arXiv subjects

Yeon Sik Jung

Publications and source records attributed to Yeon Sik Jung.

4 recordsLinked to original sources

arXiv2026

On the limits and opportunities of AI reviewers: Reviewing the reviews of Nature-family papers with 45 expert scientists

With the advancement of AI capabilities, AI reviewers are beginning to be deployed in scientific peer review, yet their capability and credibility remain in question: many scientists simply view them as probabilistic systems without the expertise to evaluate research, while other researchers are more optimistic about their readiness without concrete evidence. Understanding what AI reviewers do well, where they fall short, and what challenges remain is essential. However, existing evaluations of AI reviewers have focused on whether their verdicts match human verdicts (e.g., score alignment, acceptance prediction), which is insufficient to characterize their capabilities and limits. In this paper, we close this gap through a large-scale expert annotation study, in which 45 domain scientists in Physical, Biological, and Health Sciences spent 469 hours rating 2,960 individual criticisms (each targeting one specific aspect of a paper) from human-written and AI-generated reviews of 82 Nature-family papers on correctness, significance, and sufficiency of evidence. On a composite of all three dimensions, a reviewing agent powered by GPT-5.2 scores above each paper's top-rated human reviewer (60.0% vs. 48.2%, p = 0.009), while all three AI reviewers (including Gemini 3.0 Pro and Claude Opus 4.5) exceed the lowest-rated human across every dimension. AI reviewers' accurate criticisms are also more often rated significant and well-evidenced, and surface a distinct 26% of issues no human raises. However, AI reviewers overlap far more than humans do (21% vs. 3% for cross-reviewer pairs), and exhibit 16 recurring weaknesses humans do not share, such as limited subfield knowledge, lack of long context management over multiple files, and overly critical stance on minor issues. Overall, our results position current AI reviewers as complements to, not substitutes for, human reviewers.

cs.CL↗

arXiv2025

Acidity-Mediated Metal Oxide Heterointerfaces: Roles of Substrates and Surface Modification

Although strong modulation of interfacial electron concentrations by the relative acidity of surface additives has been suggested, direct observation of corresponding changes in surface conductivity, crucial for understanding the role of local space charge, has been lacking. Here, we introduce a model platform comprising well-aligned mixed ionic-electronic conducting $\mathrm{Pr}_{0.2}\mathrm{Ce}_{0.8}\mathrm{O}_{2-δ}$ nanowire arrays ($\mathrm{PCO}_{\mathrm{NA}}$) to show that acidity-modulated heterointerfaces predict electron depletion or accumulation, resulting in tunable electrical properties. We confirm three orders of magnitude increased $\mathrm{PCO}_{\mathrm{NA}}$ conductivity with basic $\mathrm{Li}_{2}\mathrm{O}$ infiltration. Moreover, the relative acidity of the insulating substrate supporting the $\mathrm{PCO}_{\mathrm{NA}}$ strongly influences its electronic properties as well. This strategy is further validated in purely ionic-conducting nanostructured ceria as well as $\mathrm{PCO}_{\mathrm{NA}}$. We suggest that observed conductivity changes stem not only from acidity-mediated space charge potentials at heterointerfaces but also from grain boundaries, chemically-modulated by cation in-diffusion. These findings have broad implications for how substrate and surface treatment choices can alter the conductive properties of nanostructured functional oxides.

cond-mat.mtrl-sci↗

arXiv2023

Wafer-scale fabrication of 2D nanostructures via thermomechanical nanomolding

With shrinking dimensions in integrated circuits, sensors, and functional devices, there is a pressing need to develop nanofabrication techniques with simultaneous control of morphology, microstructure, and material composition over wafer length scales. Current techniques are largely unable to meet all these conditions, suffering from poor control of morphology and defect structure or requiring extensive optimization or post-processing to achieve desired nanostructures. Recently, thermomechanical nanomolding (TMNM) has been shown to yield single-crystalline, high aspect ratio nanowires of metals, alloys, and intermetallics over wafer-scale distances. Here, we extend TMNM for wafer-scale fabrication of 2D nanostructures. Using Cu, we successfully nanomold Cu nanoribbons with widths < 50 nm, depths ~ 0.5-1 microns and lengths ~ 7 mm into Si trenches at conditions compatible with back end of line processing. Through SEM cross-section imaging and 4D-STEM grain orientation maps, we show that the grain size of the bulk feedstock is transferred to the nanomolded structures up to and including single crystal Cu. Based on the retained microstructures of molded 2D Cu, we discuss the deformation mechanism during molding for 2D TMNM.

physics.app-ph↗

arXiv2021

Template Dissolution Interfacial Patterning of Single Colloids for Nanoelectrochemistry and Nanosensing

Deterministic positioning and assembly of colloidal nanoparticles (NPs) onto substrates is a core requirement and a promising alternative to top down lithography to create functional nanostructures and nanodevices with intriguing optical, electrical, and catalytic features. Capillary-assisted particle assembly (CAPA) has emerged as an attractive technique to this end, as it allows controlled and selective assembly of a wide variety of NPs onto predefined topographical templates using capillary forces. One critical issue with CAPA, however, lies in its final printing step, where high printing yields are possible only with the use of an adhesive polymer film. To address this problem, we have developed a template dissolution interfacial patterning (TDIP) technique to assemble and print single colloidal AuNP arrays onto various dielectric and conductive substrates in the absence of any adhesion layer, with printing yields higher than 98%. The TDIP approach grants direct access to the interface between the AuNP and the target surface, enabling the use of colloidal AuNPs as building blocks for practical applications. The versatile applicability of TDIP is demonstrated by the creation of direct electrical junctions for electro- and photoelectrochemistry and nanoparticle-on-mirror geometries for single particle molecular sensing.

cond-mat.soft↗