Proton Distribution Research Articles

Hyperon and antihyperon physics

Structure, interactions and decays of hyperons can be studied at an electron-positron collider in annihilations to a hyperon-antihyperon pair. This method already has huge impact on hyperon physics since it was used in a first modern measurement of decay asymmetry in the weak decay and the result calls for reinterpretation of all polarization results for the Λ hyperon. In the experiment by the BESIII Collaboration nearly half million events were used. The pair production process involves two (complex) hadronic form factors. The observed large relative phase ΔΦ between the form factors, (42.4±0.6±0.5)°, makes it possible to use both transverse polarization and the spin correlations of the pair to simultaneously measure decay parameters for Λ and hyperons. Of particular importance is the result for the decay asymmetry parameter α− in the most probable Λ decay used to determine Λ polarization. The new α− value from BESIII, 0.750±0.009±0.004, is 17(3)% larger than the world average of 0.642 ± 0.013 adopted by all experiments between 1978 and 2019 to determine Λ polarization from the measured asymmetry in the decay proton distribution. A comparison of the concurrently measured at BESIII α− and α+, the parameter for the charge conjugated process , results in a direct CP symmetry test for the hyperon.The reaction was studied at BESIII also outside the J/ψ resonance using 66.9 pb−1 collected at GeV. The result is the first complete determination of the time-like elastic form factors GM and GE for any baryon including the relative phase ΔΦ = arg(GE/GM ) of (37 ± 12 ± 6)°. The absolute normalization of the form factors is set by the determined Born cross section of σ Born= 119.0 ± 5.3 ± 5.1 pb. In a separate run at GeV, 1.0 MeV above threshold for , a surprisingly large cross section for of 305 ± pb was measured.

Deep learning prediction of proton and photon dose distributions for paediatric abdominal tumours

ObjectiveDose prediction using deep learning networks prior to radiotherapy might lead tomore efficient modality selections. The study goal was to predict proton and photon dose distributions based on the patient-specific anatomy and to assess their clinical usage for paediatric abdominal tumours. Material and methodsData from 80 patients with neuroblastoma or Wilms’ tumour was included. Pencil beam scanning (PBS) (5 mm/ 3%) and volumetric-modulated arc therapy (VMAT) plans (5 mm) were robustly optimized on the internal target volume (ITV). Separate 3-dimensional patch-based U-net networks were trained to predict PBS and VMAT dose distributions. Doses, planning-computed tomography images and relevant optimization masks (ITV, vertebra and organs-at-risk) of 60 patients were used for training with a 5-fold cross validation.The networks’ performance was evaluated by computing the relative error between planned and predicted dose-volume histogram (DVH) parameters for 20 inference patients. In addition, the organs-at-risk mean dose difference between modalities was calculated using planned and predicted dose distributions (ΔDmean = DVMAT-DPBS). Two radiation oncologists performed a blind PBS/VMAT modality selection based on either planned or predicted ΔDmean. ResultsAverage DVH differences between planned and predicted dose distributions were ≤ |6%| for both modalities. The networks classified the organs-at-risk Dmean difference as a gain (ΔDmean > 0) with 98% precision. An identical modality selection based on planned compared to predicted ΔDmean was made for 18/20 patients. ConclusionDeep learning networks for accurate prediction of proton and photon dose distributions for abdominal paediatric tumours were established. These networks allowing fast dose visualisation might aid in identifying the optimal radiotherapy technique when experience and/or resources are unavailable.

Catalytic Hydrogen Doping of NdNiO3 Thin Films under Electric Fields.

The electric-field-assisted hydrogenation and corresponding resistance modulation of NdNiO3 (NNO) thin-film resistors were systematically studied as a function of temperature and dc electric bias. Catalytic Pt electrodes serve as triple-phase boundaries for hydrogen incorporation into a perovskite lattice. A kinetic model describing the relationship between resistance modulation and proton diffusion was proposed by considering the effect of the electric field during hydrogenation. An electric field, in addition to thermal activation, is demonstrated to effectively control the proton distribution along its gradient with an efficiency of ∼22% at 2 × 105 V/m. The combination of an electric field and gas-phase annealing is shown to enable the elegant control of the diffusional doping of complex oxides.

