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Novel thick-target inverse kinematics method for the astrophysical 12C+12C fusion reaction

NUCLEAR PHYSICS AND INTERDISCIPLINARY RESEARCH

Novel thick-target inverse kinematics method for the astrophysical 12C+12C fusion reaction

Wei-Ke Nan
You-Bao Wang
Yao-De Sheng
Jun Su
Yu-Qiang Zhang
Lu-Yang Song
Yang-Ping Shen
Fu-Qiang Cao
Chen Chen
Chao Dong
Yun-Ju Li
Zhi-Hong Li
Gang Lian
Wei Nan
Qiang Wang
Na Song
Sheng-Quan Yan
Seng Zeng
Qi-Wen Fan
Hao Zhang
Ming-hao Zhu
Bing Guo
Wei-Ping Liu
Nuclear Science and TechniquesVol.35, No.11Article number 208Published in print Nov 2024Available online 27 Oct 2024
18604

The 12C+12C fusion is one of the most important reactions in modern nuclear astrophysics. The trend and magnitude of the reaction rate within the Gamow window strongly influence various astrophysical processes. However, direct measurement of this reaction is extremely difficult, which makes it necessary to develop indirect methods. In this study, the 23Na + p reaction system was used to study the compound nucleus 24Mg. We employed a thick-target inverse kinematics method combined with the γ-charged-particle coincidence technique to measure the proton and α exit channels of 24Mg. Technical details of the 23Na + p thick-target inverse kinematics experiment and analysis are presented herein.

Nuclear astrophysics12C+12CThick-target inverse kinematics methodγ-charged particle coincidence
1

Introduction

12C+12C fusion reactions play a crucial role in various stellar burning scenarios [1-3], particularly during the final stages of massive star evolution, Type Ia supernovae events [4, 5], and superbursts [6, 7]. Hence, many direct measurements, primarily employing charged particles [8-10] and gamma ray spectroscopy [11-13], have been conducted to study nuclear astrophysical reaction rates [14]. Because the Coulomb barrier height for the 12C+12C system, at approximately 7.5 MeV, is significantly higher than the Gamow window energy (Ec.m. = 1.5 ± 0.3 MeV), the cross-section decreases rapidly to below one nanobarn in the energy region of interest. This makes it extremely difficult to measure the 12C+12C fusion reaction directly within the Gamow energy region. A series of direct measurement data [15, 9, 13, 12] suggests the existence of sub-barrier resonances in the 12C+12C fusion reaction, leading to an increase in the S-factor as the energy decreases below 2.5 MeV in the frame of the center of mass. Therefore, simple low-energy extrapolation based on high-energy data cannot accurately describe the reaction cross-section within the Gamow energy region.

The 12C+12C fusion reaction rate is mainly contributed by 12C(12C, p)23Na, 12C(12C, α)20Ne, and 12C(12C, n)23Mg. The contribution of the neutron emission channel is marginal because of its negative Q value [16]. In 2018, the Trojan horse method (THM) was employed to measure the S factor of the 12C+12C fusion reaction at Ec.m. < 2.7 MeV [17]. To date, this is the only measurement that has entered the Gamow window. The astrophysical S* factor derived from the experiment is much larger than the values of the compilation [18] and various phenomenological and microscopic models [19], such as wave-packet dynamics (TDWP) [20], and coupled channel calculations, such as CC-M3Y+Rep [21, 22]. By contrast, Jiang et al. [23] proposed a hindrance model [24, 25] that showed the opposite trend in the energy region of interest. Despite extensive experimental and theoretical efforts, the exact behavior of the 12C+12C fusion reaction remains unclear on the existence of resonances or not, particularly in the Gamow window.

Thick-target inverse kinematics (TTIK) is a novel experimental method that has been widely used in radioactive ion beam measurements [26, 27] over the last two decades. In the TTIK measurement, the excitation function is obtained in a one-shot experiment with a single-beam energy. Despite the simplicity of its experimental setup, it has been proven by many measurements [28-35] that a satisfactory resolution of the excitation function can be obtained owing to the inverse kinematics enhancement.

