Computer-aided discovery of a metal-organic framework with superior oxygen uptake

Gallic acid-loaded HFZIF-8 for tumor-targeted delivery and thermal-catalytic therapy

"Transition" metal-coordinated plant polyphenols are a type of promising antitumor nanodrugs owing to their high biosafety and catalytic therapy potency; however, the major obstacle restricting their clinical application is their poor tumor accumulation. Herein, Fe-doped ZIF-8 was tailored using tannic acid (TA) into a hollow mesoporous nanocarrier for gallic acid (GA) loading. After hyaluronic acid (HA) modification, the developed nanosystem of HFZIF-8/GA@HA was used for the targeted delivery of Fe ions and GA, thereby intratumorally achieving the synthesis of an Fe-GA coordinated complex. The TA-etching strategy facilitated the development of a cavitary structure and abundant coordination sites of ZIF-8, thus ensuring an ideal loading efficacy of GA (23.4 wt%). When HFZIF-8/GA@HA accumulates in the tumor microenvironment (TME), the framework is broken due to the competitive protonation ability of overexpressed protons in the TME. Interestingly, the intratumoral degradation of HFZIF-8/GA@HA provides the opportunity for the in situ "meeting" of GA and Fe ions, and through the coordination of polyhydroxyls assisted by conjugated electrons on the benzene ring, highly stable Fe-GA nanochelates are formed. Significantly, owing to the electron delocalization effect of GA, intratumorally coordinated Fe-GA could efficiently absorb second near-infrared (NIR-II, 1064 nm) laser irradiation and transfer it into thermal energy with a conversion efficiency of 36.7%. The photothermal performance could speed up the Fenton reaction rate of Fe-GA with endogenous H2O2 for generating more hydroxyl radicals, thus realizing thermally enhanced chemodynamic therapy. Overall, our research findings demonstrate that HFZIF-8/GA@HA has potential as a safe and efficient anticancer nanodrug.

Double-walled Al-based MOF with large microporous specific surface area for trace benzene adsorption

Double-walled metal-organic frameworks (MOFs), synthesized using Zn and Co, are potential porous materials for trace benzene adsorption. Aluminum is with low-toxicity and abundance in nature, in comparison with Zn and Co. Therefore, a double-walled Al-based MOF, named as ZJU-520(Al), with large microporous specific surface area of 2235 m2 g-1, pore size distribution in the range of 9.26-12.99 Å and excellent chemical stability, was synthesized. ZJU-520(Al) is consisted by helical chain of AlO6 clusters and 4,6-Di(4-carboxyphenyl)pyrimidine ligands. Trace benzene adsorption of ZJU-520(Al) is up to 5.98 mmol g-1 at 298 K and P/P0 = 0.01. Adsorbed benzene molecules are trapped on two types of sites. One (site I) is near the AlO6 clusters, another (site II) is near the N atom of ligands, using Grand Canonical Monte Carlo simulations. ZJU-520(Al) can effectively separate trace benzene from mixed vapor flow of benzene and cyclohexane, due to the adsorption affinity of benzene higher than that of cyclohexane. Therefore, ZJU-520(Al) is a potential adsorbent for trace benzene adsorption and benzene/cyclohexane separation.

Exploring the Potential of Metal-Organic Frameworks for Cryogenic Helium-Based Gas Gap Heat Switches via High-Throughput Computational Screening

With the advantages of a long lifetime and high reliability, gas gap heat switches (GGHSs) are attractive in many thermal management applications, especially in space-borne cryogenic systems. The performance of a GGHS is significantly affected by the adsorption characteristics of the adsorbent in the sorption pump. Compared with the commonly used adsorbent in the GGHSs (activated carbon), metal-organic frameworks (MOFs) have larger surface areas, higher pore volumes, and exceptional tunability, which motivates this study to explore their potential for application in cryogenic GGHSs. To this end, two performance metrics, the required volume of adsorbent (vsor) and total input heat (qtot), were computed for about 6000 MOFs via molecular simulations and compared with those of activated carbon. It is found that over 2300 MOFs possess a smaller vsor than activated carbon, and the smallest vsor of MOFs is about 12.7% of that of activated carbon. vsor and qtot generally change in the same direction, which implies it is possible to reduce both parameters simultaneously by choosing a suitable MOF. Structure-performance analysis reveals that 1/vsor consistently increases first and then decreases with pore limiting diameter, largest cavity diameter, available pore volume, accessible surface area, helium void fraction, and bulk density. Descriptor ranges corresponding to high-performing MOFs were identified based on Precision-Recall analysis. Notably, Zr-containing MOFs are particularly likely to have smaller vsor values than activated carbon. It is anticipated that the promising MOFs identified by this study will motivate further experimental investigations, and the insights into structure-performance relationships can serve to guide the rational design of novel MOF candidates for GGHSs.

