Cell Adhesion, Elasticity, and Rupture Forces Guide Microbial Cell Death on Nanostructured Antimicrobial Titanium Surfaces.

Naturally occurring and synthetic nanostructured surfaces have been widely reported to resist microbial colonization. The majority of these studies have shown that both bacterial and fungal cells are killed upon contact and subsequent surface adhesion to such surfaces. This occurs because the presence of high-aspect-ratio structures can initiate a self-driven mechanical rupture of microbial cells during the surface adsorption process. While this technology has received a large amount of scientific and medical interest, one important question still remains: what factors drive microbial death on the surface? In this work, the interplay between microbial-surface adhesion, cell elasticity, cell membrane rupture forces, and cell lysis at the microbial-nanostructure biointerface during adsorptive processes was assessed using a combination of live confocal laser scanning microscopy, scanning electron microscopy, in situ amplitude atomic force microscopy, and single-cell force spectroscopy. Specifically, the adsorptive behavior and nanomechanical properties of live Gram-negative (Pseudomonas aeruginosa) and Gram-positive (methicillin-resistant Staphylococcus aureus) bacterial cells, as well as the fungal species Candida albicans and Cryptococcus neoformans, were assessed on unmodified and nanostructured titanium surfaces. Unmodified titanium and titanium surfaces with nanostructures were used as model substrates for investigation. For all microbial species, cell elasticity, rupture force, maximum cell-surface adhesion force, the work of adhesion, and the cell-surface tether behavior were compared to the relative cell death observed for each surface examined. For cells with a lower elastic modulus, lower force to rupture through the cell, and higher work of adhesion, the surfaces had a higher antimicrobial activity, supporting the proposed biocidal mode of action for nanostructured surfaces. This study provides direct quantification of the differences observed in the efficacy of nanostructured antimicrobial surface as a function of microbial species indicating that a universal, antimicrobial surface architecture may be hard to achieve.

Rational Atom Substitution to Obtain Efficient, Lead-Free Photocatalytic Perovskites Assisted by Machine Learning and DFT Calculations.

Inorganic lead-free halide perovskites, devoid of toxic or rare elements, have garnered considerable attention as photocatalysts for pollution control, CO2 reduction and hydrogen production. In the extensive perovskite design space, factors like substitution or doping level profoundly impact their performance. To address this complexity, a synergistic combination of machine learning models and theoretical calculations were used to efficiently screen substitution elements that enhanced the photoactivity of substituted Cs2 AgBiBr6 perovskites. Machine learning models determined the importance of d10 orbitals, highlighting how substituent electron configuration affects electronic structure of Cs2 AgBiBr6 . Conspicuously, d10 -configured Zn2+ boosted the photoactivity of Cs2 AgBiBr6 . Experimental verification validated these model results, revealing a 13-fold increase in photocatalytic toluene conversion compared to the unsubstituted counterpart. This enhancement resulted from the small charge carrier effective mass, as well as the creation of shallow trap states, shifting the conduction band minimum, introducing electron-deficient Br, and altering the distance between the B-site cations d band centre and the halide anions p band centre, a parameter tuneable through d10 configuration substituents. This study exemplifies the application of computational modelling in photocatalyst design and elucidating structure-property relationships. It underscores the potential of synergistic integration of calculations, modelling, and experimental analysis across various applications.

Synthesis of Layered Lead-Free Perovskite Nanocrystals with Precise Size and Shape Control and Their Photocatalytic Activity.

Halide perovskites have attracted enormous attention due to their potential applications in optoelectronics and photocatalysis. However, concerns over their instability, toxicity, and unsatisfactory efficiency have necessitated the development of lead-free all-inorganic halide perovskites. A major challenge in designing efficient halide perovskites for practical applications is the lack of effective methods for producing nanocrystals with precise size and shape control. In this work, a layered perovskite, Cs4ZnSb2Cl12 (CZS), is found from calculations to exhibit size- and facet-dependent optoelectronic properties in the nanoscale, and thus, a colloidal method is used to synthesize the CZS nanoparticles with size-tunable morphologies: zero- (nanodots), one- (nanowires and nanorods), two- (nanoplates), and three-dimensional (nanopolyhedra). The growth kinetics of the CZS nanostructures, along with the effects of surface ligands, reaction temperature, and time were investigated. The optoelectronic properties of the nanocrystals varied with size due to quantum confinement effects and with shape due to anisotropy within the crystals and the exposure of specific facets. These properties could be modulated to enhance the visible-light photocatalytic performance for toluene oxidation. In particular, the 9.7 nm CZS nanoplates displayed a toluene to benzaldehyde conversion rate of 1893 µmol g-1 h-1 (95% selectivity), 500 times higher than the bulk synthesized CZS, and comparable with the reported photocatalysts. This study demonstrates the integration of theoretical calculations and synthesis, revealing an approach to the design and fabrication of novel, high-performance colloidal perovskite nanocrystals for optoelectronic and photocatalytic applications.