Molecular Dynamics Study of the Nanoscale Proton Density Distribution at the Ionomer-Catalyst Interface

The proton density in the cathode catalyst layer is a crucial variable to define the local reaction conditions in and thereby determine the performance and lifetime of polymer electrolyte fuel cells. We present a molecular modeling study to examine the proton density distribution in a water-filled, slab-like pore. The slab is confined by two distinct boundaries, the first consisting of a platinum single-crystalline surface and the second being a thin and dense skin layer of proton-conducting ionomer. Classical molecular dynamics simulations serve as a valuable tool to rationalize the impact of the molecular structure and properties of the ionomer film as well as the adsorption and charging state of the metal surface on structure and properties of interfacial water and the spatial distribution of protons. Boundary conditions at the metal surface are obtained from explicit quantum mechanical simulations at the DFT level. The oxide coverage at the metal surface and the water layer thickness are considered as crucial parameters. Results of detailed structural analyses elucidate the impact of a structured layer of near-surface water molecules at the platinum surface on accumulating protons at the interface.

INDUCING INTRINSIC γ-RAY EMISSION OF THE INTERSTELLAR MEDIUM BY INTENSE FLUXES OF PROTONS AND α-PARTICLES IN ACTIVE GALACTIC NUCLEI

Cosmic-ray induced γ-ray emission inactive galactic nuclei (AGN) has been examined in thisstudy for the first time. Cross-sections for the formation ofγ-quanta in such cosmic-ray collisions were selected in the1-150 MeV energy range. Synthetic γ-ray spectra werecomputed for both interstellar gas and dust. At the sameenergies of particle collisions and induced emission of γ-quanta, energy intervals of diagnostic interest weredetermined. Specific characteristics of emission weredetected in the energy ranges of 5-15 MeV and 23-30 MeVfor most investigated elements. Diffuse continuous γ-rayspectra for the other energy ranges were less informativewith regard to the determination of the chemicalcomposition of interstellar gas. It has been shown thatexploring cosmic-ray fluxes in the vicinity of galacticcentres by employing the examined γ-ray spectra yields apattern of their energy distribution. Diagrams of cross-sections for γ-quanta formation were computed for the α-process elements. Synthetic γ-ray spectra of interstellar gasand dust were calculated individually and collectively. Ithas been indicated that, under certain conditions in AGN,cross-sections for ionisation of atoms due to energy lossesby cosmic-ray induced ionisation and γ-quanta emissionresulting from collisions with cosmic rays are similar. It hasbeen found that when the maximum of proton and α-particle energy distribution function falls within theinvestigated range of energies, it leads to the formation ofthe peak flux of γ-rays. This is particularly important forthe interpretation of observations in the energy ranges of 5-15 MeV and 23-30 MeV. Synthetic induced γ-ray spectraof interstellar dust were computed, and methods of theirobservations for silicate and carbon-containing dust, whichaccount for 80% and 20% of the interstellar-dust total mass,respectively, were determined. It has been deduced that thecontribution of Compton processes to γ-quanta emissioncan be neglected at the investigated energies.

Microscopic description of fusion hindrance in symmetric Ni+Ni and asymmetric C12+Pt198 systems

Hindrance at deep subbarrier energies for the symmetric $^{58}\mathrm{Ni}+^{58}\mathrm{Ni}, ^{64}\mathrm{Ni}+^{64}\mathrm{Ni}$, and asymmetric $^{12}\mathrm{C}+^{198}\mathrm{Pt}$ systems is investigated using microscopic energy and the density-dependent $G$-matrix effective interaction. The proton and neutron density distributions of target and projectile are derived from Skyrme-Hartree-Fock calculations. A fair agreement with the data of the fusion excitation functions and astrophysical $S$ factors have been obtained without any fitting parameters. Hindrance is naturally reproduced at deep subbarrier energies, which is consistent with experimental observations.

Feasibility study of range verification based on proton-induced acoustic signals and recurrent neural network

Range verification in proton therapy is a critical quality assurance task. We studied the feasibility of online range verification based on proton-induced acoustic signals, using a bidirectional long-short-term-memory recurrent neural network and various signal processing techniques. Dose distribution of 1D pencil proton beams inside a CT image-based phantom was analytically calculated. The propagation of acoustic signal inside the phantom was modeled using the k-Wave toolbox. For signal processing, five methods were investigated: down-sampling (DS), DS + HT (Hilbert transform), Wavelet decomposition (Wavedec db1, db4 and db20). The performances were quantitatively evaluated in terms of mean absolute error, mean relative error (MRE) and the Bragg peak localization error (). In addition, the study analyzed the impact of noise levels, the number of sensors, as well as the location of sensors. For the noiseless case (32 sensors), the Wavedec db1 method demonstrates the best performance: is less than one pixel and the dose accuracy over the region adjacent to the Bragg peak (MRE50) is ∼3.04%. With the presence of noise, the Wavedec db1 method demonstrates the best noise immunity, achieving less than 1 mm and an MRE50 of ∼12%. The proposed machine learning framework may become a useful tool allowing for online range verification in proton therapy.