Nanomedicines for reversing immunosuppressive microenvironment of hepatocellular carcinoma

Although immunotherapeutic strategies such as immune checkpoint inhibitors (ICIs) have gained promising advances, their limited efficacy and significant toxicity remain great challenges for hepatocellular carcinoma (HCC) immunotherapy. The tumor immunosuppressive microenvironment (TIME) with insufficient T-cell infiltration and low immunogenicity accounts for most HCC patients' poor response to ICIs. Worse still, the current immunotherapeutics without precise delivery may elicit enormous autoimmune side effects and systemic toxicity in the clinic. With a better understanding of the TIME in HCC, nanomedicines have emerged as an efficient strategy to achieve remodeling of the TIME and superadditive antitumor effects via targeted delivery of immunotherapeutics or multimodal synergistic therapy. Based on the typical characteristics of the TIME in HCC, this review summarizes the recent advancements in nanomedicine-based strategies for TIME-reversing HCC treatment. Additionally, perspectives on the awaiting challenges and opportunities of nanomedicines in modulating the TIME of HCC are presented. Acquisition of knowledge of nanomedicine-mediated TIME reversal will provide researchers with a better opportunity for clinical translation of HCC immunotherapy.

Metal-Organic Frameworks for Phthalate Capture

Indoor air contamination by phthalate ester (PAE) derivatives has become a significant concern since traces of PAEs can cause endocrine disruption, among other health issues. PAE abatement from the environment is thus mandatory to further ensure a good quality of indoor air. Herein, we explored the physisorption-based capture of volatile PAEs by metal-organic frameworks (MOFs). A high-throughput computational screening approach was first applied on databases compiling more than 20,000 MOF structures in order to identify the best MOFs for adsorbing traces of dimethyl phthalate (DMP), considered as a representative molecule of the family of PAE contaminants. Among the 20 top candidates, MOF-74(Ni), which combines substantial DMP uptake at the 10 ppm concentration level (∼0.20 g g-1) with high adsorption enthalpy at infinite dilution (-ΔHads(DMP),0 = 109.9 kJ mol-1), was revealed as an excellent porous material to capture airborne DMP. This prediction was validated by further experiments: gravimetric sorption isotherms were carried out on MOF-74(Ni), replacing DMP by dimethyl maleate (DMM), a molecule with a higher vapor pressure and indeed easier to manipulate compared to DMP while mimicking the adsorption behavior of DMP by MOFs, as evidenced by Monte Carlo calculations. Notably, saturation of DMM by MOF-74(Ni) (∼0.35 g g-1 at 343 K) occurs at very low equivalent concentration of the sorbate, i.e., 15 ppm, while half of the DMM molecules remain trapped in the MOF pores, even by heating the system up to 473 K under vacuum. This computational-experimental study reveals for the first time the potential of MOFs for the capture of phthalate ester contaminants as vapors of key importance to address indoor air quality issues.

In Situ Observation of Solvent Exchange Kinetics in a MOF with Coordinatively Unsaturated Sites

Solvent exchange of synthesis solvent within metal-organic frameworks (MOFs) is an essential process for the activation of coordinatively unsaturated sites (CUS) to achieve an optimal surface area; activation of the CUS is required to exploit the versatile applications of MOFs. However, it is challenging to replace CUS-bound synthesis solvent prior to MOF activation, which can lead to a structural collapse and reduced surface area post-evacuation. Herein, we quantify the exchange behavior of a copper paddlewheel-based CUS-MOF (HKUST-1) in the presence of three different solvents: ethanol (EtOH), dichloromethane (DCM), and N,N-dimethylformamide (DMF). The DMF release profiles are monitored via in situ observation of the exchange solvent composition via 1H NMR and Raman spectroscopy at the macroscopic scale. Furthermore, the change in solvent within a single crystal is measured to directly elucidate the exchange behavior. We demonstrate the DMF release profile from HKUST-1 exhibits different rate laws depending on whether the solvent exchange occurs at the CUS or is purely diffusive through the pores. This contribution represents the first characterization of release from a CUS-MOF as a function exchange solvent and reveals that solvent exchange in a CUS-MOF is not diffusion-limited, but rather is limited by the solvent exchange kinetics at the metal center. Insights from this study can be generalized to the variety of copper-paddlewheel-based MOFs, informing best practices for solvent exchange.

DigiMOF: A Database of Metal-Organic Framework Synthesis Information Generated via Text Mining

The vastness of materials space, particularly that which is concerned with metal-organic frameworks (MOFs), creates the critical problem of performing efficient identification of promising materials for specific applications. Although high-throughput computational approaches, including the use of machine learning, have been useful in rapid screening and rational design of MOFs, they tend to neglect descriptors related to their synthesis. One way to improve the efficiency of MOF discovery is to data-mine published MOF papers to extract the materials informatics knowledge contained within journal articles. Here, by adapting the chemistry-aware natural language processing tool, ChemDataExtractor (CDE), we generated an open-source database of MOFs focused on their synthetic properties: the DigiMOF database. Using the CDE web scraping package alongside the Cambridge Structural Database (CSD) MOF subset, we automatically downloaded 43,281 unique MOF journal articles, extracted 15,501 unique MOF materials, and text-mined over 52,680 associated properties including the synthesis method, solvent, organic linker, metal precursor, and topology. Additionally, we developed an alternative data extraction technique to obtain and transform the chemical names assigned to each CSD entry in order to determine linker types for each structure in the CSD MOF subset. This data enabled us to match MOFs to a list of known linkers provided by Tokyo Chemical Industry UK Ltd. (TCI) and analyze the cost of these important chemicals. This centralized, structured database reveals the MOF synthetic data embedded within thousands of MOF publications and contains further topology, metal type, accessible surface area, largest cavity diameter, pore limiting diameter, open metal sites, and density calculations for all 3D MOFs in the CSD MOF subset. The DigiMOF database and associated software are publicly available for other researchers to rapidly search for MOFs with specific properties, conduct further analysis of alternative MOF production pathways, and create additional parsers to search for additional desirable properties.

