{"id":12,"date":"2022-03-29T07:47:17","date_gmt":"2022-03-29T07:47:17","guid":{"rendered":"https:\/\/www.res.cmb.ac.lk\/physics\/dilanga-siriwardane\/?page_id=12"},"modified":"2026-03-02T08:17:52","modified_gmt":"2026-03-02T02:47:52","slug":"research","status":"publish","type":"page","link":"https:\/\/www.res.cmb.ac.lk\/physics\/dilanga-siriwardane\/research\/","title":{"rendered":"Research"},"content":{"rendered":"<p data-start=\"0\" data-end=\"594\">Our research group, <a href=\"https:\/\/www.res.cmb.ac.lk\/physics\/matinforai\/\"><strong data-start=\"20\" data-end=\"34\">MatInforAI<\/strong><\/a>, operates at the intersection of materials science, computational modeling, and artificial intelligence, with a strong focus on the discovery and design of next-generation functional materials. We investigate advanced electrode materials for Li-, Na-, and Mg-ion batteries, spintronic materials for magnetic memory and spin-based electronic devices, semiconductor materials for optoelectronic and nanoelectronic applications, and mechanically robust materials designed to withstand extreme conditions such as high pressure, temperature, and mechanical stress.<\/p>\n<p data-start=\"596\" data-end=\"1029\">Our research is grounded in first-principles methodologies, particularly Density Functional Theory (DFT), using computational platforms such as <span class=\"hover:entity-accent entity-underline inline cursor-pointer align-baseline\"><span class=\"whitespace-normal\">Quantum ESPRESSO<\/span><\/span> and <span class=\"hover:entity-accent entity-underline inline cursor-pointer align-baseline\"><span class=\"whitespace-normal\">Pymatgen<\/span><\/span>. Through these tools, we analyze the structural, electronic, magnetic, mechanical, and electrochemical properties of graphene-based systems, MXenes, and other emerging low-dimensional and functional materials.<\/p>\n<p data-start=\"1031\" data-end=\"1596\" data-is-last-node=\"\" data-is-only-node=\"\">Beyond simulation-driven investigations, we integrate machine learning and materials informatics strategies to accelerate materials discovery and predictive modeling. By combining data-driven techniques\u2014including regression models, deep neural networks, and graph neural networks\u2014with computational materials science, our group seeks to uncover fundamental structure\u2013property relationships. Ultimately, we aim to develop sustainable, high-performance materials that address critical technological challenges in energy, electronics, and advanced engineering systems.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Our research group, MatInforAI, operates at the intersection of materials science, computational modeling, and artificial intelligence, with a strong focus [&hellip;]<\/p>\n","protected":false},"author":40,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/www.res.cmb.ac.lk\/physics\/dilanga-siriwardane\/wp-json\/wp\/v2\/pages\/12"}],"collection":[{"href":"https:\/\/www.res.cmb.ac.lk\/physics\/dilanga-siriwardane\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.res.cmb.ac.lk\/physics\/dilanga-siriwardane\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.res.cmb.ac.lk\/physics\/dilanga-siriwardane\/wp-json\/wp\/v2\/users\/40"}],"replies":[{"embeddable":true,"href":"https:\/\/www.res.cmb.ac.lk\/physics\/dilanga-siriwardane\/wp-json\/wp\/v2\/comments?post=12"}],"version-history":[{"count":5,"href":"https:\/\/www.res.cmb.ac.lk\/physics\/dilanga-siriwardane\/wp-json\/wp\/v2\/pages\/12\/revisions"}],"predecessor-version":[{"id":159,"href":"https:\/\/www.res.cmb.ac.lk\/physics\/dilanga-siriwardane\/wp-json\/wp\/v2\/pages\/12\/revisions\/159"}],"wp:attachment":[{"href":"https:\/\/www.res.cmb.ac.lk\/physics\/dilanga-siriwardane\/wp-json\/wp\/v2\/media?parent=12"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}