The Open DAC 2023 Dataset and Challenges for Sorbent Discovery in Direct Air Capture.

Direct air capture (DAC) of CO with porous adsorbents such as metal-organic frameworks (MOFs) has the potential to aid large-scale decarbonization. Previous screening of MOFs for DAC relied on empirical force fields and ignored adsorbed HO and MOF deformation. We performed quantum chemistry calculations overcoming these restrictions for thousands of MOFs.

Gaussian approximation of dispersion potentials for efficient featurization and machine-learning predictions of metal-organic frameworks.

Energy-related descriptors in machine learning are a promising strategy to predict adsorption properties of metal-organic frameworks (MOFs) in the low-pressure regime. Interactions between hosts and guests in these systems are typically expressed as a sum of dispersion and electrostatic potentials. The energy landscape of dispersion potentials plays a crucial role in defining Henry's constants for simple probe molecules in MOFs.

Perioperative symptomatic venous thromboembolism after immediate chemoprophylaxis in patients with pelvic and lower-extremity fractures.

The purpose of this study was to investigate the incidence of symptomatic venous thromboembolism (VTE) after chemoprophylaxis in patients with pelvic and lower-extremity fractures, and to identify risk factors for VTEs in this subgroup of patients. To detect VTE, multi-detector computed tomography (CT) angiography was performed. Of 363 patients assessed, the incidence of symptomatic VTE was 12.

Text Mining Metal-Organic Framework Papers.

We have developed a simple text mining algorithm that allows us to identify surface area and pore volumes of metal-organic frameworks (MOFs) using manuscript html files as inputs. The algorithm searches for common units (e.g.