Functional Janus structured liquids and aerogels.

Janus structures have unique properties due to their distinct functionalities on opposing faces, but have yet to be realized with flowing liquids. We demonstrate such Janus liquids with a customizable distribution of nanoparticles (NPs) throughout their structures by joining two aqueous streams of NP dispersions in an apolar liquid. Using this anisotropic integration platform, different magnetic, conductive, or non-responsive NPs can be spatially confined to opposite sides of the original interface using magnetic graphene oxide (mGO)/GO, Ti3C2Tx/GO, or GO suspensions. The resultant Janus liquids can be used as templates for versatile, responsive, and mechanically robust aerogels suitable for piezoresistive sensing, human motion monitoring, and electromagnetic interference (EMI) shielding with a tuned absorption mechanism. The EMI shields outperform their current counterparts in terms of wave absorption, i.e., SET ≈ 51 dB, SER ≈ 0.4 dB, and A = 0.91, due to their high porosity ranging from micro- to macro-scales along with non-interfering magnetic and conductive networks imparted by the Janus architecture.

Alignment of Breathing Metal-Organic Framework Particles for Enhanced Water-Driven Actuation.

As the majority of known metal-organic frameworks (MOFs) possess anisotropic crystal lattices and thus anisotropic physicochemical properties, a pressing practical challenge in MOF research is the establishment of robust and simple processing methods to fully harness the anisotropic properties of the MOFs in various applications. We address this challenge by applying an E-field to precisely align MIL-88A microcrystals and generate MIL-88A@polymer films. Thereafter, we demonstrate the impact of MOF crystal alignment on the actuation properties of the films as a proof of concept. We investigate how different anisotropies of the MIL-88A@polymer films, specifically, crystal anisotropy, particle alignment, and film composition, can lead to the synergetic enhancement of the film actuation upon water exposure. Moreover, we explore how the directionality in application of the external stimuli (dry/humid air stream, water/air interface) affects the direction and the extent of the MIL-88A@polymer film movement. Apart from the superior water-driven actuation properties of the developed films, we demonstrate by dynamometer measurements the higher degree of mechanical work performed by the aligned MIL-88A@polymer films with the preserved anisotropies compared to the unaligned films. The insights provided by this work into anisotropic properties displayed by aligned MIL-88A@polymer films promise to translate crystal performance benefits measured in laboratories into real-world applications. We anticipate that our work is a starting point to utilize the full potential of anisotropic properties of MOFs.

Reticular Nanoscience: Bottom-Up Assembly Nanotechnology.

The chemistry of metal-organic and covalent organic frameworks (MOFs and COFs) is perhaps the most diverse and inclusive among the chemical sciences, and yet it can be radically expanded by blending it with nanotechnology. The result is reticular nanoscience, an area of reticular chemistry that has an immense potential in virtually any technological field. In this perspective, we explore the extension of such an interdisciplinary reach by surveying the explored and unexplored possibilities that framework nanoparticles can offer. We localize these unique nanosized reticular materials at the juncture between the molecular and the macroscopic worlds, and describe the resulting synthetic and analytical chemistry, which is fundamentally different from conventional frameworks. Such differences are mirrored in the properties that reticular nanoparticles exhibit, which we described while referring to the present state-of-the-art and future promising applications in medicine, catalysis, energy-related applications, and sensors. Finally, the bottom-up approach of reticular nanoscience, inspired by nature, is brought to its full extension by introducing the concept of augmented reticular chemistry. Its approach departs from a single-particle scale to reach higher mesoscopic and even macroscopic dimensions, where framework nanoparticles become building units themselves and the resulting supermaterials approach new levels of sophistication of structures and properties.

Metallodrugs in cancer nanomedicine.

Metal complexes are extensively used for cancer therapy. The multiple variables available for tuning (metal, ligand, and metal-ligand interaction) offer unique opportunities for drug design, and have led to a vast portfolio of metallodrugs that can display a higher diversity of functions and mechanisms of action with respect to pure organic structures. Clinically approved metallodrugs, such as cisplatin, carboplatin and oxaliplatin, are used to treat many types of cancer and play prominent roles in combination regimens, including with immunotherapy. However, metallodrugs generally suffer from poor pharmacokinetics, low levels of target site accumulation, metal-mediated off-target reactivity and development of drug resistance, which can all limit their efficacy and clinical translation. Nanomedicine has arisen as a powerful tool to help overcome these shortcomings. Several nanoformulations have already significantly improved the efficacy and reduced the toxicity of (chemo-)therapeutic drugs, including some promising metallodrug-containing nanomedicines currently in clinical trials. In this critical review, we analyse the opportunities and clinical challenges of metallodrugs, and we assess the advantages and limitations of metallodrug delivery, both from a nanocarrier and from a metal-nano interaction perspective. We describe the latest and most relevant nanomedicine formulations developed for metal complexes, and we discuss how the rational combination of coordination chemistry with nanomedicine technology can assist in promoting the clinical translation of metallodrugs.

