Energy efficiency and sustainability of AI data processing in Data Centres (IA)

Expected Outcome: Pilots for new technologies and a demonstration site which contribute to energy-efficient and sustainable AI data processing in data centres, reinforcing EU strategic autonomy and climate goals. Project results are expected to contribute to one or more of the following outcomes (see more details in scope): Demonstrated innovations that substantially improve heat removal from high-power AI chips (e.g. direct on-chip cooling, advanced thermal interface materials, multi-scale thermal management), enabling higher performance without thermal throttling. This should lead to lower cooling energy needs and higher reliability for dense AI workloads. Prototypes of novel backup power systems (such as graphene-enhanced batteries) that operate with minimal cooling requirements, improving data centre resilience and enabling better use of renewable power. New methods and frameworks th… devamı

Computer sciences, information science and bioinformaticsCloud computingEdge computingdata centre technologiesenergy efficiency

1. %45
   MUHAMMED ARSLAN

   Doktor Öğretim ÜyesiAfyon Kocatepe Üniversitesi

   Ortak konular: Thermodynamic and Exergetic Analyses of Power and Cooling Systems · Hybrid Renewable Energy Systems · Integrated Energy Systems Optimization

   Örtüşen yayınlar: Thermoeconomic Optimization of a Geothermal-Assisted Hybrid LNG and Power Generation System: Simulation, Performance Assessment, and Sustainability Insights (2025) · Design and Optimization of Multigeneration Biogas Power Plant Using Waste Heat Recovery System: A Case Study with Energy, Exergy, and Thermoeconomic Approach of Power, Cooling and Heating (2022)

2. %45
   YUNUS EMRE YÜKSEL

   ProfesörAfyon Kocatepe Üniversitesi

   Ortak konular: Thermodynamic and Exergetic Analyses of Power and Cooling Systems · Hybrid Renewable Energy Systems · Integrated Energy Systems Optimization · Solar Thermal and Photovoltaic Systems

   Örtüşen yayınlar: Performance assessment of a solar tower based multigeneration system with thermal energy storage (2019) · Double-flash geothermal plant: clean energy, hydrogen, and cooling solutions (2025)

3. %43
   TOLGA TANER

   ProfesörAksaray Üniversitesi

   Ortak konular: Thermodynamic and Exergetic Analyses of Power and Cooling Systems · Hybrid Renewable Energy Systems · Electrocatalysts for Energy Conversion

   Örtüşen yayınlar: Parametric Study of Energy, Exergy And Thermoeconomic Analyses On Vapor-Compression System Cascaded With Libr/Water and Nh3/Water Absorbtion Cascade Refrigeration Cycle (2017) · Application of trigeneration with direct co-combustion of poultry waste and coal: A case study in the poultry industry from Turkey (2018)

4. %40
   BURAK AKTEKELİ

   Doktor Öğretim ÜyesiBilecik Şeyh Edebali Üniversitesi

   Ortak konular: Solar Thermal and Photovoltaic Systems · Adsorption and Cooling Systems

   Örtüşen yayınlar: Design and analysis of new solar‐powered sustainable dryers: Alfalfa crop (2023) · Drying efficiency enhancement in zucchini (Cucurbita pepo L.) using infrared heater film and algorithm-based control (2026)

5. %40
   MEHMET BALTA

   Öğretim Görevlisi (ders Vermekle Görevli)Amasya Üniversitesi

   Ortak konular: Solar Thermal and Photovoltaic Systems · Adsorption and Cooling Systems · Building Energy and Comfort Optimization

   Örtüşen yayınlar: Effect of inner channel geometry on solidification performance of phase change material (PCM) in double-pipe thermal energy storage (2023) · INVESTIGATION INTO ENERGY SAVINGS IN THE RENEWAL OF THE LIGHTING SYSTEM IN UNIVERSITY CAMPUS BUILDINGS (2019)

Uyum oranı kodla, her istekte hesaplanır. Çağrı metni (başlık, anahtar kelimeler, resmi açıklamanın başı) şu üç kaynakla karşılaştırılır: akademisyen profiliyle anlamsal yakınlık (%50), YÖKSİS anahtar kelimeleri ve OpenAlex konularındaki ortak ayırt edici terimler (%25) ve yayın içeriği — başlıklar, İngilizce özetler ve bunların Türkçe çevirileri (%25). Çeviriler sayesinde Türkçe çağrılar İngilizce yayınlarla da eşleşir. Yaygın kelimeler düşük ağırlıklıdır; %40 altı gösterilmez. Bir konu önerisidir; başvuru uygunluğu, kapasite ya da başarı değerlendirmesi değildir. Gizli profiller listelenmez.