Experimental mapping of a pH gradient from a positively charged micellar interface to bulk solution

The nanoscale pH gradients from a charged membrane interface to the bulk solution, determine fundamental properties of chemical and biological systems. We estimated the proton distribution on micelle surfaces experimentally measuring the apparent pKa of a weak acid linked at varying distances to a micelle anchoring moiety and relating these values to the electrical potential at the micellar surface. The pH probes consisted of benzoic acid connected to chains with variable number (1–5) oxyethylene (−OCH2CH2–) units. The methylene of the terminal oxyethylene was connected to a quaternary nitrogen containing a long hydrocarbon chain. We calculated the apparent pKa (pKap) of the benzoic acid derivatives with surfactant micelles by UV spectroscopy. The difference between the pKa in solution and the pKap in micelles (ΔpK) of all probes was very similar with negatively charged sodium dodecyl sulphate (SDS) or zwitterionic N-hexadecyl-N,N-dimethyl-3-ammonio-1-propanesulfonate (HPS) micelles, indicating that the dissociation of the substituted benzoates occurred at the micellar interface in both SDS and HPS. In contrast, the ΔpK of the probes decreased as a function of the benzoate's distance to the micelle interface in hexadecyltrimethylammonium chloride (CTAC) micelles, The variation of ΔpK with distance, from the CTAC micellar interface to bulk solution, was quantitatively correlated to H+ distribution from the interface. The experimental results coincided with independently calculated Poisson Boltzmann H+ distribution. These results demonstrate that that it is possible to experimentally map H+ gradients from a charged interface.

Two‐Dimensional Hybrid Particle‐in‐Cell Simulations of Magnetosonic Waves in the Dipole Magnetic Field: On a Constant L‐Shell

AbstractTwo‐dimensional hybrid particle‐in‐cell (PIC) simulations are carried out on a constant L‐shell (or drift shell) surface of the dipole magnetic field to investigate the generation process of near‐equatorial fast magnetosonic waves (a.k.a equatorial noise; MSWs hereafter) in the inner magnetosphere. The simulation domain on a constant L‐shell surface adopted here allows wave propagation and growth in the azimuthal direction (as well as along the field line) and is motivated by the observations that MSWs propagate preferentially in the azimuthal direction in the source region. Furthermore, the equatorial ring‐like proton distribution used to drive MSWs in the present study is (realistically) weakly anisotropic. Consequently, the ring‐like velocity distribution projected along the field line by Liouville's theorem extends to rather high latitude, and linear instability analysis using the local plasma conditions predicts substantial MSW growth up to ±27° latitude. In the simulations, however, the MSW intensity maximizes near the equator and decreases quasi‐exponentially with latitude. Further analysis reveals that the stronger equatorward refraction at higher latitude due to the larger gradient of the dipole magnetic field strength prevents off‐equatorial MSWs from growing continuously, whereas MSWs of equatorial origin experience little refraction and can fully grow. Furthermore, the simulated MSWs exhibit a rather complex wave field structure varying with latitude, and the scattering of energetic ring‐like protons in response to MSW excitation occurs faster than the bounce period of those protons so that they do not necessarily follow Liouville's theorem during MSW excitation.

Forward Modeling of Particle Acceleration and Transport in an Individual Solar Flare

Abstract The aim of this study is to generate maps of the hard X-ray emission produced by energetic electrons in a solar flare and compare them with observations. The ultimate goal is to test the viability of the combined MHD/test-particle approach for data-driven modeling of active events in the solar corona and their impact on the heliosphere. Based on an MHD model of X-class solar flare observed on 2017 September 8, we calculate trajectories of a large number of electrons and protons using the relativistic guiding-center approach. Using the obtained particle trajectories, we deduce the spatial and energy distributions of energetic electrons and protons, and calculate bremsstrahlung hard X-ray emission using the “thin-target” approximation. Our approach predicts some key characteristics of energetic particles in the considered flare, including the size and location of the acceleration region, energetic particle trajectories and energy spectra. Most importantly, the hard X-ray bremsstrahlung intensity maps predicted by the model are in good agreement with those observed by RHESSI. Furthermore, the locations of proton and electron precipitation appear to be close to the sources of helioseismic response detected in this flare. Therefore, the adopted approach can be used for observationally driven modeling of individual solar flares, including manifestations of energetic particles in the corona, as well as the inner heliosphere.

