Abstract
Chiral nanostructured materials have emerged to be an influential class of high-performance materials used in areas ranging from enantioselective sensing, separation, and catalysis to optoelectronics. The materials are highly sophisticated and involve chiral metal-organic frameworks, covalent organic frameworks, carbon dots, and quantum dots etc. Owing to properties such as enantioselectivity, reproducibility, and catalytic properties, facilitating their incorporation into multifunctional systems these materials offer remarkable enantiomeic separations, environmental monitoring, and sustainable energy. In the past few years, various synthetic strategies such as chiral ligands, templating techniques, and environmentally friendly synthetic methods have been investigated to achieve improved chiral materials. Great advances have been achieved in chromatographic performance and scalability toward chiral membranes, composite materials, and MOFs- and COFs-based stationary phases. Furthermore, multi-mode platforms combining fluorescence, magnetism, and other recognition approaches show vast potential for label-free real-time enantiomeric detection. Here, we review the interdisciplinary advancement in the area of nanostructured chiral materials focusing on synthetic strategies, characterization, and enantiorecognition performance of common chiral organic compounds and drugs.
Abbreviations
- L-His-ZIF-67
-
l-Histidine-Zeolitic imidazolate framework-67
- 1D
-
One-dimensional
- 3D
-
Three-dimensional
- AFM
-
Atomic force microscopy
- aMOF
-
Amorphous metal-organic framework
- AuNPs
-
Gold nanoparticles
- BSA
-
Bovine serum albumin
- BuMA
-
Butyl methacrylate
- CC
-
Carboxylated cellulose
- CCDs
-
Chiral carbon dots
- CCOFs
-
Covalent organic frameworks
- CCTF
-
Chiral covalent triazine framework
- C-CuBDC
-
Chiral copper-based MOF
- CD-MOF
-
Cyclodextrin-based metal–organic framework
- CDMPC
-
Cellulose-tris(3,5-dimethylphenylcarbamate
- CMOFs
-
Chiral metal-organic frameworks
- CQDs
-
Chiral quantum dots
- CSPs
-
Chiral stationary phases
- CT
-
Charge transfer
- CTAB
-
Cetyltrimethylammonium bromide
- CTA-PES
-
Cellulose triacetate-polyethersulfone
- CuLBH
-
[Cu(L-mal)(Bipy)]·H2O
- Cu-TA
-
Cu-tartaric acid
- DES
-
Hydrophilic deep eutectic solvent
- d-Ile
-
d-isoleucine
- DMF
-
Dimethylformamide
- EDA-β-CD
-
Ethylenediamine-β-cyclodextrin
- EDMA
-
Ethylene dimethacrylate
- ee
-
Enantiomeric excess
- Fe3O4@CuZnAl-LDH@MIL-100(Fe)
-
Magnetic layered double hydroxide/metal-organic framework
- Gln
-
Glutamine
- GO
-
Graphene oxide
- GOx
-
Glucose oxidase
- HPLC
-
High-performance liquid chromatography
- HP-MDs
-
Hydroxypropyl-Maltodextrins
- HP-MOFs
-
Hierarchical Porous Mofs
- IP
-
Interfacial Polymerization
- IPA
-
Isopropanol
- l-Cys
-
l-Cysteine
- l-Ile
-
l-Isoleucine
- l-Phe
-
l-Phenylalanine
- l-Tyr-COF
-
l-Tyrosine Functionalized COF
- MDs
-
Maltodextrins
- MONs
-
Microporous Organic Network
- nano-LC
-
Nano-Liquid Chromatography
- N-CD
-
Nitrogen-Doped Carbon Dot
- PATP
-
P-Mercaptoaniline
- PCS
-
Polyphenol Colloidal Spheres
- PCTM
-
Polycarbonate Track-Etched Membranes
- PDA
-
Polydopamine
- PE
-
1-Phenylethanol
- Phe
-
Phenylalanine
- PL
-
Photoluminescence
- PSf
-
Polysulfone
- QCM
-
Quartz Crystal Microbalance
- rGO-FSWCNT
-
Reduced Graphene Oxide-Functionalized Single-Walled Carbon Nanotube
- RSDs
-
Relative Standard Deviations
- SERS
-
Surface-Enhanced Raman Scattering
- S-NE
-
S-1-(1-Naphthyl) Ethanol
- TEM
-
Transmission Electron Microscopy
- TNT
-
Titanate Nanotubes
- TPB
-
1,3,5-Tris(4-Aminophenyl)Benzene
- Trp
-
Tryptophan
- UV–vis
-
Ultraviolet–Visible
- XRD
-
X-ray Diffraction
-
Research ethics: Not applicable.
-
Informed consent: Not applicable.
-
Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission. Vinod: Conceptualization, Supervision, Methodology, Formal analysis, Writing – Original Draft, Review & Editing. Shubham Sharma: Formal analysis, Data Interpretation. Akash Kumar Mishra: Writing – Original Draft. Neeraj Kumar Mishra: Data Acquisition, Writing – Original Draft, Formal analysis. Bhaskar Vallamkonda: Data Acquisition, Writing – Original Draft. Shubham Sharma: Formal analysis, Data Interpretation.
-
Use of Large Language Models, AI and Machine Learning Tools: None to declare.
-
Conflict of interest: Nothing to declare.
-
Research funding: Not applicable.
-
Data availability: No new data is generated.
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