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Graduate Student Graduate Student ⬅️ All Members Nicholas (Nick) Fromel Graduate Student Publications Impacts I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title Previous Next Johns Hopkins University

Undergraduate Researcher Undergraduate Researcher ⬅️ All Members Sean Hsu Undergraduate Researcher Publications Impacts I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title Previous Next University of California San Diego

Expanding access to laboratory research projects through our Undergraduate Research Experience (URE) program. Broader Impacts Broadening Participation Undergraduate Research Experiences The U.S. National Science Foundation Center for Molecularly Optimized Networks (NSF MONET) has built one of the most intentional and rigorously evaluated undergraduate research programs in the NSF Centers for Chemical Innovation portfolio. The Undergraduate Research Experience (URE) program does not position summer research as an add-on — it treats it as a sustained broader impacts strategy with documented, multi-year outcomes. From its first cohort in 2023, the program embedded access and impact by design rather than aspirational goals. In Year 3, NSF MONET selected four students from a competitive pool of 166 applicants — 50% with limited prior research experience or financial need — representing institutions spanning an R1 university, a master's-granting institution, a liberal arts college, and a historically Black college. This range reflects NSF MONET's explicit commitment to expanding the geography of innovation, in direct alignment with NSF's mandate. The program's outcomes extend well beyond the summer. Alumni tracking — conducted annually each spring — reveals that 15 of 17 URE alumni (88.2%) remain engaged in STEM through undergraduate study, research roles, graduate programs, government leadership, or industry positions. One alumnus, Len, credited the program with connecting them to graduate school opportunities across multiple institutions, ultimately leading to enrollment at Indiana University Bloomington. Others have moved into NIH research, MONET-affiliated labs, and industry — evidence that the URE experience functions as a career launchpad rather than a one-time intervention. NSF MONET has continued to strengthen the program through structured feedback loops and responsive program design. Student and mentor evaluations have directly shaped the development of the URE Program Handbook, monthly cross-institutional meetings, virtual collaboration infrastructure, and the Science Literacy Program — a structured writing and communication curriculum that helps undergraduates produce conference-ready titles, abstracts, posters, reports, and presentations. In doing so, NSF MONET reinforces that scientific communication is part of research training, not separate from it. Conference access has further extended student impact beyond the laboratory. NSF MONET's travel awards enabled undergraduates to present at ACS Spring 2026 and SACNAS NDiSTEM, with approximately $7,000 invested to support seven students in their first national presentation opportunities — strengthening résumés, expanding professional networks, and making their research visible to the broader scientific community. URE alumna Juliana Marston earned the Outstanding Research Presentation Award from SACNAS along with a travel grant to ACS 2026, a recognition that reflects both her individual excellence and the mentorship infrastructure NSF MONET has built around her. Taken together, the URE program demonstrates what it looks like to treat broadening participation as an engineered outcome. NSF MONET recruits broadly, matches deliberately, supports continuously, communicates rigorously, and tracks long-term — producing a replicable model for inclusive undergraduate research that addresses representation at the earliest career stage while generating durable pathways into STEM. Previous Next

Alumni Alumni ⬅️ All Members Cody Ng Alumni Publications Impacts I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title Previous Next University of Chicago

