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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Linear Discriminant Analysis-Based Machine Learning and All-Atom Molecular Dynamics Simulations for Probing Electro-Osmotic Transport in Cationic-Polyelectrolyte-Brush-Grafted Nanochannels

Deciphering the correct mechanisms governing certain phenomena in polyelectrolyte (PE) brush grafted systems, revealed through atomistic simulations, is an extremely challenging problem. In a recent study, our all-atom molecular dynamics (MD) simulations revealed a non-linearly large electroosmotic (EOS) flow (in the presence of an applied electric field) in nanochannels grafted with PMETAC [Poly(2-(methacryloyloxy)ethyl trimethylammonium chloride] brushes. Given the lack of any formal procedure that would have directed us to identify the correct factors responsible for such an occurrence, we needed to spend several months and devote significant analyses to unravel the involved mechanisms. In this paper, we propose a Linear Discriminant Analysis (LDA) based Machine Learning (ML) approach to address this gap. At first, we obtain data on certain basic features from the all-atom MD data. These basic features represent the number of atoms of certain species around one atom of another (or same) species. Here, we obtain such data on basic features for a reference case (case of an EOS flow in PMETAC-brush-grafted nanochannels with a smaller electric field) and a perturbed case (case of an EOS flow in PMETAC-brush-grafted nanochannels with a larger electric field) in bins in which the nanochannel half height has been divided into. These datasets are high-dimensional dataset, to which the LDA is applied. This leads to the projection of the data (between the reference and the perturbed states) in a highly separated form on a 1D line. From such LDA calculations, we are able to identify the relative importance of the different basic features in ensuring this separation of the data (between the reference and the perturbed states) on the 1D line. This relative importance of the different basic features is quantified as “importance scores” for the different features, which in turn tell us what to study and where to study. Such knowledge enables us to rapidly identify the key factors responsible for the non-linearly large EOS transport in PMETAC-brush-grafted nanochannels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Nickel Isonicotinate Framework with Optimal Pore Structure for Complete Discrimination of Hexane Isomers

Efficient separation of physicochemically similar alkanes is of vital importance. Adsorptive separation utilizing porous materials such as metal–organic frameworks with tunable pore structure and surface functionality represents an energy-efficient technology. In this study, we demonstrate successful separation of alkanes with varying degree of branching using a microporous nickel isonicotinate framework, Ni(4-PyC) 2 . Its 2-fold interpenetrated diamondoid structure with well-suited pore size enables selective adsorption of linear and monobranched hexane isomers, while excluding dibranched isomer. Breakthrough experiments validated its capability to completely discriminate all three hexane isomers. Ab initio calculations combined with in situ infrared spectroscopic analysis unveiled the nature of host–guest interactions and differences in the binding energies and diffusion barriers among the isomers. Furthermore, having well-balanced adsorption uptakes (146 and 79 mg g –1 of nHEX and 3MP), high nHEX/DMB uptake ratio (12.2) and fast kinetics, Ni(4-PyC) 2 stands out as a promising adsorbent for complete separation of hexane isomers under ambient conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Discrimination of Hexane Isomers by Temperature Swing Adsorption in a Rigid Aluminum Metal–Organic Framework

The efficient separation of alkane isomers with similar physicochemical properties remains a persistent challenge for the petrochemical industry. Adsorptive separation using metal− organic frameworks (MOFs) offers an energy-efficient alternative to conventional distillation. Herein, we report temperature swing discrimination of hexane isomers with different degrees of branching using MIL-120, a rigid aluminum pyromellitate-based MOF. MIL-120 features uniform one-dimensional channels with an aperture of ∼5.5 Å. At 30 °C, it selectively adsorbs linear and monobranched hexanes while excluding the dibranched isomer. Upon heating to 120 °C, both mono- and dibranched isomers are completely excluded, whereas linear hexane remains strongly adsorbed. Breakthrough experiments validate the temperature swing separation performance. Adsorption heat analysis combined with ab initio calculations provides a quantitative measure of distinct differences in adsorption enthalpies, binding energies, and diffusion barriers responsible for the observed separation efficiency, highlighting the potential of this MOF for efficient separation of alkane isomers via temperature swing adsorption.

Adsorption↗
DOE OSTI2022

Combining Deep Learning With Physics Based Features in Explosion-Earthquake Discrimination

This paper combines the power of deep-learning with the generalizability of physics-based features, to present an advanced method for seismic discrimination between earthquakes and explosions. The proposed method contains two branches: a deep learning branch operating directly on seismic waveforms or spectrograms, and a second branch operating on physics-based parametric features. These features are high-frequency P/S amplitude ratios and the difference between local magnitude (ML) and coda duration magnitude (MC). The combination achieves better generalization performance when applied to new regions than models that are developed solely with deep learning. Further, we also examined which parts of the waveform data dominate deep learning decisions (i.e., via Grad-CAM). Such visualization provides a window into the black-box nature of the machine-learning models and offers new insight into how the deep learning derived models use data to make decisions.