Melamine Barbiturate as a Light-Induced Nanostructured Supramolecular Material for a Bioinspired Oxygen and Organic Radical Trap and Stabilization

Use of coantioxidant systems is a prospective way to increase the effectiveness of antioxidant species in tissue repair and regeneration. In this paper, we introduce a novel scheme of a reactive oxygen species (ROS) trap and neutralization during self-assembly of supramolecular melamine barbiturate material. The performed reaction chain mimics the biological process of ROS generation in key stages and enables one to obtain stable hydroperoxyl and organic radicals in a melamine barbiturate structure. Melamine barbiturate also neutralizes hydroxyl radicals, and the effectiveness of the radical trap is controlled with ROS scavenger incorporation. The number of radicals dramatically increases during light-inducing and depends on pH. The proposed scheme of the ROS trap and neutralization opens a way to the use of supramolecular assemblies as a component of coantioxidant systems and a source of organic radicals.

Metal-Organic Frameworks for Greenhouse Gas Applications

Using petrol to supply energy for a car or burning coal to heat a building generates plenty of greenhouse gas (GHG) emissions, including carbon dioxide (CO₂ ), water vapor (H₂ O), methane (CH₄ ), nitrous oxide (N₂ O), ozone (O₃ ), fluorinated gases. These up-and-coming metal-organic frameworks (MOFs) are structurally endowed with rigid inorganic nodes and versatile organic linkers, which have been extensively used in the GHG-related applications to improve the lives and protect the environment. Porous MOF materials and their derivatives have been demonstrated to be competitive and promising candidates for GHG separation, storage and conversions as they shows facile preparation, large porosity, adjustable nanostructure, abundant topology, and tunable physicochemical property. Enormous progress has been made in GHG storage and separation intrinsically stemmed from the different interaction between guest molecule and host framework from MOF itself in the recent five years. Meanwhile, the use of porous MOF materials to transform GHG and the influence of external conditions on the adsorption performance of MOFs for GHG are also enclosed. In this review, it is also highlighted that the existing challenges and future directions are discussed and envisioned in the rational design, facile synthesis and comprehensive utilization of MOFs and their derivatives for practical applications.

Computational Characterization of Zr-Oxide MOFs for Adsorption Applications

Zr-oxide secondary building units construct metal-organic framework (MOF) materials with excellent gas adsorption properties and high mechanical, thermal, and chemical stability. These attributes have led Zr-oxide MOFs to be well-recognized for a wide range of applications, including gas storage and separation, catalysis, as well as healthcare domain. Here, we report structure search methods within the Cambridge Structural Database (CSD) to create a curated subset of 102 Zr-oxide MOFs synthesized to date, bringing a unique record for all researchers working in this area. For the identified structures, we manually corrected the proton topology of hydroxyl and water molecules on the Zr-oxide nodes and characterized their textural properties, Brunauer-Emmett-Teller (BET) area, and topology. Importantly, we performed systematic periodic density functional theory (DFT) calculations comparing 25 different combinations of basis sets and functionals to calculate framework partial atomic charges for use in gas adsorption simulations. Through experimental verification of CO₂ adsorption in selected Zr-oxide MOFs, we demonstrate the sensitivity of CO₂ adsorption predictions at the Henry's regime to the choice of the DFT method for partial charge calculations. We characterized Zr-MOFs for their CO₂ adsorption performance via high-throughput grand canonical Monte Carlo (GCMC) simulations and revealed how the chemistry of the Zr-oxide node could have a significant impact on CO₂ uptake predictions. We found that the maximum CO₂ uptake is obtained for structures with the heat of adsorption values >25 kJ/mol and the largest cavity diameters of ca. 6-7 Å. Finally, we introduced augmented reality (AR) visualizations as a means to bring adsorption phenomena alive in porous adsorbents and to dynamically explore gas adsorption sites in MOFs.