Proton resonance scattering induced by radioactive secondary beams has been investigated [36] with the TTIK method at CIAE since 2005. A series of measurements were conducted for 12C+p, 13N+p, 17F+p, and 22Na+p using stable and radioactive ion beams [37-42]. In this study, we extend the conventional TTIK method to complex exit channels for the first time using γ-charged particle coincidence spectroscopy and demonstrate its applicability to simultaneously extracting the excitation functions of different reaction channels.

2

Experiment Setup

The experiment was performed in the HI-13 tandem accelerator laboratory [43-47] at the China Institute of Atomic Energy (CIAE) in Beijing. Figure 1 illustrates the experimental setup for the 23Na+p thick-target experiments. A beam of 110 MeV 23Na9+ ions, with a current of approximately 0.2 enA, was directed onto a (CH2)n target with a thickness of 5.8 mg/cm2, resulting in an energy loss of approximately 66 MeV. Finally, the 23Na ions were fully stopped in a 15.7 mg/cm2-thick carbon target. Because a high-energy Na beam can easily undergo fusion-evaporation reactions with the carbon atoms in the target, a thick carbon target was used to measure the background.

Fig. 1
Experimental setup
pic

A silicon telescope system was placed at 0° along the beamline to measure the protons and α particles emitted from the compound nucleus 24Mg. The silicon telescope system consisted of a 70 μm double-sided silicon strip detector (DSSD), a 1.5 mm multi-guard silicon quadrant (MSQ), and a 1 mm MSQ. The DSSD has 16 strips on each side, dividing the entire Si surface into 256 pixels. The small detection unit of the DSSD provided high-precision angular resolution during the kinematic reconstruction of the charged particles. The charged particles of interest originating from the 23Na+p reaction primarily deposited energy in the first MSQ, and the signals from the second MSQ were used as anti-coincidence signals to reduce the background of high-energy protons and α particles. The wall of the target chamber was made of organic plastic to minimize absorption of the emitted γ rays. Six 3-inch lanthanum bromide detectors were uniformly arranged around the target chamber and placed on sliding rails to allow movement along the vertical beam direction to measure the characteristic γ rays from the residual nuclei 23Na and 20Ne.

3

γ-particle coincidence technique

3.1
LaBr3 detector array calibration

A three-component γ source of 60Co, 137Cs, and 241Am was used to calibrate the LaBr3 array. The Geant4 package [48] was also applied to simulate the efficiency curves of the LaBr3 detectors. The simulation of γ-ray energy spectrum of 60Co was compared with the measured data, as shown in Fig. 2. Using this set of simulation parameters, the efficiency of γ detectors at different energies was obtained. The efficiency curves of the LaBr3 detectors were fitted using Eq. (1) [49], considering several points in the simulation, as shown in Fig. 3. The systematic error in the simulation process was approximately 3%. lnη(E)=i=0nai[lnE]i, (1) For the residual nuclei 23Na and 20Ne, the full-energy peak efficiencies at the characteristic energies of 440 and 1634 keV were 28.2% and 12.6%, respectively.

Fig. 2
(Color online) Geant4 simulation for 60Co γ source
pic
Fig. 3
Efficiency curve of the LaBr3 array. The black points are the full-energy peak efficiency of the LaBr3 array for γ rays of different energies obtained from Geant4 simulations. The red line represents the fitting result
pic
3.2
γ-charged particle coincidence

The γ background originates mainly from the fusion-evaporation reaction of the high-energy 23Na beam with a carbon target nucleus. For the exit channel p1 of the compound nucleus, its residual nucleus 23Na emits 440 keV characteristic γ rays, that is, corresponding to the first excited state of 23Na. Because of the large number of γ-high-energy proton accidental coincidence events, it is difficult to quantitatively analyze the p1 exit channel based on purely γ-charged particle coincidence. The black and red lines shown in Fig. 4 represent the γ energy spectra associated with the proton emissions. After subtracting the C-induced background and correcting for a γ efficiency of 440 keV, the absolute counts of the p1 channel were obtained.

