Understanding the effect of density functional choice and van der Waals treatment on predicting the binding configuration, loading, and stability of amine-grafted metal organic frameworks.

Metal organic frameworks (MOFs) are crystalline, three-dimensional structures with high surface areas and tunable porosities. Made from metal nodes connected by organic linkers, the exact properties of a given MOF are determined by node and linker choice. MOFs hold promise for numerous applications, including gas capture and storage. M2(4,4'-dioxidobiphenyl-3,3'-dicarboxylate)-henceforth simply M2(dobpdc), with M = Mg, Mn, Fe, Co, Ni, Cu, or Zn-is regarded as one of the most promising structures for CO2 capture applications. Further modification of the MOF with diamines or tetramines can significantly boost gas species selectivity, a necessity for the ultra-dilute CO2 concentrations in the direct-air capture of CO2. There are countless potential diamines and tetramines, paving the way for a vast number of potential sorbents to be probed for CO2 adsorption properties. The number of amines and their configuration in the MOF pore are key drivers of CO2 adsorption capacity and kinetics, and so a validation of computational prediction of these quantities is required to suitably use computational methods in the discovery and screening of amine-functionalized sorbents. In this work, we study the predictive accuracy of density functional theory and related calculations on amine loading and configuration for one diamine and two tetramines. In particular, we explore the Perdew-Burke-Ernzerhof (PBE) functional and its formulation for solids (PBEsol) with and without the Grimme-D2 and Grimme-D3 pairwise corrections (PBE+D2/3 and PBEsol+D2/3), two revised PBE functionals with the Grimme-D2 and Grimme-D3 pairwise corrections (RPBE+D2/3 and revPBE+D2/3), and the nonlocal van der Waals correlation (vdW-DF2) functional. We also investigate a universal graph deep learning interatomic potential's (M3GNet) predictive accuracy for loading and configuration. These results allow us to identify a useful screening procedure for configuration prediction that has a coarse component for quick evaluation and a higher accuracy component for detailed analysis. Our general observation is that the neural network-based potential can be used as a high-level and rapid screening tool, whereas PBEsol+D3 gives a completely qualitatively predictive picture across all systems studied, and can thus be used for high accuracy motif predictions. We close by briefly exploring the predictions of relative thermal stability for the different functionals and dispersion corrections.

Stratification of chemotherapy-treated stage III colorectal cancer patients using multiplexed imaging and single-cell analysis of T-cell populations.

Colorectal cancer (CRC) has one of the highest cancer incidences and mortality rates. In stage III, postoperative chemotherapy benefits <20% of patients, while more than 50% will develop distant metastases. Biomarkers for identification of patients at increased risk of disease recurrence following adjuvant chemotherapy are currently lacking. In this study, we assessed immune signatures in the tumor and tumor microenvironment (TME) using an in situ multiplexed immunofluorescence imaging and single-cell analysis technology (Cell DIVETM) and evaluated their correlations with patient outcomes. Tissue microarrays (TMAs) with up to three 1 mm diameter cores per patient were prepared from 117 stage III CRC patients treated with adjuvant fluoropyrimidine/oxaliplatin (FOLFOX) chemotherapy. Single sections underwent multiplexed immunofluorescence staining for immune cell markers (CD45, CD3, CD4, CD8, FOXP3, PD1) and tumor/cell segmentation markers (DAPI, pan-cytokeratin, AE1, NaKATPase, and S6). We used annotations and a probabilistic classification algorithm to build statistical models of immune cell types. Images were also qualitatively assessed independently by a Pathologist as 'high', 'moderate' or 'low', for stromal and total immune cell content. Excellent agreement was found between manual assessment and total automated scores (p < 0.0001). Moreover, compared to single markers, a multi-marker classification of regulatory T cells (Tregs: CD3+/CD4+FOXP3+/PD1-) was significantly associated with disease-free survival (DFS) and overall survival (OS) (p = 0.049 and 0.032) of FOLFOX-treated patients. Our results also showed that PD1- Tregs rather than PD1+ Tregs were associated with improved survival. These findings were supported by results from an independent FOLFOX-treated cohort of 191 stage III CRC patients, where higher PD1- Tregs were associated with an increase overall survival (p = 0.015) for CD3+/CD4+/FOXP3+/PD1-. Overall, compared to single markers, multi-marker classification provided more accurate quantitation of immune cell types with stronger correlations with outcomes.

Temperature-dependent and bistable current-voltage measurements in zinc porphyrin molecular junctions.

We report bistability in current-voltage curves from di(PEP)PorZn in an electromigrated molecular junction. Bistability was observed at ±0.3 V at 300 K but did not occur at 4 K. No bistability was identified at 300 K for another porphyrin molecule (di(Xyl)PorZn), where the phenyl-ethnyl-phenyl (PEP) side groups were replaced with a flexible p-xylene. Molecular dynamics simulations show that bistability may be due to conformation changes related to the fluctuation of the dihedral angle surrounding the zinc and/or the rotation of the porphyrin central plane of the molecule. Results suggest that other mechanisms may play a role in the current-voltage characteristics observed.

Improved all-carbon spintronic device design.

The discovery of magnetism in carbon structures containing zigzag edges has stimulated new directions in the development and design of spintronic devices. However, many of the proposed structures are designed without incorporating a key phenomenon known as topological frustration, which leads to localized non-bonding states (free radicals), increasing chemical reactivity and instability. By applying graph theory, we demonstrate that topological frustrations can be avoided while simultaneously preserving spin ordering, thus providing alternative spintronic designs. Using tight-binding calculations, we show that all original functionality is not only maintained but also enhanced, resulting in the theoretically highest performing devices in the literature today. Furthermore, it is shown that eliminating armchair regions between zigzag edges significantly improves spintronic properties such as magnetic coupling.

Self-organized and cu-coordinated surface linear polymerization.

We demonstrate a controllable surface-coordinated linear polymerization of long-chain poly(phenylacetylenyl)s that are self-organized into a "circuit-board" pattern on a Cu(100) surface. Scanning tunneling microscopy/spectroscopy (STM/S) corroborated by ab initio calculations, reveals the atomistic details of the molecular structure, and provides a clear signature of electronic and vibrational properties of the poly(phenylacetylene)s chains. Notably, the polymerization reaction is confined epitaxially to the copper lattice, despite a large strain along the polymerized chain that subsequently renders it metallic. Polymerization and depolymerization reactions can be controlled locally at the nanoscale by using a charged metal tip. This control demonstrates the possibility of precisely accessing and controlling conjugated chain-growth polymerization at low temperature. This finding may lead to the bottom-up design and realization of sophisticated architectures for molecular nano-devices.

Electronic structure and transport properties of N2(AA)-doped armchair and zigzag graphene nanoribbons.

Substitutional doping in graphene nanoribbons (GNRs) promises to enable specific tuning of their electronic properties. Recent work by Lv et al (2012 Nature Sci. Rep. 2 586) on large sheets of nitrogen-doped graphene determined that a highly predominant amount of nitrogen dopants (80%) are present in pairs of neighbouring atoms of the same sublattice A, denoted as N2(AA) dopants, following the notation of Lv et al. Here, we explore the electronic and transport properties of armchair (aGNR) and zigzag (zGNR) graphene nanoribbons under different orientations of the N2(AA) dopants with respect to the ribbon growth direction. For all dopant configurations of zGNRs and aGNRs, we find a substantial decrease in conductance, with new conductance gaps opening in some cases, and spatially localized states induced around the dopant sites. We also provide simulated scanning tunnelling microscopy images that will aid in the experimental identification of the presence of these structures in N-doped GNR samples.