Indomethacin Embedded into MIL-101 Frameworks: A Solid-State NMR Study

异核分子 金属有机骨架 四氢呋喃 对苯二甲酸 分子 同核分子 固态核磁共振 氢键 化学 溶剂 材料科学 结晶学 有机化学 聚酯纤维 核磁共振 吸附 物理
作者
Tomaž Čendak,Emanuela Žunkovič,Tina Ukmar,Matjaž Mazaj,Nataša Zabukovec Logar,Gregor Mali
出处
期刊:Journal of Physical Chemistry C [American Chemical Society]
卷期号:118 (12): 6140-6150 被引量:28
标识
DOI:10.1021/jp412566p
摘要

Interactions of drug molecules embedded within the pores of drug-delivery matrices significantly influence the drug-release rate and profile. In this Article, we used solid-state NMR experiments to inspect the interactions of indomethacin drug and tetrahydrofuran solvent molecules within mesoporous MIL-101 metal–organic framework materials. MIL-101 matrices were prepared using two types of linkers, terephthalic acid for MIL-101(Cr) and MIL-101(Fe), and amino-terephthalic acid for MIL-101(Al)-NH2 and MIL-101(Fe)-NH2. Loading MIL-101 matrices with indomethacin proved to be very efficient; the obtained delivery systems accommodated from 0.9 to 1.1 g of indomethacin per 1 g of MIL-101 material. NMR measurements showed that regardless of the type of the framework metal centers or the type of the organic linker indomethacin did not attach to the metal–organic framework. Interactions between indomethacin molecules themselves were also not detected. On the contrary, the smaller tetrahydrofuran solvent molecules did attach to the framework metallic trimeric units with hydrogen bonds. The bonds and the geometry of the porous system prevented the tetrahydrofuran molecules to be expelled from the MIL-101 matrix during drying. Information on interactions and proximities among neighboring nuclei was obtained by 1H homonuclear correlation and 1H–13C heteronuclear correlation NMR measurements. Distance-dependent influence of paramagnetic chromium and iron centers was also exploited.

科研通智能强力驱动
Strongly Powered by AbleSci AI
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
一一完成签到,获得积分10
刚刚
薛禾完成签到,获得积分10
2秒前
LuheZhong发布了新的文献求助10
3秒前
3秒前
李爱国应助dong采纳,获得10
6秒前
7秒前
上官小怡发布了新的文献求助10
7秒前
星辰大海应助科研通管家采纳,获得10
7秒前
Ava应助科研通管家采纳,获得10
7秒前
田様应助科研通管家采纳,获得10
7秒前
科研通AI2S应助科研通管家采纳,获得10
7秒前
酷波er应助科研通管家采纳,获得10
7秒前
Lucas应助科研通管家采纳,获得10
7秒前
情怀应助科研通管家采纳,获得10
7秒前
7秒前
冷静完成签到,获得积分10
8秒前
8秒前
molihuakai应助科研通管家采纳,获得10
8秒前
Owen应助科研通管家采纳,获得10
8秒前
8秒前
superJ发布了新的文献求助10
9秒前
10秒前
Naza1119发布了新的文献求助20
10秒前
烟花应助内向的溪流采纳,获得10
11秒前
TYT发布了新的文献求助10
13秒前
CipherSage应助夜白采纳,获得20
14秒前
隐形曼青应助lxl采纳,获得10
14秒前
15秒前
16秒前
YOHO发布了新的文献求助10
16秒前
FAN关闭了FAN文献求助
17秒前
橘络完成签到 ,获得积分10
18秒前
19秒前
贪玩的秋柔应助pansy采纳,获得10
19秒前
elixir完成签到,获得积分10
19秒前
UHPC发布了新的文献求助10
20秒前
余周周完成签到,获得积分10
20秒前
漱石发布了新的文献求助10
20秒前
21秒前
xz完成签到,获得积分10
21秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1500
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
CLSI M100 Performance Standards for Antimicrobial Susceptibility Testing 36th edition 400
Cancer Targets: Novel Therapies and Emerging Research Directions (Part 1) 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6361439
求助须知:如何正确求助?哪些是违规求助? 8175188
关于积分的说明 17221423
捐赠科研通 5416250
什么是DOI,文献DOI怎么找? 2866218
邀请新用户注册赠送积分活动 1843512
关于科研通互助平台的介绍 1691443