Fig. 4
(Color online) γ ray single energy spectrum measured with the LaBr3 detector array in coincidence with protons. The γ spectrum obtained with (CH2)n-target and carbon-target are presented as black and red lines, respectively. The purple line is the net count spectrum obtained by subtracting the carbon background spectrum after beam normalization
pic
4

Two-body kinematics reconstruction

The energy spectrum of charged particles obtained by a silicon detector is a mixture of a series of excitation function effects. Because γ-charged-particle coincidence introduces a large number of interfering events originating from the carbon-induced background, it is necessary to subtract these effects from the energy spectrum. In the energy range of the measurement, the exit channels of the compound 24Mg consist of p0, p1, α0, and α1. Taking the p0 exit channel as an example, the detailed processing steps for the two-body kinematic reconstruction are outlined below.

Step 1: Extract the energy spectrum of the proton exit channels from the total proton energy spectrum obtained by the silicon detectors after particle identification and energy calibration. The energy spectrum of the p1 exit channel can be obtained from the charged particle spectrum of the silicon detector via γ1-proton coincidence. After subtracting the p1 energy spectrum corrected by γ efficiency from the total proton energy spectrum, the energy spectrum of p0 can be obtained. At this stage, both the p0 and p1 exit-channel energy spectra contain C-induced backgrounds. Therefore, the proton energy spectrum obtained from the carbon target must be analyzed in a similar manner.

Step 2: Perform an event-by-event two-body kinematic reconstruction based on where the reaction 23Na(p,pγ1)23Na occurs within the thick target and calculate the relationship between Ec.m. and the energy deposited in the silicon detectors. Through energy-loss calculations and reaction kinematics, the energy deposition in the silicon detectors ESi of protons is attributed to Ec.m. of the 23Na(p,pγ1)23Na reaction. As shown in Fig. 5, the red and black dots represent the correspondence between ESi and Ec.m. for the 23Na(p,pγ1)23Na reaction on the (CH2)n and carbon target, respectively.

Fig. 5
(Color online) Relationship between Ec.m. and the deposited energy in silicon for the p1 exit channel
pic

The correspondence between ESi and Ec.m. can be fitted using the least-squares method with a linear function, as expressed in Eq. (2). As shown in Fig. 5, the red and black dots approximately follow straight lines. Ec.m.(x)=ESi(x)k+b, (2)

Fig. 6
(Color online) Relationship between the bin target thickness and center-of-mass energy
pic

Step 3: Subtract the background events from the energy spectrum in the frame of the center of mass. Corrections for the beam particle and 12C atom numbers are required for the carbon-induced background. The (CH2)n and carbon targets have different energy stopping powers for 23Na. The correction factor fn for the 12C atom numbers is the ratio of the number of C atoms corresponding to 1 keV of energy deposited in the (CH2)n target and the carbon target for the same energy of the 23Na beam. This relationship was calculated using LISE++ and fitted to a linear function (Fig. 6). dmc/dEc.m.=Ec.m.kc+bc, (3) dm(CH2)n/dEc.m.=Ec.m.k(CH2)n+b(CH2)n, (4) fn=Ec.m.k(CH2)n+b(CH2)nEc.m.kc+bc (5) The number of 12C atoms corresponding to each bin of the carbon target and the (CH2)n target energy spectra is given by Eq. (3) and Eq. (4). The correction factor fn is given by Eq. (5). Subsequently, the carbon background can be subtracted from the energy spectrum of p0. As shown in Fig. 7, the black line represents the energy spectrum of the (CH2)n target and the red line represents the energy spectrum of the carbon target. The net energy spectrum of the 1H(23Na,p)23Na channel can be obtained by subtracting the normalized carbon background.

