Computational Analysis of Structural Defects in Silica Aerogels

MRS Advances ◽  
2019 ◽  
Vol 4 (46-47) ◽  
pp. 2479-2488
Author(s):  
Hunter Gore ◽  
Luis Caldera ◽  
Xiao Shen ◽  
Firouzeh Sabri
Keyword(s):  
Computational Analysis ◽  
Silica Aerogels ◽  
Structural Defects ◽  
Experimental Setup ◽  
Proof Of Concept ◽  
Structural Failure ◽  
Insulating Materials ◽  
Technological Advances ◽  
Defective Region ◽  
Formation Of Cracks

AbstractTechnological advances in synthesis and preparation of aerogels have resulted in formulations that have the mechanical integrity (while retaining flexibility) to be utilized in a broad range of applications and have overcome the initial brittleness that this class of materials was once known for. Both structural and functional aerogels show a drop in performance when subjected to certain cyclic thermal or impact loading due to the wear and formation of cracks, which reduces their lifespan. Here we present the proof-of-concept of a computational toolset that connects the change in thermal profile to structural failure and degradation. In combination with an appropriate finite element (FEM) solver, we have developed a genetic algorithm that can reconstruct the size and shape of the defective region in silica aerogels given the temperatures from a sensor grid. Results show that a heatmap can be used as the foundation for reconstructing faults and defects in thermally insulating materials. Furthermore, the model developed in this study can be expanded to accommodate other material types. Experimental setup can used to benchmark and refine the computational toolset.

Experimental Investigations on the Thermal Conductivity of Silica Aerogels by a Guarded Thin-Film-Heater Method

2009 ◽  
Vol 131 (7) ◽  
Author(s):  
Sandra Spagnol ◽  
Bérangère Lartigue ◽  
Alain Trombe ◽  
Florence Despetis
Keyword(s):  
Thin Film ◽  
Experimental Data ◽  
Thermal Conductivity ◽  
Direct Measurement ◽  
Silica Aerogels ◽  
Experimental Investigations ◽  
Experimental Setup ◽  
Insulating Materials ◽  
Grain Sizes ◽  
Major Interest

A thin-film-heater method is setup to measure the thermal conductivity of super insulating materials such as silica aerogels. The experimental setup is purposely designed for insulating materials and allows direct measurement of the thermal conductivity. Few experimental data are available in the literature concerning thermal conductivity of aerogels even though these materials are of major interest in thermal insulation. More data are necessary in order to understand thermal transport and to validate existing models. Monolithic and granular silica aerogels are investigated. Our experimental technique enables to quantify the influence of important parameters, such as air pressure and distribution of grain sizes, on the insulating performance of this material.

scholarly journals Single-cell biology to decode the immune cellular composition of kidney inflammation

2021 ◽  
Author(s):  
Yu Zhao ◽  
Ulf Panzer ◽  
Stefan Bonn ◽  
Christian F. Krebs
Keyword(s):  
Single Cell ◽  
Cell Biology ◽  
Computational Analysis ◽  
Immune Cell ◽  
Therapeutic Interventions ◽  
Experimental Setup ◽  
Disease Etiology ◽  
Rna Profiling ◽  
Immune Mediated ◽  
Health And Disease

AbstractSingle-cell biology is transforming the ability of researchers to understand cellular signaling and identity across medical and biological disciplines. Especially for immune-mediated diseases, a single-cell look at immune cell subtypes, signaling, and activity might yield fundamental insights into the disease etiology, mechanisms, and potential therapeutic interventions. In this review, we highlight recent advances in the field of single-cell RNA profiling and their application to understand renal function in health and disease. With a focus on the immune system, in particular on T cells, we propose some key directions of understanding renal inflammation using single-cell approaches. We detail the benefits and shortcomings of the various technological approaches outlined and give advice on potential pitfalls and challenges in experimental setup and computational analysis. Finally, we conclude with a brief outlook into a promising future for single-cell technologies to elucidate kidney function.

