Structure and properties of alkali aluminosilicate glasses and melts: Insights from deep learning

硅酸铝 组态熵 拉曼光谱 热力学 粘度 玻璃化转变 材料科学 折射率 矿物学 铝硅酸钠 化学 光学 物理 复合材料 生物化学 催化作用 光电子学 聚合物
作者
Charles Le Losq,Anne Valentine,Bjørn O. Mysen,Daniel R. Neuville
出处
期刊:Geochimica et Cosmochimica Acta [Elsevier BV]
卷期号:314: 27-54 被引量:23
标识
DOI:10.1016/j.gca.2021.08.023
摘要

Aluminosilicate glasses and melts are of paramount importance for geo- and materials sciences. They include most magmas, and are used to produce a wide variety of everyday materials, from windows to smartphone displays. Despite this importance, no general model exists with which to predict the atomic structure, thermodynamic and viscous properties of aluminosilicate melts. To address this, we introduce a deep learning framework, ‘i-Melt’, which combines a deep artificial neural network with thermodynamic equations. It is trained to predict 18 different latent and observed properties of melts and glasses in the K2O-Na2O-Al2O3-SiO2 system, including configurational entropy, viscosity, optical refractive index, density, and Raman signals. Viscosity can be predicted in the 100–1015 log10 Pa·s range using five different theoretical frameworks (Adam-Gibbs, Free Volume, MYEGA, VFT, Avramov-Milchev), with a precision equal to, or better than, 0.4 log10 Pa·s on unseen data. Density and optical refractive index (through the Sellmeier equation) can be predicted with errors equal or lower than 0.02 and 0.006, respectively. Raman spectra for K2O-Na2O-Al2O3-SiO2 glasses are also predicted, with a relatively high mean error of ∼25% due to the limited data set available for training. Latent variables can also be predicted with good precisions. For example, the glass transition temperature, Tg, can be predicted to within 19 K, while the melt configurational entropy at the glass transition, Sconf(Tg), can be predicted to within 0.8 J mol−1 K−1. Applied to rhyolite compositions, i-Melt shows that the rheological threshold separating explosive and effusive eruptions correlates with an increase in the fraction of non-bridging oxygens in rhyolite melts as their alkali/Al ratio becomes larger than 1. Exploring further the effect of the K/(K + Na) ratio on the properties of alkali aluminosilicate melts with compositions varying along a simplified alkali magmatic series trend, we observe that K-rich melts have systematically different structures and higher viscosities compared to Na-rich melts. Combined with the effects of the K/(K + Na) ratio on other parameters, such as the solubility, solution mechanisms and speciation of volatile elements, this could ultimately influence the eruptive dynamics of volcanic systems emitting Na-rich or K-rich alkali magmas.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
1秒前
yhtu完成签到,获得积分10
1秒前
sunyt完成签到,获得积分10
2秒前
小笼包完成签到 ,获得积分10
5秒前
6秒前
tdtk发布了新的文献求助10
6秒前
聪明藏今完成签到,获得积分10
6秒前
7秒前
打打应助罗晓倩采纳,获得10
7秒前
8秒前
8秒前
泯珉发布了新的文献求助10
10秒前
允许一切发生完成签到,获得积分10
11秒前
13秒前
13秒前
qwt00发布了新的文献求助10
13秒前
今后应助科研通管家采纳,获得10
14秒前
酷波er应助科研通管家采纳,获得10
14秒前
852应助科研通管家采纳,获得10
14秒前
14秒前
14秒前
14秒前
Theprisoners应助科研通管家采纳,获得20
14秒前
yar应助科研通管家采纳,获得10
14秒前
Jasper应助琳琳琳琳565采纳,获得10
14秒前
泯珉完成签到,获得积分10
15秒前
vigour完成签到 ,获得积分10
16秒前
帅气的璎发布了新的文献求助10
19秒前
饱满以松完成签到 ,获得积分10
20秒前
田田田田完成签到,获得积分10
21秒前
qwt00完成签到,获得积分10
22秒前
不想做实验完成签到,获得积分10
22秒前
23秒前
Elvira完成签到,获得积分10
25秒前
怕孤独的如凡完成签到 ,获得积分10
25秒前
爆米花应助鲜于灵竹采纳,获得10
26秒前
李爱国应助帅气的璎采纳,获得10
27秒前
Zx完成签到 ,获得积分10
28秒前
29秒前
高分求助中
The Mother of All Tableaux: Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 3000
A new approach to the extrapolation of accelerated life test data 1000
Problems of point-blast theory 400
北师大毕业论文 基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 390
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
Robot-supported joining of reinforcement textiles with one-sided sewing heads 320
The Cambridge Handbook of Social Theory 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3999444
求助须知:如何正确求助?哪些是违规求助? 3538780
关于积分的说明 11275184
捐赠科研通 3277604
什么是DOI,文献DOI怎么找? 1807633
邀请新用户注册赠送积分活动 883977
科研通“疑难数据库(出版商)”最低求助积分说明 810111