Fig. 7
(Color online) Yields from 1H(23Na, p0)23Na elastic scattering channel. The background from the pure carbon target is flat without any resonance structure
pic

Step 4: Calculate the excitation function of 1H(23Na,p)23Na, based on the net yield of p0 exit channel. Because each bin in the p0 energy spectrum corresponds to different H atom numbers of the (CH2)n target, the differential cross-section needs to be calculated separately for each energy point. The excitation functions of the proton and α channels are shown in Fig. 8 and Fig. 9, respectively, according to Eq. (6). dσ/dΩ=NcountNHNIΩ (6) where NH and NI represent the numbers of H atoms in the target and incident 23Na9+ beam ions, respectively. Ω denotes the solid angle of the Si detector.

Fig. 8
(Color online) Excitation function for the proton exit channels. p0 and p1 represent 1H(23Na, p0)23Na and 1H(23Na, p1)23Na440*, respectively
pic
Fig. 9
(Color online) Excitation function for the α exit channels. α0 and α1 represent 1H(23Na, α0)20Ne and 1H(23Na, α1)20Ne1634*, respectively
pic

Throughout the data analysis process, each step resulted in an error that was ultimately contained in the individual data points of the excitation function. These errors mainly include γ-charged-particle coincidence, statistical, carbon background deduction, and p1(α1) deduction errors in the p0(α0) calculations. For γ-particle coincidence, the coincidence efficiency mainly depends on the γ detection efficiency, silicon efficiency, and accidental coincidence events. The errors of these factors were independent. The γ detection efficiency error evaluated through the Geant4 simulation process was less than 3%, whereas the silicon detection efficiency error was negligible. Accidental coincidence events were uniformly distributed in the coincidence time spectrum and were evaluated as having an error of less than 2%. Before the carbon background deduction, the energy spectrum must be divided into individual bins, with statistical errors assigned to each bin. For energy points with low counts, the statistical error was relatively large, close to 2%. The error after carbon background deduction depends on statistical errors and errors introduced during the subtraction process. During carbon background deduction, the ratio of carbon background counts to total counts positively correlated with the error introduced by the subtraction process. As shown in Fig. 7, for the p0 channel, the error after carbon background subtraction at 3.8 MeV was 5%. By comparison, for most energy points with lower background contributions, the error after background subtraction was approximately 3.5%. For the p0(α0) channel, similar errors caused by data processing were introduced when subtracting the p1(α1) channel. The γ-efficiency error must be considered separately when calculating the final error in the p1(α1) channel. Overall, the two subtraction processes were the main sources of excitation function errors. The total errors for p1 and α1 were less than 8% and 10%, respectively. p0 and α0 errors were correspondingly larger, that is, less than 10% and 17% over the entire energy range.

The R-matrix theory [50, 51] is a parametric framework that describes compound nuclear reactions and theoretically describes the resonance phenomena in nuclear reactions. For excitation functions that include resonance states, R-matrix analysis can decompose the differential cross section into three overlapping components: hard-sphere scattering background, independent resonances, and interference of multiple resonances. This study provided the exit-channel excitation functions of the compound nucleus 24Mg populated by the 23Na+p entrance channel. The Azure package was used to extract a series of exit channel resonance parameters related to the 12C+12C fusion reaction. The fitting results are indicated by the red lines in Fig. 8 and Fig. 9. The fitting results indicate that nearly 50 24Mg resonances are included to reproduce the excitation functions, not only the 0+ and 2+ resonance levels relevant to the 12C+12C fusion reaction, but also other levels such as 1- and 3-. The 24Mg resonances observed in the 23Na+p entrance channel are very complex and discrete, but densely packed in the energy region of 12C+12C Gamow window. However, the resonance parameters of the proton and α decay channels are useful for the further study of the 12C+12C fusion reaction. The detailed results of the R-matrix analysis and its impact on the 12C+12C astrophysical S factor will be presented in a forthcoming paper.

