Energy Loss of Swift Protons in Liquid Water: Role of Optical Data Input and Extension Algorithms

García-Molina, Rafael; Abril, Isabel; Kyriakou, Ioanna; Emfietzoglou, Dimitris

doi:10.1007/978-94-007-2564-5_15

Cited by 20 publications

(41 citation statements)

References 67 publications

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“…For this purpose, we use a similar expression to eq 2, but replacing the Drude dielectric functions by Mermin dielectric functions. 38 The values of the parameters A i , ω i , and γ i are, in principle, the same as those that appear in Table 1, since in the optical limit (i.e., at zero momentum transfer) the Drude and the Mermin ELF are identical; 33 however, in what follows, these parameters will be modified in order to improve the ELF.…”

Section: Improving the Elf Through The Melf-gosmentioning

confidence: 99%

Energy Loss Function of Solids Assessed by Ion Beam Energy-Loss Measurements: Practical Application to Ta₂O₅

et al. 2015

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We present a study where the energy loss function of Ta 2 O 5 , initially derived in the optical limit for a limited region of excitation energies from reflection electron energy loss spectroscopy (REELS) measurements, was improved and extended to the whole momentum and energy excitation region through a suitable theoretical analysis using the Mermin dielectric function and requiring the fulfillment of physically motivated restrictions, such as the f-and KK-sum rules. The material stopping cross section (SCS) and energy-loss straggling measured for 300−2000 keV proton and 200− 6000 keV helium ion beams by means of Rutherford backscattering spectrometry (RBS) were compared to the same quantities calculated in the dielectric framework, showing an excellent agreement, which is used to judge the reliability of the Ta 2 O 5 energy loss function. Based on this assessment, we have also predicted the inelastic mean free path and the SCS of energetic electrons in Ta 2 O 5 .

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Section: Improving the Elf Through The Melf-gosmentioning

confidence: 99%

Energy Loss Function of Solids Assessed by Ion Beam Energy-Loss Measurements: Practical Application to Ta₂O₅

et al. 2015

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“…In this work, we present theoretical calculations of the IMFP and the stopping power (SP) of swift electrons in several targets of biological relevance, such as liquid water, DNA, protein, lipid, or sugar, using the extended‐optical‐data methodology to describe the dielectric function of the material. Specifically, the electronic excitation spectrum of each biomaterial is properly described by the MELF–GOS (Mermin Energy Loss Function – Generalized Oscillator Strength) model . The advantages of this methodology lie in that the MELF–GOS model incorporates damping corrections because of a plasmon's finite lifetime, an automatic extension to arbitrary momentum transfer (without introducing any especially designed extension algorithms), and takes into account many‐body, chemical and phase effects of the target.…”

Section: Introductionmentioning

confidence: 99%

Inelastic scattering and energy loss of swift electron beams in biologically relevant materials

García-Molina

Abril

Kyriakou

et al. 2016

Surface & Interface Analysis

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The inelastic mean free path and the stopping power of swift electrons in relevant biomaterials, such as liquid water, DNA, protein, lipid, carotene, sugar, and ice are calculated in the framework of the dielectric formalism. The Mermin Energy Loss Function – Generalized Oscillator Strength model is used to determine the energy loss function of these materials for arbitrary energy and momentum transfer using electron energy‐loss spectroscopy data as input. To ensure the consistency of the model, efforts are made so that both the Kramers–Kronig and f‐sum rules are fulfilled to better than 2%. Our findings indicate sizeable differences in the inelastic mean free path and stopping power among these biomaterials for low‐energy electrons. For example, at 100‐eV electron energy, the inelastic mean free path in protein is 25% smaller than for water and around 10% smaller than for the other biomaterials. The stopping power values of protein, DNA, and sugar are rather similar but 20% larger than for water. Taking into account these results, we conclude that electron interactions with living tissues at the nanometric scale cannot be reliably described using only liquid water as the surrogate of the biological target. Copyright © 2016 John Wiley & Sons, Ltd.

