The Chinese Academy of Sciences (CAS) announced on 29 September the creation of a new programme intended to deliver “major original research achievements” by organising resources, talent and artificial intelligence around the most profound scientific questions.
Programme aims and initial projects
The initiative, described at a Beijing press conference, is explicitly framed to tackle challenges that could produce a paradigm shift in scientific understanding. CAS vice-president Zhou Qi said the scheme will concentrate on questions that open new frontiers and marshal shared access to large-scale research infrastructure alongside AI-driven methods.
"the programme focuses on major scientific questions that will drive a paradigm shift in research and open up new frontiers"
At the launch CAS unveiled an initial cohort of 10 projects. The announced topics for this first batch include:
- the synthesis of new chemical elements;
- the nature of dark matter and dark energy;
- microscopic measurement of chemical bonds;
- the creation of synthetic cells.
Method: infrastructure, AI and organised teams
CAS officials framed the programme not as a series of isolated grants but as a systemic, institutional approach. Wei Zhixiang, director of the Bureau of Basic Science Research at CAS, said the scheme will deeply integrate coordinated use of major facilities with AI tools, focussing on extremes — the very large, the very small, extreme conditions, and convergent interdisciplinary problems.
The organisers are explicitly inviting leading scientists from inside and outside CAS, and from around the world, to participate and to make use of the CAS network of large-scale facilities, AI platforms and collaborative networks. The stated ambition is to create sustained campaigns of research rather than one-off projects — a shift in operational style that mirrors approaches seen in other nations where big-science infrastructure and computing are pooled to tackle high-risk, high-payoff problems.
Why this matters
There are three reasons this announcement is noteworthy for observers of international science policy:
- Scale and coordination: directing major facilities and AI resources into coherent programmes can accelerate experimental throughput and reduce duplication of effort;
- Research direction: the listed topics — from element synthesis to synthetic cells — indicate an interest in foundational questions across physical and life sciences that could enable future technology;
- International engagement: explicit encouragement of overseas researchers suggests CAS seeks global collaboration, even as it centralises infrastructure domestically.
Initial project areas in brief
| Project focus | Scope (as announced) |
|---|---|
| Synthesis of new elements | Experimental programmes aimed at producing and characterising previously unknown chemical elements |
| Dark matter and dark energy | Investigations into the fundamental constituents and forces shaping the Universe |
| Microscopic measurement of chemical bonds | High-precision measurement techniques for molecular-scale interactions |
| Creation of synthetic cells | Research into the construction and function of cell-like systems from first principles |
Each table entry summarises the fields highlighted by CAS at the press event; the organisation said a further list of priority areas for subsequent project rounds will include physical sciences, life sciences, Earth system sciences and space sciences.
Implications and next steps
The success of such a programme depends on execution: the ability to integrate heterogeneous facilities, to deploy reliable AI methods for experiment design and analysis, and to sustain long-term collaborative teams. CAS has signalled it will use institutional structures to coordinate these elements, but details about funding mechanisms, timelines and how access to major facilities will be allocated were not released at the announcement.
Observers will watch whether the programme fosters open collaboration — including data and method sharing — or whether it leads to more centrally managed, competitive projects. Either outcome could reshape how challenging scientific problems are addressed: broadly accessible, AI-augmented infrastructure can democratise discovery, while concentrated control might speed targeted advances.
For the time being, CAS has set a clear marker: it intends to mobilise significant infrastructure and AI capabilities against a shortlist of ambitious scientific questions. The first 10 projects will be the test case for whether that ambition can be translated into concrete breakthroughs.