5

Summary

The thick-target inverse kinematics method is widely used to measure the excitation functions of p(α) elastic and inelastic scattering induced by radioactive ion beams. In this study, the conventional TTIK method was extended to include complex reaction channels for the first time, which enables the simultaneous extraction of the excitation functions of different reaction channels. The high energy resolution and high detection efficiency γ-charged particle coincidence are essential for promoting this novel method for radioactive ion beam-induced reactions. Although the 24Mg resonances observed in this study were useful, they were largely beyond the relevance of the 12C+12C fusion reaction. A similar measurement utilizing 20Ne+α can be performed to significantly reduce 24Mg resonances in the excitation functions.

References
1. S.E. Woosley, A. Heger, and T.A. Weaver,

The evolution and explosion of massive stars

. Rev. Mod. Phys. 74, 1015 (2002). https://doi.org/10.1103/RevModPhys.74.1015
Baidu ScholarGoogle Scholar
2. A. Cumming and L. Bildsten,

Carbon flashes in the heavy-element ocean on accreting neutron stars

. Astrophys. J. 559, L127-L130 (2001). https://doi.org/10.1086/323937
Baidu ScholarGoogle Scholar
3. X.D. Tang and L.H. Ru,

The 12C +12C fusion reaction at stellar energies

. EPJ Web Conf. 260, 10 (2022). https://doi.org/10.1051/epjconf/202226001002
Baidu ScholarGoogle Scholar
4. K. Mori, M.A. Famiano, T. Kajino,

Impacts of the new carbon fusion cross-sections on type Ia supernovae

. MNRAS: Letters 482, L70-L74 (2019). https://doi.org/10.1093/mnrasl/sly188
Baidu ScholarGoogle Scholar
5. Z.H. Li, G.X. Li, H.K. Wang et al.,

Supernovae and their scientific secrets

. Nucl. Tech. (in Chinese) 46, 195-200 (2023). https://doi.org/10.11889/j.0253-3219.2023.hjs.46.080021
Baidu ScholarGoogle Scholar
6. B.B. Back, H. Esbensen and C.L. Jiang et al.,

Recent developments in heavy ion fusion reactions

. Rev. Mod. Phys. 86, 317-360 (2014). https://doi.org/10.1103/RevModPhys.86.317
Baidu ScholarGoogle Scholar
7. T.E. Strohmayer and E.F. Brown,

A remarkable 3 hour thermonuclear burst from 4u 1820-30

. Astrophys. J. 566, 1045-1059 (2002). https://doi.org/10.1086/338337
Baidu ScholarGoogle Scholar
8. J.R. Patterson, H. Winkler, C.S. Zaidins et al.,

Experimental investigation of the stellar nuclear reaction 12C +12C at low energies

. Astrophys. J. 157, 367 (1969). https://doi.org/10.1086/150073
Baidu ScholarGoogle Scholar
9. H.W. Becker, K.U. Kettner, C. Rolfs et al.,

The 12C +12C reaction at sub-coulomb energies (II)

. Z. Phys. A 303, 305-312 (1981). https://doi.org/10.1007/BF01421528
Baidu ScholarGoogle Scholar
10. J. Zickefoose, A.D. Leva, F. Strieder et al.,

Measurement of the 12C(12C, p)23Na cross section near the Gamow energy

. Phys. Rev. C 97, 065806 (2018). https://doi.org/10.1103/PhysRevC.97.065806
Baidu ScholarGoogle Scholar
11. E.F. Aguilera, P. Rosales, E. Martinez-Quiroz et al.,

New γ-ray measurements for 12C +12C sub-coulomb fusion: Toward data unification

. Phys. Rev. C 73, 064601 (2006). https://doi.org/10.1103/PhysRevC.73.064601
Baidu ScholarGoogle Scholar
12. T. Spillane, F. Raiola, C. Rolfs et al.,

12C +12C fusion reactions near the Gamow energy

. Phys. Rev. Lett. 98, 122501 (2007). https://doi.org/10.1103/PhysRevLett.98.122501
Baidu ScholarGoogle Scholar
13. L. Barrón-Palos, E.F. Aguilera, and J. Aspiazu et al.,

