40,741 research outputs found
Inorganic materials in industrial processes
Although inorganic materials represent a small number to the extreme number of the organic ones, they play a number of crucial roles in several processes of industrial interest. Two significant technologically processes have been selected as “case studies” for this presentation: metallic corrosion and its control, and mitigation of inorganic deposits, both related to industrial water systems.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech
Mechanical Properties of Microstructural Components of Inorganic Materials
Disertační práce se zabývá studiem strukturních a mechanických vlastností anorganických materiálů. Cílem je nalezení jednotlivých fází ve zkoumaném materiálu a hlavně lokalizace (mechanicky) nejslabšího místa, jeho ovlivnění a následně výroba materiálu o lepších mechanických vlastnostech. Z důvodu velkého množství použitých metod je základní teorie vložena vždy na začátku příslušné kapitoly. Taktéž z důvodu značného množství výsledků jsou na konci kapitol uvedeny dílčí závěry. Práce je rozdělena na tři části, kdy první se zabývá seznámením s možnostmi modelování mikro-mechanických vlastností a provedením experimentů umožňujících posouzení rozsahu platnosti některého modelu. V druhé části je provedeno shrnutí současných možností indentačních zkoušek pro měření mechanických vlastností strukturních složek betonu a praktické zvládnutí metodiky vhodné k užití pro výzkum materiálů zkoumaných domovským pracovištěm. V třetí části je navržena metoda identifikace nejslabších článků struktury anorganických pojiv a její ověření na konkrétním materiálu zkoumaném na domovském pracovišti. V této dizertační práci jsou použity tyto metody: kalorimetrie, ultrazvukové testování, jednoosá pevnost v tlaku, nanoindentace, korelativní mikroskopie a rastrovací elektronová mikroskopie s energiově disperzním spektrometrem. Dílčími výsledky jsou kompletní charakterizace cementových materiálů, upřesnění stávajících poznatků a nalezení optimálního postupu pro charakterizaci. Hlavním výsledkem je inovativní přístup vedoucí k pozitivnímu ovlivnění materiálu.The doctoral thesis deals with study of structural and mechanical properties of inorganic materials. Goal is to find the weakest (mechanically) phases and interfaces of material. By affecting these structures it should be possible consequently produce a material with better mechanical properties. Due to the large amount of used methods the basic theory is discussed always in the beginning of relevant chapter. Similarly, due to the considerable amount of results every chapter includes partial conclusions. The work is divided in three parts. The first deals with the introduction of the possibilities of modeling micro-mechanical properties and performing of experiments that allow assessment of the scope of some model. In second part itis performed an overview of current possibilities of indentation tests for measuring mechanical properties of structural components of concrete and the practical managing of methods suitable for use for materials research examined at our faculty. In third part the method of identifying the weakest points in structure of inorganic binders is proposed and validation on the particular material examined at our faculty is performed. The methods used in this doctoral thesis are: calorimetry, ultrasonic testing, uniaxial compression, nanoindentation, correlative microscopy and scanning electron microscopy with energy dispersive spectrometer. Partial results are a complete characterization of cementitious materials, specification of existing knowledge and finding the optimal procedure for characterization. The main result is an innovative approach that leads to a positive effect on the material.
Machine learning-guided synthesis of advanced inorganic materials
Synthesis of advanced inorganic materials with minimum number of trials is of
paramount importance towards the acceleration of inorganic materials
development. The enormous complexity involved in existing multi-variable
synthesis methods leads to high uncertainty, numerous trials and exorbitant
cost. Recently, machine learning (ML) has demonstrated tremendous potential for
material research. Here, we report the application of ML to optimize and
accelerate material synthesis process in two representative multi-variable
systems. A classification ML model on chemical vapor deposition-grown MoS2 is
established, capable of optimizing the synthesis conditions to achieve higher
success rate. While a regression model is constructed on the
hydrothermal-synthesized carbon quantum dots, to enhance the process-related
properties such as the photoluminescence quantum yield. Progressive adaptive
model is further developed, aiming to involve ML at the beginning stage of new
material synthesis. Optimization of the experimental outcome with minimized
number of trials can be achieved with the effective feedback loops. This work
serves as proof of concept revealing the feasibility and remarkable capability
of ML to facilitate the synthesis of inorganic materials, and opens up a new
window for accelerating material development
Ceramic-coated boat is chemically inert, provides good heat transfer
Refractory metal foil sprayed with ceramic coating serves as evaporating boat for inorganic materials. The high thermal conductivity of this boat makes it useful with ohmic heaters
Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks
Leveraging new data sources is a key step in accelerating the pace of
materials design and discovery. To complement the strides in synthesis planning
driven by historical, experimental, and computed data, we present an automated
method for connecting scientific literature to synthesis insights. Starting
from natural language text, we apply word embeddings from language models,
which are fed into a named entity recognition model, upon which a conditional
variational autoencoder is trained to generate syntheses for arbitrary
materials. We show the potential of this technique by predicting precursors for
two perovskite materials, using only training data published over a decade
prior to their first reported syntheses. We demonstrate that the model learns
representations of materials corresponding to synthesis-related properties, and
that the model's behavior complements existing thermodynamic knowledge.
Finally, we apply the model to perform synthesizability screening for proposed
novel perovskite compounds.Comment: Added new funding support to the acknowledgments section in this
versio
High-Throughput Identification of Electrides from all Known Inorganic Materials
In this paper, we present the results of a large-scale, high-throughput
computational search for electrides among all known inorganic materials.
Analyzing a database of density functional theory results on more than 60,000
compounds, we identify 69 new electride candidates. We report on all these
candidates and discuss the structural and chemical factors leading to electride
formation. Among these candidates, our work identifies the first
partially-filled 3d transition metal containing electrides Ba3CrN3 and Sr3CrN3;
an unexpected finding that contravenes conventional chemistry.Comment: 5 page manuscript in letter format, 27 page Supplementary Informatio
A metamorphic inorganic framework that can be switched between eight single-crystalline states
The design of highly flexible framework materials requires organic linkers, whereas inorganic materials are more robust but inflexible. Here, by using linkable inorganic rings made up of tungsten oxide (P8W48O184) building blocks, we synthesized an inorganic single crystal material that can undergo at least eight different crystal-to-crystal transformations, with gigantic crystal volume contraction and expansion changes ranging from −2,170 to +1,720 Å3 with no reduction in crystallinity. Not only does this material undergo the largest single crystal-to-single crystal volume transformation thus far reported (to the best of our knowledge), the system also shows conformational flexibility while maintaining robustness over several cycles in the reversible uptake and release of guest molecules switching the crystal between different metamorphic states. This material combines the robustness of inorganic materials with the flexibility of organic frameworks, thereby challenging the notion that flexible materials with robustness are mutually exclusive
Materials processing in space
The feasibility and possible advantages of processing materials in a nongravitational field are considered. Areas of investigation include biomedical applications, the processing of inorganic materials, and flight programs and funding
Thermal Analysis of Inorganic Materials
Traballo presentado ao seminario internacional: Thermal Analysis and Rheology (1. 2003. Ferrol)
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