Loading…
Strategic Analysis
This Innovation Action (IA) targets the critical challenge of the escalating energy consumption and environmental footprint of AI data processing in data centres. A winning proposal will demonstrate cutting-edge innovations in thermal management, energy-efficient power backup, and AI-driven data centre optimization, culminating in a robust, open pilot demonstration site. The focus must be on achieving TRL 6-8, showcasing tangible, scalable breakthroughs for European digital sovereignty and sustainability.
TRL 6 → 8
Direct on-chip cooling and thermal management, including novel and innovative cooling techniques applied at chip and module level (direct liquid cooling, heat spreaders, thermal interface materials, and advanced packaging) and multi-scale thermal management techniques.
Energy-efficient power backup and storage systems: Innovations in early-stage energy storage concepts (graphene-enhanced batteries, supercapacitors, and other emerging battery chemistries) and approaches for net-zero backup.
Sustainable data centre architectures and AI workload optimization: addressing AI-driven workload scheduling, adaptive power management, dynamic resource allocation and integration of data centre heat capture and reuse.
Materials research for energy efficiency: Projects to make use of existing research in new materials and components supporting energy efficiency and thermal management, and to employ these for data centres benefit.
Optimisation of data centre operation and functioning: explore AI solutions to optimize the Data centre functioning, computing architecture, and virtualization, minimizing its carbon and environmental footprint.
Integration of data centres into energy systems and the wider region: including solutions that integrate Data centres into energy system planning and operation.
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 that optimise the entire data centre for energy-efficient AI processing. This includes intelligent workload scheduling and AI model optimisation techniques to reduce energy use (e.g. carbon-aware job scheduling and power capping to cut energy demand and peak temperatures), as well as designs for integrating on-site/off-site renewables and waste-heat reuse.
As a result of all the above bullet points, an open pilot demonstration site that allows for the testing and integration of the outcomes of these projects and serves as the European reference for showcasing the breakthroughs and cutting-edge technologies for energy-efficient and sustainable data centres developed under this topic. This site should serve as a model for technology uptake for the European data centre industry.
Developing an agile and secure single market for data and trustworthy AI services is central to Europe’s digital sovereignty and competitiveness.
The convergence of the Telco-Edge-Cloud continuum (3C) with open orchestration platforms will unlock the transformative potential of AI across strategic sectors, from mobility and energy to health and manufacturing, fostering new services and business models.
Building a sovereign Open Internet Stack, rooted in open-source, interoperable and standard-based solutions, will reinforce trust, resilience and innovation, while ensuring Europe retains control over critical digital infrastructures.
Decentralised and federated approaches to AI data processing, combined with breakthroughs in sustainable data centres, will help overcome Europe’s compute bottlenecks and dependencies, and reduce the environmental footprint of AI.
By aligning with the Data Union Strategy and Common European Data Spaces, these efforts will deliver secure, compliant and adaptive data-sharing frameworks that empower citizens, businesses and administrations.
Strengthen Europe’s ability to innovate, scale and lead globally in data and AI, anchoring digital sovereignty in line with EU values and strategic interests.
Data Union Strategy
highThe European Data Strategy, often referred to in broader terms like 'Data Union Strategy', aims to create a single market for data within the EU, enabling its free flow across sectors and Member States for the benefit of businesses, researchers, and public administrations. It seeks to position the EU as a leader in the data economy, ensuring data availability, trustworthiness, and ethical use, while upholding EU values and regulations.
Proposals should demonstrate how they contribute to the overarching goals of the European Data Strategy, particularly by fostering greater data availability, interoperability, and responsible data sharing. For this call focusing on energy efficiency and sustainability of AI data processing in data centres, evaluators will look for how the proposed solutions contribute to a sustainable and efficient data economy, aligning with the strategy's objectives while minimizing environmental impact. This could involve showing how energy-efficient AI processing facilitates the strategy's aims for data utilization in a responsible and environmentally conscious manner.