Absolute cross sections measurement for the 12C +12C system at astrophysically relevant energies

. Nucl. Phys. A 779, 318 (2006). https://doi.org/10.1016/j.nuclphysa.2006.09.004
Baidu ScholarGoogle Scholar
14. Z.L. Shen, J.J. He,

Study of primordial deuterium abundance in Big Bang nucleosynthesis

. Nucl. Sci. Tech. 35, 63 (2024). https://doi.org/10.1007/s41365-024-01423-3
Baidu ScholarGoogle Scholar
15. M.D. High and B. Cujec,

The 12C +12C sub-coulomb fusion cross section

. Nucl. Phys. A 282, 181-188 (1977). https://doi.org/10.1016/0375-9474(77)90179-8
Baidu ScholarGoogle Scholar
16. B. Bucher, X.D. Tang and X. Fang et al.,

First direct measurement of 12C(12C, n)23Mg at stellar energies

. Phys. Rev. Lett. 114, 251102 (2015). https://doi.org/10.1103/PhysRevLett.114.251102
Baidu ScholarGoogle Scholar
17. A. Tumino, C. Spitaleri, M. L. Cognata et al.,

An increase in the 12C +12C fusion rate from resonances at astrophysical energies

. Nature 557, 687-690 (2018). https://doi.org/10.1038/s41586-018-0149-4
Baidu ScholarGoogle Scholar
18. G.R. Caughlan and W.A. Fowler,

Thermonuclear Reaction Rates V.

. Atom. Data Nucl. Data. 40, 1 (1988). https://doi.org/10.1016/0092-640X(88)90009-5
Baidu ScholarGoogle Scholar
19. N.T. Zhang, X.Y. Wang and D. Tudor et al.,

Constraining the 12C +12C astrophysical S-factors with the 12C +13C measurements at very low energies

. Phys. Lett. B 801, 135170 (2020). https://doi.org/10.1016/j.physletb.2019.135170
Baidu ScholarGoogle Scholar
20. A. Diaz-Torres and M. Wiescher,

Characterizing the astrophysical s factor for 12C +12C fusion with wave-packet dynamics

. Phys. Rev. C 97, 055802 (2018). https://doi.org/10.1103/PhysRevC.97.055802
Baidu ScholarGoogle Scholar
21. M. Assuncao and P. Descouvemont,

Role of the hoyle state in 12C +12C fusion

. Phys. Lett. B 723, 355-359 (2013). https://doi.org/10.1016/j.physletb.2013.05.030
Baidu ScholarGoogle Scholar
22. H. Esbensen, X. Tang and C.L. Jiang,

Effects of mutual excitations in the fusion of carbon isotopes

. Phys. Rev. C 84, 064613 (2011). https://doi.org/10.1103/PhysRevC.84.064613
Baidu ScholarGoogle Scholar
23. C.L. Jiang, D. Santiago-Gonzalez, S. Almaraz-Calderon et al.,

Reaction rate for carbon burning in massive stars

. Phys. Rev. C 97, 012801 (2018). https://doi.org/10.1103/PhysRevC.97.012801
Baidu ScholarGoogle Scholar
24. C.L. Jiang, K.E. Rehm and R.V.F. Janssens et al.,

Influence of Nuclear Structure on Sub-Barrier Hindrance in Ni+Ni Fusion

. Phys. Rev. Lett. 93, 012701 (2004). https://doi.org/10.1103/PhysRevLett.93.012701
Baidu ScholarGoogle Scholar
25. C.L. Jiang, B.B. Back, K.E. Rehm et al.,

Heavy-ion fusion reactions at extreme sub-barrier energies

. Eur. Phys. J. A 57, 235 (2021). https://doi.org/10.1140/epja/s10050-021-00536-2
Baidu ScholarGoogle Scholar
26. A. Galindo-Uribarri, J. Gomez del Campo, J.R. Beene et al.,

