MOFBuilder: Automated end-to-end modeling ofMOF dynamics for high-throughput screening

The vast chemical design space of Metal–Organic Frameworks (MOFs) offersunparalleled opportunities for targeted materials design, yet computationalscreening remains largely restricted to static structure derived from the CIFfile. We introduce MOFBuilder, a modular end-to-end pipeline that leveragesmolecular-level identities to automatically generate chemically consistent, molec-ular dynamics (MD) ready MOF models, flexibly supporting periodic, defective,cluster, and slab representations. By eliminating the manual effort typicallyrequired for model preparation, the pipeline enables a seamless construction ofcomplex systems ranging from large-scale bio-hybrid interfaces to functionalizedhigh-throughput libraries. As proof of the need for high-throughput dynamicmodeling, we show that dynamic screening is necessary to circumvent the "Poros-ity Paradox". Several functionalized UiO-66 variants classified as non-porous bystatic geometric analysis exhibit significant CO2 uptake through gate-openingmechanisms captured only via MD. By enabling the high-throughput generationof consistent, dynamic datasets, MOFBuilder addresses a critical gap in discoverypipelines and provides the foundation for more predictive, data-driven materialsdesign.