scholarly journals Mechanical Degradation Analysis of an Amorphous Silicon Solar Module

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4126
Author(s):  
Gilbert Osayemwenre ◽  
Edson Meyer
Keyword(s):  
Solar Cells ◽  
Amorphous Silicon ◽  
Adhesion Force ◽  
Structural Defects ◽  
Mechanical Degradation ◽  
Solar Module ◽  
Photovoltaic Modules ◽  
Degradation Analysis ◽  
Defective Region

This work examines the degradation of photovoltaic modules. It assesses the structural defects of amorphous silicon solar cells, which result from mechanical stress at nanoscale level. Firstly, it analyses the interface morphology, deformation, and internal delamination of a single junction amorphous silicon solar module. Secondly, it explores the interface deformation of the layers of the defective region of the module with some statistical tools including root mean root (RSM) and arithmetic mean (Rq). It used the aforementioned tools to demonstrate the effect of microstructural defects on the mechanical behaviour of the entire layers of the module. The study established that the defect observed in the module, emanated from long-term degradation of the a-Si solar cells after years of exposure to various light and temperature conditions. It tested the mechanism of mechanical degradation and its effect on the reliability and stability of the defective and non-defective regions of the module with adhesion force characterisation.

scholarly journals The revolution of personalized psychiatry: will technology make it happen sooner?

2017 ◽  
Vol 48 (5) ◽  
pp. 705-713 ◽  
Author(s):  
G. Perna ◽  
M. Grassi ◽  
D. Caldirola ◽  
C. B. Nemeroff
Keyword(s):  
Clinical Decision Making ◽  
Clinical Decision ◽  
Machine Learning Techniques ◽  
Proof Of Concept ◽  
Time Data ◽  
New Approach ◽  
Technological Advances ◽  
Learning Techniques ◽  
Personalized Psychiatry ◽  
Smart Wearable

Personalized medicine (PM) aims to establish a new approach in clinical decision-making, based upon a patient's individual profile in order to tailor treatment to each patient's characteristics. Although this has become a focus of the discussion also in the psychiatric field, with evidence of its high potential coming from several proof-of-concept studies, nearly no tools have been developed by now that are ready to be applied in clinical practice. In this paper, we discuss recent technological advances that can make a shift toward a clinical application of the PM paradigm. We focus specifically on those technologies that allow both the collection of massive as much as real-time data, i.e., electronic medical records and smart wearable devices, and to achieve relevant predictions using these data, i.e. the application of machine learning techniques.

scholarly journals Service Design Creating Value for Industrial Corporates through AI Proofs of Concept

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Essi KUURE ◽  
Titta JYLKÄS ◽  
Satu MIETTINEN
Keyword(s):  
Artificial Intelligence ◽  
Case Studies ◽  
Service Design ◽  
Service Development ◽  
Proof Of Concept ◽  
New Ways Of Working ◽  
Technological Advances ◽  
Industrial Service ◽  
Industrial Context

The field of service design has set practices that are useful during servitization transformations intended to help businesses respond to customers’ rising expectations regarding the value of the service experience itself. As businesses increasingly pursue service development alongside product development, they need new ways of working and of evaluating solutions. Simultaneously, technological advances open avenues to new services and ways of interacting with customers. This paper draws on two workshop case studies of artificial intelligence (AI) assistant projects to examine service design in the industrial context. Through these case studies, the paper illustrates how proof of concept (PoC) is used at different project stages and explores how service design can support creation of PoCs in large industrial corporate contexts. The findings reveal the aspects of PoC as embodied experiencing of intangible AI concepts, the creation of PoCs through conversations, and the role of PoCs in industrial service design process.