Nuclear structure properties in neutron stars

The charge, proton and neutron density distributions along with nuclear properties were calculated by Hartree–Fock approach with Skyrme force interaction for isotopic Pb chain ([Formula: see text]). The effects of correlation on neutron skin thicknesses by obtaining bulk and surface contributions were analyzed by three different approaches. The occurrence of the nuclei with bubble structure due to central depletion in nucleonic was investigated for Pb isotopes as a function of relative neutron excess [Formula: see text]. The important role of the bubble effect in heavy region was explained by the relation between Coulomb and nn-interaction. The single particle energy levels were determined by each [Formula: see text] state of stable Pb isotopes, as well as charge form factors [Formula: see text]. Besides, the average neutron–proton [Formula: see text] and residual neutron–proton [Formula: see text] interactions of the Pb isotopes were calculated by the theoretical binding energies. The fluctuations in the obtained results were considered in detail because its variation may give a good criterion for the mass model approaches.

Layout optimization of corrector magnets for a proton therapy beamline via genetic algorithm

Proton therapy is one of the most effective radiotherapy methods for cancer and the dose distribution of protons on patients is superior to conventional rays. However, it is likewise more sensitive to the beam misalignment raised from errors in the magnets, girders and beam diagnostic devices. According to the clinical treatment guidelines, beam position accuracy at the iso-center should be controlled within ±0.5 mm. While the response matrix method is widely used in beam orbit correction, the correction performance relies largely on the locations of corrector magnets. This paper introduces an optimization approach for the layout of corrector magnets by using the multi-objective genetic algorithm NSGA-II and this technique is applied to a cyclotron-based proton therapy facility. All potential locations of the corrector magnets are encoded with an integer sequence. After 300 generations of crossover, mutation and selection, seventeen Pareto-front solutions were obtained and the best configuration was selected by taking the overall beam misalignment along the beamline into considerations. Finally, the maximum deviation of the corrected beam orbit in the beamline is less than 4.5 mm and the beam position at the iso-center can be optimized within ±0.3 mm, fulfilling the clinical requirement.

FRoG: An independent dose and LETd prediction tool for proton therapy at ProBeam® facilities.

Particle therapy is becoming increasingly available world-wide for precise tumor targeting, its favorable depth dose deposition, and increased biological damage to tumor tissue compared to conventional photon therapy. As demand increases for improved robustness and conformality, next-generation secondary dose calculation engines are needed to verify treatment plans independently and provide estimates for clinical decision-making factors, such as dose-averaged linear energy transfer (LETd ) and relative biological effectiveness (RBE). FRoG (Fast dose Recalculation on GPU) has been installed and commissioned at the Danish Centre for Particle Therapy (DCPT). FRoG was developed for synchrotron-based facilities and has previously demonstrated good agreement with gold-standard Monte Carlo simulations and measurements. In this work, additions and modifications to FRoG's pencil beam algorithm to support the ion beam delivery with cyclotron-based technology as used at the DCPT, range shifter (RS) implementation, and robustness analysis methods are presented. FRoG dose predictions are compared to measurements and predictions of the clinical treatment planning system (TPS) Eclipse (Varian Medical Systems, Palo Alto, United States of America, CA, v.13.7.16) in both homogenous and heterogeneous scenarios using a solid-water/water and a half-head anthropomorphic phantom, respectively. Additional capabilities of FRoG are explored by performing a plan robustness analysis, analyzing dose and LETd for ten patients. Mid-target measurements in spread-out Bragg Peaks (SOBP) were on average within -0.19%±0.30% and ≤0.5% of FRoG predictions for irradiations withoutand with RS, respectively. Average 3%/2mm 3D γ-analysis passing rates were 99.1% for ~200 patient plan QA comparisons. Measurement with an anthropomorphic head-phantom yielded a γ-passing rate >98%. Overall, maximum target differences in D02% of <2% between the TPS and FRoG were observed for patient plans. The robustness analysis study accounting for range, delivery, and positioning uncertainties revealed small differences in target dose and a maximum LETd VH02% (LETd received by 2% of the volume having dose larger than 1% of maximum dose) values below 10.1keV/µm to the brain stem. We demonstrate that auxiliary dose calculation systems like FRoG can yield excellent agreement to measurements comparable to clinical beam models. Through this work, application of FRoG as a secondary engine at third party cyclotron-based particle treatment facilities is now established for dose verification as well as providing further insight on LETd and variable RBE distributions for protons, currently absent from the standard clinical TPS.

