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The exponential growth of digital content has generated massive textual datasets, necessitating the use of advanced analytical approaches. Large Language Models (LLMs) have emerged as tools that are capable of processing and extracting insights from massive unstructured textual datasets. However, how to leverage LLMs for text analytics Information Systems (IS) research is currently unclear. To assist the IS community in understanding how to operationalize LLMs, we propose a Text Analytics for Information Systems Research (TAISR) framework. Our proposed framework provides detailed recommendations grounded in IS and LLM literature on how to conduct meaningful text analytics IS research for design science, behavioral, and econometric streams. We conducted three business intelligence case studies using our TAISR framework to demonstrate its application in several IS research contexts. We also outline the potential challenges and limitations of adopting LLMs for IS. By offering a systematic approach and evidence of its utility, our TAISR framework contributes to future IS research streams looking to incorporate powerful LLMs for text analytics. 

Abstract Organic compounds containing luminous rare-earth ions are of interest for numerous nanophotonic and plasmonic applications, including nanoscale lasers, biosensors, and optical magnetism studies. Optical studies of Eu³⁺complexes revealed that ultra-thin LB monolayers are highly luminescent even when deposited directly on plasmonic metal, which makes these materials very promising for plasmonic applications and studies, including control and enhancement of magnetic dipole emission with a plasmonic environment. In this work, we synthesize amphiphilic complexes with various rare-earth ions Nd³⁺, Yb³⁺, and DPT ligands and show that they all are suitable for monolayer or multilayer deposition with the Langmuir–Blodgett (LB) technique. Graphical abstract 

Abstract Chemical doping is an important approach to manipulating charge-carrier concentration and transport in organic semiconductors (OSCs)^1–3and ultimately enhances device performance^4–7. However, conventional doping strategies often rely on the use of highly reactive (strong) dopants^8–10, which are consumed during the doping process. Achieving efficient doping with weak and/or widely accessible dopants under mild conditions remains a considerable challenge. Here, we report a previously undescribed concept for the photocatalytic doping of OSCs that uses air as a weak oxidant (p-dopant) and operates at room temperature. This is a general approach that can be applied to various OSCs and photocatalysts, yielding electrical conductivities that exceed 3,000 S cm^–1. We also demonstrate the successful photocatalytic reduction (n-doping) and simultaneous p-doping and n-doping of OSCs in which the organic salt used to maintain charge neutrality is the only chemical consumed. Our photocatalytic doping method offers great potential for advancing OSC doping and developing next-generation organic electronic devices. 

Abstract Accurate prediction of tropical cyclone (TC) intensity is quite challenging due to multiple competing processes among the TC internal dynamics and the environment. Most previous studies have evaluated the environmental effects on TC intensity change from both internal dynamics and external influence. This study quantifies the environmental effects on TC intensity change using a simple dynamically based dynamical system (DBDS) model recently developed. In this simple model, the environmental effects are uniquely represented by a ventilation parameterB, which can be expressed as multiplicative of individual ventilation parameters of the corresponding environmental effects. Their individual ventilation parameters imply their relative importance to the bulk environmental ventilation effect and thus to the TC intensity change. Six environmental factors known to affect TC intensity change are evaluated in the DBDS model using machine learning approaches with the best track data for TCs over the North Atlantic, central, eastern, and western North Pacific and the Statistical Hurricane Intensity Prediction Scheme (SHIPS) dataset during 1982–2021. Results show that the deep-layer vertical wind shear (VWS) is the dominant ventilation factor to reduce the intrinsic TC intensification rate or to drive the TC weakening, with its ventilation parameter ranging between 0.5 and 0.8 when environmental VWS between 200 and 850 hPa is larger than 8 m s⁻¹. Other environmental factors are generally secondary, with their respective ventilation parameters over 0.8. An interesting result is the strong dependence of the environmental effects on the stage of TC development. 

Abstract In this study, based on the 6-hourly tropical cyclone (TC) best track data and the ERA-Interim reanalysis data, statistical analyses as well as a machine learning approach, XGBoost, are used to identify and quantify factors that affect the overwater weakening rate (WR) of TCs over the western North Pacific (WNP) during 1980–2017. Statistical analyses show that the TC rapid weakening events usually occur when intense TCs cross regions with a sharp decrease in sea surface temperature (DSST) with relatively faster eastward or northward translational speeds, and move into regions with large environmental vertical wind shear (VWS) and dry conditions in the upshear-left quadrant. Results from XGBoost indicate that the relative intensity of TC (TC intensity normalized by its maximum potential intensity), DSST, and VWS are dominant factors determining TC WR, contributing 26.0%, 18.3%, and 14.9% to TC WR, and 9, 5, and 5 m s−1 day−1 to the variability of TC WR, respectively. Relative humidity in the upshear-left quadrant of VWS, zonal translational speed, divergence at 200 hPa, and meridional translational speed contribute 12.1%, 11.8%, 8.8%, and 8.1% to TC WR, respectively, but only contribute 2–3 m s−1 day−1 to the variability of TC WR individually. These findings suggest that the improved accurate analysis and prediction of the dominant factors may lead to substantial improvements in the prediction of TC WR. 

Abstract A new approach to control the n‐doping reaction of organic semiconductors is reported using surface‐functionalized gold nanoparticles (f‐AuNPs) with alkylthiols acting as the catalyst only upon mild thermal activation. To demonstrate the versatility of this methodology, the reaction of the n‐type dopant precursor N‐DMBI‐H with several molecular and polymeric semiconductors at different temperatures with/without f‐AuNPs, vis‐à‐vis the unfunctionalized catalyst AuNPs, was investigated by spectroscopic, morphological, charge transport, and kinetic measurements as well as, computationally, the thermodynamic of catalyst activation. The combined experimental and theoretical data demonstrate that while f‐AuNPs is inactive at room temperature both in solution and in the solid state, catalyst activation occurs rapidly at mild temperatures (~70 °C) and the doping reaction completes in few seconds affording large electrical conductivities (~10–140 S cm⁻¹). The implementation of this methodology enables the use of semiconductor+dopant+catalyst solutions and will broaden the use of the corresponding n‐doped films in opto‐electronic devices such as thin‐film transistors, electrochemical transistors, solar cells, and thermoelectrics well as guide the design of new catalysts. 

Abstract Conducting polymers, such as thep-doped poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS), have enabled the development of an array of opto- and bio-electronics devices. However, to make these technologies truly pervasive, stable and easily processable,n-doped conducting polymers are also needed. Despite major efforts, non-type equivalents to the benchmark PEDOT:PSS exist to date. Here, we report on the development of poly(benzimidazobenzophenanthroline):poly(ethyleneimine) (BBL:PEI) as an ethanol-basedn-type conductive ink. BBL:PEI thin films yield ann-type electrical conductivity reaching 8 S cm⁻¹, along with excellent thermal, ambient, and solvent stability. This printablen-type mixed ion-electron conductor has several technological implications for realizing high-performance organic electronic devices, as demonstrated for organic thermoelectric generators with record high power output andn-type organic electrochemical transistors with a unique depletion mode of operation. BBL:PEI inks hold promise for the development of next-generation bioelectronics and wearable devices, in particular targeting novel functionality, efficiency, and power performance.