Enhancement of Low Temperature Superionic Conductivity by Suppression of Li Site Ordering in Li7Si2-xGexS7I.

Ge4+ substitution into the recently discovered superionic conductor Li7Si2S7I is demonstrated by synthesis of Li7Si2-xGexS7I, where x ≤ 1.2. The anion packing and tetrahedral silicon location of Li7Si2S7I are retained upon substitution. Single crystal X-ray diffraction shows that substitution of larger Ge4+ for Si4+ expands the unit cell volume and further increases Li+ site disorder, such that Li7Si0.88Ge1.12S7I has one Li+ site more (sixteen in total) than Li7Si2S7I. The ionic conductivity of Li7Si0.8Ge1.2S7I (x = 1.2) at 303 K is 1.02(3) × 10-2 S cm-1 with low activation energies for Li+ transport demonstrated over a wide temperature range by AC impedance and 7Li NMR spectroscopy. All sixteen Li+ sites remain occupied to temperatures as low as 30 K in Li7Si0.88Ge1.12S7I as a result of the structural expansion. This differs from Li7Si2S7I, where the partial Li+ site ordering observed below room temperature reduces the ionic conductivity. The suppression of Li+ site depopulation by Ge4+ substitution retains the high mobility to temperatures as low as 200 K, yielding low temperature performance comparable with state-of-the-art Li ion conducting materials.

Improvement in Accuracy and Concordance of American Society of Anesthesiologist's Physical Status (ASA-PS) Scoring Assignment over a 11 Year Time Period Using Patient BMI as a Comorbidity Finding.

Background: Anesthesia providers categorize patients utilizing the American Society of Anesthesiologists Physical Status (ASA-PS) classification originally created by the ASA in 1941. There is published variability and discordance among providers when assigning patient ASA scores in part due to the subjectivity of scoring utilizing patient medical conditions, but variability is also found using objective findings like BMI. To date, there are few studies evaluating the accuracy of anesthesia providers' ASA assignment based on objective body mass index (BMI) alone. The aim of this retrospective chart review is to determine improvement in accuracy of anesthesia providers to correctly assign patient ASA scores, based on BMI criteria added to the ASA-PS in October of 2014, utilizing a multifaceted strategy including creation of an active finance committee in the fall of 2015, multiple e-mail communications about the updated definitions and recommendations for ASA-PS scoring in the fall of 2015 and spring of 2016, a department grand rounds presentation in February 2016, placement of laminated copies of the ASA definitions and recommendations in the anesthesia chartrooms, and the development of a tool embedded into our EMR providing a recommendation of ASA-PS based on patient comorbidity findings. Methods: After attaining IRB approval, all eligible patients over the age of 18 who had surgical procedures under general anesthesia at Mayo Clinic in Rochester, MN, between January 1, 2010, and December 31, 2020, were retrospectively analyzed. A segmented logistic regression model was used to estimate the trends (per-year change in odds) of ASA under classification according to severity of obesity during 3 epochs: preimplementation (2010-2014), implementation (2015), and postimplementation (2016-2020). Results: A total of 16,467 patients of the 200,423 (8.2%) patients with obesity (class 1, 2, and 3) were underscored based on BMI alone. Accuracy of ASA-PS classification, as it pertains to BMI alone, was found to show meaningful improvement year-to-year following the updated ASA-PS guidelines with examples released in October of 2014 (P < 0.001). Most of the improvement occurred in 2015-2017 with relatively little between-year variability in the rate of underscoring from 2017-2020. Conclusion: Despite updated ASA-PS published guidelines, providers may still be unaware of the updated guidelines and inclusion of examples used within the ASA-PS classification system. Accuracy of scoring did improve annually following the release of the updated guidelines with examples as well as department-wide educational activities on the topic. Additional education and awareness should be offered to those responsible for preanesthesia evaluation and assignment of ASA-PS in patients to improve accuracy as it pertains to BMI.

Synthesis, Structure, and Properties of CuBiSeCl2: A Chalcohalide Material with Low Thermal Conductivity.