The polymer data platform that turned Center data standards into independent, self-sustaining infrastructure — now a B-corporation with paying subscribers and standards in use by groups with no Center affiliation. Broader Impacts Innovation & Industry CRIPT The Community Resource for Innovation in Polymer Technology (CRIPT) is the data platform that lets polymer researchers capture and share structured data. For the U.S. National Science Foundation Center for Molecularly Optimized Networks (NSF MONET), it is the clearest case of Center-developed infrastructure outliving the grant that produced it. CRIPT App ITE 2134795 Why this matters Polymer data does not travel well. The same material can be described a dozen ways across labs, and without a shared representation, automation and machine learning cannot be applied at scale. An independent 2024 review in Macromolecules , written with no Center-affiliated authors, names this directly as one of the principal barriers facing the field: "a dearth of standards for open interchange of hardware, software, and data among the polymer community." CRIPT is the Center's answer to that barrier, and the answer is a platform rather than a paper. Structured polymer data becomes reusable only if there is somewhere durable to put it, a standard notation to put it in, and an organization with a reason to keep the system running after federal funding ends. What has actually happened Milestone Date Significance Transition to a B-corporation April 2025 CRIPT became a legally independent entity with a mission-locked corporate structure, rather than a project line inside a grant Soft launch with paid services June 2025 First revenue generated from data entry services and subscriptions, establishing a path to operating without Center support Subscription model in place 2025 $120/year for non-commercial users and $1,200/year for commercial users, with institutional licensing identified as the next step The platform now offers three routes into structured data: the CRIPT Editor , which builds a live data graph as researchers enter information; a Python SDK for programmatic bulk upload; and a Featured Datasets interface for searching, sorting, and downloading curated data. Paid services span data entry, custom data ingestion, consulting, and training. Evidence the standards are being used outside the Center Independent validation of BigSMILES by an unaffiliated group A team at Korea University built and validated an automated workflow converting conventional SMILES representations of homopolymers into BigSMILES, publishing the workflow and dataset in Scientific Data in 2024. No Center authors were involved. Someone else investing the effort to make a notation easier to adopt is a stronger signal of uptake than any citation count: the standard was useful enough to justify building tooling around it. Center data standards appearing in independent field reviews The 2024 Macromolecules review on automation and machine learning for polymer characterization discusses PolyDAT as a standardized polymer data schema and BigSMILES for structural encoding, with no Center-affiliated authors. Worth stating plainly for reviewers: the paper treats these as part of the field's working vocabulary, but it does not attribute specific results or impact to them. The honest claim is recognition and active discussion, not measured downstream impact. Center data published as a public reference dataset NSF MONET compiled associative polymer mechanical property data from the literature and made it available on CRIPT as a featured dataset, alongside a curated set of more than 5,300 block copolymer phase measurements. This is the loop closing: Center research generates data, the data lands in shared infrastructure, and researchers outside the Center can find and download it. What comes next The stated next step is moving from individual subscriptions to institutional licenses, supported by new platform features in development. The open question for the Center is not whether CRIPT works technically but whether subscription and service revenue reaches the level that sustains the platform independently — the test any research infrastructure faces when the founding grant ends. Previous Next

Graduate Student Graduate Student ⬅️ All Members Calvin Shih Graduate Student Publications Impacts I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title Previous Next University of California San Diego

Graduate Student Graduate Student ⬅️ All Members Jafer Vakil Graduate Student Publications Impacts I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title Previous Next Duke University

Undergraduate Researcher Undergraduate Researcher ⬅️ All Members Zina S. Medina-Barreto Undergraduate Researcher Publications Impacts I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title Previous Next Norfolk Naval Shipyard

Graduate Student Graduate Student ⬅️ All Members Shixuan (Shishan) Wei Graduate Student Publications Impacts I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title Previous Next Columbia University

