Spin-ordered electronic states in hydrogen-terminated zigzag nanographene give rise to magnetic quantum phenomena 1,2 that have sparked renewed interest in carbon-based spintronics 3,4 . Zigzag graphene nanoribbons (ZGNRs)quasi one-dimensional semiconducting strips of graphene featuring two parallel zigzag edges along the main axis of the ribbonare predicted to host intrinsic electronic edge states that are ferromagnetically ordered along the edges of the ribbon and antiferromagnetically coupled across its width 1,2,5 . Despite recent advances in the bottom-up synthesis of atomically-precise ZGNRs, their unique electronic structure has thus far been obscured from direct observations by the innate chemical reactivity of spin-ordered edge states [6][7][8][9][10][11] . Here we present a general technique for passivating the chemically highly reactive spin-polarized edge states by introducing a superlattice of substitutional nitrogen-dopants along the edges of a ZGNR. First-principles GW calculations and scanning tunneling spectroscopy reveal a giant spin splitting of the low-lying nitrogen lone-pair flat bands by a large exchange field (~850 Tesla) induced by the spin-polarized ferromagnetically ordered edges of ZGNRs. Our findings directly corroborate the nature of the predicted emergent magnetic order in ZGNRs and provide a robust platform for their exploration and functional integration into nanoscale sensing and logic devices [11][12][13][14][15][16][17] .Graphene nanostructures terminated by zigzag edges host spin-ordered electronic states that give rise to quantum magnetism 1,2 . These intrinsic magnetic edge states emerge from the zigzag edge structure of graphene itself, and create opportunities for the exploration of carbon-based spintronics and qubits [18][19][20] , paving the way for the realization of high-speed, low-power operation spin-logic devices for data storage and information processing [21][22][23][24] . The edge states of zigzag graphene nanoribbons (ZGNRs) have been predicted to exhibit a parallel (ferromagnetic) alignment of spins on either edge of the ribbon while the spins on opposing edges are antiferromagnetically coupled (antiparallel alignment) 1,2 . This unusual electronic structure can give rise to field-or strain-driven half-metallicity in ZGNRs 2,25 . A strong hybridization of the electronic states of ZGNRs with those of the underlying support, along with the susceptibility of zigzag edges to undergo passivation through atom-abstraction or radical-recombination reactions represents a veritable challenge to their exploration.

Scanning tunneling spectroscopy (STS), a technique that records the change in the tunneling current as a function of the bias (dI/dV) across the gap between a tip and the sample, is a powerful tool to characterize the electronic structure of single molecules and nanomaterials. While performing STS, the structure and condition of the scanning probe microscopy (SPM) tips are critical for reliably obtaining high quality point spectra. Here, we present an automated program based on machine learning models that can identify the Au(111) Shockley surface state in dI/dV point spectra and perform tip conditioning on clean or sparsely covered gold surfaces with minimal user intervention. We employed a straightforward height-based segmentation algorithm to analyze STM topographic images to identify tip conditioning positions and used 1789 archived dI/dV spectra to train machine learning models that can ascertain the condition of the tip by evaluating the quality of the spectroscopic data. Decision tree based ensemble and boosting models and deep neural networks (DNNs) have been shown to reliably identify tips in suitable conditions for STS. We expect the automated program to reduce operational costs and time, increase reproducibility in surface science studies, and accelerate the discovery and characterization of novel nanomaterials by STM. The strategies presented in this paper can readily be adapted to STM tip conditioning on a wide variety of other common substrates.

We measured photoinduced charge separation in isolated individual C60-tethered 2,5-dithienylpyrrole triad (C60 triad) molecules with submolecular resolution using a custom-built laser-assisted scanning tunneling microscope. Laser illumination was introduced evanescently into the tunneling junction through total internal reflection, and the changes in tunneling current and electronic spectra caused by photoexcitation were measured and spatially resolved. Photoinduced charge separation was not detected for all C60 triad molecules, indicating that the conformations of the molecules may affect the excitation probability, lifetime, and/or charge distribution. A photoinduced signal was not observed for dodecanethiol molecules in the surrounding matrix or for control molecules without C60 moieties, as neither absorbs incident photons at this energy. This spectroscopic imaging technique has the potential to elucidate detailed photoinduced carrier dynamics, which are inaccessible via ensemble-scale (i.e., averaging) measurements, which can be used to direct the rational design and optimization of molecular p–n junctions and assemblies for energy harvesting.

We prepared titanyl phthalocyanine (TiOPc) monolayers on sapphire-prism supported Au{111} substrates through solution deposition and characterized their photo-responses using a custom-built laser-assisted scanning tunneling microscope under ambient conditions. Two types of lattice structures (hexagonal and rectangular) were observed and the distributions of photo-induced charges were measured under evanescently introduced 633 nm and 780 nm laser illumination. The distributions of photoelectrons in molecules in hexagonal lattices match theoretically calculated charge density changes in TiOPc molecules upon excitation. However, the photo-responses of TiOPc molecules in rectangular lattices are different than those predicted and TiOPc molecules in these arrangements may have lower excitation probabilities at 633 nm and 780 nm. Our results suggest that the photo carrier generation efficiency of TiOPc molecules is related to their packing arrangements in monolayers and local environments.