Study of resonant reactions with radioactive ion beams

. Nucl. Instrum. Meth. B 172, 647-654 (2000). https://doi.org/10.1016/S0168-583X(00)00220-2
Baidu ScholarGoogle Scholar
27. Shigeru Kubono,

Experimental determination of astrophysical reaction rates with radioactive nuclear beams

. Nucl. Phys. A 693, 221-248 (2001). https://doi.org/10.1016/S0375-9474(01)01140-X
Baidu ScholarGoogle Scholar
28. J.J. He, S. Kubono, T. Teranishi et al.,

Investigation of structure in 23Al via resonant proton scattering of 22Mg + p and the 22Mg(p, γ)23Al astrophysical reaction rate

. Phys. Rev. C 76, 055802 (2007). https://doi.org/10.1103/PhysRevC.76.055802
Baidu ScholarGoogle Scholar
29. J.J. He, P.J. Woods, T. Davinson et al.,

Measurement of the inelastic branch of the 14O(α, p)17F reaction: Implications for explosive burning in novae and x-ray bursters

. Phys. Rev. C 80, 042801(R) (2009). https://doi.org/10.1103/PhysRevC.80.042801
Baidu ScholarGoogle Scholar
30. J.J. He, S. Kubono, T. Teranishi et al.,

Investigation of excited states in 22Mg via resonant elastic scattering of 21Na + p and its astrophysical implicationss

. Phys. Rev. C 80, 015801 (2009). https://doi.org/10.1103/PhysRevC.80.015801
Baidu ScholarGoogle Scholar
31. J.J. He, L.Y. Zhang, A. Parikh et al.,

The 18Ne(α, p)21Na breakout reaction in x-ray bursts: Experimental determination of spin-parities for α resonances in 22Mg via resonant elastic scattering of 21Na+p

. Phys. Rev. C 88, 012801(R) (2013). https://doi.org/10.1103/PhysRevC.88.012801
Baidu ScholarGoogle Scholar
32. Y.B. Wang, B.X. Wang, X. Qin et al.,

13N + p elastic resonance scattering via a thick-target method

. Phys. Rev. C 77, 044304 (2008). https://doi.org/10.1103/PhysRevC.77.044304
Baidu ScholarGoogle Scholar
33. T. Teranishi, S. Kubono, S. Shimoura et al.,

Study of resonance states in 12N using a radioactive ion beam of 11C

. Phys. Lett. B 556, 27-32 (2003). https://doi.org/10.1016/S0370-2693(03)00098-4
Baidu ScholarGoogle Scholar
34. C. Ruiz, T. Davinson, F. Sarazin et al.,

Multichannel R-matrix analysis of elastic and inelastic resonances in the 21Na + p compound system

. Phys. Rev. C 71, 025802 (2005). https://doi.org/10.1103/PhysRevC.71.025802
Baidu ScholarGoogle Scholar
35. G.V. Rogachev, P. Boutachkov, A. Aprahamian et al.,

Analog States of 7He Observed via the 6He(p, n) Reaction

. Phys. Rev. Lett. 92, 232502 (2004). https://doi.org/10.1103/PhysRevLett.92.232502
Baidu ScholarGoogle Scholar
36. Y.B. Wang, B.X. Wang, X.X. Bai et al.,

A Setup for Resonance Scattering Reactions with Thick Target

. HEP NP 30(Suppl. II), 202 (2006).
Baidu ScholarGoogle Scholar
37. X. Qin, Y.B. Wang, X.X. Bai et al.,

Levels in 13N examined by 12C + p elastic resonance scattering with thick target

. Chin. Phys. C 32, 957 (2008). https://doi.org/10.1088/1674-1137/32/12/004
Baidu ScholarGoogle Scholar
38. Y.B. Wang, X. Qin, B.X. Wang et al.,

Simulation and analysis of 13N+p elastic resonance scattering

. Chin. Phys. C 33, 181 (2009). https://doi.org/10.1088/1674-1137/33/3/004
Baidu ScholarGoogle Scholar
39. S.J. Jin, Y.B. Wang, B.X. Wang et al.,

