Research themes

schege882 · schege882 · commit 1d93bea860e6 · 2025-02-25T20:14:08.000+03:00
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     <h1>Research Themes</h1>
+    <p> 
+        Material science is a dynamic field at the forefront of innovation bridging fundamental
+        research and practical applications.
+    </p>
     <h2><b>Electronic structure</b></h2>
     <p>
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+        Electronic structure refers to how electrons are arranged within a material, influencing 
+        properties like conductivity and strength of a material. Electronic structure is studied 
+        using methods such as <abbr title="Density Functional Theory">DFT</abbr>.
     </p>
     <br>
     <h2><b>Machine learning</b></h2>
     <p>
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+        Machine learning, a subset of artificial intelligence, involves training algorithms on large
+        datasets to identify patterns and make predictions, reducing the need for extensive experimental 
+        trials. In material science, it is applied to predict crystal structures, material properties, and 
+        discover new materials with specific characteristics. Common algorithms include neural networks, 
+        support vector machines, and random forests. These models are trained on datasets from sources like 
+        the Materials Project, enabling predictions with high accuracy in fields such as superconductivity, 
+        thermoelectrics, and catalysis.
     </p>
     <br>
-    <h2><b>High perfomance computing</b></h2>
+    <h2><b>High throughput computing</b></h2>
     <p>
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+        High throughput calculations involve automating computational processes to screen a large number of 
+        materials or parameter sets efficiently, often using methods like Density Functional Theory (DFT). 
+        The methodology includes setting up and running multiple simulations in parallel, with specific parameters,
+        enabling the identification of promising candidate materials and in turn facilitating focused experimental efforts.
     </p>
-    <h2><b>High throughput computing</b></h2>
+    <br>
+    <h2><b>High perfomance computing</b></h2>
     <p>
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+        HPC involves aggregating computing power to deliver performance far beyond typical desktop computers, essential for 
+        simulations requiring significant processing power, such as quantum mechanical calculations, molecular dynamics, 
+        and large-scale data analysis. It supports parallel processing and is characterized by high-speed processing power,
+        high-performance networks, and large-memory capacity. In material science, HPC is crucial in powering complex simulations
+        such as DFT calculations for electronic structure.
     </p>
     
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