Mapping the Porous and Chemical Structure-Function Relationships of Trace CH3I Capture by Metal-Organic Frameworks using Machine Learning

Large-scale computational screening has become an indispensable tool for functional materials discovery. It, however, remains a challenge to adequately interrogate the large amount of data generated by a screening study. Here, we computationally screened 1087 metal-organic frameworks (MOFs), from the CoRE MOF 2014 database, for capturing trace amounts (300 ppmv) of methyl iodide (CH₃I); as a primary representative of organic iodides, CH₃¹²⁹I is one of the most difficult radioactive contaminants to separate. Furthermore, we demonstrate a simple and general approach for mapping and interrogating the high-dimensional structure-function data obtained by high-throughput screening; this involves learning two-dimensional embeddings of the high-dimensional data by applying unsupervised learning to encoded structural and chemical features of MOFs. The resulting various porous and chemical structure-function maps are human-interpretable, revealing not only top-performing MOFs but also complex structure-function correlations that are hidden when inspecting individual MOF features. These maps also alleviate the need of laborious visual inspection of a large number of MOFs by clustering similar MOFs, per the encoding features, into defined regions on the map. We also show that these structure-function maps are amenable to supervised classification of the performances of MOFs for trace CH₃I capture. We further show that the machine-learning models trained on the 1087 CoRE MOFs can be used to predict an unseen set of 250 MOFs randomly selected from a different MOF database, achieving high prediction accuracies.

Capture, Storage, and Release of Oxygen by Metal–Organic Frameworks (MOFs)

Oxygen is a critical gas for medical and industrial settings. Much of today's global oxygen supply is via inefficient technologies such as cryogenic distillation, membranes or zeolites. Metal–organic frameworks (MOFs) promise a superior alternative for oxygen separation, as their fundamental chemistry can in principle be tailored for reversible and selective oxygen capture. We evaluate the characteristics for reversible and selective uptake of oxygen by MOFs, focussing on redox‐active sites. Key characteristics for separation can also be seen in MOFs for oxygen storage roles. Engineering solutions to release adsorbed oxygen from the MOFs are discussed including Temperature Swing Adsorption (TSA), Pressure Swing Adsorption (PSA) and the highly efficient Magnetic Induction Swing Adsorption (MISA). We conclude with the applications and outlooks for oxygen capture, storage and release, and the likely impacts the next generation of MOFs will have on industry and the broader community.

Multi-scale computer-aided design and photo-controlled macromolecular synthesis boosting uranium harvesting from seawater

By integrating multi-scale computational simulation with photo-regulated macromolecular synthesis, this study presents a new paradigm for smart design while customizing polymeric adsorbents for uranium harvesting from seawater. A dissipative particle dynamics (DPD) approach, combined with a molecular dynamics (MD) study, is performed to simulate the conformational dynamics and adsorption process of a model uranium grabber, i.e., PAO_m-b-PPEGMA_n, suggesting that the maximum adsorption capacity with atomic economy can be achieved with a preferred block ratio of 0.18. The designed polymers are synthesized using the PET-RAFT polymerization in a microfluidic platform, exhibiting a record high adsorption capacity of uranium (11.4 ± 1.2 mg/g) in real seawater within 28 days. This study offers an integrated perspective to quantitatively assess adsorption phenomena of polymers, bridging metal-ligand interactions at the molecular level with their spatial conformations at the mesoscopic level. The established protocol is generally adaptable for target-oriented development of more advanced polymers for broadened applications.

Developing materials for uranium harvesting from seawater with high adsorption capacity remains challenging. Here, the authors develop a new protocol, by combining multi-scale computational simulations with the PET-RAFT polymerization, for rational design and precise synthesis of block copolymers with optimal architectures and atomic economy, achieving a capacity of 11.4 mg/g within 28 days.

How Reproducible are Surface Areas Calculated from the BET Equation?

Porosity and surface area analysis play a prominent role in modern materials science. At the heart of this sits the Brunauer-Emmett-Teller (BET) theory, which has been a remarkably successful contribution to the field of materials science. The BET method was developed in the 1930s for open surfaces but is now the most widely used metric for the estimation of surface areas of micro- and mesoporous materials. Despite its widespread use, the calculation of BET surface areas causes a spread in reported areas, resulting in reproducibility problems in both academia and industry. To prove this, for this analysis, 18 already-measured raw adsorption isotherms were provided to sixty-one labs, who were asked to calculate the corresponding BET areas. This round-robin exercise resulted in a wide range of values. Here, the reproducibility of BET area determination from identical isotherms is demonstrated to be a largely ignored issue, raising critical concerns over the reliability of reported BET areas. To solve this major issue, a new computational approach to accurately and systematically determine the BET area of nanoporous materials is developed. The software, called "BET surface identification" (BETSI), expands on the well-known Rouquerol criteria and makes an unambiguous BET area assignment possible.