Common European Data Spaces
highCommon European Data Spaces are a key component of the European Data Strategy, designed to establish secure, trusted, and interoperable environments for data sharing across specific sectors (e.g., health, energy, manufacturing) and Member States. They aim to overcome legal and technical barriers to data sharing, pooling data from diverse sources to fuel innovation, research, and public good, all while ensuring data sovereignty and compliance with EU data protection regulations.
Proposals should clearly articulate how their work contributes to or leverages the principles underpinning Common European Data Spaces. This includes demonstrating how their solutions facilitate secure, trusted, and interoperable data sharing, potentially across different sectors, while adhering to ethical guidelines and robust data governance frameworks. For this call, proposals could highlight how energy-efficient AI data processing contributes to the sustainability and long-term viability of these data spaces, or how data from such spaces could be utilized to optimize energy consumption within data centres, thereby supporting their overall environmental objectives.
1. Admissibility conditions — Proposal page limit and layout described in Annex A and Annex E of the Horizon Europe Work Programme General Annexes. Proposal page limits and layout: described in Part B of the Application Form available in the Submission System.
2. Eligible Countries — described in Annex B of the Work Programme General Annexes. A number of non-EU/non-Associated Countries that are not automatically eligible for funding have made specific provisions for making funding available for their participants in Horizon Europe projects. See the information in the Horizon Europe Programme Guide .
3. Other Eligibility Conditions — In line with the “ restriction on control in innovation actions in critical technology areas ” delineated in General Annex B of the General Annexes, entities established in an eligible country but which are directly or indirectly controlled by China or by a legal entity established in China are not eligible to participate in the action. Subject to restrictions for the protection of European communication networks. Described in Annex B of the Work Programme General Annexes.
4. Financial and operational capacity and exclusion — described in Annex C of the Work Programme General Annexes.
5a. Evaluation and award: Award criteria, scoring and thresholds — To ensure a balanced portfolio coverage, grants will be awarded to applications not only in order of ranking, but also to at least three proposals addressing expected outcomes 1-3 (improve heat removal from high-power AI, novel backup power systems and data centre optimisation for energy-efficient AI processing) and one proposal focussed on offering an open pilot demonstration site, subject to proposals passing all evaluation thresholds. Described in Annex D of the Work Programme General Annexes.
5b. Evaluation and award: Submission and evaluation processes — are described in Annex F of the Work Programme General Annexes and the Online Manual .
5c. Evaluation and award: Indicative timeline for evaluation and grant agreement — described in Annex F of the Work Programme General Annexes.
6. Legal and financial set-up of the grants — described in Annex G of the Work Programme General Annexes.
described in the [specific topic of the Work Programme]
Application form templates — the application form specific to this call is available in the Submission System Standard application form (HE RIA, IA) Evaluation form templates — will be used with the necessary adaptations Standard evaluation form (HE RIA, IA) Guidance HE Programme Guide Model Grant Agreements (MGA) HE MGA Call-specific instructions Ownership Control Declaration Annex
HE Main Work Programme 2026-2027 – 1. General Introduction HE Main Work Programme 2026-2027 – 7. Digital, Industry and Space HE Main Work Programme 2026-2027 – 15. General Annexes HE Programme Guide HE Framework Programme 2021/695 HE Specific Programme Decision 2021/764 EU Financial Regulation 2024/2509 Rules for Legal Entity Validation, LEAR Appointment and Financial Capacity Assessment EU Grants AGA — Annotated Model Grant Agreement Funding & Tenders Portal Online Manual Funding & Tenders Portal Terms and Conditions Funding & Tenders Portal Privacy Statement Guidance on participation in EU calls with ownership and control restrictions
Evaluators will prioritize proposals that clearly demonstrate substantial improvements in heat removal from high-power AI chips (@EO1), novel backup power systems with minimal cooling (@EO2), and new methods for energy-efficient AI processing across the entire data centre (@EO3). Crucially, a strong emphasis will be placed on the establishment of an open pilot demonstration site (@EO4) that serves as a European reference for showcasing these integrated, cutting-edge technologies and facilitating their uptake by the industry. Proposals must show a clear path to TRL 6-8.
Everything the call asks for, seen from the call's point of view. Each line shows what answers it, and which partner carries it.