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“…We show in Figure 5 the electronic mean free path Drude-GOS ELF do not agree so well [20]. The influence of the exchange factor is only visible at very low electron en-47 ergies ( 10 eV).…”

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“…This result is in good agreement with the fact 67 that single-particle excitations prevail over collective ex-68 citation as the momentum transfer increases due to the 69 plasmon damping. The dispersion of the damping coef-70 ficient, only considered (implicitly) in the MELF model, 71 provides the expected momentum broadening of the Bethe 72 ridge; the results from the MELF model agree better than 73 those from the extended-Drude model with the few ex-74 perimental data at k = 0 measured for graphite [28,29], 75 aluminum [30,31] or liquid water [20,32,33].…”

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Simulation of the secondary electrons energy deposition produced by proton beams in PMMA: influence of the target electronic excitation description

et al. 2015

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Abstract. We have studied the radial dependence of the energy deposition of the secondary electrons generated by swift proton beams incident with energies T = 50 keV-5 MeV on poly(methylmethacrylate) (PMMA). Two different approaches have been used to model the electronic excitation spectrum of PMMA through its energy loss function (ELF), namely the extended-Drude ELF and the Mermin ELF. The singly differential cross section and the total cross section for ionization, as well as the average energy of the generated secondary electrons, show sizeable differences at T 0.1 MeV when evaluated with these two ELF models. In order to know the radial distribution around the proton track of the energy deposited by the cascade of secondary electrons, a simulation has been performed that follows the motion of the electrons through the target taking into account both the inelastic interactions (via electronic ionizations and excitations as well as electron-phonon and electron trapping by polaron creation) and the elastic interactions. The radial distribution of the energy deposited by the secondary electrons around the proton track shows notable differences between the simulations performed with the extended-Drude ELF or the Mermin ELF, being the former more spread out (and, therefore, less peaked) than the latter. The highest intensity and sharpness of the deposited energy distributions takes place for proton beams incident with T ∼ 0.1-1 MeV. We have also studied the influence in the radial distribution of deposited energy of using a full energy distribution of secondary electrons generated by proton impact or using a single value (namely, the average value of the distribution); our results show that differences between both simulations become important for proton energies larger than ∼0.1 MeV. The results presented in this work have potential applications in materials science, as well as hadron therapy (due to the use of PMMA as a tissue phantom) in order to properly consider the generation of electrons by proton beams and their subsequent transport and energy deposition through the target in nanometric scales.

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Energy Loss of Swift Protons in Liquid Water: Role of Optical Data Input and Extension Algorithms

Cited by 20 publications

References 67 publications

Energy Loss Function of Solids Assessed by Ion Beam Energy-Loss Measurements: Practical Application to Ta₂O₅

Energy Loss Function of Solids Assessed by Ion Beam Energy-Loss Measurements: Practical Application to Ta₂O₅

Inelastic scattering and energy loss of swift electron beams in biologically relevant materials

Simulation of the secondary electrons energy deposition produced by proton beams in PMMA: influence of the target electronic excitation description

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Energy Loss of Swift Protons in Liquid Water: Role of Optical Data Input and Extension Algorithms

Cited by 20 publications

References 67 publications

Energy Loss Function of Solids Assessed by Ion Beam Energy-Loss Measurements: Practical Application to Ta2O5

Energy Loss Function of Solids Assessed by Ion Beam Energy-Loss Measurements: Practical Application to Ta2O5

Inelastic scattering and energy loss of swift electron beams in biologically relevant materials

Simulation of the secondary electrons energy deposition produced by proton beams in PMMA: influence of the target electronic excitation description

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Product

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Energy Loss Function of Solids Assessed by Ion Beam Energy-Loss Measurements: Practical Application to Ta₂O₅

Energy Loss Function of Solids Assessed by Ion Beam Energy-Loss Measurements: Practical Application to Ta₂O₅