Multi-Level Computational Screening of in Silico Designed MOFs for Efficient SO2 Capture

SO₂ presence in the atmosphere can cause significant harm to the human and environment through acid rain and/or smog formation. Combining the operational advantages of adsorption-based separation and diverse nature of metal-organic frameworks (MOFs), cost-effective separation processes for SO₂ emissions can be developed. Herein, a large database of hypothetical MOFs composed of >300,000 materials is screened for SO₂/CH₄, SO₂/CO₂, and SO₂/N₂ separations using a multi-level computational approach. Based on a combination of separation performance metrics (adsorption selectivity, working capacity, and regenerability), the best materials and the most common functional groups in those most promising materials are identified for each separation. The top bare MOFs and their functionalized variants are determined to attain SO₂/CH₄ selectivities of 62.4-16899.7, SO₂ working capacities of 0.3-20.1 mol/kg, and SO₂ regenerabilities of 5.8-98.5%. Regarding SO₂/CO₂ separation, they possess SO₂/CO₂ selectivities of 13.3-367.2, SO₂ working capacities of 0.1-17.7 mol/kg, and SO₂ regenerabilities of 1.9-98.2%. For the SO₂/N₂ separation, their SO₂/N₂ selectivities, SO₂ working capacities, and SO₂ regenerabilities span the ranges of 137.9-67,338.9, 0.4-20.6 mol/kg, and 7.0-98.6%, respectively. Besides, using breakdowns of gas separation performances of MOFs into functional groups, separation performance limits of MOFs based on functional groups are identified where bare MOFs (MOFs with multiple functional groups) tend to show the smallest (largest) spreads.

Applications of nanocomposites based on zeolitic imidazolate framework-8 in photodynamic and synergistic anti-tumor therapy

Due to the limitations resulting from hypoxia and the self-aggregation of photosensitizers, photodynamic therapy (PDT) has not been applied clinically to treat most types of solid tumors. Zeolitic imidazolate framework-8 (ZIF-8) is a common metal-organic framework that has ultra-high porosity, an adjustable structure, good biocompatibility, and pH-induced biodegradability. In this review, we summarize the applications of ZIF-8 and its derivatives in PDT. This review is divided into two parts. In the first part, we summarize progress in the application of ZIF-8 to enhance PDT and realize theranostics. We discuss the use of ZIF-8 to avoid the self-aggregation of photosensitizers, alleviate hypoxia, increase the PDT penetration depth, and combine PDT with multi-modal imaging. In the second part, we summarize how ZIF-8 can achieve synergistic PDT with other anti-tumor therapies, including chemotherapy, photothermal therapy, chemodynamic therapy, starvation therapy, protein therapy, gene therapy, and immunotherapy. Finally, we highlight the challenges that must be overcome for ZIF-8 to be widely applied in PDT. To the best of our knowledge, this is the first review of ZIF-8-based nanoplatforms for PDT.

Tunable acetylene sorption by flexible catenated metal-organic frameworks

The safe storage of flammable gases, such as acetylene, is essential for current industrial purposes. However, the narrow pressure (P) and temperature range required for the industrial use of pure acetylene (100 < P < 200 kPa at 298 K) and its explosive behaviour at higher pressures make its storage and release challenging. Flexible metal-organic frameworks that exhibit a gated adsorption/desorption behaviour-in which guest uptake and release occur above threshold pressures, usually accompanied by framework deformations-have shown promise as storage adsorbents. Herein, the pressures for gas uptake and release of a series of zinc-based mixed-ligand catenated metal-organic frameworks were controlled by decorating its ligands with two different functional groups and changing their ratio. This affects the deformation energy of the framework, which in turn controls the gated behaviour. The materials offer good performances for acetylene storage with a usable capacity of ~90 v/v (77% of the overall amount) at 298 K and under a practical pressure range (100-150 kPa).

From computational high-throughput screenings to the lab: taking metal–organic frameworks out of the computer

Computational high-throughput screenings (HTS) have become a standard method of sieving the vast amount of metal–organic frameworks (MOFs) data. But not many HTS studies have been able to bring MOFs to the lab.

Conquering the Hypoxia Limitation for Photodynamic Therapy

Photodynamic therapy (PDT) has aroused great research interest in recent years owing to its high spatiotemporal selectivity, minimal invasiveness, and low systemic toxicity. However, due to the hypoxic nature characteristic of many solid tumors, PDT is frequently limited in therapeutic effect. Moreover, the consumption of O₂ during PDT may further aggravate the tumor hypoxic condition, which promotes tumor proliferation, metastasis, and invasion resulting in poor prognosis of treatment. Therefore, numerous efforts have been made to increase the O₂ content in tumor with the goal of enhancing PDT efficacy. Herein, these strategies developed in past decade are comprehensively reviewed to alleviate tumor hypoxia, including 1) delivering exogenous O₂ to tumor directly, 2) generating O₂ in situ, 3) reducing tumor cellular O₂ consumption by inhibiting respiration, 4) regulating the TME, (e.g., normalizing tumor vasculature or disrupting tumor extracellular matrix), and 5) inhibiting the hypoxia-inducible factor 1 (HIF-1) signaling pathway to relieve tumor hypoxia. Additionally, the O₂ -independent Type-I PDT is also discussed as an alternative strategy. By reviewing recent progress, it is hoped that this review will provide innovative perspectives in new nanomaterials designed to combat hypoxia and avoid the associated limitation of PDT.

