arXiv subjects

J. Mammo

Publications and source records attributed to J. Mammo.

6 recordsLinked to original sources

arXiv2026

AIMBio-Mat: An AI-Native FAIR Platform for Closed-Loop Materials Discovery and Biomedical Translation

Materials discovery and biomedical translation increasingly require models that can reason across composition, processing, structure, biological response, manufacturability, safety, and governance constraints. Existing materials and biomedical data ecosystems are powerful but remain poorly coupled for AI-guided discovery. Here we present AIMBio, a conceptual framework for an AI-native, FAIR, and governance-aware decision layer that links materials provenance, biomedical context, knowledge graphs, uncertainty-aware machine learning, and human-in-the-loop active learning. The framework formulates biomedical-materials discovery as constrained multi-objective optimization under uncertainty and introduces practical requirements for metadata, model documentation, risk-tiered governance, evaluation metrics, and phased implementation. To make the roadmap testable, we add a minimum viable prototype specification and a worked pilot for AI-guided nanomaterials for drug delivery. AIMBio is positioned as exploratory and preclinical discovery infrastructure, not as clinical decision-support software; any clinical or regulated-device use would require separate validation, change control, and regulatory review. The central contribution is a publishable platform blueprint for converting fragmented materials and biomedical records into auditable, experimentally actionable, and translationally responsible discovery workflows.

physics.app-ph↗

arXiv2026

Building a Regional Data-Centric Materials Science Ecosystem for Processing-Rich Materials Innovation in the Great Plains

Data-centric materials science is changing how materials are discovered, optimized, manufactured, and qualified, yet many deployment-limiting materials problems still depend on experimental, processing-rich, device-level, and field-relevant data that are difficult to capture in conventional materials databases. This perspective argues that the Great Plains and adjacent interior research corridor can make a distinctive national contribution by organizing distributed experimental assets into a trusted regional materials-data ecosystem. The proposed model emphasizes FAIR metadata, provenance, persistent sample identifiers, uncertainty-aware modeling, semi-closed-loop workflows, stackable workforce training, and tiered governance for academic, public, controlled-access, and industry-protected data. We identify five coupled barriers -- fragmented data, weak algorithm--laboratory translation, uneven access to cyberinfrastructure and technical staff, workforce gaps at the materials--data interface, and insufficient incentives for sharing and reuse -- and propose a staged roadmap for addressing them. A high-purity germanium pilot illustrates how regional strengths can be converted into reusable datasets, benchmark models, trained personnel, and decision-improving workflows. The broader message is that regional leadership in data-centric materials science will depend less on geographic concentration than on trustworthy data practices, interoperable infrastructure, cross-trained people, and application-driven materials challenges.

cond-mat.mtrl-sci↗

arXiv2023

Precision measurement of the index of refraction of deep glacial ice at radio frequencies at Summit Station, Greenland

Glacial ice is used as a target material for the detection of ultra-high energy neutrinos, by measuring the radio signals that are emitted when those neutrinos interact in the ice. Thanks to the large attenuation length at radio frequencies, these signals can be detected over distances of several kilometers. One experiment taking advantage of this is the Radio Neutrino Observatory Greenland (RNO-G), currently under construction at Summit Station, near the apex of the Greenland ice sheet. These experiments require a thorough understanding of the dielectric properties of ice at radio frequencies. Towards this goal, calibration campaigns have been undertaken at Summit, during which we recorded radio reflections off internal layers in the ice sheet. Using data from the nearby GISP2 and GRIP ice cores, we show that these reflectors can be associated with features in the ice conductivity profiles; we use this connection to determine the index of refraction of the bulk ice as n=1.778 +/- 0.006.

astro-ph.IM↗

arXiv2022

Radiofrequency Ice Dielectric Measurements at Summit Station, Greenland

We recently reported on the radio-frequency attenuation length of cold polar ice at Summit Station, Greenland, based on bistatic radar measurements of radio-frequency bedrock echo strengths taken during the summer of 2021. Those data also include echoes attributed to stratified impurities or dielectric discontinuities within the ice sheet (layers), which allow studies of a) estimation of the relative contribution of coherent (discrete layers, e.g.) vs. incoherent (bulk volumetric, e.g.) scattering, b) the magnitude of internal layer reflection coefficients, c) limits on the azimuthal asymmetry of reflections (birefringence), and d) limits on signal dispersion in-ice over a bandwidth of ~100 MHz. We find that i) after averaging 10000 echo triggers, reflected signal observable over the thermal floor (to depths of approximately 1500 m) are consistent with being entirely coherent, ii) internal layer reflection coefficients are measured at approximately -60 to -70 dB, iii) birefringent effects for vertically propagating signals are smaller by an order of magnitude relative to comparable studies performed at South Pole, and iv) within our experimental limits, glacial ice is non-dispersive over the frequency band relevant for neutrino detection experiments.

physics.ins-det↗

arXiv2022

Triboelectric Backgrounds to radio-based UHE Neutrino Exeperiments

The proposed IceCube-Gen2 (ICG2) seeks to instrument ~500 sq. km of Antarctic ice near the geographic South Pole with radio antennas, in order to observe the highest energy (E>1 EeV) neutrinos in the Universe. To this end, ICG2 will use the impulsive radio-frequency (RF) signal produced by neutrino interactions in polar ice caps. In such experiments, rare single event candidates must be unambiguously separated from background; to date, signal identification strategies primarily reject thermal noise and anthropogenic backgrounds. Here, we consider the possibility that fake neutrino signals may also be naturally generated via the 'triboelectric effect'. This broadly includes any process in which force applied at a boundary layer results in displacement of surface charge, generating a potential difference ΔV. Wind blowing over granular surfaces such as snow can induce such a ΔV, with subsequent discharge. Discharges over nanosecond-timescales can then lead to RF emissions at characteristic MHz-GHz frequencies. We find that such backgrounds are evident in the several neutrino experiments considered, and are generally characterized by: a) a threshold wind velocity which likely depends on the experimental signal trigger threshold and layout; for the experiments considered herein, this value is typically O(10 m/s), b) frequency spectra generally shifted to the low-end of the frequency regime to which current radio experiments are typically sensitive (100-200 MHz), c) for the strongest background signals, an apparent preference for discharges from above-surface structures, although the presence of more isotropic, lower amplitude triboelectric discharges cannot be excluded.

astro-ph.IM↗

arXiv2022

In situ, broadband measurement of the radio frequency attenuation length at Summit Station, Greenland

Over the last 25 years, radiowave detection of neutrino-generated signals, using cold polar ice as the neutrino target, has emerged as perhaps the most promising technique for detection of extragalactic ultra-high energy neutrinos (corresponding to neutrino energies in excess of 0.01 Joules, or $10^{17}$ electron volts). During the summer of 2021 and in tandem with the initial deployment of the Radio Neutrino Observatory in Greenland (RNO-G), we conducted radioglaciological measurements at Summit Station, Greenland to refine our understanding of the ice target. We report the result of one such measurement, the radio-frequency electric field attenuation length $L_α$. We find an approximately linear dependence of $L_α$ on frequency with the best fit of the average field attenuation for the upper 1500 m of ice: $\langle L_α\rangle = \big( (1154 \pm 121) - (0.81 \pm 0.14) (ν/$MHz$)\big)$ m for frequencies $ν\in [145 - 350]$ MHz.

astro-ph.IM↗