Probing the limits of forward screening and inverse design of crystal materials

Key numbers

• 4.5% of its crystal-property pairs
• 428 GPa

Caveats

• Preprint; not yet peer reviewed.

Crystal materials are designed either by screening known crystals for a target property or by generating new crystals with that property. Both routes are judged against public databases of known crystals, but these databases name the same crystal differently. Several materials announced as new by recent generative and autonomous discovery campaigns have since proved to be known phases or close variants of them. The limits of both routes remain unmeasured. Here we probe them by matching the crystals of 55 databases by structure into one self-extending database of 14.6 million crystals and 131.8 million property values, each traced to its source. Only 4.5% of its crystal-property pairs carry a value. To fill the empty pairs, we developed CGTNet, an equivariant graph transformer with state-of-the-art accuracy on several tasks of two public benchmarks. Trained on each task, it forms a library of property models whose predictions we release. The reach of forward screening has been underestimated. Known crystals hold tens of thousands of ultra-incompressible candidates without a recorded bulk modulus, and a post hoc audit of synthesis evidence finds among them ReN2, whose bulk modulus was measured at 428 GPa. The novelty claimed for inverse design has been overestimated. At an equal verification budget, a stiffness-conditioned generator returned more stiff hits than screening (100 versus 55), but all contained osmium and 82 repeated recorded compositions. Integrating and completing the databases of known crystals therefore moves the limits of both routes: it widens what screening can reach and sets the reference against which generated crystals are judged new.

Zhilong Song, Zijun Pang, Lixue Cheng

Leverage3 / 5

A method or resource many groups across the field will adopt within a year.

18% of this desk’s rubric

Magnitude3 / 5

Large gain: roughly 2x, or a clear new state of the art on a hard, unsaturated problem.

20% of this desk’s rubric

Evidence3 / 5

Solid: multiple benchmarks or cohorts, ablations, fair baselines, released code or data.

22% of this desk’s rubric

Novelty2 / 5

A new combination of known ideas.

22% of this desk’s rubric

Trajectory2 / 5

Some room to improve with obvious engineering.

10% of this desk’s rubric

Stakes2 / 5

Benefits a professional community (practitioners, clinicians, engineers).

8% of this desk’s rubric

No attention signals recorded yet.

• Reviewed by heuristic-v10 on Oct 26, 2026, 07:29 UTC. Paper type: empirical.
• Categories: cond-mat.mtrl-sci, cs.LG
• BRIEF, No.5 in the Physics edition of October 26, 2026.