Bond Valence Parameters for Sn(II)―X and Sn(IV)―X (X=O, S, N, C, P, As, Se, Te, F, Cl, Br, I)

胡盛志,; 谢兆雄,; Palenik, Gus J.

doi:10.3866/pku.whxb20122819

Cited by 12 publications

(5 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Here, the EEG/behavioral data of intensity discrimination in the EEG evaluation task (Task2) and the data of position discrimination in the tactile discrimination task (Task1) were both used for correlation analyses. Consistent with the results of our previous work [27], the accuracies of discriminating stimulated intensities were linearly correlated with contralateral alpha ERD, and the correlation coefficient r was larger for the phantom finger area (r = 0.88) than that for the upper arm (r = 0.76), as shown in figure 8(a). As for the linear fitting between the accuracies of discriminating stimulated positions and contralateral alpha ERD, the correlation coefficient r was larger for the upper arm (r = 0.83) when compared with the phantom finger area (r = 0.65), as shown in figure 8(b).…”

Section: Correlations Between Alpha Erd/ers and Discrimination Perfor...supporting

confidence: 91%

“…It was suggested that there was no significant difference in attention engagement to different stimulated positions during tactile discrimination, which might further excluded the influence of attention on the difference of discrimination performance between the two interface areas. What's more, the results of linear regression were consistent with our previous work [27], in which linear correlations were found between contralateral somatosensory alpha ERD and discrimination performance. The proposed alpha ERD could be used as a biomarker for the evaluation of sensory acuity.…”

Section: Comparison Between Somatotopic and Non-somatotopic Interfacessupporting

confidence: 91%

“…1: 62 channel, 2: 45 Hz, [−3.5 −0.5] s for baseline and [0.5 3.5] s for task state. Based on the result of our previous work [27], the alpha band was involved in the evoked brain response during tactile discrimination. So, R 2 values were averaged within the alpha band (8-13 Hz) and along the 3 s epochs.…”

Section: Discussionmentioning

confidence: 98%

“…ERSP task and ERSP baseline were calculated by averaging the ERSP values within the period of task state and baseline, respectively. Channels of FC3, C5, C3, C1 and CP3 on the left hemisphere, channels of FC4, C6, C4, C2 and CP4 on the right hemisphere were selected for the calculation of ERD/ERS [27]. Alpha ERD/ERS was obtained by averaging the normalized ERSP values in the alpha band (8-13 Hz) over corresponding channels.…”

Section: Discussionmentioning

confidence: 99%

See 3 more Smart Citations

Towards optimizing the non-invasive sensory feedback interfaces in a neural prosthetic control

Su¹,

Chai²,

Meng³

et al. 2022

J. Neural Eng.

View full text Add to dashboard Cite

Objective. The somatotopic interface (SI) and non-somatotopic interface (NI) are commonly used to provide non-invasive sensory feedback. Nevertheless, differences between SI and NI are rarely reported, and objective evaluations of the corresponding brain response are missing as well. Few studies have reported how to design the stimulation encoding based on the two interfaces. The objective of this study was to investigate the difference in sensory characteristics between SI and NI, and propose an optimal encoding method for non-invasive feedback interfaces. Approach. We recruited seven amputees and compared the tactile sensitivity to stimulated positions and intensities between SI (phantom finger area) and NI (upper arm) in a tactile discrimination task. Electroencephalography (EEG) evaluation task was subsequently conducted to objectively evaluate the stimulus-evoked brain response. Finally, the two kinds of tactile information (stimulated position and intensity) was applied to an object recognition task. Specifically, the object size was reflected by the prosthetic finger position through stimulated position encoding, and the object stiffness was reflected by the contact force of prosthetic fingers through stimulated intensity encoding. We compared the performance under four feedback conditions (combinations between two kinds of tactile information and two interfaces). Results. Behavioral results showed that NI was more sensitive to position information while SI was more sensitive to intensity information. EEG results were consistent with behavioral results, showing a higher sensitivity of sensory alpha ERD for NI in the position discrimination, while the trend was opposite in the intensity discrimination. The feedback encoding allowed amputees to discriminate the size and stiffness of nine objects with the best performance of 62% overall accuracy (84% for size discrimination, 71% for stiffness discrimination) when position and intensity information was delivered on the NI and SI, respectively. Signicance. Our results provided an instructive strategy for sensory feedback via non-invasive solutions.

show abstract

Section: Correlations Between Alpha Erd/ers and Discrimination Perfor...supporting

confidence: 91%

Section: Comparison Between Somatotopic and Non-somatotopic Interfacessupporting

confidence: 91%

Section: Discussionmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

Towards optimizing the non-invasive sensory feedback interfaces in a neural prosthetic control