Using Helium Pycnometry to Study the Apparent Densities of Metal-Organic Frameworks

When investigating the gas storage capacities of metal-organic frameworks, volumetric values are often reported based on crystallographic densities. Although it is widely accepted that Langmuir and BET surface areas of a given MOF can vary depending on the exact synthetic conditions used to prepare the materials, it is rare that deviations in density from the optimal crystallographic density are considered. The actual (apparent) densities of these materials are highly variable depending on the presence of defects, impurities, or multiple phases that arise during synthesis. The apparent density of specific samples, which represent an experimentally determined crystallographic density, can be measured with helium pycnometry where the skeletal density measured via pycnometry is easily converted to an apparent density. In the work reported here, apparent density was measured for 46 samples across a series of different structure types where experimentally measured density was consistently lower than crystallographic density, up to 30% in some cases. Subsequently, use of this technique allows for quantification of densities for those materials whose structures have not been crystallographically determined.

Relationship between Atomic Structure, Composition, and Dielectric Constant in Zr-SiO2 Glasses

Computational methods, or computer-aided material design (CAMD), used for the analysis and design of materials have a relatively long history. However, the applicability of CAMD has been limited by the scales of computational resources generally available in the past. The surge in computational power seen in recent years is enabling the applicability of CAMD to unprecedented levels. Here, we focus on the CAMD for materials critical for the continued advancement of the complementary metal oxide semiconductor (CMOS) semiconductor technology. In particular, we apply CAMD to the engineering of high-permittivity dielectric materials. We developed a Reax forcefield that includes Si, O, Zr, and H. We used this forcefield in a series of simulations to compute the static dielectric constant of silica glasses for low Zr concentration using a classical molecular dynamics approach. Our results are compared against experimental values. Not only does our work reveal numerical estimations on ZrO₂-doped silica dielectrics, it also provides a foundation and demonstration of how CAMD can enable the engineering of materials of critical importance for advanced CMOS technology nodes.

The development of a comprehensive toolbox based on multi-level, high-throughput screening of MOFs for CO/N2 separations

The separation of CO/N2 mixtures is a challenging problem in the petrochemical sector due to the very similar physical properties of these two molecules, such as size, molecular weight and boiling point. To solve this and other challenging gas separations, one requires a holistic approach. The complexity of a screening exercise for adsorption-based separations arises from the multitude of existing porous materials, including metal-organic frameworks. Besides, the multivariate nature of the performance criteria that needs to be considered when designing an optimal adsorbent and a separation process - i.e. an optimal material requires fulfillment of several criteria simultaneously - makes the screening challenging. To address this, we have developed a multi-scale approach combining high-throughput molecular simulation screening, data mining and advanced visualization, as well as process system modelling, backed up by experimental validation. We have applied our recent advances in the engineering of porous materials' morphology to develop advanced monolithic structures. These conformed, shaped monoliths can be used readily in industrial applications, bringing a valuable strategy for the development of advanced materials. This toolbox is flexible enough to be applied to multiple adsorption-based gas separation applications.

Nanoscale metal-organic frameworks for tumor phototherapy

Metal-Organic Frameworks (MOFs) are constructed from metal ions/cluster nodes and functional organic ligands through coordination bonds. Owing to the advantages of diverse synthetic methods, easy modification after synthesis, large adsorption capacity for heavy metals, and short equilibrium time, considerable attention has recently been paid to MOFs for tumor phototherapy. Through rational tuning of metal ions and ligands, MOFs present abundant properties for various applications. Light-triggered phototherapy, including photodynamic therapy (PDT) and photothermal therapy (PTT), is an emerging cancer treatment approach. Nanosized MOFs can be applied as phototherapeutic agents to accomplish phototherapy with excellent phototherapeutic efficacy. This review outlines the latest advances in the field of phototherapy with various metal ion-based MOFs.

Zr-MOFs for CF4/CH4, CH4/H2, and CH4/N2 separation: towards the goal of discovering stable and effective adsorbents

Zirconium metal-organic frameworks (MOFs) can be promising adsorbents for various applications as they are highly stable in different chemical environments. In this work, a collection of Zr-MOFs comprised of more than 100 materials is screened for CF₄/CH₄, CH₄/H₂, and CH₄/N₂ separations using atomistic-level simulations. The top three MOFs for the CF₄/CH₄ separation are identified as PCN-700-BPDC-TPDC, LIFM-90, and BUT-67 exhibiting CF₄/CH₄ adsorption selectivities of 4.8, 4.6, and 4.7, CF₄ working capacities of 2.0, 2.0, and 2.1 mol kg^-1, and regenerabilities of 85.1, 84.2, and 75.7%, respectively. For the CH₄/H₂ separation, MOF-812, BUT-67, and BUT-66 are determined to be the top performing MOFs demonstrating CH₄/H₂ selectivities of 61.6, 36.7, and 46.2, CH₄ working capacities of 3.0, 4.1, and 3.4 mol kg^-1, and CH₄ regenerabilities of 70.7, 82.7, and 74.7%, respectively. Regarding the CH₄/N₂ separation, BUT-67, Zr-AbBA, and PCN-702 achieving CH₄/N₂ selectivities of 4.5, 3.4, and 3.8, CH₄ working capacities of 3.6, 3.9, and 3.5 mol kg^-1, and CH₄ regenerabilities of 81.1, 84.0, and 84.5%, in successive order, show the best overall separation performances. To further elucidate the adsorption in top performing adsorbents, the adsorption sites in these materials are analyzed using radial distribution functions and adsorbate density profiles. Finally, the water affinities of Zr-MOFs are explored to comment on their practical use in real gas separation applications. Our findings may inspire future studies probing the adsorption/separation mechanisms and performances of Zr-MOFs for different gases.

