Data from: Polymer sequence alters sensitivity and resolution in chemically amplified polypeptoid photoresists
Data files
Aug 01, 2025 version files 762.55 KB
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Figures.zip
746.64 KB
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README.md
7.96 KB
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README.txt
7.95 KB
Abstract
This dataset accompanies the article "Polymer sequence alters sensitivity and resolution in chemically amplified polypeptoid photoresists" by Cameron P. Adams, Carolyn Henein, Xiangxi Meng, Javier Read de Alaniz, Christopher K. Ober, and Rachel A. Segalman. The abstract for the full manuscript is:
Continuous progress in semiconductor technology relies on the ability to pattern transistors at sub-10 nm dimensions, necessitating the development of high-resolution photoresists for extreme ultraviolet (EUV) lithography. Chemically amplified resists, traditionally composed of multicomponent polymer systems, face increasing challenges at such patterning wavelengths due to nanoscale heterogeneity and stochastic defects. To address these limitations, this study explores polypeptoids—monodisperse, sequence-defined polymers—as a new class of photoresists with precise molecular control. Systematic variation of polypeptoid chain length reveals a critical threshold necessary for successful pattern formation. Additionally, variations in monomer sequence strongly impact both photoresist sensitivity and feature fidelity, challenging conventional models that assume sequence effects should average out across polymer chains. Finally, processing conditions such as post-exposure bake temperature can be optimized to mitigate sequence-dependent variability. These results highlight polymer sequence as a powerful yet underexplored tool for tuning resist performance, offering a promising pathway towards improved nanoscale lithography.
This README.txt file was generated on 2025-06-30 by CAMERON ADAMS
GENERAL INFORMATION
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Title of Dataset: Polymer sequence alters sensitivity and resolution in chemically amplified polypeptoid photoresists.
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Author Information
A. Principal Investigator Contact Information
Name: Rachel A. Segalman
Institution: University of California, Santa Barbara
Address: Materials Research Laboratory, University of California, Santa Barbara, California 93106
Email: segalman@ucsb.eduB. Principal Investigator Contact Information
Name: Christopher K. Ober
Institution: Cornell University
Address: Department of Materials Science and Engineering, Cornell University, Ithaca, New York 14853
Email: cko3@cornell.eduC. Principal Investigator Contact Information
Name: Javier Read de Alaniz
Institution: University of California, Santa Barbara
Address: Department of Chemistry & Biochemistry, University of California, Santa Barbara, California 93106
Email: javier@chem.ucsb.eduD. Associate or Co-investigator Contact Information
Name: Cameron P. Adams
Institution: University of California, Santa Barbara
Address: Department of Chemical Engineering, University of California, Santa Barbara, California 93106
Email: cameronadams@ucsb.eduE. Associate or Co-investigator Contact Information
Name: Carolyn Henein
Institution: University of California, Santa Barbara
Address: Department of Chemistry & Biochemistry, University of California, Santa Barbara, California 93106
Email: chenein@ucsb.eduF. Associate or Co-investigator Contact Information
Name: Xiangxi Meng
Institution: University of California, Santa Barbara
Address: Department of Chemical Engineering, University of California, Santa Barbara, California 93106
Email: xiangximeng@ucsb.eduG. Associate or Co-investigator Contact Information
Name: Chenyun Yuan
Institution: Cornell University
Address: Department of Materials Science and Engineering, Cornell University, Ithaca, New York 14853
Email: cy479@cornell.edu -
Date of data collection (single date, range, approximate date): April 2024 - May 2025
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Geographic location of data collection: Santa Barbara, CA, USA
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This work was supported as part of the Center for High Precision Patterning Science (CHiPPS), an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences at Lawrence Berkeley National Laboratory under Contract No. DE-AC02-05CH11231. X.M. also acknowledges support from Intel Corporation’s CINEMA program during the early development of polypeptoid photoresists. Polymer synthetic development was supported by the BioPACIFIC Materials Innovation Platform of the National Science Foundation under Award No. DMR-1933487. SEM, AFM, and 248 nm KrF lithography were performed in the UCSB Nanofabrication Facility, an open access laboratory.
SHARING/ACCESS INFORMATION
- Licenses/restrictions placed on the data: N/A
- Links to publications that cite or use the data:
- Links to other publicly accessible locations of the data: N/A
- Links/relationships to ancillary data sets: N/A
- Was data derived from another source? No
- Recommended citation for this dataset:
DATA & FILE OVERVIEW
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File List: Files are organized into folders based on figure number from the corresponding manuscript and supporting information. Files are named as "Figure #.csv".