Mixed anion halide-chalcogenide materials have recently attracted attention for a variety of applications, owing to their desirable optoelectronic properties. We report the synthesis of a previously unreported mixed-metal chalcohalide material, CuBiSeCl2 (Pnma), accessed through a simple, low-temperature solid-state route. The physical structure is characterized through single-crystal X-ray diffraction and reveals significant Cu displacement within the CuSe2Cl4 octahedra. The electronic structure of CuBiSeCl2 is investigated computationally, which indicates highly anisotropic charge carrier effective masses, and by experimental verification using X-ray photoelectron spectroscopy, which reveals a valence band dominated by Cu orbitals. The band gap is measured to be 1.33(2) eV, a suitable value for solar absorption applications. The electronic and thermal properties, including resistivity, Seebeck coefficient, thermal conductivity, and heat capacity, are also measured, and it is found that CuBiSeCl2 exhibits a low room temperature thermal conductivity of 0.27(4) W K-1 m-1, realized through modifications to the phonon landscape through increased bonding anisotropy.

Statistically Derived Proxy Potentials Accelerate Geometry Optimization of Crystal Structures.

The crystal structures of known materials contain the information about the interatomic interactions that produced these stable compounds. Similar to the use of reported protein structures to extract effective interactions between amino acids, that has been a useful tool in protein structure prediction, we demonstrate how to use this statistical paradigm to learn the effective inter-atomic interactions in crystalline inorganic solids. By analyzing the reported crystallographic data for inorganic materials, we have constructed statistically derived proxy potentials (SPPs) that can be used to assess how realistic or unusual a computer-generated structure is compared to the reported experimental structures. The SPPs can be directly used for structure optimization to improve this similarity metric, that we refer to as the SPP score. We apply such optimization step to markedly improve the quality of the input crystal structures for DFT calculations and demonstrate that the SPPs accelerate geometry optimization for three systems relevant to battery materials. As this approach is chemistry-agnostic and can be used at scale, we produced a database of all possible pair potentials in a tabulated form ready to use.

Accessing Mg-Ion Storage in V2PS10 via Combined Cationic-Anionic Redox with Selective Bond Cleavage.

Magnesium batteries attract interest as alternative energy-storage devices because of elemental abundance and potential for high energy density. Development is limited by the absence of suitable cathodes, associated with poor diffusion kinetics resulting from strong interactions between Mg2+ and the host structure. V2PS10 is reported as a positive electrode material for rechargeable magnesium batteries. Cyclable capacity of 100 mAh g-1 is achieved with fast Mg2+ diffusion of 7.2 × ${\times }$ 10-11-4 × ${\times }$ 10-14 cm2 s-1. The fast insertion mechanism results from combined cationic redox on the V site and anionic redox on the (S2)2- site; enabled by reversible cleavage of S-S bonds, identified by X-ray photoelectron and X-ray absorption spectroscopy. Detailed structural characterisation with maximum entropy method analysis, supported by density functional theory and projected density of states analysis, reveals that the sulphur species involved in anion redox are not connected to the transition metal centres, spatially separating the two redox processes. This facilitates fast and reversible Mg insertion in which the nature of the redox process depends on the cation insertion site, creating a synergy between the occupancy of specific Mg sites and the location of the electrons transferred.

Control of Polarity in Kagome-NiAs Bismuthides.

A 2×2×1 superstructure of the P63/mmc NiAs structure is reported in which kagome nets are stabilized in the octahedral transition metal layers of the compounds Ni0.7Pd0.2Bi, Ni0.6Pt0.4Bi, and Mn0.99Pd0.01Bi. The ordered vacancies that yield the true hexagonal kagome motif lead to filling of trigonal bipyramidal interstitial sites with the transition metal in this family of "kagome-NiAs" type materials. Further ordering of vacancies within these interstitial layers can be compositionally driven to simultaneously yield kagome-connected layers and a net polarization along the c axes in Ni0.9Bi and Ni0.79Pd0.08Bi, which adopt Fmm2 symmetry. The polar and non-polar materials exhibit different electronic transport behaviour, reflecting the tuneability of both structure and properties within the NiAs-type bismuthide materials family.

Inferring energy-composition relationships with Bayesian optimization enhances exploration of inorganic materials.

Computational exploration of the compositional spaces of materials can provide guidance for synthetic research and thus accelerate the discovery of novel materials. Most approaches employ high-throughput sampling and focus on reducing the time for energy evaluation for individual compositions, often at the cost of accuracy. Here, we present an alternative approach focusing on effective sampling of the compositional space. The learning algorithm PhaseBO optimizes the stoichiometry of the potential target material while improving the probability of and accelerating its discovery without compromising the accuracy of energy evaluation.