58 GEOSCIENCES↗
DOE OSTI2023

Cut site preference allows influenza A virus PA-X to discriminate between host and viral mRNAs

Many viruses block host gene expression to take over the infected cell. This process, termed host shutoff, is thought to promote viral replication by preventing antiviral responses and redirecting cellular resources to viral processes. Several viruses from divergent families accomplish host shutoff through RNA degradation by endoribonucleases. However, viruses also need to ensure expression of their own genes. The influenza A virus endoribonuclease PA-X solves this problem by sparing viral mRNAs and some host RNAs necessary for viral replication. Here, to understand how PA-X distinguishes between RNAs, we characterized PA-X cut sites transcriptome-wide using 5' rapid amplification of complementary DNA ends coupled to high-throughput sequencing. This analysis, along with RNA structure predictions and validation experiments using reporters, shows that PA-Xs from multiple influenza strains preferentially cleave RNAs at GCUG tetramers in hairpin loops. Importantly, GCUG tetramers are enriched in the human but not the influenza transcriptome. Moreover, optimal PA-X cut sites inserted in the influenza A virus genome are quickly selected against during viral replication in cells. This finding suggests that PA-X evolved these cleavage characteristics to preferentially target host over viral mRNAs in a manner reminiscent of cellular self versus non-self discrimination.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Structure of the Wnt–Frizzled–LRP6 initiation complex reveals the basis for coreceptor discrimination

Wnt morphogens are critical for embryonic development and tissue regeneration. Canonical Wnts form ternary receptor complexes composed of tissue-specific Frizzled (Fzd) receptors together with the shared LRP5/6 coreceptors to initiate β-catenin signaling. The cryo-EM structure of a ternary initiation complex of an affinity-matured XWnt8–Frizzled8–LRP6 complex elucidates the basis of coreceptor discrimination by canonical Wnts by means of their N termini and linker domains that engage the LRP6 E1E2 domain funnels. Chimeric Wnts bearing modular linker “grafts” were able to transfer LRP6 domain specificity between different Wnts and enable non-canonical Wnt5a to signal through the canonical pathway. Synthetic peptides comprising the linker domain serve as Wnt-specific antagonists. The structure of the ternary complex provides a topological blueprint for the orientation and proximity of Frizzled and LRP6 within the Wnt cell surface signalosome.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Topological background discrimination in the PandaX-III neutrinoless double beta decay experiment

The PandaX-III experiment plans to search for neutrinoless double beta decay (0ν ββ ) of 136 Xe in the China JinPing underground Laboratory (CJPL). The experiment will use a high pressure gaseous time projection chamber (TPC) to register both the energy and the electron track topology of an event. This article is devoted to demonstrate our particular detector setup capabilities for the identification of 0ν ββ and the consequent background reduction. As software tool we use REST, a framework developed for the reconstruction and simulation of TPC-based detector systems. We study the potential for background reduction by introducing appropriate parameters based on the properties of 0ν ββ events. We exploit for the first time not only the energy density of the electron track-ends, but also the electron scattering angles produced by an electron near the end of its trajectory. To implement this, we have added new algorithms for detector signal and track processing inside REST. Their assessment shows that background can be reduced by about 7 orders of magnitude while keeping 0ν ββ efficiency above 20% for the PandaX-III baseline readout scheme, a two-dimensional 3 mm pitch stripped readout. More generally, we use the potential of REST to handle 2D/3D data to assess the impact on signal-to-background significance at different detector granularities, and to validate the PandaX-III baseline choice. Finally, we demonstrate the additional potential to discriminate surface background events generated at the readout plane in the absence of to, by making use of event parameters related with the diffusion of electrons.

Majorana↗
DOE OSTI2023

Studies in pulse shape discrimination for an optimized ASIC design

The continued advancements of Silicon Photomultipliers (SiPMs) have made them viable photosensors for low recoil energy Pulse Shape Discrimination (PSD) between fast neutron and gamma interactions when coupled to an appropriate scintillator. At the same time, the large number of channels in a typical array calls for the development of low-cost and low-power electronics. A custom integrated circuit (ASIC) is an ideal solution for this purpose. To assess the requirements for such an ASIC, studies were performed using two scintillators, Stilbene and EJ-276, coupled to a 6 x 6 mm SiPM from Onsemi. We demonstrate that both scintillators are viable for performing PSD for interaction energies from 100 keV to several MeV while optimizing the integration periods used in the PSD metric. These measurements inform the design parameters of the ASIC under development.