Su¹,

Chai²,

Meng³

et al. 2022

J. Neural Eng.

View full text Add to dashboard Cite

show abstract

“…The topological analysis and charge transfer between the PS and the dye molecule is determined by atomic dipole corrected Hirshfeld charges using Multiwfn [13,14] . The topological parameters are calculated using the method proposed by Bader [15] from the bond critical points between the PS and the dye molecules and tabulated in the Table 4.…”

Section: Discussionmentioning

confidence: 99%

Adsorption studies of dye molecule on two-dimensional assembly of porphyrin using density functional theory

Suresh,

Rajaramakrishna,

Vijayakumar

2023

Mater. Chem. Phys.

View full text Add to dashboard Cite

<p>Highly toxic dye molecules can be found in trace amounts in the treated effluent from several industrial wastes. A challenging research area of this decade is the dye treatment and adsorption from the effluents of these industries using low-cost alternative adsorbents. Recent studies have demonstrated the effectiveness of metal oxides and porous materials in the adsorption of dye, so we have taken into consideration an organic porous material made with metal free porphyrin. The adsorption of dye molecules on the surface of the porphyrin sheet is investigated. Porphyrin is an organic substance with several special properties. Density functional theory (DFT) is used to investigate the adsorption of charged and neutral dye, as well as complex heavy metal dye, on the surface of porphyrin sheets. Positive dye has a higher affinity for the adsorbent than negative dye, according to the data on adsorption; however, complex dye has a higher adsorption energy than the other dyes, which is consistent with the cohesive energy of the PS-dye complex. In the present work the adsorbing capacity of PS for different dye molecules is demonstrated by the topological analysis and DFT calculations on the electronic structure.</p>

show abstract

Atomic and Electronic Structures of the Interfaces between Perovskite La_0.75Sr_0.25MnO₃ and Brownmillerite SrCoO_2.₅

Xing

Zhu

et al. 2022

Physica Status Solidi (b)

View full text Add to dashboard Cite

Epitaxial thin films composed of perovskite and brownmillerite oxides have received increasing attention because of the novel phenomena found in these systems. Herein, the atomic and electronic structures of the La0.75Sr0.25MnO3/SrCoO2.5 interface have been studied using first‐principles calculations. From the perspective of polarity compensation, three types of possible interface models are constructed, which have different interface terminations or orientation relationship. In the model where the [100] direction of SrCoO2.5 is parallel to the interface, the interface is polar. The way to compensate polarity is atomic reconstruction. For the model with the [100] direction of SrCoO2.5 perpendicular to the interface, there are two possible interface terminations. One is nonpolar. The other is polar, but its polarity can be compensated by electronic redistribution, i.e., the valence change of Mn from +3 to +4 at the interface, as consistently revealed by the change of the bond valence sums and magnetic moments of Mn ions. For this model with electronic redistribution, accompanied by the valence change, the MnO6 octahedra near the interface have the largest distortion compared with the other two models. The density of states around Fermi level and the magnetic coupling across the interface are also discussed.

show abstract

Bond Valence Parameters for Sn(II)―X and Sn(IV)―X (X=O, S, N, C, P, As, Se, Te, F, Cl, Br, I)

Cited by 12 publications

References 0 publications

Towards optimizing the non-invasive sensory feedback interfaces in a neural prosthetic control

Towards optimizing the non-invasive sensory feedback interfaces in a neural prosthetic control

Adsorption studies of dye molecule on two-dimensional assembly of porphyrin using density functional theory

Atomic and Electronic Structures of the Interfaces between Perovskite La_0.75Sr_0.25MnO₃ and Brownmillerite SrCoO_2.₅

Contact Info

Product

Resources

About

Bond Valence Parameters for Sn(II)―X and Sn(IV)―X (X=O, S, N, C, P, As, Se, Te, F, Cl, Br, I)

Cited by 12 publications

References 0 publications

Towards optimizing the non-invasive sensory feedback interfaces in a neural prosthetic control

Towards optimizing the non-invasive sensory feedback interfaces in a neural prosthetic control

Adsorption studies of dye molecule on two-dimensional assembly of porphyrin using density functional theory

Atomic and Electronic Structures of the Interfaces between Perovskite La0.75Sr0.25MnO3 and Brownmillerite SrCoO2.5

Contact Info

Product

Resources

About

Atomic and Electronic Structures of the Interfaces between Perovskite La_0.75Sr_0.25MnO₃ and Brownmillerite SrCoO_2.₅