Superionic lithium transport via multiple coordination environments defined by two-anion packing.

Fast cation transport in solids underpins energy storage. Materials design has focused on structures that can define transport pathways with minimal cation coordination change, restricting attention to a small part of chemical space. Motivated by the greater structural diversity of binary intermetallics than that of the metallic elements, we used two anions to build a pathway for three-dimensional superionic lithium ion conductivity that exploits multiple cation coordination environments. Li7Si2S7I is a pure lithium ion conductor created by an ordering of sulphide and iodide that combines elements of hexagonal and cubic close-packing analogously to the structure of NiZr. The resulting diverse network of lithium positions with distinct geometries and anion coordination chemistries affords low barriers to transport, opening a large structural space for high cation conductivity.

Unveiling the Morphology of Carbon-Supported Ru Nanoparticles by Multiscale Modeling.

Simulating the behavior of metal nanoparticles on supports is crucial for boosting their catalytic performance and various nanotechnology applications; however, such simulations are limited by the conflicts between accuracy and efficiency. Herein, we introduce a multiscale modeling strategy to unveil the morphology of Ru supported on pristine and N-doped graphene. Our multiscale modeling started with the electronic structures of a supported Ru single atom, revealing the strong metal-support interaction around pyridinic nitrogen sites. To determine the stable configurations of Ru2-13 clusters on three different graphene supports, global energy minimum searches were performed. The sintering of the global minimum Ru13 clusters on supports was further simulated by ab initio molecular dynamics (AIMD). The AIMD data set was then collected for deep potential molecular dynamics to study the melting of Ru nanoparticles. This study presents comprehensive descriptions of carbon-supported Ru and develops modeling approaches that bridge different scales and can be applied to various supported nanoparticle systems.

MethMotif.Org 2024: a database integrating context-specific transcription factor-binding motifs with DNA methylation patterns.

MethMotif (https://methmotif.org) is a publicly available database that provides a comprehensive repository of transcription factor (TF)-binding profiles, enriched with DNA methylation patterns. In this release, we have enhanced the platform, expanding our initial collection to over 700 position weight matrices (PWM), all of which include DNA methylation profiles. One of the key advancements in this release is the segregation of TF-binding motifs based on their cofactors and DNA methylation status. We have previously demonstrated that gene ontology (GO) enriched terms associated with TF target genes may differ based on their association with alternative cofactors and DNA methylation status. MethMotif provides precomputed GO annotations for each human TF of interest, as well as for TF-co-TF complexes, enabling a comprehensive analysis of TF functions in the context of their co-factors. Additionally, MethMotif has been updated to encompass data for two new species, Mus musculus and Arabidopsis thaliana, widening its applicability to a broader community. MethMotif stands out as the first and only TF-binding motifs database to incorporate context-specific PWM coupled with epigenetic information, thereby enlightening context-specific TF functions. This enhancement allows the community to explore and gain deeper insights into the regulatory mechanisms governing transcriptional processes.

Cost-effectiveness of nivolumab and ipilimumab versus pembrolizumab and axitinib in advanced renal cell carcinoma with intermediate or poor prognostic risk: a Brazilian private healthcare system perspective.

OBJECTIVE: Nivolumab plus ipilimumab (NIVO + IPI) and pembrolizumab plus axitinib (PEM + AXI) have demonstrated significant clinical benefits as first-line (1 L) treatments for intermediate/poor-risk advanced renal cell carcinoma (aRCC) patients. This study aimed to assess the cost-effectiveness of NIVO + IPI versus PEM + AXI from a Brazilian private healthcare system perspective, utilizing a novel approach to estimate comparative efficacy between the treatments. METHODS: A three-state partitioned survival model (progression-free, progressed, and death) was developed to estimate costs, life-years (LYs), quality-adjusted LYs (QALYs), and the incremental cost-utility ratio (ICUR) over a 40-year time horizon. In the absence of head-to-head comparisons between NIVO + IPI and PEM + AXI, clinical data for NIVO + IPI was obtained from CheckMate 214 (NCT02231749) and for PEM + AXI from KEYNOTE-426 (NCT02853331). A matching-adjusted indirect comparison was conducted to account for the imbalance of treatment effect modifiers between the trials. Patient characteristics, resource use, health state utilities, and costs were based on Brazilian-specific sources. Costs and health outcomes were both discounted by 5% annually in line with Brazilian guidelines. The robustness of the results was evaluated through extensive sensitivity analysis and scenario analyses. RESULTS: When comparing the matched versus unmatched OS, PFS, and TTD curves there was no noteworthy difference. NIVO + IPI was associated with cost savings (R$ 350,232), higher LYs (5.54 vs. 4.61), and QALYs (4.74 vs. 3.76) versus PEM + AXI, resulting in NIVO + IPI dominating PEM + AXI. Key model drivers were the treatment duration for PEM, NIVO, and AXI. NIVO + IPI remained dominant in all scenario analyses, which indicated that model results were robust to alternative modelling inputs or assumptions. CONCLUSIONS: This analysis shows that NIVO + IPI is estimated to be a life-extending and potentially cost-saving 1 L treatment option when compared with PEM + AXI for intermediate/poor-risk a RCC patients in the Brazilian private healthcare system.