This matrix lists everything the call asks for: outcomes, impacts, scope, the requirements buried in the call text, and policy alignment. Sign up free and GrantForge tracks each line against the concept you build.
| Requirement | Covered by | Carried | Status |
|---|---|---|---|
| Scope activities | |||
| SC1Direct on-chip cooling and thermal management, including novel and innovative cooling techniques applied at chip and module level (direct liquid cooling, heat spreaders, thermal interface materials, and advanced packaging) and multi-scale thermal management techniques. | · | · | Sign up to track |
| SC2Energy-efficient power backup and storage systems: Innovations in early-stage energy storage concepts (graphene-enhanced batteries, supercapacitors, and other emerging battery chemistries) and approaches for net-zero backup. | · | · | Sign up to track |
| SC3Sustainable data centre architectures and AI workload optimization: addressing AI-driven workload scheduling, adaptive power management, dynamic resource allocation and integration of data centre heat capture and reuse. | · | · | Sign up to track |
| SC4Materials research for energy efficiency: Projects to make use of existing research in new materials and components supporting energy efficiency and thermal management, and to employ these for data centres benefit. | · | · | Sign up to track |
| SC5Optimisation of data centre operation and functioning: explore AI solutions to optimize the Data centre functioning, computing architecture, and virtualization, minimizing its carbon and environmental footprint. | · | · | Sign up to track |
| SC6Integration of data centres into energy systems and the wider region: including solutions that integrate Data centres into energy system planning and operation. | · | · | Sign up to track |
| Expected outcomes | |||
| EO1Demonstrated 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. | · | · | Sign up to track |
| EO2Prototypes 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. | · | · | Sign up to track |
| EO3New methods and frameworks that optimise the entire data centre for energy-efficient AI processing. This includes intelligent workload scheduling and AI model optimisation techniques to reduce energy use (e.g. carbon-aware job scheduling and power capping to cut energy demand and peak temperatures), as well as designs for integrating on-site/off-site renewables and waste-heat reuse. | · | · | Sign up to track |
| EO4As a result of all the above bullet points, an open pilot demonstration site that allows for the testing and integration of the outcomes of these projects and serves as the European reference for showcasing the breakthroughs and cutting-edge technologies for energy-efficient and sustainable data centres developed under this topic. This site should serve as a model for technology uptake for the European data centre industry. | · | · | Sign up to track |
| Other requirements | |||
| No other requirements in this call. | |||
| Expected impacts | |||
| EI1Developing an agile and secure single market for data and trustworthy AI services is central to Europe’s digital sovereignty and competitiveness. | · | · | Sign up to track |
| EI2The convergence of the Telco-Edge-Cloud continuum (3C) with open orchestration platforms will unlock the transformative potential of AI across strategic sectors, from mobility and energy to health and manufacturing, fostering new services and business models. | · | · | Sign up to track |
| EI3Building a sovereign Open Internet Stack, rooted in open-source, interoperable and standard-based solutions, will reinforce trust, resilience and innovation, while ensuring Europe retains control over critical digital infrastructures. | · | · | Sign up to track |
| EI4Decentralised and federated approaches to AI data processing, combined with breakthroughs in sustainable data centres, will help overcome Europe’s compute bottlenecks and dependencies, and reduce the environmental footprint of AI. | · | · | Sign up to track |
| EI5By aligning with the Data Union Strategy and Common European Data Spaces, these efforts will deliver secure, compliant and adaptive data-sharing frameworks that empower citizens, businesses and administrations. | · | · | Sign up to track |
| EI6Strengthen Europe’s ability to innovate, scale and lead globally in data and AI, anchoring digital sovereignty in line with EU values and strategic interests. | · | · | Sign up to track |
| Underlying policies | |||
| POL1european data strategyThe European Data Strategy, often referred to in broader terms like 'Data Union Strategy', aims to create a single market for data within the EU, enabling its free flow across sectors and Member States for the benefit of businesses, researchers, and public administrations. It seeks to position the EU as a leader in the data economy, ensuring data availability, trustworthiness, and ethical use, while upholding EU values and regulations. | · | · | Sign up to track |
| POL2common european data spacesCommon European Data Spaces are a key component of the European Data Strategy, designed to establish secure, trusted, and interoperable environments for data sharing across specific sectors (e.g., health, energy, manufacturing) and Member States. They aim to overcome legal and technical barriers to data sharing, pooling data from diverse sources to fuel innovation, research, and public good, all while ensuring data sovereignty and compliance with EU data protection regulations. | · | · | Sign up to track |
The binding rules of this call. Items marked auto are verified by GrantForge from the call and the template. The others are yours to confirm.
