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By providing a large gaseous volume for nuclear interactions while simultaneously recording the tracks of resulting reaction products, an active target serves as both a thick target and a detector. Once a reaction occurs, the emitted charged fragments strip electrons from the target gas along their path as they transverse the detector. Collection of these stripped electrons allow for detection of the product tracks. As beam intensity increases, the resulting ionization in the active target can significantly distort this collection of electrons. If left uncorrected, the resulting measurements could be wrong. In this paper, we investigate the impact of the space charge produced by heavy radioactive beams within the Active Target - Time Projection Chamber at Michigan State University. The beams are injected parallel to the electric field of the time projection chamber which is operated without a magnetic field for this experiment. We analyze the rate dependence of the space charge effects and demonstrate that they can be modeled and effectively corrected. 

Conducting detailed cellular analysis of complex biological samples poses challenges in cell sorting and recovery for downstream analysis. Label-free microfluidics provide a promising solution for these complex applications. In this work, we investigate particle manipulation on two label-free microdevice designs using cDEP to enrich E. coli from whole human blood to mimic infection workflows. E. coli is still a growing source of bacteremia, sepsis, and other infections in modern countries, affecting millions of patients globally. The two microfluidic designs were evaluated for throughput, scaling, precision targeting, and high-viability recovery. While CytoChip D had the potential for higher throughput, given its continuous method of DEP-based sorting to accommodate larger clinical samples like a 10 mL blood draw, it could not effectively recover the bacteria. CytoChip B achieved a high-purity recovery of over 98% of bacteria from whole human blood, even in concentrations on the order of <100 CFU/mL, demonstrating the feasibility of processing and recovering ultra-low concentrations of bacteria for downstream analysis, culture, and drug testing. Future work will aim to scale CytoChip B for larger volume throughput while still achieving high bacteria recovery. 

This experimental work investigates the impact dynamics of drops on vertically oriented, three-dimensional-printed (3D-printed) fiber arrays with variations in packing density, fiber arrangement, and wettability. These fiber arrays are inspired by mammalian fur, and while not wholly representative of the entire morphological range of fur, they do reside within its spectrum. We define an aspect ratio, a modified fiber porosity relative to the drop size, that characterizes various impact regimes. Using energy conservation, we derive a model relating drop penetration depth in vertical fibers to the Weber number. In sparse fibers where the Ohnesorge number is less than 4×10−3, penetration depth scales linearly with the impact Weber number. In hydrophobic fibers, density reduces penetration depth when the contact angle is sufficiently high. Hydrophilic arrays have greater penetration than their hydrophobic counterparts due to capillarity, a result that contrasts the drop impact-initiated infiltration of horizontal fibers. Vertical capillary infiltration of the penetrated liquid is observed whenever the Bond number is less than 0.11. For hydrophilic fibers, we predict that higher density will promote drop penetration when the contact angle is sufficiently low. Complete infiltration by the drop is achieved at sufficient times regardless of drop impact velocity. 

In this work, we assess the use of machine learning to classify fission events in the Active Target Time Projection Chamber (AT-TPC) using data from an experiment performed at the National Superconducting Cyclotron Laboratory at Michigan State University. The experiment produces an extremely large quantity of data, less than 3% of which are fission events. Therefore, separating fission events from the background beam events is critical to an efficient analysis. A heuristic method was developed to classify events as Fission or Non-Fission based on hand-tuned parameters. However, this heuristic method places 5% of all events into an Unlabeled category, including 15% of all fission events. We present a PointNet model trained on the data labeled by the heuristic method. This model is then used to generate labels for the events in the Unlabeled category. Using the heuristic and machine learning methods together, we can successfully identify 99% of fission events. 

A new neutron SIMulation program based on the versatile GEANT4 toolkit, neuSIM4, has been developed to describe interactions of neutrons in the NE213 liquid scintillator from 0.1 to 3000 MeV. neuSIM4 is designed to accommodate complicated modern detector geometry setups with multiple scintillator detectors, each of which can be outfitted with more than one photo-multiplier. To address a broad spectrum of neutron energies, two new neutron interaction physics models, KSCIN and NxQMD, have been implemented in GEANT4. For neutrons with energy below 110 MeV, we incorporate a total of eleven neutron induced reaction channels on hydrogen and carbon nuclei, including nine carbon inelastic reaction channels, into KSCIN. Beyond 110 MeV, we implement a neutron induced reaction model, NxQMD, in GEANT4. We use its results as reference to evaluate other neutron-interaction physics models in GEANT4. We find that results from an existing cascade physics model (INCL) in GEANT4 agree very well with the results from NxQMD, and results from both codes agree with new and existing light response data. To connect KSCIN to NxQMD or INCL, we introduce a transition region where the contribution of neuSIM4 linearly decreases with corresponding increased contributions from NxQMD or INCL. To demonstrate the application of the new code, we simulate the light response and performance of a 2 × 2 m2 neutron detector wall array consisting of 25 2m-long scintillation bars. We are able to compare the predicted light response functions to the shape of the experimental response functions and calculate the efficiency of the neutron detector array for neutron energies up to 200 MeV. These simulation results will be pivotal for understanding the performance of modern neutron arrays with intricate geometries, especially in the measurements of neutron energy spectra in heavy-ion reactions. 

This white paper is the result of a collaboration by many of those that attended a workshop at the facility for rare isotope beams (FRIB), organized by the FRIB Theory Alliance (FRIB-TA), on ‘Theoretical Justifications and Motivations for Early High-Profile FRIB Experiments’. It covers a wide range of topics related to the science that will be explored at FRIB. After a brief introduction, the sections address: section 2: Overview of theoretical methods, section 3: Experimental capabilities, section 4: Structure, section 5: Near-threshold Physics, section 6: Reaction mechanisms, section 7: Nuclear equations of state, section 8: Nuclear astrophysics, section 9: Fundamental symmetries, and section 10: Experimental design and uncertainty quantification. 

Abstract MotivationNative top-down proteomics (nTDP) integrates native mass spectrometry (nMS) with top-down proteomics (TDP) to provide comprehensive analysis of protein complexes together with proteoform identification and characterization. Despite significant advances in nMS and TDP software developments, a unified and user-friendly software package for analysis of nTDP data remains lacking. ResultsWe have developed MASH Native to provide a unified solution for nTDP to process complex datasets with database searching capabilities in a user-friendly interface. MASH Native supports various data formats and incorporates multiple options for deconvolution, database searching, and spectral summing to provide a “one-stop shop” for characterizing both native protein complexes and proteoforms. Availability and implementationThe MASH Native app, video tutorials, written tutorials, and additional documentation are freely available for download at https://labs.wisc.edu/gelab/MASH_Explorer/MASHSoftware.php. All data files shown in user tutorials are included with the MASH Native software in the download .zip file.