In Silico Tuning of the Pore Surface Functionality in Al-MOFs for Trace CH3I Capture

Aluminum (Al)-based metal-organic frameworks (MOFs) have been shown to have good stability toward γ irradiation, making them promising candidates for durable adsorbents for capturing volatile radioactive nuclides. In this work, we studied a series of existing Al-MOFs to capture trace radioactive organic iodide (ROI) from a gas composition (100 ppm CH₃I, 400 ppm CO₂, 21% O₂, and 78% N₂) resembling the off-gas composition from reprocessing the used nuclear fuel using Grand canonical Monte Carlo (GCMC) simulations and density functional theory (DFT) calculations. Based on the results and understanding established from studying the existing Al-MOFs, we proceed by functionalizing the top-performing CAU-11 with different functional groups to propose better MOFs for ROI capture. Our study suggests that extraordinary ROI adsorption and separation capability could be realized by -SO₃H functionalization in CAU-11. It was mainly owing to the joint effect of the enhanced pore surface polarity arising from -SO₃H functionalization and the μ-OH group of CAU-11.

stk: An extendable Python framework for automated molecular and supramolecular structure assembly and discovery

Computational software workflows are emerging as all-in-one solutions to speed up the discovery of new materials. Many computational approaches require the generation of realistic structural models for property prediction and candidate screening. However, molecular and supramolecular materials represent classes of materials with many potential applications for which there is no go-to database of existing structures or general protocol for generating structures. Here, we report a new version of the supramolecular toolkit, stk, an open-source, extendable, and modular Python framework for general structure generation of (supra)molecular structures. Our construction approach works on arbitrary building blocks and topologies and minimizes the input required from the user, making stk user-friendly and applicable to many material classes. This version of stk includes metal-containing structures and rotaxanes as well as general implementation and interface improvements. Additionally, this version includes built-in tools for exploring chemical space with an evolutionary algorithm and tools for database generation and visualization. The latest version of stk is freely available at github.com/lukasturcani/stk.

Molecular Surgery at Microporous MOF for Mesopore Generation and Renovation

Hierarchically porous MOFs (HP-MOFs) present advantageous synergism of micro- and mesopore but challenging in synthetic control at molecular scale. Herein, we present the first example of reversible and controllable mesopore generation and renovation in a microporous MOF of HKUST-1 via synthetic manipulation at molecular scale. An ammonia-gas etching strategy is proposed to create mesopores in carboxylate-based microporous MOFs and thus produce HP-MOFs. Gas-phase etching ensures uniform mesopore formation inside the MOF crystals via plane-oriented cutting the carboxylate-metal bonds off without affecting the crystal size and morphology. The mesopore size is controlled by the etching temperature, while the mesopore volume could be tuned by adjusting etchant pressure. The generated mesopores could be renovated using MOF precursors solutions so that to achieve controllable mesopore generation/closure, and encapsulation of the adsorbed molecules. This work demonstrates a powerful protocol for precisely tailoring and tuning the properties of MOF materials at molecular scale.

Au@ZIF-8 Core-Shell Nanoparticles as a SERS Substrate for Volatile Organic Compound Gas Detection

Surface-enhanced Raman spectroscopy (SERS) is a promising ultrasensitive analysis technology due to outstanding molecular fingerprint identification. However, the measured molecules generally need to be adsorbed on a SERS substrate, which makes it difficult to detect weakly adsorbed molecules, for example, the volatile organic compound (VOC) molecules. Herein, we developed a kind of a SERS detection method for weak adsorption molecules with Au@ZIF-8 core-shell nanoparticles (NPs). The well-uniformed single- and multicore-shell NPs can be synthesized controllably, and the shell thickness of the ZIF-8 was able to be precisely controlled (from 3 to 50 nm) to adjust the distance and electromagnetic fields between metal nanoparticles. After analyzing the chemical and physical characterization, Au@ZIF-8 core-shell NPs were employed to detect VOC gas by SERS. In contrast with multicore or thicker-shell nanoparticles, Au@ZIF-8 with a shell thickness of 3 nm could efficiently probe various VOC gas molecules, such as toluene, ethylbenzene, and chlorobenzene. Besides, we were capable of observing the process of toluene gas adsorption and desorption using real-time SERS technology. As observed from the experimental results, this core-shell nanostructure has a promising prospect in diverse gas detection and is expected to be applied to the specific identification of intermediates in catalytic reactions.

