The ALCF user community continually pushes the boundaries of scientific computing, producing groundbreaking studies in chemistry, materials science, biology, and astrophysics. Below, we highlight some of the recent results published by ALCF users.

"Microfluidic Digital Twin for Enhanced Single-Cell Analysis," The International Conference on Computer Science 2025

ALCF principal investigator (PI): Amanda Randles, Duke University

Advancing single-cell analysis requires tools that not only enable precise experimental measurements but also offer predictive capabilities to guide device optimization and expand experimental possibilities. In this paper, the authors address this need by leveraging ALCF supercomputing resources to develop a digital twin framework for mechano-node-pore sensing (mechano-NPS), a high-throughput microfluidic platform for single-cell analysis. By creating a virtual replica that integrates models of fluid dynamics and cellular behavior, the digital twin serves as a critical tool for both device development and hypothesis exploration. The foundation of the digital twin was established by accurately modeling the fluid dynamics within the mechano-NPS device, with ALCF-enabled simulations at various inlet pressures verified against analytical solutions, and the digital twin’s performance was validated against experimental data. This framework not only demonstrates the potential to enhance the mechano-NPS platform but also exemplifies how digital twins can transform experimental approaches in cellular biology.

"Quantum Mechanical Dataset of 836k Neutral Closed-Shell Molecules with Up to 5 Heavy Atoms from C, N, O, F, Si, P, S, Cl, Br," Scientific Data

ALCF PI: Anouar Benali, Chembricks

The authors leverage ALCF resources to introduce the Vector-QM24 (VQM24) dataset, comprehensively covering all possible neutral closed-shell small organic and inorganic molecules with up to five heavy (p-block) atoms: C, N, O, F, Si, P, S, Cl, Br. All valid stoichiometries, Lewis-rule-consistent graphs, and stable conformers were enumerated combinatorially, yielding 577k conformational isomers spanning 258k constitutional isomers and 5,599 unique stoichiometries. Density functional theory optimizations were performed for all, and diffusion quantum Monte Carlo energies are provided for 10,793 lowest-energy conformers with up to 4 heavy atoms. VQM24 includes structures, vibrational modes, rotational constants, thermodynamic properties, and electronic properties such as atomization, electron interaction, exchange-correlation, dispersion energies, multipole moments, alchemical potentials, Mulliken charges, and wavefunctions. Machine learning models of atomization energies on this dataset reveal significantly higher complexity than QM9, with none achieving chemical accuracy. VQM24 offers a rigorous, high-fidelity benchmark for evaluating quantum machine learning models.

"Channels of Stellar-Mass Black Hole Formation," The Astrophysical Journal

ALCF PI: Adam Burrows, Princeton University

Based on a large collection of detailed 3D core-collapse supernova simulations carried out on ALCF supercomputers, the authors identify four channels of stellar-mass black hole formation. Their examples include the formation of black holes in energetic asymmetric supernova explosions, a modest supernova explosion that nevertheless leaves behind a black hole, and an aborted core-collapse explosion. The authors speculate that the statistics and prevalence of these various channels depend not only on still-evolving supernova theory, but also on unresolved issues with the theory of massive star evolution, binary interaction, wind mass loss, metallicity, and the nuclear equation of state. Importantly, they suggest, but do not prove, that the silent channel for black hole formation may not be the dominant formation modality.

"High-Throughput Screening of Altermagnetic Materials," Physical Review Materials

ALCF PI: Trevor Rhone, Rensselaer Polytechnic Institute

Altermagnets are a special class of magnetic materials that exhibit an unusual combination of features from both ferromagnets and antiferromagnets: they have zero net magnetization (i.e., antiferromagnetic properties) with electronic bands that are not Kramers spin degenerate. This offers the possibility of generating spin-polarized currents without the stray magnetic fields associated with ferromagnets, making them ideal candidates for potential applications in quantum computing and energy-efficient spintronic devices. In this paper, the authors investigate a well-known altermagnet form, using high-throughput density functional theory calculations carried out on ALCF supercomputers. Promising candidates are determined by analyzing their preferred magnetic ordering and spin degeneracy. The magnetic ground states of the altermagnet candidates are then confirmed using spin-spiral calculations. Based on the presence of Kramers degeneracy in the band structure, the candidate structures are classified as 𝑑-wave and 𝑔-wave altermagnets.

If your team has a recent publication that used ALCF resources, please let us know by contacting us at pubs@alcf.anl.gov.