Excited states in 18Ne studied via 17F+p

. Chin. Phys. Lett. 27, 032102 (2010). https://doi.org/10.1088/0256-307X/27/3/032102
Baidu ScholarGoogle Scholar
40. X. Liu, Y.B. Wang, Z.H. Li et al.,

Angular distribution of 6He+p elastic scattering

. Chin. Phys. C 36, 716 (2012). https://doi.org/10.1088/1674-1137/36/8/006
Baidu ScholarGoogle Scholar
41. S.J. Jin, Y.B. Wang, J. Su et al.,

Resonant scattering of 22Na+p studied by the thick-target inverse-kinematic method

. Phys. Rev. C 88, 035801 (2013). https://doi.org/10.1103/PhysRevC.88.035801
Baidu ScholarGoogle Scholar
42. Y.J. Chen, L.Y. Zhang,

Examining the fluorine overabundance problem by conducting Jinping deep underground experiment

. Nucl. Tech. (in Chinese) 46, 110501 (2023). https://doi.org/10.11889/j.0253-3219.2023.hjs.46.110501
Baidu ScholarGoogle Scholar
43. J.X. Yu,

The IAE Peking HI-13 tandem accelerator

. Nucl. Instr. and Meth. 184, 157-159 (1981). https://doi.org/10.1016/0029-554X(81)90862-4
Baidu ScholarGoogle Scholar
44. Y.M. Tian, J.X. Yu and Z.Y. liu et al.,

Progress report on the HI-13 tandem accelerator

. Nucl. Instrum. Meth. A 244, 39-47 (1986). https://doi.org/10.1016/0168-9002(86)90734-5
Baidu ScholarGoogle Scholar
45. J.Y.H. Li, Y.J. Li, Z.H. Li et al.,

Nuclear astrophysics research based on HI-13 tandem accelerator

. Nucl. Tech. (in Chinese) 46, 30-42 (2023). https://doi.org/10.11889/j.0253-3219.2023.hjs.46.080002
Baidu ScholarGoogle Scholar
46. W.P. Liu,

Review of the development of tandem accelerator laboratory in 35 years

. Nucl. Tech. (in Chinese) 46, 201-206 (2023). https://doi.org/10.11889/j.0253-3219.2023.hjs.46.080022
Baidu ScholarGoogle Scholar
47. K.N. Li, C.X. Kan, X.F. Wang et al.,

Practice and innovation in the operation and maintenance of HI-13 tandem accelerator for 35 years

. Nucl. Tech. (in Chinese) 46, 63-69 (2023). https://doi.org/10.11889/j.0253-3219.2023.hjs.46.080005
Baidu ScholarGoogle Scholar
48. S. Agostinelli, J. Allison and K. Amako et al.,

Geant4–a simulation toolkit

. Nucl. Instrum. Meth. B 506, 250-303 (2003). https://doi.org/10.1016/S0168-9002(03)01368-8
Baidu ScholarGoogle Scholar
49. Z. Kis, B. Fazekas and J. Ostör et al.,

Comparison of efficiency functions for Ge gamma-ray detectors in a wide energy range

. Nucl. Instrum. Meth. A 418, 374-386 (1998). https://doi.org/10.1016/S0168-9002(98)00778-5
Baidu ScholarGoogle Scholar
50. A.M. Lane and R.G. Thomas,

R-matrix theory of nuclear reactions

. Rev. Mod. Phys. 30, 257-353 (1958). https://doi.org/10.1103/RevModPhys.30.257
Baidu ScholarGoogle Scholar
51. P. Descouvemont and D. Baye,

R-matrix theory of nuclear reactions

. Rep. Prog. Phys. 73, 036301 (2010). https://doi.org/10.1088/0034-4885/73/3/036301
Baidu ScholarGoogle Scholar
Footnote

Wei-Ping Liu is an editorial board member/editor-in-chief for Nuclear Science and Techniques and was not involved in the editorial review, or the decision to publish this article. All authors declare that there are no competing interests.