Challenges in conducting fractional polynomial and standard parametric network meta-analyses of immune checkpoint inhibitors for first-line advanced renal cell carcinoma.

Aim: Network meta-analyses (NMAs) increasingly feature time-varying hazards to account for non-proportional hazards between different drug classes. This paper outlines an algorithm for selecting clinically plausible fractional polynomial NMA models. Methods: The NMA of four immune checkpoint inhibitors (ICIs) + tyrosine kinase inhibitors (TKIs) and one TKI therapy for renal cell carcinoma (RCC) served as case study. Overall survival (OS) and progression free survival (PFS) data were reconstructed from the literature, 46 models were fitted. The algorithm entailed a-priori face validity criteria for survival and hazards, based on clinical expert input, and predictive accuracy against trial data. Selected models were compared with statistically best-fitting models. Results: Three valid PFS and two OS models were identified. All models overestimated PFS, the OS model featured crossing ICI + TKI versus TKI curves as per expert opinion. Conventionally selected models showed implausible survival. Conclusion: The selection algorithm considering face validity, predictive accuracy, and expert opinion improved the clinical plausibility of first-line RCC survival models.

Optimality guarantees for crystal structure prediction.

Crystalline materials enable essential technologies, and their properties are determined by their structures. Crystal structure prediction can thus play a central part in the design of new functional materials1,2. Researchers have developed efficient heuristics to identify structural minima on the potential energy surface3-5. Although these methods can often access all configurations in principle, there is no guarantee that the lowest energy structure has been found. Here we show that the structure of a crystalline material can be predicted with energy guarantees by an algorithm that finds all the unknown atomic positions within a unit cell by combining combinatorial and continuous optimization. We encode the combinatorial task of finding the lowest energy periodic allocation of all atoms on a lattice as a mathematical optimization problem of integer programming6,7, enabling guaranteed identification of the global optimum using well-developed algorithms. A single subsequent local minimization of the resulting atom allocations then reaches the correct structures of key inorganic materials directly, proving their energetic optimality under clear assumptions. This formulation of crystal structure prediction establishes a connection to the theory of algorithms and provides the absolute energetic status of observed or predicted materials. It provides the ground truth for heuristic or data-driven structure prediction methods and is uniquely suitable for quantum annealers8-10, opening a path to overcome the combinatorial explosion of atomic configurations.

Manipulation of the Structure and Optoelectronic Properties through Bromine Inclusion in a Layered Lead Bromide Perovskite.

One of the great advantages of organic-inorganic metal halides is that their structures and properties are highly tuneable and this is important when optimizing materials for photovoltaics or other optoelectronic devices. One of the most common and effective ways of tuning the electronic structure is through anion substitution. Here, we report the inclusion of bromine into the layered perovskite [H3N(CH2)6NH3]PbBr4 to form [H3N(CH2)6NH3]PbBr4·Br2, which contains molecular bromine (Br2) intercalated between the layers of corner-sharing PbBr6 octahedra. Bromine intercalation in [H3N(CH2)6NH3]PbBr4·Br2 results in a decrease in the band gap of 0.85 eV and induces a structural transition from a Ruddlesden-Popper-like to Dion-Jacobson-like phase, while also changing the conformation of the amine. Electronic structure calculations show that Br2 intercalation is accompanied by the formation of a new band in the electronic structure and a significant decrease in the effective masses of around two orders of magnitude. This is backed up by our resistivity measurements that show that [H3N(CH2)6NH3]PbBr4·Br2 has a resistivity value of one order of magnitude lower than [H3N(CH2)6NH3]PbBr4, suggesting that bromine inclusion significantly increases the mobility and/or carrier concentration in the material. This work highlights the possibility of using molecular inclusion as an alternative tool to tune the electronic properties of layered organic-inorganic perovskites, while also being the first example of molecular bromine inclusion in a layered lead halide perovskite. By using a combination of crystallography and computation, we show that the key to this manipulation of the electronic structure is the formation of halogen bonds between the Br2 and Br in the [PbBr4]∞ layers, which is likely to have important effects in a range of organic-inorganic metal halides.

