Nonradiative recombination centers (NRCs) are known to negatively affect the efficiency of light-emitting diodes (LEDs). NRCs contribute not only to Shockley–Read–Hall (SRH) recombination, but also to trap-assisted Auger recombination (TAAR). The relationship between NRCs and the TAAR processes has been predicted theoretically and observed experimentally to a limited degree. However, some details about TAAR are still under debate, including its magnitude relative to intrinsic Auger and SRH recombination, its dependence on carrier density (e.g., ∝n2 or ∝n3), and its role in the green gap, particularly in high-quality commercial-grade LEDs. TAAR is typically assumed to be linearly dependent on trap density, directly tying the magnitude of TAAR to the quality of the sample. Previous studies have examined TAAR using time-resolved photoluminescence and optical differential lifetime measurements, which do not capture certain effects related to electrical injection. In this work, we report a quantitative study of TAAR in c-plane commercial-grade green LEDs grown by metal-organic chemical vapor deposition (MOCVD). We investigate a series of three wafers with identical active regions (3X, 3-nm-thick quantum wells) but different NRC trap densities (4.4e14 cm-3 < Nt < 1.5e15 cm-3). We use small-signal electroluminescence (SSEL) and deep-level optical spectroscopy (DLOS) to study the carrier dynamics and density of NRCs in the samples, respectively. SSEL is used to determine the carrier lifetime, which is used in conjunction with the internal quantum efficiency (IQE) to decouple the radiative and nonradiative recombination rates. The total recombination lifetime in higher quality growth is found to be longer than that in lower quality growth and is attributed to the longer nonradiative recombination time in higher quality samples. On the other hand, the radiative recombination rates for different growth qualities at a given carrier density (n) are identical, as expected from samples with the same active region design. We extract the relationship between the density of NRCs and the corresponding nonradiative recombination rates at a given carrier density (n). The difference in nonradiative recombination between the samples offers information about both SRH and TAAR with respect to growth quality. The linear dependence between the SRH recombination rate and the density of NRCs at low n was confirmed. However, TAAR was found to be sublinear with the density of NRCs, possibly due to the relatively small changes (~3X) in defect density (Nt) in these samples. We find that TAAR is best fit to an n2 dependence on carrier density. This is supported by the observation that all three samples have similar IQE at high carrier density, which would not be consistent with an n3 process. We also show that the TAAR recombination coefficients (D) are on the order of ~1e13 cm3 s-1, which is similar to that reported for violet LEDs and shows the weak dependence of TAAR on bandgap. Using the extracted TAAR coefficients, we calculate that TAAR accounts for about 10% of the total nonradiative recombination rate at moderate carrier densities. Thus, intrinsic Auger dominates the nonradiative recombination and TAAR is not a major contributor to the green gap in these commercial LEDs. SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525.

Trap-Assisted Auger Recombination in Commercial Green InGaN/GaN LEDs

Developing Preliminary Clinical Taxonomy and Treatment Fidelity Tool: Stuttering Treatment

<a href="https://docs.google.com/document/d/1yGl1Yp9Z87g-Cddk6hicfgUS7GXsWTEP/edit#heading=h.gjdgxs">**CHAT REFERENCE CHART**</a>




Let's CHAT: Supervising Students, CFs and SLPAs With a Visual Hierarchy

Working with School-Age Children who Stutter: Evaluation, Therapy, Empowerment, Connection, and Inclusion

Creating a Linguistically and Culturally-Responsive Children’s Book about Stuttering: Methodological Considerations

This talk investigates the intersection of emotion, communication, and social change in the artistic work and biography of Karima 2G, a cross-cultural identity voicing social exclusion, discrimination, and inequality in contemporary Italy. A second-generation migrant whose language is “feelingfully harnessed” in the task of questioning a white-only view of Italianness. 
From a methodological point of view, the focus is primarily the social and discursive construction of emotion in Karima’s songs and the pragmatic meaning of this ‘emotion talk’. We will not, however, be evaluating Karima’s artistic output; instead, we will use and collect Karima’s biographical data so that her songs make sense within her personal life story. Our investigation relies on an “anthropology of the person” that focuses on the subject rather than on socio/anthropological categories, classes, and ethnicities.

Emotion, communication and social change in Italian second-generation migrants: Karima 2G

Due to information processing constraints and cognitive limitations, humans must form limited representations of complex decision making tasks. However, the mechanisms by which humans generate representations of task-relevant stimulus remain unclear. We develop a model that seeks to account for the formation of these representations using a β-variational autoencoder (β-VAE) trained with a novel utility based learning objective. The proposed model forms latent representations of decision making tasks that are constrained in their information complexity. We show through simulation that this approach can account for important phenomena in human economic decision making tasks. This model provides a method of forming task-relevant representations that can be used to make decisions in a human-like manner.

