Tin monosulfide (SnS) is an emerging thin-film absorber material for photovoltaics. An outstanding challenge is to improve carrier lifetimes to >1 ns, which should enable >10% device efficiencies. However, reported results to date have only demonstrated lifetimes at or below 100 ps. In this study, we employ defect modeling to identify the sulfur vacancy and defects from Fe, Co, and Mo as most recombination-active. We attempt to minimize these defects in crystalline samples through high-purity, sulfur-rich growth and experimentally improve lifetimes to >3 ns, thus achieving our 1 ns goal. This framework may prove effective for unlocking the lifetime potential in other emerging thin-film materials by rapidly identifying and mitigating lifetime-limiting point defects.

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Dynamic Laser Stimulation (DLS) techniques proved to be very efficient in soft defect localization bringing a lot of information about the device internal behavior. We need to use external parameter measurements such as frequency, delay, voltage etc to perform these techniques. So they can't be used to study internal signal propagation problems in latched device since signals are resynchronized. We will show that we can use the power analysis coupled with DLS techniques set up to characterize soft defect when we don't have a direct access to monitored signal propagation such as in some transistor transition issues. Laser stimulation in addition of power analysis is used to decrypt security codes in security chip, but in failure analysis it is a new way to reach internal information in order to localize soft defects.

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Laser Stimulation techniques are continuously developed in accordance with the apparition of new kind of defect. We propose the Full Dynamic La-ser Stimulation where the test is fully embedded in the localization process. By using a modulated laser instead of a continuous one we discriminate vectors fail in ad-dition to localization.