scholarly journals The role of Sb in solar cell material Cu2ZnSnS4

2017 ◽  
Vol 5 (14) ◽  
pp. 6606-6612 ◽  
Author(s):  
Xiaoli Zhang ◽  
Miaomiao Han ◽  
Zhi Zeng ◽  
Yuhua Duan
Keyword(s):  
Solar Cells ◽  
Solar Cell ◽  
First Principles ◽  
Point Of View ◽  
Efficiency Improvement ◽  
First Principles Calculations ◽  
Cell Material ◽  
Related Defect ◽  
Solar Cell Material

In this study, based on first-principles calculations we report a possible mechanism of efficiency improvement of Sb-doped Cu2ZnSnS4 (CZTS) solar cells from the Sb-related defect point of view.

Prediction of Solar Cell Materials via Unsupervised Literature Learning

2021 ◽  
Author(s):  
Lei Zhang ◽  
Mu He
Keyword(s):  
Solar Cells ◽  
Solar Cell ◽  
Language Processing ◽  
Perovskite Solar Cells ◽  
Dye Sensitized Solar Cells ◽  
Cell Types ◽  
Data Driven ◽  
Cell Material ◽  
Textual Data ◽  
Solar Cell Material

Abstract Despite the significant advancement of the data-driven studies for physical science, the textual data that are numerous in the literature are not fully embraced by the physics and materials community. In this manuscript, we successfully employ the natural language processing (NLP) technique to unsupervisedly predict the existence of solar cell types including the dye-sensitized solar cells and the perovskite solar cells based on literatures published prior to their first discovery without human annotation. Enlightened by this, we further identify possible solar cell material candidates via NLP starting with a comprehensive training database of 3.2 million paper abstracts published before 2021. The NLP model effectively predicts the existing solar cell materials, while an uncommon solar cell material namely PtSe2 is suggested as an appropriate candidate for the future solar cells. Its optoelectronic properties are comprehensive investigated via first-principles calculations to reveal the decent stability and optoelectronic performance of the NLP-predicted candidate. This study demonstrates the viability of the textual data for the data-driven materials prediction and highlights the NLP method as a powerful tool to reliably predict the solar cell materials.

scholarly journals An Assessment Framework for Solar Cell Material Based on a Modified Fuzzy DEMATEL Approach

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5708
Author(s):  
Chia-Chi Sun ◽  
Shih-Chi Chang
Keyword(s):  
Decision Making ◽  
Solar Cells ◽  
Solar Cell ◽  
Evaluation System ◽  
Assessment Framework ◽  
Fuzzy Dematel ◽  
Cell Material ◽  
Casual Relationship ◽  
Solar Cell Material

We propose an evaluation system to choose appropriate materials for solar cells. A fuzzy DEMATEL information procedure was used for decision-making to gather information and analyze the casual relationship. These data acquired were partitioned into causal and impact bunches, empowering users to gather an improved understanding of the intelligent relationship among them, as well as making recommendations for changes to upgrade their general execution. The proposed approach can deliver a compelling fabric choice assessment with satisfactory criteria that fit the respondent’s discernment designs; particularly, these evaluation dimensions are interlaced. Recommendations are given to assist government authorities to plan a Taiwan solar cell industry approach and for industries to develop commerce techniques for improvement in the solar cell field.

Computational mining of Janus Sc2C-based MXenes for spintronic, photocatalytic, and solar cell applications

2021 ◽  
Author(s):  
Yinggan Zhang ◽  
Baisheng Sa ◽  
Naihua Miao ◽  
Jian Zhou ◽  
Zhimei Sun
Keyword(s):  
Solar Cells ◽  
Solar Cell ◽  
First Principles ◽  
Near Infrared ◽  
First Principles Calculations

A novel class of Janus MXene Sc2CTT′ (T, T′ = H, O, OH, F, Cl) for spintronic materials, near-infrared-driven photocatalysts, and heterostructure solar cells have been investigated by first-principles calculations.

Approach using the electrical structure and optical properties of aluminium-doped zinc oxide for solar cells

RSC Advances ◽  
2016 ◽  
Vol 6 (112) ◽  
pp. 110943-110950 ◽  
Author(s):  
Yanfang Zhao ◽  
Zhixiang Liu ◽  
Haiying Yang ◽  
Tianbo Li ◽  
Ping Yang
Keyword(s):  
Zinc Oxide ◽  
Optical Properties ◽  
Solar Cells ◽  
Solar Cell ◽  
Electrical Structure ◽  
Cell Material ◽  
Solar Cell Material

Aluminium-doped zinc oxide (AZO) is attracting a continuously increasing amount of attention because of its potential as a solar cell material.

An effective and efficient approach to p-type AlN by Be2:O codoping from first-principles calculations

2016 ◽  
Vol 30 (20) ◽  
pp. 1650257
Author(s):  
Meng Zhao ◽  
Wenjun Wang ◽  
Jun Wang ◽  
Junwei Yang ◽  
Weijie Hu ◽  
...  
Keyword(s):  
First Principles ◽  
Ionization Energy ◽  
Hole Concentration ◽  
Valence Band Maximum ◽  
First Principles Calculations ◽  
Mutual Compensation ◽  
Efficient Approach ◽  
P Type ◽  
Codoping Method

Various Be:O-codoped AlN crystals have been investigated via first-principles calculations to evaluate the role of the different combinations in effectively and efficiently inducing p-type carriers. It is found that the O atom is favored to bond with two Be atoms. The formed Be2:O complexes decrease the acceptor ionization energy to 0.11 eV, which is 0.16 eV lower than that of an isolated Be in AlN, implying that the hole concentration could probably be increased by 2–3 orders of magnitude. The electronic structure of Be2:O-codoped AlN shows that the lower ionization energy can be attributed to the interaction between Be and O. The Be–O complexes, despite failing to induce p-type carriers for the mutual compensation of Be and O, introduce new occupied states on the valence-band maximum (VBM) and hence the energy needed for the transition of electrons to the acceptor level is reduced. Thus, the Be2:O codoping method is expected to be an effective and efficient approach to realizing p-type AlN.

Computational and Experimental Insights into the Role of Acidic Molecules on the Corrosion Behavior on 7A46 Aluminum Alloy

2021 ◽  
Vol 21 (4) ◽  
pp. 2221-2233
Author(s):  
Yaru Liu ◽  
Qinglin Pan ◽  
Xiangdong Wang ◽  
Ye Ji ◽  
Qicheng Liu ◽  
...  
Keyword(s):  
Corrosion Resistance ◽  
Aluminum Alloy ◽  
Corrosion Behavior ◽  
First Principles ◽  
First Principles Calculations ◽  
Corrosive Media ◽  
Corrosion Depth ◽  
Corrosion Mechanisms ◽  
Nanoscale Level

The corrosion mechanisms for different corrosive media on the aged 7A46 aluminum alloy were systematically investigated at nanoscale level. The combination of empirical intergranular and exfoliation corrosion behavior was employed, and coupled with first-principles calculations. Results revealed that the dispersed distribution of matrix precipitates (MPs) leads to the enhancement of the corrosion resistance pre-ageing (PA) followed by double-ageing (PA-DA) alloy. The deepest corrosion depth of PA-DA alloy was in hydrochloric acid, and the calculation result demonstrates that the passivation effect in combination with the accumulation of corrosion products in nitric acid protect the PA-DA alloy from further corrosion.

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