Si-PMTs↗
DOE OSTI2023

Pulse shape measurements for neutron/gamma discrimination using the TOFPET2 ASIC

Many highly pixelated organic scintillator detection systems would benefit from independent readout of each scintillator pixel. Recent advances in Silicon Photomultiplier (SiPM) technology makes this goal feasible, however the data acquisition from potentially hundreds or thousands of channels requires a low-cost and compact solution. For pixelated neutron detection with organic scintillators, the capability to distinguish between neutron and gamma interactions using Pulse Shape Discrimination (PSD) is required along with pulse charge and time of arrival. The TOFPET2 ASIC from PETsys Electronics is a 64-channel readout chip providing pulse time and charge integration measurements from SiPMs, and is specifically designed for time-of-flight positron-emission tomography. Using an 8 × 8 array of 6 mm × 6 mm J-series SiPMs from SensL/OnSemi (ArrayJ-60035-64P-PCB), we have studied the energy and PSD performance of the TOFPET2 ASIC using a 4 × 4 array of 6 mm × 6 mm × 30 mm trans -Stilbene crystals from Inrad Optics and a custom SiPM routing board from PETsys Electronics. In conclusion, using a time-over-threshold method, we measure a maximum PSD figure-of-merit of approximately 1.2 at 478 keV (the Compton edge of 662 keV) for a J-series SiPM operating at an over-voltage of 3V.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

The CMOS Pseudo-Thyristor: a zero-static current discriminator circuit

We report a very low power discriminator circuit for pixelized detectors, called the Pseudo-Thyristor is described in this document. It is a positive feedback topology using regular PMOS and NMOS field-effect transistors (FET's) with zero static current. When a small charge is injected into the circuit, it flips rapidly due to the positive feedback and outputs a logic transition for further digitization. Simulation shows that in a 65 nm process, it is possible to achieve a detecting threshold below 5 fC while maintain the average power consumption below 10 micro-Watts when the hit occupancy is <10% for 40 MHz operation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Discriminative versus generative approaches to simulation-based inference

Most of the fundamental, emergent, and phenomenological parameters of particle and nuclear physics are determined through parametric template fits. Simulations are used to populate histograms which are then matched to data. This approach is inherently lossy, since histograms are binned and low-dimensional. Deep learning has enabled unbinned and high-dimensional parameter estimation through neural likelihood(-ratio) estimation. We compare two approaches for neural simulation-based inference (NSBI): one based on discriminative learning (classification) and one based on generative modeling. These two approaches are directly evaluated on the same datasets, with a similar level of hyperparameter optimization in both cases. In addition to a Gaussian dataset, we study NSBI using a Higgs boson dataset from the FAIR Universe Challenge. We find that both the direct likelihood and likelihood ratio estimation are able to effectively extract parameters with reasonable uncertainties. For the numerical examples and within the set of hyperparameters studied, we found that the likelihood ratio method is more accurate and/or precise. Both methods have a significant spread from the network training and would require ensembling or other mitigation strategies in practice.

high energy physics↗
DOE OSTI2025

Pulse Shape Discrimination in JSNS 2

JSNS 2 (J-PARC Sterile Neutrino Search at J-PARC Spallation Neutron Source) is an experiment that is searching for sterile neutrinos via the observation of $\overline{ν}$ μ → $\overline{ν}$ e appearance oscillations using neutrinos from muon decay-at-rest. For this search, rejecting cosmic-ray-induced neutron events by Pulse Shape Discrimination (PSD) is essential because the JSNS2 detector is located above ground, on the third floor of the building. We have achieved 94.95% ± 0.15% rejection of neutron events while keeping 92.82% ± 1.77% of signal, electron-like events using a data-driven likelihood method. This article will report the PSD technique using the full fiducial volume of the JSNS2 detector.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Prototype reactor-antineutrino detector based on 6 Li-doped pulse-shape-discriminating plastic scintillator

An aboveground 60-kg reactor-antineutrino detector prototype, comprising a two-dimensional array of 36 6 ⁢Li-doped pulse-shape-sensitive plastic scintillator bars, is described. Each bar is 50 cm long with a square cross section of 5.5 cm. Doped with 6 ⁢Li at 0.1% by mass, the detector is capable of identifying correlated energy depositions for the detection of reactor antineutrinos via the inverse-𝛽-decay (IDB) reaction. Each bar is wrapped with a specular reflector that directs photons toward photomultiplier tubes mounted at both ends of the bar. Here, this paper highlights the construction, key features, and main performance characteristics of the system. The system, which relies on multiple observables such as pulse-shape discrimination, energy, position, and timing, is capable of detecting IBD-like neutron-correlated backgrounds, long-lived decay chains, and cosmogenic isotopes.

