Sensors containing metal-carbon nanotube (CNT) hybrid materials as the active sensing layer were demonstrated for ethanol vapor detection at room temperature. The metal-CNT hybrid materials were synthesized by infiltrating single wall carbon nanotubes (SWNTs) with the transition metals Ti, Mn, Fe, Co, Ni, Pd or Pt. Each sensor was prepared by drop-casting dilute dispersions of a metal-CNT hybrid onto quartz substrate electrodes and the impedimetric responses to varying ethanol concentration were recorded. Upon exposure to ethanol vapor, the ac impedance (Z') of the sensors was found to decrease to different extents. The sensor containing pristine CNT material was virtually non-responsive at low ethanol concentrations (<50 ppm). In contrast, all metal-CNT hybrid sensors showed extremely high sensitivity to trace ethanol levels with 100-fold or more gains in sensitivity relative to the starting SWNT sensor. All hybrid sensors, with the exception of Ni filled CNT, exhibited significantly larger sensor responses to ethanol vapor up to 250 ppm compared to the starting SWNT sensor.
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http://dx.doi.org/10.1088/0957-4484/20/23/235502 | DOI Listing |
Chem Sci
January 2025
Department of Chemistry, Rice University Houston Texas 77005 USA
We recently demonstrated molecular plasmons in cyanine dyes for the conversion of photon energy into mechanical energy through a whole-molecule coherent vibronic-driven-action. Here we present a model, a molecular plasmon analogue of molecular orbital theory and of plasmon hybridization in metal nanostructures. This model describes that molecular plasmons can be obtained from the combination or hybridization of elementary molecular fragments, resulting in molecules with hybridized plasmon resonances in the electromagnetic spectrum.
View Article and Find Full Text PDFJAMIA Open
February 2025
Department of Medicine, University of Wisconsin-Madison, Madison, WI 53792, United States.
Objective: To evaluate large language models (LLMs) for pre-test diagnostic probability estimation and compare their uncertainty estimation performance with a traditional machine learning classifier.
Materials And Methods: We assessed 2 instruction-tuned LLMs, Mistral-7B-Instruct and Llama3-70B-chat-hf, on predicting binary outcomes for Sepsis, Arrhythmia, and Congestive Heart Failure (CHF) using electronic health record (EHR) data from 660 patients. Three uncertainty estimation methods-Verbalized Confidence, Token Logits, and LLM Embedding+XGB-were compared against an eXtreme Gradient Boosting (XGB) classifier trained on raw EHR data.
Clin Cosmet Investig Dent
January 2025
Department of Restorative Dentistry, Faculdade de Odontologia de Piracicaba, Universidade Estadual de Campinas, Piracicaba, SP, Brazil.
Objective: This study aimed to evaluate the in vitro effects of coffee exposure on the color and roughness of conventional and bulk-fill resin composites, with and without surface pre-reacted glass-ionomer (S-PRG) filler.
Methodology: Forty-eight cylindrical samples (Ø6 mm × 2 mm) were prepared and categorized as follows (n = 12 per group): conventional nano-hybrid (Tetric N-Ceram, Ivoclar); nano-hybrid with S-PRG filler (Beautifil II, Shofu); bulk-fill (Tetric N-Ceram Bulk Fill, Ivoclar); and bulk-fill with S-PRG filler (Beautifil Bulk Restorative, Shofu). The samples were assessed for surface roughness (Ra, μm), color coordinates (CIE Lb), and overall color change (ΔE, ΔE).
J Oral Microbiol
January 2025
Department of Biosciences; Piracicaba School of Dentistry, University of Campinas, Piracicaba, Brazil.
Background: The aim of this article is to evaluate the effect of different portions of Platelet Rich Fibrin (PRF) membranes and liquid-PRF, prepared by two distinct protocols/centrifuges each, on the multispecies subgingival biofilm.
Materials And Methods: PRF membranes and liquid-PRF were prepared using two protocols: centrifuge 1 uses fixed acceleration while centrifuge 2, progressive acceleration. PRF samples were introduced into device concurrently with 33-species bacterial inoculum.
Phys Chem Chem Phys
January 2025
Department of Physics, Institute for Sustainable Energy and Environment, Virginia Commonwealth University, Richmond, VA, 23284, USA.
We propose a new stable three-dimensional (3D) porous and metallic boron nitride anode material, named h-BN, with good ductility for sodium-ion batteries (SIBs). Based on first-principles calculations and a tight-binding model, we demonstrate that the metallicity originates from the synergistic contribution of the p-orbital of the sp-hybridized B and N atoms, while the ductility is due to the unique configurations of B-B and N-N dimers in the structure. More importantly, this boron nitride allotrope exhibits a high reversible capacity of 582.
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