分光计                        
                
                                
                        
                            仪表(计算机编程)                        
                
                                
                        
                            计算机科学                        
                
                                
                        
                            杠杆(统计)                        
                
                                
                        
                            光学                        
                
                                
                        
                            纳米技术                        
                
                                
                        
                            材料科学                        
                
                                
                        
                            物理                        
                
                                
                        
                            人工智能                        
                
                                
                        
                            操作系统                        
                
                        
                    
            作者
            
                Ryan Bogucki,Mary Greggila,Paul Mallory,Jiansheng Feng,Kelly Siman,Banafsheh Khakipoor,Hunter King,Adam W. Smith            
         
                    
        
    
            
            标识
            
                                    DOI:10.1021/acs.jchemed.8b00870
                                    
                                
                                 
         
        
                
            摘要
            
            Low cost, open-source analytical instrumentation has the potential to increase educational outcomes for students and enable large-scale citizen science projects. Many of these instruments rely on smartphones to collect the data, mainly because they can effectively leverage a dramatic price-to-performance ratio of the optical sensors. However, several hurdles need to be overcome for these devices to be more widely adapted. In this communication we focus on visible spectrophotometers, which are common in chemistry laboratories because of the day-to-day need for quantifying concentration. To make smartphone-based spectrometers practical for wider use, we have designed a 3D-printable spectrophotometer with a dual-beam optical geometry. This geometry allows for sample and reference data to be collected on the same photograph and thus improves the signal-to-noise ratio and reproducibility of the spectra. A universal mounting system was also developed to allow for a wide variety of smartphone form factors to be coupled to the spectrophotometer. To demonstrate potential applications of this device, two assays are reported. The first is a simple illustration of the Beer–Lambert Law with common household dyes. The second is a colorimetric nitrate assay, which shows a quantitative relationship between absorption and nitrate concentration. Kinetic data are also shown for the nitrate assay, which illustrate the long time-stability of the spectral data acquired from the device.
         
            
 
                 
                
                    
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