Durable CuxO/mesoporous TiO2 photocatalyst for stable and efficient hydrogen evolution.

Heterogeneous structures containing highly dispersed semiconductor nanoparticles on a photoactive support are effective for the photocatalytic hydrogen evolution reaction (HER). In this work, the interlayer ion-exchange and space confining nature of layered titanate nanosheets was used to embed copper ions in titanates, which were then transitioned to mesoporous CuxO/TiO2 with highly dispersed CuxO nanostructures. Both experimental and density functional theory (DFT) studies demonstrated that the fine-decoration of CuxO nanostructures and the reducible valence of the copper species enabled stable superior photocatalytic activity. The HER efficiency was enhanced to 12.45 mmol g-1 h-1 for the mesoporous CuxO/TiO2 composites in comparison to an efficiency of 0.38 mmol g-1 h-1 for the non-modified TiO2. Steady HER performances over 10 h, cyclic HER measurement over 60 h, and testing of the composite kept under ambient conditions for over one year, demonstrated excellent stability of the composite against photochemical and wet-chemical erosion.

Machine Learning in the Development of Adsorbents for Clean Energy Application and Greenhouse Gas Capture.

Addressing climate change challenges by reducing greenhouse gas levels requires innovative adsorbent materials for clean energy applications. Recent progress in machine learning has stimulated technological breakthroughs in the discovery, design, and deployment of materials with potential for high-performance and low-cost clean energy applications. This review summarizes basic machine learning methods-data collection, featurization, model generation, and model evaluation-and reviews their use in the development of robust adsorbent materials. Key case studies are provided where these methods are used to accelerate adsorbent materials design and discovery, optimize synthesis conditions, and understand complex feature-property relationships. The review provides a concise resource for researchers wishing to use machine learning methods to rapidly develop effective adsorbent materials with a positive impact on the environment.

Dual-action silver functionalized nanostructured titanium against drug resistant bacterial and fungal species.

HYPOTHESIS: Titanium and its alloys are commonly used implant materials. Once inserted into the body, the interface of the biomaterials is the most likely site for the development of implant-associated infections. Imparting the titanium substrate with high-aspect-ratio nanostructures, which can be uniformly achieved using hydrothermal etching, enables a mechanical contact-killing (mechanoresponsive) mechanism of bacterial and fungal cells. Interaction between cells and the surface shows cellular inactivation via a physical mechanism meaning that careful engineering of the interface is needed to optimse the technology. This mechanism of action is only effective towards surface adsorbed microbes, thus any cells not directly in contact with the substrate will survive and limit the antimicrobial efficacy of the titanium nanostructures. Therefore, we propose that a dual-action mechanoresponsive and chemical-surface approach must be utilised to improve antimicrobial activity. The addition of antimicrobial silver nanoparticles will provide a secondary, chemical mechanism to escalate the microbial response in tandem with the physical puncture of the cells. EXPERIMENTS: Hydrothermal etching is used as a facile method to impart variant nanostrucutres on the titanium substrate to increase the antimicrobial response. Increasing concentrations (0.25 M, 0.50 M, 1.0 M, 2.0 M) of sodium hydroxide etching solution were used to provide differing degrees of nanostructured morphology on the surface after 3 h of heating at 150 °C. This produced titanium nanospikes, nanoblades, and nanowires, respectively, as a function of etchant concentration. These substrates then provided an interface for the deposition of silver nanoparticles via a reduction pathway. Methicillin-resistant Staphylococcous aureus (MRSA) and Candida auris (C. auris) were used as model bacteria and fungi, respectively, to test the effectiveness of the nanostructured titanium with and without silver nanoparticles, and the bio-interactions at the interface. FINDINGS: The presence of nanostructure increased the bactericidal response of titanium against MRSA from âˆ¼ 10 % on commercially pure titanium to a maximum of âˆ¼ 60 % and increased the fungicidal response from âˆ¼ 10 % to âˆ¼ 70 % in C. auris. Introducing silver nanoparticles increased the microbiocidal response to âˆ¼ 99 % towards both bacteria and fungi. Importantly, this study highlights that nanostructure alone is not sufficient to develop a highly antimicrobial titanium substrate. A dual-action, physical and chemical antimicrobial approach is better suited to produce highly effective antibacterial and antifungal surface technologies.

Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery.

Electrocatalysts and photocatalysts are key to a sustainable future, generating clean fuels, reducing the impact of global warming, and providing solutions to environmental pollution. Improved processes for catalyst design and a better understanding of electro/photocatalytic processes are essential for improving catalyst effectiveness. Recent advances in data science and artificial intelligence have great potential to accelerate electrocatalysis and photocatalysis research, particularly the rapid exploration of large materials chemistry spaces through machine learning. Here a comprehensive introduction to, and critical review of, machine learning techniques used in electrocatalysis and photocatalysis research are provided. Sources of electro/photocatalyst data and current approaches to representing these materials by mathematical features are described, the most commonly used machine learning methods summarized, and the quality and utility of electro/photocatalyst models evaluated. Illustrations of how machine learning models are applied to novel electro/photocatalyst discovery and used to elucidate electrocatalytic or photocatalytic reaction mechanisms are provided. The review offers a guide for materials scientists on the selection of machine learning methods for electrocatalysis and photocatalysis research. The application of machine learning to catalysis science represents a paradigm shift in the way advanced, next-generation catalysts will be designed and synthesized.

Fabrication of a Reusable Carbon Dot/Gold Nanoparticle/Metal-Organic Framework Film for Fluorescence Detection of Lead Ions in Water.

Solid-state sensing platforms are desirable for the development of reusable sensors to promote public health measures such as testing for drinking water contamination. A bioinspired metal-organic framework (MOF)-based material has been developed by imitating metal-protein interactions in biological systems to attain high sensitivity and selectivity to Pb2+ through fluorescence sensing. A zirconium terephthalate-type framework (also known as NH2-UiO-66) was modified with both gold nanoparticles and thiol-functionalized carbon dots to give HS-C/Au(x)/UiO-66 composites with different Au content (x) and were subsequently adapted into films that show extraordinary sensitivity to Pb2+. The HS-C/Au(1.4)/UiO-66 film that consists of 1.4 wt % Au shows a quenching response with the limit of detection of 80 parts per trillion and sustained performance for five cycles. Moreover, the fluorescence response of the HS-C/Au(x)/UiO-66 film to Pb2+ can be reversed from emission quenching to enrichment of fluorescence by increasing the Au content. The performance of the HS-C/Au(x)/UiO-66 film as a solid-state sensor demonstrates its potential for application in reusable sensing devices to ensure public safety from Pb2+ contamination in drinking water.

Metal-organic frameworks for chemical sensing devices.

Metal-organic frameworks (MOFs) are exceptionally large surface area materials with organized porous cages that have been investigated for nearly three decades. Due to the flexibility in their design and predisposition toward functionalization, they have shown promise in many areas of application, including chemical sensing. Consequently, they are identified as advanced materials with potential for deployment in analytical devices for chemical and biochemical sensing applications, where high sensitivity is desirable, for example, in environmental monitoring and to advance personal diagnostics. To keep abreast of new research, which signposts the future directions in the development of MOF-based chemical sensors, this review examines studies since 2015 that focus on the applications of MOF films and devices in chemical sensing. Various examples that use MOF films in solid-state sensing applications were drawn from recent studies based on electronic, electrochemical, electromechanical and optical sensing methods. These examples underscore the readiness of MOFs to be integrated in optical and electronic analytical devices. Also, preliminary demonstrations of future sensors are indicated in the performances of MOF-based wearables and smartphone sensors. This review will inspire collaborative efforts between scientists and engineers working within the field of MOFs, leading to greater innovations and accelerating the development of MOF-based analytical devices for chemical and biochemical sensing applications.

Developing sustainable, high-performance perovskites in photocatalysis: design strategies and applications.

