A new evolutional model for institutional field knowledge flow network

Purpose:This paper aims to address the limitations in existing research on the evolution of knowledge flow networks by proposing a meso-level institutional field knowledge flow network evolution model(IKM).The purpose is to simulate the construction process of a knowledge flow network using knowledge organizations as units and to investigate its effectiveness in replicating institutional field knowledge flow networks.Design/Methodology/Approach:The IKM model enhances the preferential attachment and growth observed in scale-free BA networks,while incorporating three adjustment parameters to simulate the selection of connection targets and the types of nodes involved in the network evolution process Using the PageRank algorithm to calculate the significance of nodes within the knowledge flow network.To compare its performance,the BA and DMS models are also employed for simulating the network.Pearson coefficient analysis is conducted on the simulated networks generated by the IKM,BA and DMS models,as well as on the actual network.Findings:The research findings demonstrate that the IKM model outperforms the BA and DMS models in replicating the institutional field knowledge flow network.It provides comprehensive insights into the evolution mechanism of knowledge flow networks in the scientific research realm.The model also exhibits potential applicability to other knowledge networks that involve knowledge organizations as node units.Research Limitations:This study has some limitations.Firstly,it primarily focuses on the evolution of knowledge flow networks within the field of physics,neglecting other fields.Additionally,the analysis is based on a specific set of data,which may limit the generalizability of the findings.Future research could address these limitations by exploring knowledge flow networks in diverse fields and utilizing broader datasets.Practical Implications:The proposed IKM model offers practical implications for the construction and analysis of knowledge flow networks within institutions.It provides a valuable tool for understanding and managing knowledge exchange between knowledge organizations.The model can aid in optimizing knowledge flow and enhancing collaboration within organizations.Originality/value:This research highlights the significance of meso-level studies in understanding knowledge organization and its impact on knowledge flow networks.The IKM model demonstrates its effectiveness in replicating institutional field knowledge flow networks and offers practical implications for knowledge management in institutions.Moreover,the model has the potential to be applied to other knowledge networks,which are formed by knowledge organizations as node units.

Are Contributions from Chinese Physicists Undercited?

Purpose:In this work,we want to examine whether or not there are some scientific fields to which contributions from Chinese scholars have been un der or over cited.Design/methodology/approach:We do so by comparing the number of received citations and the IOF of publications in each scientific field from each country.The IOF is calculated from applying the modified closed system input–output analysis(MCSIOA)to the citation network.MCSIOA is a PageRank-like algorithm which means here that citations from the more influential subfields are weighted more towards the IOF.Findings:About 40% of subfields in physics in China are undercited,meaning that their net influence ranks are higher(better)than the direct rank,while about 75% of subfields in the USA and German are undercited.Research limitations:Only APS data is analyzed in this work.The expected citation influence is assumed to be represented by the IOF,and this can be wrong.Practical implications:MCSIOA provides a measure of net influences and according to that measure.Overall,Chinese physicists’publications are more likely overcited rather than being undercited.Originality/value:The issue of under or over cited has been analyzed in this work using MCSIOA.

Anomalous magnetic property and broadband photodetection in ultrathin non-layered manganese selenide semiconductor

Two-dimensional(2D)semiconductors with intrinsic ferromagnetism are highly desirable for potential applications in nextgeneration spintronic and optoelectronic devices.However,controllable synthesis of intrinsic 2D magnetic semiconductor on a substrate is still a challenging task.Herein,large-area 2D non-layered rock salt(α-phase)MnSe nanosheets were grown on mica substrates,with the thickness changing from 54.2 to 0.9 nm(one unit cell),by chemical vapour deposition.The X-ray diffraction,Raman spectroscopy,transmission electron microscopy,and X-ray photoelectron spectroscopy measurements confirmed that the resulting 2Dα-MnSe nanosheets were obtained as high-quality single crystals.The magnetic hysteresis loops and synchrotron X-ray measurements directly indicated the anomalous magnetic properties inα-MnSe nanosheets.Comprehensive analysis of the reasons for magnetic property revealed that the low-temperature phase transition,small number of stacking differences in crystals,and surface weak oxidation in(111)-orientedα-MnSe were the main mechanisms.Furthermore,α-MnSe nanosheets exhibited broadband photoresponse from 457 to 671 nm with an outstanding detectivity and responsivity behaviours.This study presents the detailed growth process of ultrathin 2D magnetic semiconductorα-MnSe,and its outstanding magnetic properties and broadband photodetection,which provide an excellent platform for magneto-optical and magneto-optoelectronic research.