Open-source polymer data notations, schemas, and platforms that make complex network data more interoperable, searchable, and reusable. Broader Impacts Innovation & Industry Data Tools The Data Tools initiative is the Data Tools-tagged component of the Innovation & Industry area of the U.S. National Science Foundation Center for Molecularly Optimized Networks (NSF MONET) . It develops open-source notations, data schemas, and software platforms that make complex polymer-network information searchable, interoperable, and reusable across research and application settings. BigSMILES PolyDAT Noncovalent BigSMILES Why this matters Polymer-network data are difficult to compare because the materials combine stochastic molecular structures, network topology, processing history, and measured properties. The Center's Year 4 reporting narrative describes this as a practical barrier to using modern data science: researchers need ways to name, find, compare, and reuse data from different experiments and simulations. Data Tools addresses that barrier through three connected layers: BigSMILES provides a machine-readable line notation for stochastic polymer structures, including extensions for coarse-grained and non-covalent systems. PolyDAT provides a standardized schema for polymer-characterization data and supports interoperability across tools and laboratories. CRIPT carries these capabilities into a searchable, open-source polymer data platform linking synthesis, processing, and property measurements. CRIPT completed incorporation as a public benefit corporation in spring 2025. Together, these tools lower the friction of sharing and reusing polymer data. That matters for faster materials discovery, more reproducible computational work, and translation of Center research into software and data infrastructure that can be used beyond the originating laboratories. Documented reach and activity Activity or outcome Period Documented result BigSMILES and polymer machine-learning benchmarking 2024 study, reported in the Year 4 report SMILES and BigSMILES were assessed across 12 polymer machine-learning tasks; the report states that BigSMILES enabled 24% faster training in large-language-model frameworks than competing notations while maintaining predictive accuracy for homopolymers and improving chemical encoding for copolymers. Validated BigSMILES conversion workflow 2024 A published workflow validated automated conversion from SMILES to BigSMILES for homopolymeric macromolecules. The Center's impact tracker attributes 4.9 million automatically generated BigSMILES records to this work. CRIPT incorporation Spring 2025 CRIPT completed incorporation as a public benefit corporation and was described in the Year 4 report as a searchable, open-source polymer database linking synthesis, processing, and property measurements. CRIPT soft launch Mid-2025 The platform began generating revenue through data-entry services and subscriptions. The recorded subscription prices were 120 USD/year for non-commercial users and 1,200 USD/year for commercial users; the revenue amount was not disclosed pending board approval. External use tracked across the polymer community Updated November 12, 2025 The Center's tracking record counted 273 papers citing CRIPT, BigSMILES, or PolyDAT; 247 (90.5%) were attributed to non-MONET-affiliated authors. The same record identified seven external research teams with documented active use of the tools. These are database-tracking figures, not an independent audit. Evidence that the approach works Measured computational benefit The Year 4 report identifies a 2024 benchmark across 12 polymer machine-learning tasks as evidence that BigSMILES can support large-scale computational work without sacrificing predictive accuracy for homopolymers. The reported 24% training-time advantage in large-language-model frameworks is a measured comparison, not an attendance or self-report metric. The Center's tracking record also summarizes separate reported findings of reduced prediction error and faster preprocessing; those figures are kept distinct from the Year 4 benchmark because they come from a different study and source trail. Reusable data infrastructure The published BigSMILES conversion workflow demonstrates a concrete interoperability function: it translates conventional SMILES representations into validated BigSMILES representations that can be reused in polymer-informatics datasets. The associated record describes the workflow as reducing translation inconsistencies and supporting dataset reuse. The Year 4 report further describes BigSMILES-to-structure drawing software, polymer search, and similarity-scoring tools being transitioned to the broader user community through CRIPT. External validation and adoption The Center's external-use tracker applies a defined inclusion criterion: documented use in a publication, conference proceeding, technical report, or patent filing; citation or use of BigSMILES, PolyDAT, or CRIPT; and authorship by an institution not directly affiliated with NSF MONET. Its November 2025 update lists examples including automated BigSMILES conversion, BigSMILES benchmarking, CRIPT-based data management, and PolyDAT schemas adapted for solid-electrolyte research. The tracker is useful evidence of reach, while the page preserves the distinction between internally recorded adoption and independently verified impact. An independent 2024 Macromolecules perspective identifies the lack of open standards for exchanging polymer hardware, software, and data as a barrier to automation and machine learning, and discusses PolyDAT and BigSMILES in that context. The corresponding database record explicitly notes that the article does not provide concrete examples attributing utility or impact to NSF MONET tools; it is therefore used here as field context, not as a quantified outcome. Response to reviewer feedback Review feedback identified a need for simple software for generating BigSMILES descriptors, clear training materials, and practical examples. The documented response identifies the BigSMILES Builder, the PolyDAT Data Form, integrations with free chemical-drawing software, and video tutorials as existing or expanding resources. The feedback record marks the general response as implemented, while a related publication-focused implementation remains in progress. What comes next The Center's current tracking record sets a goal of at least 25 external research laboratories actively using and publishing with the tools; its November 2025 update documented seven external research teams. The documented next steps are to continue quarterly review of cited papers, expand training materials and practical examples, encourage use of BigSMILES in Center publications, and explore further integration with chemical-drawing software and commercial vendors. For CRIPT, the 2025 soft-launch record describes additional features in the pipeline and a possible progression from individual subscriptions toward institutional licenses. Those plans are reported as future work rather than completed outcomes. Previous Next

Graduate Student Graduate Student ⬅️ All Members Grace Yao Graduate Student Publications Impacts I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title I'm an image title Previous Next Duke University

Graduate Student Graduate Student ⬅️ All Members Anthony Mack Graduate Student Publications Impacts Previous Next Duke University