Solar energy is attractive because it is free, renewable, abundant and sustainable. Photocatalysis is one of the feasible routes to utilize solar energy for the degradation of pollutants and the production of fuel. Perovskites and their derivatives have received substantial attention in both photocatalytic wastewater treatment and energy production because of their highly tailorable structural and physicochemical properties. This review illustrates the basic principles of photocatalytic reactions and the application of these principles to the design of robust and sustainable perovskite photocatalysts. It details the structures of the perovskites and the physics and chemistry behind photocatalytic reactions and describes the advantages and limitations of popular strategies for the design of photoactive perovskites. This is followed by examples of how these strategies are applied to enhance the photocatalytic efficiency of oxide, halide and oxyhalide perovskites, with a focus on materials with potential for practical application, that is, not containing scarce or toxic elements. It is expected that this overview of the development of photocatalysts and deeper understanding of photocatalytic principles will accelerate the exploitation of efficient perovskite photocatalysts and bring about effective solutions to the energy and environmental crisis.

Use of metamodels for rapid discovery of narrow bandgap oxide photocatalysts.

New photocatalysts are traditionally identified through trial-and-error methods. Machine learning has shown considerable promise for improving the efficiency of photocatalyst discovery from a large potential pool. Here, we describe a multi-step, target-driven consensus method using a stacking meta-learning algorithm that robustly predicts bandgaps and H2 evolution activities of photocatalysts. Trained on small datasets, these models can rapidly screen a large space (>10 million materials) to identify promising, non-toxic compounds as candidate water splitting photocatalysts. Two effective compounds and two controls possessing optimal bandgap values (∼2 eV) but not photoactivity as predicted by the models were synthesized. Their experimentally measured bandgaps and H2 evolution activities were consistent with the predictions. Conspicuously, the two compounds with strong photoactivities under UV and visible light are promising visible-light-driven water splitting photocatalysts. This study demonstrates the power of machine learning and the potential of big data to accelerate discovery of next-generation photocatalysts.

Hierarchically Porous WO3/CdWO4 Fiber-in-Tube Nanostructures Featuring Readily Accessible Active Sites and Enhanced Photocatalytic Effectiveness for Antibiotic Degradation in Water.

The intentional design and construction of photocatalysts containing heterojunctions with readily accessible active sites will improve their ability to degrade pollutants. Herein, hierarchically porous WO3/CdWO4 fiber-in-tube nanostructures with three accessible surfaces (surface of core fiber and inner and outer surfaces of the porous tube shell) were fabricated by an electrospinning method. This WO3/CdWO4 heterostructure, assembled by interconnected nanoparticles, displays good photocatalytic degradation of ciprofloxacin (CIP, 93.4%) and tetracycline (TC, 81.6%) after 90 min of simulated sunlight irradiation, much higher than the pristine WO3 (<75.3% for CIP and <53.6% for TC) or CdWO4 materials (<58.9% for CIP and <39.5% for TC). The WO3/CdWO4 fiber-in-tube promotes the separation of photoinduced electrons and holes and also provides readily accessible reaction sites for photocatalytic degradation. The dominant active species determined by trapping active species and electron paramagnetic resonance were hydroxyl radicals followed by photogenerated holes and superoxide anions. The WO3/CdWO4 materials formed a Z-scheme heterojunction that generated superoxide anion and hydroxyl radicals, leading to degradation of antibiotics (CIP and TC) via photocatalysis in aqueous solution.

Trace-Level Fluorination of Mesoporous TiO2 Improves Photocatalytic and Pb(II) Adsorbent Performances.

Fluorination is an effective way of tuning the physicochemical property and activity of TiO2 nanocrystallites, which usually requires a considerable amount of hydrofluoric acid (or NH4F) for a typical F/Ti molar ratio, RF, of 0.5-69.0 during synthesis. This has consequential environmental issues due to the high toxicity and hazard of the reactants. In the present work, an environmentally benign fluorination approach is demonstrated that uses only a trace amount of sodium fluoride with an RF of 10-6 during synthesis. While it maintained the desirable high surface area (102.4 m2/g), the trace-level fluorination enabled significant enhancements on photocatalytic activities (e.g., a 56% increase on hydrogen evolution rate) and heavy metal Pb(II) removal (31%) of the mesoporous TiO2. This can be attributed to enriched Ti3+ and localized spatial charge separation due to fluorination as proved by X-ray photoelectron spectroscopy (XPS), electron paramagnetic resonance spectroscopy (EPR), and density functional theory (DFT) analyses.