Highly variable hearing loss due to POU4F3 (c.37del) is revealed by longitudinal, frequency specific analyses.

Genotype-phenotype correlations add value to the management of families with hereditary hearing loss (HL), where age-related typical audiograms (ARTAs) are generated from cross-sectional regression equations and used to predict the audiogram phenotype across the lifespan. A seven-generation kindred with autosomal dominant sensorineural HL (ADSNHL) was recruited and a novel pathogenic variant in POU4F3 (c.37del) was identified by combining linkage analysis with whole exome sequencing (WES). POU4F3 is noted for large intrafamilial variation including the age of onset of HL, audiogram configuration and presence of vestibular impairment. Sequential audiograms and longitudinal analyses reveal highly variable audiogram features among POU4F3 (c.37del) carriers, limiting the utility of ARTAs for clinical prognosis and management of HL. Furthermore, a comparison of ARTAs against three previously published families (1 Israeli Jewish, 2 Dutch) reveals significant interfamilial differences, with earlier onset and slower deterioration. This is the first published report of a North American family with ADSNHL due to POU4F3, the first report of the pathogenic c.37del variant, and the first study to conduct longitudinal analysis, extending the phenotypic spectrum of DFNA15.

Control of Ionic Conductivity by Lithium Distribution in Cubic Oxide Argyrodites Li6+xP1-xSixO5Cl.

Argyrodite is a key structure type for ion-transporting materials. Oxide argyrodites are largely unexplored despite sulfide argyrodites being a leading family of solid-state lithium-ion conductors, in which the control of lithium distribution over a wide range of available sites strongly influences the conductivity. We present a new cubic Li-rich (>6 Li+ per formula unit) oxide argyrodite Li7SiO5Cl that crystallizes with an ordered cubic (P213) structure at room temperature, undergoing a transition at 473 K to a Li+ site disordered F4̅3m structure, consistent with the symmetry adopted by superionic sulfide argyrodites. Four different Li+ sites are occupied in Li7SiO5Cl (T5, T5a, T3, and T4), the combination of which is previously unreported for Li-containing argyrodites. The disordered F4̅3m structure is stabilized to room temperature via substitution of Si4+ with P5+ in Li6+xP1-xSixO5Cl (0.3 < x < 0.85) solid solution. The resulting delocalization of Li+ sites leads to a maximum ionic conductivity of 1.82(1) × 10-6 S cm-1 at x = 0.75, which is 3 orders of magnitude higher than the conductivities reported previously for oxide argyrodites. The variation of ionic conductivity with composition in Li6+xP1-xSixO5Cl is directly connected to structural changes occurring within the Li+ sublattice. These materials present superior atmospheric stability over analogous sulfide argyrodites and are stable against Li metal. The ability to control the ionic conductivity through structure and composition emphasizes the advances that can be made with further research in the open field of oxide argyrodites.

Predicting spinel solid solutions using a random atom substitution method.

Exploration of chemical composition and structural configuration space is the central problem in crystal structure prediction. Even in limiting structure space to a single structure type, many different compositions and configurations are possible. In this work, we attempt to address this problem using an extension to the existing ChemDASH code in which variable compositions can be explored. We show that ChemDASH is an efficient method for exploring a fixed-composition space of spinel structures and build upon this to include variable compositions in the Mn-Fe-Zn-O spinel phase field. This work presents the first basin-hopping crystal structure prediction method that can explore variable compositions.

Cation Disorder and Large Tetragonal Supercell Ordering in the Li-Rich Argyrodite Li7Zn0.5SiS6.

