel along with a conformant graphical modeling workbench to model DCNNs for CV tasks in AVP at a higher abstraction level. Furthermore, Model-To-Text (M2T) transformations are provided to generate executable code for MATLAB® and Python. The framework is validated via two case studies on benchmark datasets for key AVP tasks. The results prove that MoDLF effectively enables model-driven architectural exploration of deep convnets for AVP system development while supporting integration with renowned existing standards like EAST-ADL.
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