Low-Temperature Solution-Processed Amorphous Titania Nanowire Thin Films for 1 cm2 Perovskite Solar Cells.

The development of solution-processed inorganic amorphous electron-transporting layers (ETLs) is important for the future commercialization of perovskite solar cells (PSCs). The formation of such ETLs using low-temperature processing techniques will lower potential production costs and accommodate diverse substrate materials. Herein, a low-temperature (<150 °C) solution process forms amorphous titania nanowire (Am-TNW) thin films on fluorine-doped tin oxide conducting glass substrates. When applied as an ETL in PSCs, the Am-TNW layer achieves a higher average power conversion efficiency (18.3%) relative to that of a nanocrystalline anatase TNW (ATNW) layer obtained after high-temperature (500 °C) heating (16.7%). Compared to the ATNW counterparts, the Am-TNW-based PSCs exhibit inferior charge extraction across the TNW/CH3NH3PbI3 interface but more effectively suppress interfacial charge recombination. The insertion of a fullerene layer between the Am-TNW and CH3NH3PbI3 improves the charge extraction. The Am-TNW-based bilayer ETL gave optimal power conversion efficiencies of 20.3% and 19.0% for PSCs with 0.16 cm2 and 1.00 cm2 apertures, respectively. This is due to the concurrent advantages of enhanced light absorption, facilitated charge extraction, and reduced charge recombination. The use of the Am-TNW as an ETL in PSCs provides a facile, efficient way to increase the effectiveness of PSCs.

Ordered Mesoporous Graphitic Carbon/Iron Carbide Composites with High Porosity as a Sulfur Host for Li-S Batteries.

The lithium-sulfur battery (LSB) is a promising candidate for future energy storage but faces technological challenges including the low electronic conductivity of sulfur and the solubility of intermediates during cycling. Additionally, current host materials often lack sufficient conductivity and porosity to raise the sulfur loading to over 80 wt %. Here, ordered mesoporous graphitic carbon/iron carbide nanocomposites were prepared via an evaporation-induced self-assembly process using soluble resol, prehydrolyzed tetraethyl orthosilicate (TEOS), and iron(III) chloride as the carbon, silica (SiO2), and iron precursors, respectively. Graphitization and SiO2 etching were conducted simultaneously via Teflon-assisted, solid-state decomposition at high temperature. A high surface area (∼3100 m2 g-1), large pore volume (∼3.3 cm3 g-1), and graphitized carbon frame were achieved, giving a high sulfur loading (85 wt %) while tolerating volumetric expansion during discharge. Electrochemical testing of a LSB containing the composite/sulfur cathode exhibited a superior reversible capacity exceeding 1300 mAh g-1 at a moderate current (C/10) and a low decay in capacity of 9% after 500 cycles at C/5. The interaction between mesoporous graphitic carbon and sulfur is proposed.

Solvent-Mediated Intragranular-Coarsening of CH3NH3PbI3 Thin Films toward High-Performance Perovskite Photovoltaics.

The deposition of dense and uniform perovskite films with large grains is crucial for fabricating high-performance perovskite solar cells (PSCs). High-quality CH3NH3PbI3 films were produced by a self-induced intragranular-coarsening approach. The perovskite precursor solution contained a Lewis base, N,N-dimethyl sulfoxide (DMSO), and was deposited using a gas-assisted, one-step, spin-coating method that was followed by a solvent vapor-assisted annealing treatment using a mix of DMSO and chlorobenzene (CBZ). Combining solvent-engineering with gas-assisted deposition helps to form intermediate crystalline entities upon evaporation of the parent solvent but retards the otherwise fast reaction between the precursor ingredients. Subsequent cosolvent annealing induces further grain-coarsening via a facilitated dissolution-precipitation process. This technique produced flat CH3NH3PbI3 films featuring large grain microstructures, with well-coarsened subgrains and a reduction of intragranular defects that minimized carrier recombination. The optimized CH3NH3PbI3 films exhibited enhanced crystallinity, excellent carrier transport and injection, as well as suppressed charge recombination. Benefiting from these advantages, PSCs based on the optimized perovskite films delivered a power conversion efficiency of 17.99% and a stabilized power output above 17.30%. This study presents an effective strategy for the fabrication of high-quality, hybrid perovskite films with potential applications in optoelectronic devices.

