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ImportanceVirtual patient-physician communications have increased since 2020 and negatively impacted primary care physician (PCP) well-being. Generative artificial intelligence (GenAI) drafts of patient messages could potentially reduce health care professional (HCP) workload and improve communication quality, but only if the drafts are considered useful. ObjectivesTo assess PCPs’ perceptions of GenAI drafts and to examine linguistic characteristics associated with equity and perceived empathy. Design, Setting, and ParticipantsThis cross-sectional quality improvement study tested the hypothesis that PCPs’ ratings of GenAI drafts (created using the electronic health record [EHR] standard prompts) would be equivalent to HCP-generated responses on 3 dimensions. The study was conducted at NYU Langone Health using private patient-HCP communications at 3 internal medicine practices piloting GenAI. ExposuresRandomly assigned patient messages coupled with either an HCP message or the draft GenAI response. Main Outcomes and MeasuresPCPs rated responses’ information content quality (eg, relevance), using a Likert scale, communication quality (eg, verbosity), using a Likert scale, and whether they would use the draft or start anew (usable vs unusable). Branching logic further probed for empathy, personalization, and professionalism of responses. Computational linguistics methods assessed content differences in HCP vs GenAI responses, focusing on equity and empathy. ResultsA total of 16 PCPs (8 [50.0%] female) reviewed 344 messages (175 GenAI drafted; 169 HCP drafted). Both GenAI and HCP responses were rated favorably. GenAI responses were rated higher for communication style than HCP responses (mean [SD], 3.70 [1.15] vs 3.38 [1.20];P = .01,U = 12 568.5) but were similar to HCPs on information content (mean [SD], 3.53 [1.26] vs 3.41 [1.27];P = .37;U = 13 981.0) and usable draft proportion (mean [SD], 0.69 [0.48] vs 0.65 [0.47],P = .49,t = −0.6842). Usable GenAI responses were considered more empathetic than usable HCP responses (32 of 86 [37.2%] vs 13 of 79 [16.5%]; difference, 125.5%), possibly attributable to more subjective (mean [SD], 0.54 [0.16] vs 0.31 [0.23];P < .001; difference, 74.2%) and positive (mean [SD] polarity, 0.21 [0.14] vs 0.13 [0.25];P = .02; difference, 61.5%) language; they were also numerically longer (mean [SD] word count, 90.5 [32.0] vs 65.4 [62.6]; difference, 38.4%), but the difference was not statistically significant (P = .07) and more linguistically complex (mean [SD] score, 125.2 [47.8] vs 95.4 [58.8];P = .002; difference, 31.2%). ConclusionsIn this cross-sectional study of PCP perceptions of an EHR-integrated GenAI chatbot, GenAI was found to communicate information better and with more empathy than HCPs, highlighting its potential to enhance patient-HCP communication. However, GenAI drafts were less readable than HCPs’, a significant concern for patients with low health or English literacy. 

Abstract Determining the relative energies of transport states in organic semiconductors is critical to understanding the properties of electronic devices and in designing device stacks. Futhermore, defect states are also highly important and can greatly impact material properties and device performance. Recently, energy‐resolved electrochemical impedance spectroscopy (ER‐EIS) is developed to probe both the ionization energy (IE) and electron affinity (EA) as well as sub‐bandgap defect states in organic semiconductors. Herein, ER‐EIS is compared to cyclic voltammetry (CV) and photoemission spectroscopies for extracting IE and EA values, and to photothermal deflection spectroscopy (PDS) for probing defect states in both polymer and molecular organic semiconductors. The results show that ER‐EIS determined IE and EA are in better agreement with photoemission spectroscopy measurements as compared to CV for both polymer and molecular materials. Furthermore, the defect states detected by ER‐EIS agree with sub‐bandgap features detected by PDS. Surprisingly, ER‐EIS measurements of regiorandom and regioregular poly(3‐hexylthiophene) (P3HT) show clear defect bands that occur at significantly different energies. In regioregular P3HT the defect band is near the edge of the occupied states while it is near the edge of the unoccupied states in regiorandom P3HT. 

Abstract Hydraulic fracturing of oil and gas wells is a water intensive process. Limited availability, cost and increasing government regulations restraining the use and disposal of fresh water have led to the need for alternative fracturing fluids. Using CO2 foam as a fracturing fluid can drastically reduce the need for water in hydraulic fracturing. We address the addition of polyelectrolyte complex nanoparticles (PECNP) to surfactant solutions to improve foam stability, durability and rheological properties at high foam qualities. Polyelectrolyte pH and polyanion/polycation ratios were varied to minimize particle size and maximize absolute zeta potential of the resulting nanoparticles. Rheological tests were conducted on foam systems of varying surfactant/PECNP ratios and different foam quality to understand the effect of shear on viscosity under simulated reservoir conditions of 40°C and 1300 psi. The same foam systems were tested for stability and durability in a view cell at reservoir conditions. Supercritical CO2 foam generated by surfactant alone resulted in short lived, low viscosity foam because of surfactant drainage from foam lamellae. However, addition of PECNP strengthens the foam film by swelling the film due to increased osmotic pressure and electrostatic forces. Electrostatic interactions reduce dynamic movement of surfactant micelles, thereby stabilizing the foam lamellae, which imparts high durability and viscosity to supercritical CO2 foams. From the rheology test results, it was concluded that increasing foam quality and the presence of PECNP resulted in improved viscosity. Also, foam systems with PECNP showed promising results compared with foam generated using surfactant alone in the view cell durability test. The addition of optimized polyelectrolyte nanoparticles to the surfactant can improve viscosity and durability of supercritical CO2 foam during hydraulic fracturing, which can lead to large reductions in water requirements. 

ABSTRACT Precipitate scale formation is a major issue for the oil industry, plugging equipment, and reservoirs and resulting in increased operational costs. Poly(vinyl sulfonate) (PVS) is often used as a scale inhibitor to prevent the formation of barium sulfate scale. However, PVS effectiveness is limited by its short lifetime in reservoir. In this article, PVS has been entrapped in polyelectrolyte complex nanoparticles (PECNPs), altering its charge and thus enabling improved adsorption on the rock surface. As the ionic strength of the surrounding brine increases, the PVS is then released from the PECNPs, making it available to inhibit scale formation gradually. Positively charged PECNPs were made using a combination of poly(ethyleneimine) (PEI) and PVS. After NPs optimization, static adsorption tests were performed, which confirm the nanoparticles' rapid and strong adsorption. An increase in the ionic strength of the displacing fluid was used to decompose the PECNPs structure and release the PVS into solution. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci.2019,136, 47225.