Fiber Augmented Steel Technology Pipe (FAST-Pipe™): An Alternative to High Strength Steel

2010 ◽  
Author(s):  
Mamdouh M. Salama
Keyword(s):  
High Strength Steel ◽  
Life Cycle Cost ◽  
High Strength Steels ◽  
Performance Testing ◽  
High Strength ◽  
Proof Of Concept ◽  
Long Distance ◽  
Steel Technology ◽  
Technological Advances ◽  
Bending Load

A key imperative to the transportation of natural gas for long distance is the continued technological advances to reduce the development and life cycle cost of high pressure gas pipeline while maintaining the required high level of safety, reliability and environmental stewardship. Therefore, advances in high strength steels such as X100 and X120 have been pursued by several companies. This paper presents an alternative solution namely FAST-Pipe™ (Fiber Augmented Steel Technology - Pipe). The FAST-Pipe™ Concept involves wrapping a conventional strength steel pipe (X70) whose thickness is selected to satisfy axial and bending load requirement with dry fiberglass to achieve the pressure load requirement. The FAST-Pipe™ offers several technical and economical advantages over High strength steel concepts. The paper presents the results of the proof of concept validation program that included cost analysis and performance testing. The paper also summarizes the results of the rigorous qualification program that was implemented subsequent to the successful results of the proof of concept phase.

scholarly journals Computational analysis of thermal and structural failure criteria of a multi-storey steel frame exposed to fire

2019 ◽  
Vol 180 ◽  
pp. 524-543 ◽  
Author(s):  
Egle Rackauskaite ◽  
Panagiotis Kotsovinos ◽  
Ann Jeffers ◽  
Guillermo Rein
Keyword(s):  
Computational Analysis ◽  
Failure Criteria ◽  
Steel Frame ◽  
Structural Failure

Computational Analysis of Historical Hebrew Newspapers: Proof of Concept

Zutot ◽  
2020 ◽  
Vol 17 (1) ◽  
pp. 97-110
Author(s):  
Oren Soffer ◽  
Zef Segal ◽  
Nurit Greidinger ◽  
Sinai Rusinek ◽  
Vered Silber-Varod
Keyword(s):  
Computational Analysis ◽  
Geographical Location ◽  
Morphological Structure ◽  
Proof Of Concept ◽  
Computational Tools ◽  
Specific Term ◽  
Hebrew Language ◽  
Micro Level ◽  
Shed Light

Abstract This article focuses on one decade, 1874–1883, in the relatively long lifespan of the Hebrew weekly Ha-Tzefirah, which was founded in Warsaw in 1862. Applying computational tools to the study of the early Hebrew press requires a unique effort. The Hebrew language in general is distinct in its characters, morphological structure, and word order. The contribution of this proof-of-concept study is two-fold: First, computational analysis provides a long-term indication of trends in the discourse that cannot be attained through qualitative study. The second contribution is on the micro level: Computational analysis can potentially shed light, in a diachronic perspective, on the use of a specific term or the discussion of a specific geographical location.

scholarly journals Molecular representations in AI-driven drug discovery: a review and practical guide

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Laurianne David ◽  
Amol Thakkar ◽  
Rocío Mercado ◽  
Ola Engkvist
Keyword(s):  
Drug Discovery ◽  
High Throughput Screening ◽  
Computational Analysis ◽  
Bioactive Molecules ◽  
Past Century ◽  
Graph Representations ◽  
The Past ◽  
Technological Advances ◽  
Fast Development ◽  
Chemical Representations

Abstract The technological advances of the past century, marked by the computer revolution and the advent of high-throughput screening technologies in drug discovery, opened the path to the computational analysis and visualization of bioactive molecules. For this purpose, it became necessary to represent molecules in a syntax that would be readable by computers and understandable by scientists of various fields. A large number of chemical representations have been developed over the years, their numerosity being due to the fast development of computers and the complexity of producing a representation that encompasses all structural and chemical characteristics. We present here some of the most popular electronic molecular and macromolecular representations used in drug discovery, many of which are based on graph representations. Furthermore, we describe applications of these representations in AI-driven drug discovery. Our aim is to provide a brief guide on structural representations that are essential to the practice of AI in drug discovery. This review serves as a guide for researchers who have little experience with the handling of chemical representations and plan to work on applications at the interface of these fields.

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