This article provides an in-depth analysis of the X-ray detectors used in Non-Destructive Testing (NDT), starting from the simplest technologies such as radiographic films and scintillators, up to the most innovative systems including solid-state detectors, perovskite sensors, and photon counting detectors.
The physics underlying their operation is explored, followed by an overview of applications in industrial, medical, aerospace, security, and cultural heritage fields.
Significant attention is devoted to emerging technologies such as superconducting nanowire detectors (SNSPDs), free electron lasers (XFELs), and artificial intelligence for automated analysis.
The article concludes with reflections on the technical challenges and future prospects of X-ray detectors in improving precision, reliability, and automation in NDT.

L’articolo fornisce un’analisi approfondita dei detettori a raggi X impiegati nei controlli non distruttivi (CND), partendo dalle tecnologie più semplici, come le pellicole radiografiche e i scintillatori, fino ai sistemi più innovativi, tra cui i rivelatori a stato solido, i sensori a perovskiti e i photon counting detectors.
Viene esplorata la fisica alla base del funzionamento, seguita da una panoramica delle applicazioni in ambito industriale, medico, aerospaziale, sicurezza e beni culturali.
Ampio spazio è dedicato alle tecnologie emergenti, come i detettori a nanofili superconduttori (SNSPDs), i laser a elettroni liberi (XFELs) e l’intelligenza artificiale per l’analisi automatizzata.
L’articolo si conclude con una riflessione sulle sfide tecniche e le prospettive future dei detettori X nel migliorare la precisione, l’affidabilità e l’automazione nei CND.

The manufacturing industry is integrating Artificial Intelligence (AI) into Additive Manufacturing (AM) to optimize product design and quality. AI enhances design by identifying optimal geometries for AM and optimizes process parameters in real-time, reducing defects and improving repeatability. Additionally, when combined with computed tomography (CT), AI automates product inspection, detecting internal and external defects that are not visible with traditional methods. This approach increases efficiency, reduces production times and wasted materials, and opens new possibilities for design innovation, promising a revolution in the manufacturing sector.