LMIC entities auto-eligible
Low/middle-income country entities are automatically eligible for funding.
EU space data infrastructures
If the project uses satellite-based Earth observation, positioning, navigation or timing data/services, beneficiaries must use Copernicus and/or Galileo/EGNOS. Other sources may be added but not substitute EU infrastructures.
Civil applications only
Horizon Europe funds exclusively civil applications. Research with exclusive military or dual-use application is excluded.
Gender Equality Plan
Having a Gender Equality Plan (GEP) is an eligibility criterion for public bodies, research organisations, and higher education institutions from Member States and Associated Countries.
Open Science
Mandatory open access to peer-reviewed scientific publications and responsible management of research data (FAIR principles, DMP required).
Talk to the Grant Coach to build your concept. The steps below fill in as it takes shape, and your coverage tracks the progress. You can refine everything once your project workspace is created.
Step 1 of 2 · Build your concept
The problems this call frames, and who they affect. Your concept and plan address them.
The increasing demand for AI computing power leads to a significant rise in energy consumption by data centres, contributing to greenhouse gas emissions and environmental degradation.
Current cooling technologies struggle to efficiently dissipate heat from increasingly powerful AI chips, leading to performance limitations (thermal throttling), higher cooling energy demands, and reduced hardware reliability.
Traditional backup power systems for data centres are often energy-intensive, reliant on fossil fuels, and lack the efficiency and minimal cooling requirements needed for truly net-zero and resilient operations, especially when integrating renewables.
Data centres often operate with siloed systems for power, cooling, and workload management, missing opportunities for holistic optimization, waste heat reuse, and seamless integration with broader energy systems, leading to suboptimal energy efficiency.
There is a need for a dedicated, open platform in Europe to test, validate, and showcase advanced energy-efficient and sustainable data centre technologies, hindering industry adoption and Europe's leadership in this critical area.
Entities responsible for the operation, maintenance, and strategic planning of data centre facilities, seeking to improve energy efficiency, reduce operational costs, and enhance sustainability.
Professionals and academic groups involved in developing and deploying AI/ML models and applications, who require high-performance, energy-efficient computing infrastructure.
Companies specializing in the development and supply of advanced cooling solutions, energy storage systems, power management hardware, and novel materials for IT infrastructure.
Organizations managing energy grids and supply, interested in integrating data centres as flexible loads or sources of waste heat for district heating/cooling.
Bodies responsible for shaping digital and environmental policies, setting standards, and promoting sustainable digital infrastructure across Europe.
Academics, researchers, and R&D institutions working on advanced computing, thermal engineering, energy storage, and sustainable IT, seeking to advance knowledge and collaborate on cutting-edge solutions.
The general public benefiting from a more sustainable digital economy, reduced environmental impact of IT, and enhanced digital services.
Step 2 of 2 · Build your concept
The long-term impacts your project should drive — this shapes the objectives next.
The project will significantly decrease the energy consumption and greenhouse gas emissions associated with AI data processing in data centres, contributing to climate change mitigation.
By developing and demonstrating cutting-edge sustainable data centre technologies, Europe will strengthen its position as a global leader in data and AI, reducing dependencies and fostering a secure, agile single market.
Innovations in thermal management, power backup, and workload optimization will lead to substantially more energy-efficient and resilient data centres, reducing operational costs and improving reliability.
The establishment of an open pilot demonstration site will serve as a crucial reference, facilitating the testing, validation, and rapid adoption of new energy-efficient and sustainable data centre solutions by the European industry.
The project will generate new scientific knowledge and foster expertise in advanced thermal management, energy storage, and AI-driven optimization for sustainable data centres, contributing to the European research landscape.