Effect of the Microstructure of the Functional Layers on the Efficiency of Perovskite Solar Cells.

The efficiencies of the hybrid organic-inorganic perovskite solar cells have been rapidly approaching the benchmarks held by the leading thin-film photovoltaic technologies. Arguably, one of the most important factors leading to this rapid advancement is the ability to manipulate the microstructure of the perovskite layer and the adjacent functional layers within the device. Here, an analysis of the nucleation and growth models relevant to the formation of perovskite films is provided, along with the effect of the perovskite microstructure (grain sizes and voids) on device performance. In addition, the effect of a compact or mesoporous electron-transport-layer (ETL) microstructure on the perovskite film formation and the optical/photoelectric properties at the ETL/perovskite interface are overviewed. Insight into the formation of the functional layers within a perovskite solar cell is provided, and potential avenues for further development of the perovskite microstructure are identified.

High-Performance Coral Reef-like Carbon Nitrides: Synthesis and Application in Photocatalysis and Heavy Metal Ion Adsorption.

Synthesis of carbon nitrides (CNx) by refluxing under nitrogen exhibited mixed growth mechanisms of oriented attachment and Ostwald ripening, leading to the formation of coral reef-like microstructures from spherical agglomerates. Some phase transformation from ß-phase to α-phase CNx occurred upon refluxing for 1.5 h, producing a biphasic CNx. The N content relative to C was determined from CHN elemental analysis, and the presence of C═N and terminal groups (i.e., COOH and NH2) was consistent with the Fourier transform infrared, nuclear magnetic resonance, and X-ray photoelectron spectroscopic results. The sample refluxed for 2.0 h (CNx/2.0 h) had the highest surface area of 24.5 m2·g-1 and displayed enhanced adsorption capacities for methylene blue (MB) molecules and heavy metal ions Pb2+ (720 mg·g-1), Cd2+ (480 mg·g-1), and As(V) (220 mg·g-1), which was attributed to the presence of COOH functional groups. CNx samples had a negative surface charge that electrostatically attracted the cationic heavy metal ions as well as MB molecules for subsequent photodecomposition under visible-light illumination. The photocatalytic activity of CNx/2.0 h toward phenol, a common pollutant in aqueous waste, was also demonstrated and a possible photocatalytic route was proposed.

Probing the Effects of Templating on the UV and Visible Light Photocatalytic Activity of Porous Nitrogen-Modified Titania Monoliths for Dye Removal.

Porous nitrogen-modified titania (N-titania) monoliths with tailored morphologies were prepared using phase separation and agarose gel templating techniques. The doping and templating process were simultaneously carried out in a one-pot step using alcohol amine-assisted sol-gel chemistry. The amount of polymer used in the monoliths that were prepared using phase separation was shown to affect both the physical and optical properties: higher poly(ethylene glycol) content increased the specific surface area, porosity, and visible light absorption of the final materials. For the agarose-templated monoliths, the infiltration conditions affected the monolith morphology. A porous monolith with high surface area and the least shrinkage was obtained when the N containing alkoxide precursor was infiltrated into the agarose scaffolds at 60 °C. The effect of the diverse porous morphologies on the photocatalytic activity of N-titania was studied for the decomposition of methylene blue (MB) under visible and UV light irradiation. The highest visible light activity was achieved by the agarose-templated N-titania monolith, in part due to higher N incorporation. This sample also showed better UV activity, partly because of the higher specific surface area (up to 112 m(2) g(-1)) compared to the phase separation-induced monoliths (up to 103 m(2) g(-1)). Overall, agarose-templated, porous N-titania monoliths provided better features for effectively removing the MB contaminant.

Flowerlike WSe2 and WS2 microspheres: one-pot synthesis, formation mechanism and application in heavy metal ion sequestration.

Flowerlike WSe2 and WS2 microspheres were synthesized by a facile and scalable one-pot solvothermal method. Their formation mechanism followed the reaction between dissolved W(CO)6 and dissolved S or melted Se without complete decomposition of W(CO)6 into tungsten. As novel efficient sorbents, WSe2 and WS2 demonstrated outstanding uptake capacities for Pb(2+) and Hg(2+).