Prediction of single event upset critical charge and sensitive volume depth by energy deposition analysis of low energy protons

Single Event Upset (SEU) critical charge and sensitive volume depth of 65-nm CMOS bulk SRAM are predicted through energy deposition analysis of low energy protons. The deposited energy distributions of protons calculated by GEANT4 are incorporated into the three-dimensional device simulator to perform the Single Event Effects (SEE) simulation. Based on the analysis of the relationship between the energy deposition distributions and the single event responses, the deposited energy is correlated with the SEU critical charge, and valuable information of the upset sensitive volume depth is provided. Our prediction method is validated by the results of SPICE simulation method as well as experimental data.

The Development of Paeonia ostii Seeds and Oil Quality Formation

Paeonia ostii is a woody oil crop with potential value as an edible oil. With the aim of acquiring systematic knowledge of the development of P. ostii seeds, the oil content, biomass, and water content of the seeds were determined. Changes in the distribution of hydrogen protons in P. ostii seeds during follicle development were traced using magnetic resonance imaging (MRI). The formation of oil bodies in the endosperm and embryo was observed using transmission electron microscopy (TEM). Dynamic changes in oleic acid, linoleic acid, and α-linolenic acid contents were assessed by gas chromatography-mass spectrometry (GC-MS). The magnetic resonance images showed that, during early follicle development [45–85 days after flowering (DAF)], a greater quantity of liquid mucus was present within the seeds, and seeds in the same follicle developed at different rates. At 95 to 115 DAF, proton density was distributed evenly in all areas of the seed. A small dark area appeared in the center of the seed, and mucus in the follicles and water in the pericarp disappeared gradually. TEM observations showed that at 45 DAF, a few oil bodies were scattered at the cell periphery in the endosperm, and oil bodies were more numerous in the embryo. With the progression of seed development, the number and size of oil bodies in the embryo and endosperm continued to increase. The fresh and dry mass of P. ostii seeds increased from 45 to 105 DAF, then decreased after 105 DAF. The moisture content decreased, whereas the oil content increased and attained 33.1% at seed maturity. The three predominant unsaturated fatty acids accumulated simultaneously and showed stages of initial accumulation (45–65 DAF) and rapid accumulation (65–105 DAF). The results suggest that 65 to 105 DAF is a critical period for unsaturated fatty acid accumulation in P. ostii seeds.

A nonlocal optical potential with a Gaussian nonlocality for proton elastic scattering off light 1p-shell nuclei

In a recent work we used the nonlocal optical model of Perey and Buck (Nucl Phys A 32:353, 1962) to fit the angular distribution data corresponding to neutron elastic scattering off light nuclei from $$^6\hbox {Li}$$ to $$^{18}\hbox {O}$$ over the 9–35 MeV energy range. Although such nuclei posses diffuse edges that complicate the scattering process, the model resulted in improved angular distribution fits compared to those obtained using local optical models. In this work we extend the treatment to the case of proton elastic scattering off light 1p-shell nuclei, but consider the wider 10–70 MeV energy range. No single global set of nonlocal parameters adequately described the measured data across the entire energy range. Instead, we obtained two global sets of fixed nonlocal parameters; one corresponds to the 10–39 MeV range, the other is for the higher 40–70 MeV incident energies. Each set resulted in angular distribution fits which are in very good agreement with experimental data even in the large-angle scattering region, which is usually endowed by nonlocal effects. The fits were improved even further by expressing the imaginary volume and imaginary surface depths as linear functions of energy and the $$(N-Z)/A$$ asymmetry term. This indicates that there is still need for energy-dependent parameters even when nonlocality is explicitly included in the potential. We also used the model to predict elastic angular distributions for proton scattering off nuclei not included in the fitting procedure. The theoretical predictions showed very good agreement with experiment. As a further test of the nonlocal model, we calculated total reaction cross sections for proton scattering off light 1p-shell nuclei. Our predictions are in fair overall agreements with the experimental data.