Modeling Capacity-Limited Decision Making Using a Variational Autoencoder

Adults have been shown to favor stable causal relationships – those that hold robustly across background contexts – in their actions and causal/explanatory generalizations (Vasilyeva et al, 2018). Here we explore how this preference develops. We present results from one study with 141 4-7-year-olds investigating whether children pay attention to causal stability when they explain observations and design interventions in novel contexts. We report developmental shifts in reliance on causal stability in a range of inferential tasks, highlight the important role of perceived average causal strength in determining children’s causal preferences, and discuss the implications of our findings for theories of early causal learning. To our knowledge, this is the first study exploring the role of stability in children’s causal reasoning.

“It Depends”: How Children Reason about Stable and Unstable Causes

Perceptual training leads to improvements in a wide range of simple visual tasks. However, it is still unclear how effective it can be for more difficult visual tasks in real-world domains such as radiology. Is it possible to train people to the level of experts? If so, what method is best, and how much training is necessary? Over four training sessions, we trained medically naive participants to identify the degree of fatty liver tissue present in ultrasound images. We found that both COMPARISON and SINGLE-CASE perceptual training techniques resulted in significant post-training improvement, but that the SINGLE-CASE training was more effective. Whilst people showed rapid learning with less than one hour of training, they did not improve to the level of experts, and additional training sessions did not provide significant benefits beyond the initial session. This suggests that perceptual training could usefully augment, but not replace, the traditional rule-based training that medical students currently receive.

How effective is perceptual training? Evaluating two perceptual training methods on a difficult visual categorisation task

Bayesian experimental design (BED) is a methodology to identify designs that are expected to yield informative data. Recent work in cognitive science considered BED for cognitive models with tractable and known likelihood functions. However, as cognitive models have become more complex and richer, their likelihood functions are often intractable. In this work, we leverage recent advances in BED for intractable models and demonstrate their application on a set of multi-armed bandit tasks. We further propose a generalized latent state model that unifies two previously proposed models. Our experiments show that data gathered using optimal designs results in improved model discrimination and parameter estimation, as compared to naive designs. Furthermore, we find that increasing the number of bandit arms increases the expected information gain in experiments.

Bayesian Experimental Design for Intractable Models of Cognition

Many studies have demonstrated that testing students on to-be-learned materials can be an effective learning activity. However, past studies have also shown that some practice test formats are more effective than others. Open-ended recall or short answer practice tests may be effective because the questions prompt deeper processing as students must generate an answer. With closed-ended testing formats such as multiple-choice or true-false tests, there are concerns that they may prompt only superficial processing, and that any benefits will not extend to non-practiced information or over time. They also may not be effective for improving comprehension from text as measured by how-and-why questions. The present study explored the utility of practice tests with closed-ended questions to improve learning from text. Results showed closed-ended practice testing can lead to benefits even when the learning outcome was comprehension of text.

Can Closed-ended Practice Tests Promote Understanding from Text?

There are many ways to go wrong when evaluating new information, e.g. by putting unwarranted trust in non-experts, or failing to scrutinize information about threats. We examined how effective people were at evaluating information about the COVID-19 pandemic. Early in the course of the pandemic, we recruited 1791 participants from six countries with varying levels of pandemic severity, and asked them to evaluate true and false pandemic-related statements (assertions and prescriptions) sampled from the media. We experimentally manipulated the source of each statement (a doctor, a political/religious leader, social media, etc.). Overall, people proved to be epistemically vigilant: they distinguished between true and false statements, especially prescriptions, and they trusted doctors more than other sources. These effects were moderated by feeling threatened by the pandemic, and by strong identification with some sources (political/religious leaders). These findings provide optimism in the fight against misinformation, while highlighting challenges posed by politics and ideology.

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Trap-Assisted Auger Recombination in Commercial Green InGaN/GaN LEDs

Developing Preliminary Clinical Taxonomy and Treatment Fidelity Tool: Stuttering Treatment

Let's CHAT: Supervising Students, CFs and SLPAs With a Visual Hierarchy

Working with School-Age Children who Stutter: Evaluation, Therapy, Empowerment, Connection, and Inclusion

Creating a Linguistically and Culturally-Responsive Children’s Book about Stuttering: Methodological Considerations

Emotion, communication and social change in Italian second-generation migrants: Karima 2G

Modeling Capacity-Limited Decision Making Using a Variational Autoencoder

“It Depends”: How Children Reason about Stable and Unstable Causes

How effective is perceptual training? Evaluating two perceptual training methods on a difficult visual categorisation task

Bayesian Experimental Design for Intractable Models of Cognition

Can Closed-ended Practice Tests Promote Understanding from Text?

Evaluating Information and Misinformation during the COVID-19 Pandemic: Evidence for Epistemic Vigilance

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