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1. Group 7 carbonyl complexes of a PNN-heteroscorpionate ligand

   https://doi.org/10.1039/D4RA05287K  

   Valdivieso, Jorge P; Erickson, Alexander N; Gardinier, James R (October 2024, RSC Advances)

   A PNN heteroscorpionate ligand facilitates CO-release in univalent tricarbonyl group 7 complexes. 

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2. Building Scalable Silicon Microring Resonator‐Based Neuromorphic Photonic Circuits Using Post‐Fabrication Processing with Photochromic Material

   https://doi.org/10.1002/adom.202402706  

   Xu, Lei; Zhang, Jiawei; Doris, Eli_A; Bilodeau, Simon; Wisch, Jesse_A; Gui, Manting; Jimoh, Yusuf_O; Shastri, Bhavin; Rand, Barry_P; Prucnal, Paul_R (March 2025, Advanced Optical Materials)

   Abstract Neuromorphic photonics has become one of the research forefronts in photonics, with its benefits in low‐latency signal processing and potential in significant energy consumption reduction when compared with digital electronics. With artificial intelligence (AI) computing accelerators in high demand, one of the high‐impact research goals is to build scalable neuromorphic photonic integrated circuits which can accelerate the computing of AI models at high energy efficiency. A complete neuromorphic photonic computing system comprises seven stacks: materials, devices, circuits, microarchitecture, system architecture, algorithms, and applications. Here, we consider microring resonator (MRR)‐based network designs toward building scalable silicon integrated photonic neural networks (PNN), and variations of MRR resonance wavelength from the fabrication process and their impact on PNN scalability. Further, post‐fabrication processing using organic photochromic layers over the silicon platform is shown to be effective for trimming MRR resonance wavelength variation, which can significantly reduce energy consumption from the MRR‐based PNN configuration. Post‐fabrication processing with photochromic materials to compensate for the variation in MRR fabrication will allow a scalable silicon system on a chip without sacrificing today's performance metrics, which will be critical for the commercial viability and volume production of large‐scale silicon photonic circuits. 

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3. Aves del Parque Nacional Natural Chingaza y zona de amortiguación, Cordillera Oriental de Colombia

   https://doi.org/10.21068/c2020.v21n01a09  

   Linares, Luis Guillermo (January 2020, Biota Colombiana)

   null (Ed.)

   Describimos la composición de especies de aves del Parque Nacional Natural (PNN) Chingaza y su zona de amortiguación, a partir de la revisión de 10 estudios ornitológicos, trabajo de campo entre 2008–2017 y la expedición Colombia Bio en 2018. Reportarmos para el PNN Chingaza y su zona de amortiguación un total de 531 especies, agrupadas en 339 géneros y 57 familias. Seis especies presentes en el parque son endémicas de Colombia, 14 casi endémicas, 1 en peligro crítico, 6 en peligro, 4 vulnerables, 3 casi amenazadas y 37 migratorias. Esta lista incluye 149 especies adicionales a la información previamente conocida por datos publicados y colecciones ornitológicas. Adicionalmente, generamos códigos de barras genéticos, con base en secuencias del gen mitocondrial COI, para 74 especies y presentamos los primeros registros genéticos de Colombia en la plataforma para códigos de barra genéticos Barcode of Life Datasystems (BOLD) para Dysithamnus leucostictus, Chamaeza turdina, Rupicola peruvianus, Atlapetes semirufus, Euphonia mesochrysa y Chlorospingus flavopectus olsoni.  El presente listado es una herramienta para incentivar el estudio y conservación de las aves en este sector de la Cordillera Oriental colombiana. 

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4. Pincers with diverse donors and their interconversion: application to Ni(II)

   https://doi.org/10.1002/zaac.202100064  

   Cabelof, Alyssa C.; Carta, Veronica; Chen, Chun‐Hsing; Pink, Maren; Caulton, Kenneth G. (July 2021, Zeitschrift für anorganische und allgemeine Chemie)

   Abstract A pincer ligand composed of a pyridine with ortho positions substituted by a bulky phosphine arm and a pyrazole arm (PNNH) is installed on nickel(II) to yield the diamagnetic planar complex [(PNNH)NiCl]Cl. The chloride anion can be replaced by BPh₄⁻by a metathesis. The acidic pyrazole proton can be removed with LiN(SiMe₃)₂to yield the square planar neutral molecule (PNN⁻)NiCl. The coordinated chloride can be metathetically replaced by azide to yield diamagnetic (PNN⁻)Ni(N₃). To evaluate changing the phosphine donor for a phosphine sulfide, the corresponding pincer ligand SPNNH was synthesized and installed on NiBr₂. The reduced steric bulk from the more distant phosphorous keeps both halides coordinated in the paramagnetic molecular species (SPNNH)NiBr₂. Several attempts to dehydrobrominate this species result in synthesis and characterization of two unexpected products. One effort revealed that the electrophilic character of P(V) leaves the phosphorus atom in (SPNNH)NiBr₂vulnerable to nucleophilic attack, resulting in a P/C cleavage product which was characterized. 

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5. Advances in photonic neuromorphic computing (Conference Presentation)

   https://doi.org/10.1117/12.2509838  

   Sorger, Volker J.; George, Jonathan K.; Mehrabian, Armin; Shastri, Bhavin; El-Ghazawi, Tarek; Prucnal, Paul R.; Lee, El-Hang; He, Sailing (March 2019, Proceedings Volume 10922, Smart Photonic and Optoelectronic Integrated Circuits XXI)

   Abstract Photonic neural networks (PNN) are a promising alternative to electronic GPUs to perform machine-learning tasks. The PNNs value proposition originates from i) near-zero energy consumption for vector matrix multiplication once trained, ii) 10-100 ps short interconnect delays, iii) weak required optical nonlinearity to be provided via fJ/bit efficient emerging electrooptic devices. Furthermore, photonic integrated circuits (PIC) offer high data bandwidth at low latency, with competitive footprints and synergies to microelectronics architectures such as foundry access. This talk discusses recent advances in photonic neuromorphic networks and provides a vision for photonic information processors. Details include, 1) a comparison of compute performance technologies with respect to compute efficiency (i.e. MAC/J) and compute speed (i.e. MAC/s), 2) a discussion of photonic neurons, i.e. perceptrons, 3) architectural network implementations, 4) a broadcast-and-weight protocol, 5) nonlinear activation functions provided via electro-optic modulation, and 6) experimental demonstrations of early-stage prototypes. The talk will open up answering why neural networks are of interest, and concludes with an application regime of PNN processors which reside in deep-learning, nonlinear optimization, and real-time processing. 

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