A. Figure 2: AFM height profiles of 400nm half-pitch patterns to accompany SEM images found in the manuscript. a. Figure 2c.csv and Figure 2d.csv 1. Variables: Horizontal Distance [um], Film thickness [nm] 2. Column names: Horizontal Distance, X (um); Film Thickness, Z (nm) B. Figure 3d: Deep Ultraviolet (248nm) contrast curves for alternating, intermediate, and blocky 20-mer polypeptoid sequences. a. Figure 3d.csv 1. Variables: Exposure Dose [mJ/cm2], Film thickness [nm], Normalized film thickness 2. Column names: Dose (mJ/cm2), Alt. Film Thickness (nm), Alt. Normalized Thickness, Blocky Film Thickness (nm), Blocky Normalized Thickness, Int. Film Thickness (nm), Int. Normalized Thickness C. Figure S1-S5: High-Performance Liquid Chromatography + Mass Spectrometry (HPLC-MS) spectra of synthesized polypeptoids. a. Figure S1.csv 1. Variables: Retention Time [min], Intensity [arb. units], Mass/charge (m/z) 2. Column names: Chromatogram: Ret. Time (min), Chromatogram: Intensity, MS: m/z, MS: Absolute Intensity, MS: Relative Intensity b. Figure S2.csv 1. Variables: Retention Time [min], Intensity [arb. units], Mass/charge (m/z) 2. Column names: Chromatogram: Ret. Time (min), Chromatogram: Intensity, MS: m/z, MS: Absolute Intensity, MS: Relative Intensity c. Figure S3.csv 1. Variables: Retention Time [min], Intensity [arb. units], Mass/charge (m/z) 2. Column names: Chromatogram: Ret. Time (min), Chromatogram: Intensity, MS: m/z, MS: Absolute Intensity, MS: Relative Intensity d. Figure S4.csv 1. Variables: Retention Time [min], Intensity [arb. units], Mass/charge (m/z) 2. Column names: Chromatogram: Ret. Time (min), Chromatogram: Intensity, MS: m/z, MS: Absolute Intensity, MS: Relative Intensity e. Figure S5.csv 1. Variables: Retention Time [min], Intensity [arb. units], Mass/charge (m/z) 2. Column names: Chromatogram: Ret. Time (min), Chromatogram: Intensity, MS: m/z, MS: Absolute Intensity, MS: Relative Intensity D. Figure S6-S7: Differential scanning calorimetry (DSC) traces of synthesized polypeptoids for determining glass transition temperature. a. Figure S6.csv 1. Variables: Temperature [°C], Normalized Heat Flow [W/g] 2. Column names: Alt. 10-mer: Temperature (°C), Alt. 10-mer: Heat Flow (Normalized) (W/g), Alt. 20-mer: Temperature (°C), Alt. 20-mer: Heat Flow (Normalized) (W/g), Alt. 30-mer: Temperature (°C), Alt. 30-mer: Heat Flow (Normalized) (W/g) b. Figure S7.csv 1. Variables: Temperature [°C], Normalized Heat Flow [W/g] 2. Column names: Alt. 20-mer: Temperature (°C), Alt. 20-mer: Heat Flow (Normalized) (W/g), Int. 20-mer: Temperature (°C), Int. 20-mer: Heat Flow (Normalized) (W/g), Blocky 20-mer: Temperature (°C), Blocky 20-mer: Heat Flow (Normalized) (W/g) -
Relationship between files, if important: N/A
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Additional related data collected that was not included in the current data package: N/A
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Are there multiple versions of the dataset? No
METHODOLOGICAL INFORMATION
- Description of methods used for collection/generation of data: Please refer to supporting information document for methodology of data generation and collection.
- Methods for processing the data: Please refer to supporting information document for methodology of data processing.
- Instrument- or software-specific information needed to interpret the data: All figure plots in the manuscript and the supporting information were plotted using Python Code in Spyder 6.
- Standards and calibration information, if appropriate: N/A
- Environmental/experimental conditions: N/A
- Describe any quality-assurance procedures performed on the data: N/A
- People involved with sample collection, processing, analysis and/or submission: Cameron P. Adams, Carolyn Henein, Xiangxi Meng, Chenyun Yuan, Javier Read de Alaniz, Christopher K. Ober, Rachel A. Segalman