In Situ Tracking of Wetting-Front Transient Heat Release on a Surface-Mounted Metal-Organic Framework

Transient heat generation during guest adsorption and host-guest interactions is a natural phenomenon in metal-organic framework (MOF) chemistry. However, in situ tracking of such MOF released heat is an insufficiently researched field due to the fast heat dissipation to the surroundings. Herein, a facile capillary-driven liquid-imbibition approach is developed for in situ tracking of transient heat release at the wetting front of surface-mounted MOFs (SURMOFs) on cellulosic fiber substrates. Spatiotemporal temperature distributions are obtained with infrared thermal imaging for a range of MOF-based substrates and imbibed liquids. Temperature rises at the wetting front of water and binary mixtures with organic solvents are found to be over 10 K with an ultrafast and distinguishable thermal signal response (<1 s) with a detectable concentration limit ≤1 wt%. As an advancement to the state-of-the-art in trace-solvent detection technologies, this study shows great prospects for the integration of SURMOFs in future sensor devices. Inspired by this prototypal study, SURMOF-based transient heat signal transduction is likely to be extended to an ever-expanding library of SURMOFs and other classes of surface-grafted porous materials, translating into a wide range of convenient, portable, and ubiquitous sensor devices.

Digital navigation of energy-structure-function maps for hydrogen-bonded porous molecular crystals

Energy-structure-function (ESF) maps can aid the targeted discovery of porous molecular crystals by predicting the stable crystalline arrangements along with their functions of interest. Here, we compute ESF maps for a series of rigid molecules that comprise either a triptycene or a spiro-biphenyl core, functionalized with six different hydrogen-bonding moieties. We show that the positioning of the hydrogen-bonding sites, as well as their number, has a profound influence on the shape of the resulting ESF maps, revealing promising structure-function spaces for future experiments. We also demonstrate a simple and general approach to representing and inspecting the high-dimensional data of an ESF map, enabling an efficient navigation of the ESF data to identify 'landmark' structures that are energetically favourable or functionally interesting. This is a step toward the automated analysis of ESF maps, an important goal for closed-loop, autonomous searches for molecular crystals with useful functions.

Antibacterial application and toxicity of metal-organic frameworks

Metal-organic frameworks (MOFs), which are also referred to as coordination polymers, have been widely used in adsorption separation and catalysis, especially in the field of physical chemistry in the past few years, because of their unique physical structure and potential chemical properties. In recent years, particularly with the continuous expansion of the research field, deepening of research levels, and sustained advancements in science and technology, powerful and diverse MOFs that have demonstrated great biomedical application potential have been successively developed. Consequently, this study summarizes the origin, development, and common synthesis methods of MOFs, with major emphasis on their antibacterial application and safety evaluation in biomedicine.

State-of-the-art advances of copper-based nanostructures in the enhancement of chemodynamic therapy

Chemodynamic therapy (CDT) is a new emerging strategy for the in situ treatment of tumors. In the microenvironment of tumor cells, CDT may be achieved through the generation of reactive oxygen species (ROS), e.g., hydroxyl radicals (˙OH) and singlet oxygen (¹O₂), which induce the death of tumor cells. Copper (Cu) or other transition-metal ions catalyze the production of ˙OH by hydrogen peroxide (H₂O₂) through Fenton or Fenton-like reactions. With the development of advanced nanotechnology, nanotherapeutic systems with Cu-based nanostructures have received extensive attention and have been demonstrated for their wide applications in the design and construction of nanotherapeutic systems for CDT, along with multimodal synergistic therapy. Herein, the cutting-edge developments of Cu-based nanostructures in CDT are reviewed and discussed, by focusing on the monotherapy of CDT as well as synergistic treatments by hyphenating CDT with various therapeutic protocols, e.g., photothermal therapy (PTT), photodynamic therapy (PDT), sonodynamic therapy (SDT), and so on. In addition, the potential challenges and future perspectives are described in the improvement of CDT therapeutic efficacy, the enhancement of targeting capability, and mechanistic investigations on CDT therapy.

Too Many Materials and Too Many Applications: An Experimental Problem Waiting for a Computational Solution

Finding the best material for a specific application is the ultimate goal of materials discovery. However, there is also the reverse problem: when experimental groups discover a new material, they would like to know all the possible applications this material would be promising for. Computational modeling can aim to fulfill this expectation, thanks to the sustained growth of computing power and the collective engagement of the scientific community in developing more efficient and accurate workflows for predicting materials' performances. We discuss the impact that reproducibility and automation of the modeling protocols have on the field of gas adsorption in nanoporous crystals. We envision a platform that combines these tools and enables effective matching between promising materials and industrial applications.

Wiz: A Web-Based Tool for Interactive Visualization of Big Data

In an age of information, visualizing and discerning meaning from data is as important as its collection. Interactive data visualization addresses both fronts by allowing researchers to explore data beyond what static images can offer. Here, we present Wiz, a web-based application for handling and visualizing large amounts of data. Wiz does not require programming or downloadable software for its use and allows scientists and non-scientists to unravel the complexity of data by splitting their relationships through 5D visual analytics, performing multivariate data analysis, such as principal component and linear discriminant analyses, all in vivid, publication-ready figures. With the explosion of high-throughput practices for materials discovery, information streaming capabilities, and the emphasis on industrial digitalization and artificial intelligence, we expect Wiz to serve as an invaluable tool to have a broad impact in our world of big data.