Rigid, conjugated molecules are excellent candidates as molecular wires since they can achieve full extension between electrodes while maintaining conjugation. Molecular design can be used to minimize the accessible pi surface and interactions between the bridging wire and the electrode. Polyynes are archetypal molecular wires that feature a rigid molecular framework with a cross-section of a single carbon atom. Understanding the behavior of polyynes in molecular junctions is essential for testing models of length versus electron transport. We report the construction of molecular junctions using polyynes with a well-defined length up to ca. 5 nm in devices characterized by scanning tunneling microscopy break junctions. The polyynes, ( = 4, 6, 8, 10, 12, 16), are end-capped with pyridyl groups, and we demonstrate good agreement between the length of the molecular junction and the calculated molecular length, with an average discrepancy of just 0.1 nm. This highlights the power of STM-BJ experiments to accurately determine the molecular length. The range of molecular lengths, from 1.8 to 4.8 nm, mark this as the most accurate determination of β in polyynes to date (β = 2.2 ± 0.1 nm). We have applied a model based on the single and triple bond lengths to interpret β-values, which predicts β = 1.9 nm, consistent with the experimental value. This model also confirms that electronic coupling in polyynes is unaffected by the rotation about the single bonds. At all molecular lengths, we observe conductance in the tunneling regime due to the long effective conjugation length of polyynes.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1021/jacs.4c12895 | DOI Listing |
Neuro Oncol
January 2025
Division of Oncology, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
Background: Central nervous system (CNS) tumors lead to cancer-related mortality in children. Genetic ancestry-associated cancer prevalence and outcomes have been studied, but is limited.
Methods: We performed genetic ancestry prediction in 1,452 pediatric patients with paired normal and tumor whole genome sequencing from the Open Pediatric Cancer (OpenPedCan) project to evaluate the influence of reported race and ethnicity and ancestry-based genetic superpopulations on tumor histology, molecular subtype, survival, and treatment.
Syst Biol
January 2025
Simon F. S. Li Marine Science Laboratory, School of Life Sciences and State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong SAR.
Obtaining a timescale for bacterial evolution is crucial to understand early life evolution but is difficult owing to the scarcity of bacterial fossils. Here, we introduce multiple new time constraints to calibrate bacterial evolution based on ancient symbiosis. This idea is implemented using a bacterial tree constructed with genes found in the mitochondrial lineages phylogenetically embedded within Proteobacteria.
View Article and Find Full Text PDFJCI Insight
January 2025
Division of Nephrology, Department of Medicine, Vanderbildt University Medical Center, Nashville, United States of America.
Urinary obstruction causes injury to the renal medulla, impairing the ability to concentrate urine, and increasing the risk of progressive kidney disease. However, the regenerative capacity of the renal medulla after reversal of obstruction is poorly understood. To investigate this, we developed a mouse model of reversible urinary obstruction.
View Article and Find Full Text PDFBrief Bioinform
November 2024
Department of Automation, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Minhang District, Shanghai 200240, China.
Studying the changes in cellular transcriptional profiles induced by small molecules can significantly advance our understanding of cellular state alterations and response mechanisms under chemical perturbations, which plays a crucial role in drug discovery and screening processes. Considering that experimental measurements need substantial time and cost, we developed a deep learning-based method called Molecule-induced Transcriptional Change Predictor (MiTCP) to predict changes in transcriptional profiles (CTPs) of 978 landmark genes induced by molecules. MiTCP utilizes graph neural network-based approaches to simultaneously model molecular structure representation and gene co-expression relationships, and integrates them for CTP prediction.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!