Benhua Wang

Water-Soluble Poly(p-aryleneethynylene)s: A Sensor Array Discriminates Aromatic Carboxylic Acids

A chemical tongue consisting of 11 elements (four poly(p-aryleneethynylene)s (PAE) at pH 7 and pH 13, and seven electrostatic complexes formed from oppositely charged poly(p-aryleneethynylene)s at pH 7) discriminate 21 benzoic and phenylacetic acid derivatives in aqueous solution. The mechanism of discrimination is the fluorescence modulation of the PAEs, leading to quenching or fluorescence turn-on. The PAEs alone at both pH values and the tongue, consisting of the complexes only, discriminate the 21 acids with 92% (PAEs at pH 7), 95% (PAEs at pH 13), and 99% (complexes at pH 7) reliability after linear discriminant analysis (LDA). A sensor field with all 14 elements, according to LDA, discriminates all of the 21 acids with 100% accuracy.

Poly(aryleneethynylene) Tongue That Identifies Nonsteroidal Anti-Inflammatory Drugs in Water: A Test Case for Combating Counterfeit Drugs

We report a sensor array composed of a highly fluorescent positively charged poly(para-phenyleneethynylene) P1 and its complex C with a negatively charged pyridine-containing poly(para-aryleneethynylene) P2 (quencher) at pH 10 and pH 13; a sensor field composed of four elements, P1 (pH 10), P1 (pH 13), C (pH 10), and C (pH 13), results. The elements of this small sensor field experience either fluorescence turn on or fluorescence quenching upon exposure toward nonsteroidal anti-inflammatory drugs (NSAIDs), such as aspirin, ibuprofen, diclofenac, or naproxen. The combined responses of the sensor field are analyzed by linear discriminant analysis (LDA). All of the NSAIDs were identified and discriminated, and the sensing mechanism, hydrophobic versus electrostatic, was discussed.

Polymer/Peptide Complex-Based Sensor Array Discriminates Bacteria in Urine

A negatively charged poly(para-phenyleneethynylene) (PPE) forms electrostatic complexes with four positively charged antimicrobial peptides (AMP). The AMPs partially quench the fluorescence of the PPE and discriminate fourteen different bacteria in water and in human urine by pattern-based fluorescence recognition; the AMP-PPE complexes bind differentially to the components of bacterial surfaces. The bacterial species and strains form clusters according to staining properties (Gram-positive and Gram-negative) or genetic similarity (genus, species, and strain). The identification and data treatment is performed by pattern evaluation with linear discriminant analysis (LDA) of the collected fluorescence intensity data.

Fingerprinting antibiotics with PAE-based fluorescent sensor arrays

We outline an evolution process for tongue elements composed of poly(p-aryleneethynylene)s (PAE) and detergents, resulting in a chemical tongue (24 elements) that discerns antibiotics. Cross-breeding of this new tongue with tongue elements that consist of simple poly(p-phenyleneethynylene)s (PPE) at different pH-values leads to an enlarged sensor array, composed of 30 elements. This tongue was pruned, employing principal component analysis. We find that a filial tongue featuring three elements from each original array (i.e. a six element tongue) is superior to either of the prior tongues and the composite tongue in the discrimination of structurally different antibiotics. Such a selection process should be general and give an idea how to successfully generate powerful low-selectivity sensor elements and configure them into discriminative chemical tongues.

An Optimized Sensor Array Identifies All Natural Amino Acids

Wet-chemical discrimination of amino acids is still a challenge due to their structural similarity. Here, an optimized self-assembled eight-member sensor array is reported. The optimized sensor array stems from the combination of elements of different tongues, containing poly( para-phenyleneethynylene)s (PPE) and a supercharged green fluorescent protein (GFP) variant. The responsivity of the sensor dyes (PPEs and GFP) is enhanced in elements that contain adjuvants, such as metal salts but also cucurbit[7]uril (CB[7]) and acridine orange; a suitable and robust eight element array discriminates all of the 20 natural amino acids in water at 25 mM concentration with 100% accuracy. The results group well to the amino acid type, i.e., hydrophobic, polar, and aromatic ones.

A Simple Optoelectronic Tongue Discriminates Amino Acids

A self-assembled nine-element optoelectronic tongue consisting of a positively charged water-soluble poly(para-phenyleneethynylene) and three metal ions (Fe2+ , Co2+ , and Cu2+ ) at three different pH values (7, 10, and 13) discriminates all of the 20 natural amino acids in water. Unknown identification was not ideal. Addition of a highly positively charged green fluorescent protein in the presence of Fe2+ , Co2+ , and Cu2+ increased the unknown identification to above 86 %. Linear discriminant analysis (LDA) orders the responses according to the amino acid type, that is, hydrophobic, polar, anionic, or cationic.