A tetragonal argyrodite with >7 mobile cations, Li7Zn0.5SiS6, is experimentally realized for the first time through solid state synthesis and exploration of the Li-Zn-Si-S phase diagram. The crystal structure of Li7Zn0.5SiS6 was solved ab initio from high-resolution X-ray and neutron powder diffraction data and supported by solid-state NMR. Li7Zn0.5SiS6 adopts a tetragonal I4 structure at room temperature with ordered Li and Zn positions and undergoes a transition above 411.1 K to a higher symmetry disordered F43m structure more typical of Li-containing argyrodites. Simultaneous occupation of four types of Li site (T5, T5a, T2, T4) at high temperature and five types of Li site (T5, T2, T4, T1, and a new trigonal planar T2a position) at room temperature is observed. This combination of sites forms interconnected Li pathways driven by the incorporation of Zn2+ into the Li sublattice and enables a range of possible jump processes. Zn2+ occupies the 48h T5 site in the high-temperature F43m structure, and a unique ordering pattern emerges in which only a subset of these T5 sites are occupied at room temperature in I4 Li7Zn0.5SiS6. The ionic conductivity, examined via AC impedance spectroscopy and VT-NMR, is 1.0(2) × 10-7 S cm-1 at room temperature and 4.3(4) × 10-4 S cm-1 at 503 K. The transition between the ordered I4 and disordered F43m structures is associated with a dramatic decrease in activation energy to 0.34(1) eV above 411 K. The incorporation of a small amount of Zn2+ exercises dramatic control of Li order in Li7Zn0.5SiS6 yielding a previously unseen distribution of Li sites, expanding our understanding of structure-property relationships in argyrodite materials.

An Analysis of 5-Level Version of EQ-5D Adjusting for Treatment Switching: The Case of Patients With Epidermal Growth Factor Receptor T790M-Positive Nonsmall Cell Lung Cancer Treated With Osimertinib.

OBJECTIVES: Treatment switching from control to treatment after disease progression is common in oncology trials. Analyses of survival data typically adjust for this bias, but such adjustments are rarely performed in analyses of patient-reported outcomes. This analysis aimed to examine the impact of adjusting for treatment switching on estimated treatment effects on 5-level version of EQ-5D (EQ-5D-5L) utilities and quality-adjusted life-years (QALYs). The AURA3 trial (NCT02151981) was a randomized controlled trial comparing osimertinib with platinum-based doublet chemotherapy (standard care) in patients with locally advanced or metastatic epidermal growth factor receptor mutant- and T790M-positive nonsmall cell lung cancer whose disease has progressed with previous epidermal growth factor receptor tyrosine kinase inhibitor therapy. METHODS: Descriptive analyses were used to compare treatment arms. The primary analysis used a 2-stage least squares instrumental variable regression to estimate treatment effect adjusting for treatment crossover. Time to deterioration, defined from baseline to minimally important deterioration in EQ-5D-5L utility, was assessed using a rank preserving structural failure time model. RESULTS: Intention-to-treat analysis of imputed data showed incremental QALYs for osimertinib of 0.23 at 60 weeks. Accounting for treatment switching increased this to 0.52 in the primary analysis and to 0.63 QALYs in sensitivity analysis at 150 weeks. Time to deterioration analysis showed longer health-related quality of life maintenance with osimertinib, of 12.76 weeks, although this was at the borderline of statistical significance (acceleration factor, ψ = -0.275; 95% confidence interval -0.50 to 0.00). CONCLUSIONS: This analysis demonstrates methods to adjust for treatment switching in the analysis of EQ-5D-5L from clinical trials. Failure to account for crossover substantially underestimated the QALY gain for osimertinib.

Machine-Learning Prediction of Metal-Organic Framework Guest Accessibility from Linker and Metal Chemistry.

The choice of metal and linker together define the structure and therefore the guest accessibility of a metal-organic framework (MOF), but the large number of possible metal-linker combinations makes the selection of components for synthesis challenging. We predict the guest accessibility of a MOF with 80.5 % certainty based solely on the identity of these two components as chosen by the experimentalist, by decomposing reported experimental three-dimensional MOF structures in the Cambridge Structural Database into metal and linker and then learning the connection between the components' chemistry and the MOF porosity. Pore dimensions of the guest-accessible space are classified into four ranges with three sequential models. Both the dataset and the predictive models are available to download and offer simple guidance in prioritization of the choice of the components for exploratory MOF synthesis for separation and catalysis based on guest accessibility considerations.