Valerie Zemba’s research while affiliated with Cold Regions Research and Engineering Laboratory and other places

Resilience is increasingly recognized as a factor that improves the functioning and performance of individuals and communities; however, it is underexamined in smaller groups or teams. We performed a comprehensive literature review to examine how resilience is defined, measured and used in small teams. Additionally, we evaluated the effectiveness of trainings or interventions on teams towards increasing unit resilience and performance. Following a literature review, 74 measures across 37 articles were assessed. Study eligibility criteria include English-language publications between 1980 and 2017 that included output from a research trial or survey on military or civilian groups pertaining to their resiliency to adverse events. Resilience of units/teams was assessed across the four phases of resilience defined by NAS: prepare, absorb, recover, adapt. Our review found that while the concept of resilience is not often studied in small groups empirically, the focus of available studies is on recovery with limited attention given to absorption and adaptation. This work reveals a potential mechanism to improve team/unit performance via unit resilience training and improved unit cohesion. Training had small but significant effects on the preparation (r = 0.03, k = 5) and recover (r = 0.05, k = 6) phases of unit resilience. In order to improve resilience in small groups, training programs and other interventions must be appropriately focused on the essential phases of resilience associated with mission execution.

While beneficial in many applications, questions remain as to whether advanced materials (AdMs) are more or less sustainable than the conventional materials that they may replace. Currently, there is no available tool to provide clarity to these questions. Traditional approaches for evaluating the sustainability of a chemical or material are usually not standardized and, as a result, the metrics used in sustainability measurements are subjective and often vary from assessor to assessor. Additionally, sustainability characterizations resulting from these approaches are typically presented qualitatively and are often vaguely drawn, making it difficult to confidently and transparently conclude that one material is more sustainable than another. This paper aims to address these gaps by enabling stakeholders involved in the production, use, or governance of AdMs to assess the sustainability of AdMs in a consistent, objective, and quantitative way using a multi‐criteria decision analysis (MCDA)‐based model. The model proposed herein adapts a triple‐bottom‐line (TBL) framework from the Institution of Chemical Engineers (IChemE) and incorporates criteria weights identified through a stakeholder values assessment conducted by surveying AdM practitioners. Results from the stakeholder values assessment show that the perceived importance of the economic component of the TBL varies the most across stakeholders, and that practitioners providing responses from the perspective of a non‐governmental environmental advocacy group or a regulator of AdMs such as the U.S. Environmental Protection Agency were more likely to score and weigh economic indicators lower and environmental indicators higher compared to when responding from a business owner perspective. The resulting MCDA‐based model allows stakeholders to assess the sustainability of an AdM or AdM‐enabled product and compare it to product alternatives, predict how other stakeholders might score a product by identifying the extent to which components of the TBL are valued by other stakeholders, and identify which subcriteria contribute most to an improvement in a product's sustainability score. This article is protected by copyright. All rights reserved.

Novel materials with unique or enhanced properties relative to conventional materials are being developed at an increasing rate. These materials are often referred to as advanced materials (AdMs) and they enable technological innovations that can benefit society. Despite their benefits, however, the unique characteristics of many AdMs, including many nanomaterials, are poorly understood and may pose environmental safety and occupational health (ESOH) risks that are not readily determined by traditional risk assessment methods. To assess these risks while keeping up with the pace of development, technology developers and risk assessors frequently employ risk‐screening methods that depend on a clear definition for the materials that are to be assessed (e.g., engineered nanomaterial) as well as a method for binning materials into categories for ESOH risk prioritization. The term advanced material lacks a consensus definition and associated categorization or grouping system for risk screening. In this study, we aim to establish a practitioner‐driven definition for AdMs and a practitioner‐validated framework for categorizing AdMs into conceptual groupings based on material characteristics. Results from multiple workshops and interviews with practitioners provide consistent differentiation between AdMs and conventional materials, offer functional nomenclature for application science, and provide utility for future ESOH risk assessment prioritization. The definition and categorization framework established here serve as a first step in determining if and when there is a need for specific ESOH and regulatory screening for an AdM as well as the type and extent of risk‐related information that should be collected or generated for AdMs and AdM‐enabled technologies.

The volume and variety of manufactured chemicals is increasing, although little is known about the risks associated with the frequency and extent of human exposure to most chemicals. The EPA and the recent signing of the Lautenberg Act have both signaled the need for high‐throughput methods to characterize and screen chemicals based on exposure potential, such that more comprehensive toxicity research can be informed. Prior work of Mitchell et al. using multicriteria decision analysis tools to prioritize chemicals for further research is enhanced here, resulting in a high‐level chemical prioritization tool for risk‐based screening. Reliable exposure information is a key gap in currently available engineering analytics to support predictive environmental and health risk assessments. An elicitation with 32 experts informed relative prioritization of risks from chemical properties and human use factors, and the values for each chemical associated with each metric were approximated with data from EPA's CP_CAT database. Three different versions of the model were evaluated using distinct weight profiles, resulting in three different ranked chemical prioritizations with only a small degree of variation across weight profiles. Future work will aim to include greater input from human factors experts and better define qualitative metrics.