Search for: All records

The presence of heavy metals in our water supply poses an immense global public health burden. Heavy metal consumption is tied to increased mortality and a wide range of insidious health outcomes. In recent years, great strides have been made toward nanotechnological approaches for environmental problems, specifically the design of adsorbents to detoxify water, as well as for a related challenge of recovering valuable metals at low concentrations. However, applying nanomaterials at scale and differentiating which nanomaterials are best suited for particular applications can be challenging. Here, we report a methodology for loading nanomaterial coatings onto adsorbent membranes, testing different coatings against one another, and leveraging these materials under a variety of conditions. Our tailored coating for lead remediation, made from manganese-doped goethite nanoparticles, can filter lead from contaminated water to below detectable levels when coated onto a cellulose membrane, and the coated membrane can be recovered and reused for multiple cycles through mild tuning of pH. The Nano-SCHeMe methodology demonstrates a platform approach for effectively deploying nanomaterials for environmental applications and for direct and fair comparisons among these nanomaterials. Moreover, this approach is flexible and expansive in that our coatings have the potential to be applied to a range of sorbents. 

Abstract Material properties strongly depend on the nature and concentration of defects. Characterizing these features may require nano- to atomic-scale resolution to establish structure–property relationships. 4D-STEM, a technique where diffraction patterns are acquired at a grid of points on the sample, provides a versatile method for highlighting defects. Computational analysis of the diffraction patterns with virtual detectors produces images that can map material properties. Here, using multislice simulations, we explore different virtual detectors that can be applied to the diffraction patterns that go beyond the binary response functions that are possible using ordinary STEM detectors. Using graphene and lead titanate as model systems, we investigate the application of virtual detectors to study local order and in particular defects. We find that using a small convergence angle with a rotationally varying detector most efficiently highlights defect signals. With experimental graphene data, we demonstrate the effectiveness of these detectors in characterizing atomic features, including vacancies, as suggested in simulations. Phase and amplitude modification of the electron beam provides another process handle to change image contrast in a 4D-STEM experiment. We demonstrate how tailored electron beams can enhance signals from short-range order and how a vortex beam can be used to characterize local symmetry. 

Abstract High-density phase change memory (PCM) storage is proposed for materials with multiple intermediate resistance states, which have been observed in 1T-TaS₂due to charge density wave (CDW) phase transitions. However, the metastability responsible for this behavior makes the presence of multistate switching unpredictable in TaS₂devices. Here, we demonstrate the fabrication of nanothick verti-lateralH-TaS₂/1T-TaS₂heterostructures in which the number of endotaxial metallicH-TaS₂monolayers dictates the number of resistance transitions in 1T-TaS₂lamellae near room temperature. Further, we also observe optically active heterochirality in the CDW superlattice structure, which is modulated in concert with the resistivity steps, and we show how strain engineering can be used to nucleate these polytype conversions. This work positions the principle of endotaxial heterostructures as a promising conceptual framework for reliable, non-volatile, and multi-level switching of structure, chirality, and resistance.