Physics↗
DOE OSTI2022

Quantum advantage for noisy channel discrimination

Many quantum mechanical experiments can be viewed as multiround interactive protocols between known quantum circuits and an unknown quantum process. Fully quantum “coherent” access to the unknown process is known to provide an advantage in many discrimination tasks compared to when only incoherent access is permitted, but it is unclear if this advantage persists when the process is noisy. Here, we show that a quantum advantage can be maintained when distinguishing between two noisy single-qubit rotation channels. Numerical and analytical calculations reveal a distinct transition between the performance of fully coherent and fully incoherent protocols as a function of noise strength. Moreover, the size of the region of coherent quantum advantage shrinks inverse polynomially in the number of channel uses, and in an intermediate regime an improved strategy is a hybrid of fully coherent and fully incoherent subroutines. The fully coherent protocol is based on quantum signal processing, suggesting a generalizable algorithmic framework for the study of quantum advantage in the presence of realistic noise.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

First Measurement of Discrimination between Helium and Electron Recoils in Liquid Xenon for Low-Mass Dark Matter Searches

We report the first measurement of discrimination between low-energy helium recoils and electron recoils in liquid xenon. This result is relevant to proposed low-mass dark matter searches which seek to dissolve light target nuclei in the active volume of liquid-xenon time projection chambers. Low-energy helium recoils were produced by degrading α particles from Po 210 with a gold foil situated on the cathode of a liquid xenon time-projection chamber. The resulting population of helium recoil events is well separated from electron recoils and is also offset from the expected position of xenon nuclear recoil events. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Performance of a second generation of the Fermilab Constant Fraction Discriminator ASIC for time-stamping long-strip AC-LGAD sensors.

We present the design and performance characterization results of the second generation of the novel Fermilab Constant Fraction Discriminator ASIC (FCFD) developed to readout AC-coupled low gain avalanche detector (AC-LGAD) sensors. This study presents the performance of the ASIC which was optimized specifically for reading out strip AC-LGAD sensors designed for ePIC experiment at EiC. Performance was measured using charge injection and particle beams with prototype AC-LGAD sensors wirebonded to the FCFD ASIC.

Apresyan, A.↗
DOE OSTI2022

ASDFL: An adaptive super‐pixel discriminative feature‐selective learning for vehicle matching

Abstract There are a large number of cameras in modern transportation system that capture numerous vehicle images continuously. Therefore, automatic analysis of these vehicle images is helpful for traffic flow management, criminal investigations and vehicle inspections. Vehicle matching, which aims to determine whether two input images depict an identical vehicle, is one of the core tasks in vehicle analysis. Recent relevant studies have focused on local feature extraction instead of global extraction, since local details can provide crucial cues to distinguish between cars. However, these methods do not select local features; that is, they do not assign weights to local features. Therefore, in this research, we systematically study the vehicle matching task, and present a novel annotation‐free local‐based deep learning method called Adaptive super‐pixel discriminative feature‐selective learning (ASDFL) to address this issue. In ASDFL, vehicle images are segmented into clusters of super‐pixels of similar size by considering the location and colour similarities of pixels without using any component‐level annotation. These super‐pixels are deemed to be the virtual components of vehicles. Moreover, a convolutional neural network is used to extract the deep features of these virtual components. Thereafter, an instance‐specific mask generation module driven by the extracted global features is enhanced to produce a mask to select the most distinctive virtual components of each vehicle image pair in the feature space. Finally, the vehicle matching task is accomplished by classifying the selected virtual component features of each imaged vehicle pair. Extensive experiments on two popular vehicle identification benchmarks demonstrate that our method is 1.57% and 0.8% more accurate than the previous baselines in a vehicle matching task on the VeRi and VehicleID datasets, respectively, which demonstrates the effectiveness of our method.

Qin, Rong↗
DOE OSTI2021

Pulse-shape discrimination against low-energy Ar-39 beta decays in liquid argon with 4.5 tonne-years of DEAP-3600 data

The DEAP-3600 detector searches for the scintillation signal from dark matter particles scattering on a 3.3 tonne liquid argon target. The largest background comes from 39 Ar beta decays and is suppressed using pulse-shape discrimination (PSD). We use two types of PSD estimator: the prompt-fraction, which considers the fraction of the scintillation signal in a narrow and a wide time window around the event peak, and the log-likelihood-ratio, which compares the observed photon arrival times to a signal and a background model. We furthermore use two algorithms to determine the number of photons detected at a given time: (1) simply dividing the charge of each PMT pulse by the mean single-photoelectron charge, and (2) a likelihood analysis that considers the probability to detect a certain number of photons at a given time, based on a model for the scintillation pulse shape and for afterpulsing in the light detectors. The prompt-fraction performs approximately as well as the log-likelihood-ratio PSD algorithm if the photon detection times are not biased by detector effects. We explain this result using a model for the information carried by scintillation photons as a function of the time when they are detected.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