You are invited to use Elsevier’s artificial intelligence search tool Scopus AI

January 2, 2025
We are pleased to announce that in 2025 VILNIUS TECH community members will have the opportunity to use the Scopus AI tool.

This tool can be accessed from the Scopus database (from local University’s network, through a VPN service or with personal Scopus user account; more information >>>, in the tab “General information” -> “Scopus user account“):

Scopus AI – is Elsevier's intuitive and intelligent search tool, powered by generative artificial intelligence. One of the most important advantages of Scopus AI, which distinguishes it from many other generative AI tools, is the reliability of the used data. This reliability is ensured by only using scientific publications that are indexed in the Scopus database.

Scopus AI tool is able to:

  • Generate a concise answer to user's query, along with a list of sources and their references in the text, which is based on information contained in the abstracts and metadata of publications indexed in Scopus.
  • Expand on the initial response by generating a broader summary of the topic.
  • Provide lists of a topic’s foundational and associated publications.
  • Provide a list of most prominent experts on a topic.
  • Create an interactive concept map and generate a concise text about the connections between various research topics.
  • Help discover established, emerging, and novel research topics.
  • Suggest additional queries for deeper analysis of a topic.
More information about Scopus AI >>> and its use >>>

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VILNIUS TECH Library invites you to follow the published new dissertations. The dissertation „Analysis and modeling of deformations induced by the extrusion of fiber-reinforced polymers“ prepared at VILNIUS TECH by Mahmoud Samy Mahmoud Mohammed Farh. The dissertation was prepared in 2021–2026. Scientific consultant – Prof. Dr Viktor Gribniak. The dissertation was defended at the public meeting of the Dissertation Defense Council of the Scientific Field of Materials Engineering in the Aula Doctoralis Meeting Hall of Vilnius Gediminas Technical University at 2 p.m. on 10 June 2026. Additive manufacturing via fused filament fabrication (FFF) enables the creation of geometrically complex components. Yet, its use in structural and semi‑structural applications remains limited by anisotropic mechanical response, defect sensitivity, and fabrication‑induced residual stresses that cause warpage and geometric inaccuracy. This dissertation investigates polylactic acid (PLA)- based materials manufactured by FFF, including neat and partially recycled PLA, continuously reinforced PLA, and short-fiber-reinforced composites, to develop an integrated experimental-computational methodology for evaluating mechanical efficiency and predicting process-induced distortion. The research object comprises the mechanical, thermal, viscoelastic, microstructural, and thermo‑mechanical characteristics of these materials. The dissertation develops a unified approach linking reinforcement strategy, material structure, thermal history, mechanical performance, and warpage behavior. The adopted methodology combines quasi‑static tensile and flexural testing, thermomechanical characterization, scanning electron microscopy, and finite-element simulations. Continuous aramid reinforcement developed in this study for FFF increases the load-bearing capacity of the tension specimens by 67%. Still, reinforcement efficiency was limited by toolpath continuity, interfacial defects, and the absence of in‑process fiber tensioning. Short‑fiber-reinforced composites exhibit distinct fiber‑type‑dependent behavior: carbon‑filled PLA increases stiffness, while wood‑filled PLA enhances crystallinity, stiffness retention near the glass‑transition temperature, toughness, and dimensional fidelity. Wood‑fiber reinforcement reduces edge warpage by 43% and carbon fiber by 14.3% under identical conditions. A staged thermo‑mechanical simulation framework is developed to model printing, cooling, and detachment, transferring residual stress and distortion fields into subsequent mechanical simulations. The ABAQUS model for neat PLA predicts warpage with an average error of 8.2–10.6%, whereas a Digimat workflow captures the deformation in short‑fiber-reinforced PLA with an error of 14.3–17.9%. The latter predictions were obtained for the first time. The dissertation consists of an introduction, three main chapters, general conclusions, and references. The First Chapter provides a literature review of FFF of reinforced polymers, including material combination and modeling strategies. The Second Chapter specifies the chosen materials, test program, and thermo mechanical modeling concept. The Third Chapter evaluates experimental and numerical results, integrating mechanical, thermal, microstructural, and simulation based findings. The General Conclusions summarize the dissertation work, which is supported by four publications, including three articles in Web of Science indexed journals with impact factors, and four conference presentations. Doctoral dissertation readers can search via VILNIUS TECH Virtual Library.    
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