AIMC Topic: Nickel

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Machine learning-based fabrication of phytogenic NiO nanoparticles for anticancer activity in HepG2 Cell Culture.

Journal of materials science. Materials in medicine
Metal oxide nanomaterials play a central role in biomedical applications due to their unique physicochemical properties. In particular, various treatment methods such as drug delivery, hyperthermia therapy, radiation, and chemotherapy are used for th...

Post ferric-substitution detection method optimization for Ni(II)-organic complexes measurement: Simulation, experimentation, and modeling.

Environmental monitoring and assessment
Nickel (Ni(II)) complexes, especially those formed with strong ligands such as ethylenediaminetetraacetic acid (EDTA), are difficult to quantify due to their low environmental concentrations and weak ultraviolet (UV) absorbance. These characteristics...

ANN-assisted comprehensive screening of silica gel-alunite composite sorbent system for efficient adsorption of toxic nickel ions: Batch and continuous mode water treatment applications.

Chemosphere
Through batch and fixed-bed column operations, nickel ions were extracted from a contaminated aqueous media by adsorption onto silica gel-immobilized alunite (Sg@Aln). A three-layer backward-propagating network with an ideal pattern of 5-10-1 and 4-1...

Liquid-Metal-Based Multichannel Strain Sensor for Sign Language Gesture Classification Using Machine Learning.

ACS applied materials & interfaces
Liquid metals are highly conductive like metallic materials and have excellent deformability due to their liquid state, making them rather promising for flexible and stretchable wearable sensors. However, patterning liquid metals on soft substrates h...

Quantification of L-lactic acid in human plasma samples using Ni-based electrodes and machine learning approach.

Talanta
This work presents a robust strategy for quantifying overlapping electrochemical signatures originating from complex mixtures and real human plasma samples using nickel-based electrochemical sensors and machine learning (ML). This strategy enables th...

An artificial intelligence handheld sensor for direct reading of nickel ion and ethylenediaminetetraacetic acid in food samples using ratiometric fluorescence cellulose paper microfluidic chip.

International journal of biological macromolecules
User-friendly in-field sensing protocol is crucial for the effective tracing of intended analytes under less-developed countries or resources-limited environments. Nevertheless, existing sensing strategies require professional technicians and expensi...

Tensile strength analysis of additively manufactured CM 247LC alloy specimen by employing machine learning classifiers.

PloS one
Using a cutting-edge net-shape manufacturing technique called Additive Layer Manufacturing (ALM), highly complex components that are not achievable with conventional wrought and cast methods can be produced. As a result, the aerospace sector is payin...

Combination of headspace single-drop microextraction (HS-SDME) with a nickel-embedded paper-based analytical device for cyanide quantification.

Analytica chimica acta
BACKGROUND: Cyanide anion can be found in foodstuffs, tobacco smoke and a variety of types of waters, mainly originating from anthropogenic activities. Due to its highly toxic nature, several agencies have established limits for cyanide levels in wat...

Light-driven microrobots: capture and transport of bacteria and microparticles in a fluid medium.

Journal of materials chemistry. B
The design of simple microrobotic systems with capabilities to address various applications like cargo transportation, as well as biological sample capture and manipulation in an individual unit, provides a novel route for designing advanced multifun...

Machine Learning Yield Prediction from NiCOlit, a Small-Size Literature Data Set of Nickel Catalyzed C-O Couplings.

Journal of the American Chemical Society
Synthetic yield prediction using machine learning is intensively studied. Previous work has focused on two categories of data sets: high-throughput experimentation data, as an ideal case study, and data sets extracted from proprietary databases, whic...