The 18 November 2015 Magnetopause Crossing: The GEM Dayside Kinetic Challenge Event Observed by MMS/HPCA

AbstractAt Earth's dayside magnetopause, the fundamental process known as magnetic reconnection is responsible for connecting geomagnetic field lines to interplanetary magnetic field lines and converting magnetic energy into particle energy and heat. As part of a coordinated analysis effort by the Geospace Environment Modeling (GEM) community to determine the reconnection location and other aspects of reconnection, a magnetopause crossing by the Magnetospheric Multiscale (MMS) mission on 18 November 2015 was selected. The crossing occurred during stable solar wind and dominantly southward interplanetary magnetic field conditions. The MMS satellites were located close to the subsolar region and observed southward accelerated ion jets during encounters with the magnetopause boundary layers, indicating the presence of an active X‐line north of the satellites. Using proton distributions from the Hot Plasma Composition Analyzer (HPCA) instruments, the distance from the spacecraft to the reconnection site was initially determined to be between 5 to 7 RE. A slight rotation of the interplanetary magnetic field caused a change of the magnetic topology at the magnetopause. This topology change produced conditions which are known to change the location of the X‐line. After the change, the location of the component reconnection line was estimated to be less than 4 RE, but most likely was much closer to the observing satellites.

Microscopic description of the fusion excitation function of 32,36S+90,94,96Zr

The fusion excitation function for the systems [Formula: see text]S+[Formula: see text]Zr is investigated using a microscopic internuclear potential derived from Skyrme energy density functional. The inputs in this approach are the proton and neutron density distributions of the interacting nuclei, which are derived from Skyrme–Hartree–Fock calculations. The SkM[Formula: see text] interaction is used in the calculation of the nuclear densities as well as the internuclear potential. The coupling to low lying inelastic excited states of target and projectile is considered. The role of the neutron transfer is discussed, where it is considered through the CCFULL model calculation. A good agreement with the experimental data is obtained without adjustable parameters.

Classification of equation of state in relativistic heavy-ion collisions using deep learning

Convolutional Neural Nets, which is a powerful method of Deep Learning, is applied to classify equation of state of heavy-ion collision event generated within the UrQMD model. Event-by-event transverse momentum and azimuthal angle distributions of protons are used to train a classifier. An overall accuracy of classification of 98% is reached for Au+Au events at sqrt{s_{NN}} = 11 GeV. Performance of classifiers, trained on events at different colliding energies, is investigated. Obtained results indicate extensive possibilities of application of Deep Learning methods to other problems in physics of heavy- ion collisions.

Water-Assisted Proton Transport in Confined Nanochannels

Hydrated excess protons under hydrophobic confinement are a critical component of charge transport behavior and reactivity in nanoporous materials and biomolecular systems. Herein, excess proton confinement effects are computationally investigated for sub-2 nm hydrophobic nanopores by varying the diameters (d = 0.81, 0.95, 1.09, 1.22, 1.36, 1.63, and 1.90 nm), lengths (l ∼3 and ∼5 nm), curvature, and chirality of cylindrical carbon nanotube (CNT) nanopores. CNTs with a combination of different diameter segments are also explored. The spatial distribution of water molecules under confinement is diameter-dependent; however, proton solvation and transport are consistently found to occur in the water layer adjacent to the pore wall, showing an “amphiphilic” character of the hydrated excess proton hydronium-like structure. The proton transport free energy barrier also decreases significantly as the nanopore diameter increases and proton transport becomes almost barrierless in the d > 1 nm nanopores. Among the nanopores studied, the Zundel cation (H5O2+) is populated only in the d = 0.95 nm CNT (7,7) nanopore. The presence of the hydrated excess proton and K+ inside the CNT (7,7) nanopore induces a water density increase by 40 and 20%, respectively. The K+ transport through CNT nanopores is also consistently higher in the free energy barrier than proton transport. Interestingly, the evolution of excess protonic charge defect distribution reveals a “frozen” single water wire configuration in the d = 0.81 nm CNT (6,6) nanopore (or segment), through which hydrated excess protons can only shuttle via the Grotthuss mechanism. Vehicular diffusion becomes relevant to proton transport in the “flat” free energy regions and in the wider nanopores, where protons do not primarily shuttle in the axial direction.