MOF Synthesis Prediction Enabled by Automatic Data Mining and Machine Learning.

Despite rapid progress in the field of metal-organic frameworks (MOFs), the potential of using machine learning (ML) methods to predict MOF synthesis parameters is still untapped. Here, we show how ML can be used for rationalization and acceleration of the MOF discovery process by directly predicting the synthesis conditions of a MOF based on its crystal structure. Our approach is based on: i) establishing the first MOF synthesis database via automatic extraction of synthesis parameters from the literature, ii) training and optimizing ML models by employing the MOF database, and iii) predicting the synthesis conditions for new MOF structures. The ML models, even at an initial stage, exhibit a good prediction performance, outperforming human expert predictions, obtained through a synthesis survey. The automated synthesis prediction is available via a web-tool on https://mof-synthesis.aimat.science.

The Current Status of MOF and COF Applications.

The amalgamation of different disciplines is at the heart of reticular chemistry and has broadened the boundaries of chemistry by opening up an infinite space of chemical composition, structure, and material properties. Reticular design has enabled the precise prediction of crystalline framework structures, tunability of chemical composition, incorporation of various functionalities onto the framework backbone, and as a consequence, fine-tuning of metal-organic framework (MOF) and covalent organic framework (COF) properties beyond that of any other material class. Leveraging the unique properties of reticular materials has resulted in significant advances from both a fundamental and an applied perspective. Here, we wish to review the milestones in MOF and COF research and give a critical view on progress in their real-world applications. Finally, we briefly discuss the major challenges in the field that need to be addressed to pave the way for industrial applications.

25 Years of Reticular Chemistry.

At its core, reticular chemistry has translated the precision and expertise of organic and inorganic synthesis to the solid state. While initial excitement over metal-organic frameworks (MOFs) and covalent organic frameworks (COFs) was undoubtedly fueled by their unprecedented porosity and surface areas, the most profound scientific innovation of the field has been the elaboration of design strategies for the synthesis of extended crystalline solids through strong directional bonds. In this contribution we highlight the different classes of reticular materials that have been developed, how these frameworks can be functionalized, and how complexity can be introduced into their backbones. Finally, we show how the structural control over these materials is being extended from the molecular scale to their crystal morphology and shape on the nanoscale, all the way to their shaping on the bulk scale.

Artificial Bioaugmentation of Biomacromolecules and Living Organisms for Biomedical Applications.

The synergistic union of nanomaterials with biomaterials has revolutionized synthetic chemistry, enabling the creation of nanomaterial-based biohybrids with distinct properties for biomedical applications. This class of materials has drawn significant scientific interest from the perspective of functional extension via controllable coupling of synthetic and biomaterial components, resulting in enhancement of the chemical, physical, and biological properties of the obtained biohybrids. In this review, we highlight the forefront materials for the combination with biomacromolecules and living organisms and their advantageous properties as well as recent advances in the rational design and synthesis of artificial biohybrids. We further illustrate the incredible diversity of biomedical applications stemming from artificially bioaugmented characteristics of the nanomaterial-based biohybrids. Eventually, we aim to inspire scientists with the application horizons of the exciting field of synthetic augmented biohybrids.

Machine Learning for Tailoring Optoelectronic Properties of Single-Walled Carbon Nanotube Films.

A machine learning technique, namely, support vector regression, is implemented to enhance single-walled carbon nanotube (SWCNT) thin-film performance for transparent and conducting applications. We collected a comprehensive data set describing the influence of synthesis parameters (temperature and CO2 concentration) on the equivalent sheet resistance (at 90% transmittance in the visible light range) for SWCNT films obtained by a semi-industrial aerosol (floating-catalyst) CVD with CO as a carbon source and ferrocene as a catalyst precursor. The predictive model trained on the data set shows principal applicability of the method for refining synthesis conditions toward the advanced optoelectronic performance of multiparameter processes such as nanotube growth. Further doping of the improved carbon nanotube films with HAuCl4 results in the equivalent sheet resistance of 39 Ω/□-one of the lowest values achieved so far for SWCNT films.