Engineering topics

Hou, Yi

Publications and source records attributed to Hou, Yi.

6 records

DOE OSTI2023

Roadmap on commercialization of metal halide perovskite photovoltaics

Perovskite solar cells (PSCs) represent one of the most promising emerging photovoltaic technologies due to their high power conversion efficiency. However, despite the huge progress made not only in terms of the efficiency achieved, but also fundamental understanding of the relevant physics of the devices and issues which affect their efficiency and stability, there are still unresolved problems and obstacles on the path toward commercialization of this promising technology. In this roadmap, we aim to provide a concise and up to date summary of outstanding issues and challenges, and the progress made toward addressing these issues. While the format of this article is not meant to be a comprehensive review of the topic, it provides a collection of the viewpoints of the experts in the field, which covers a broad range of topics related to PSC commercialization, including those relevant for manufacturing (scaling up, different types of devices), operation and stability (various factors), and environmental issues (in particular the use of lead). We hope that the article will provide a useful resource for researchers in the field and that it will facilitate discussions and move forward toward addressing the outstanding challenges in this fast-developing field.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Quantifying Movement Motivations, Demand, and Inflow-Outflow Dynamics in Four Cities (New York, Chicago, Austin, and San Diego) During COVID-19

The COVID-19 pandemic has impacted a wide range of human activities, from food delivery habits to major moving and travel decisions. Results indicate multiple pandemic-related factors have influenced millions of relocation decisions by Americans (e.g., health risk, financial pressures, more space, and employment), and there are various positive economic and social outcomes of this influence (e.g., remote work and education), enabling more affordable living and opportunity. This paper addresses COVID-19 impacts on mobility, especially involving permanent relocations. Survey design and data analysis with U-Haul targeted customers in Austin, New York, San Diego, and Chicago to understand mobility, new moving dynamics, and motivations.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

DOE OSTI2022

Quantum-size-tuned heterostructures enable efficient and stable inverted perovskite solar cells

The energy landscape of reduced-dimensional perovskites (RDPs) can be tailored by adjusting their layer width (n). Recently, 2D/3D heterostructures containing n = 1 and 2 RDPs have produced PSCs with > 25% power conversion efficiency (PCE). Unfortunately, this method does not translate to inverted PSCs due to electron blocking at the 2D/3D interface. Here we report a method to increase the layer width of RDPs in 2D/3D heterostructures in order to address this problem. We discover that bulkier organics form 2D heterostructures more slowly, resulting in wider RDPs; and that small modifications to ligand design induce preferential growth of n ≥ 3 RDPs. Levering these insights, we developed efficient inverted PSCs (certified 23.91% quasi-steady state efficiency). Furthermore, unencapsulated devices operate at room temperature and ~50% relative humidity for over 1000 hrs without loss of PCE; and, when subjected to ISOS-L3 accelerated aging encapsulated devices retain 92% of PCE after 500 hrs.

14 SOLAR ENERGY↗

DOE OSTI2022

Automated vehicle occupancy detection

Described herein are systems and methods for detecting the number of occupants in a vehicle. The detecting may be performed using a camera and a processing device. The detecting may be anonymous and the image of the interior of the vehicle is not stored on the processing device.

Moniot, Matthew Louis↗

DOE OSTI2022

Ferric chloride aided peracetic acid pretreatment for effective utilization of sugarcane bagasse

The synergetic impacts of ferric chloride aided peracetic acid (FPA) pretreatment were investigated to enhance the total biomass utilization through effective cellulose conversion and high-quality lignin production. The sugarcane bagasse pretreatment with 2% peracetic acid (PAA) and 0.1 mol/L ferric chloride (FeCl 3 ) effectively removed 57.3% of lignin and 72.2% of xylan while preserving ~ 97% of cellulose from sugarcane bagasse under mild temperature (90 °C). The FPA pretreated sugarcane bagasse was effectively hydrolyzed with a glucose yield of 313.0 mg/g-biomass, which was 4.5 times higher than the yield of untreated biomass (69.75 mg/g-biomass) and 1.6 and 3.6 times higher than that of individual PAA and FeCl 3 pretreated sugarcane bagasse, respectively. The regenerated lignin (FPA lignin) showed great potential for further valorization by preserving the major interunit linkage (up to 86% of β-O-4) without significant carbohydrate contamination and lignin condensation due to its mild reaction conditions. In this paper, the combination of PAA and FeCl 3 synergistically enhanced the pretreatment efficiency on sugarcane bagasse and resulted in high fermentable sugar and high-quality lignin production.

09 BIOMASS FUELS↗

DOE OSTI2022

Real-Time Highly Resolved Spatial-Temporal Vehicle Energy Consumption Estimation Using Machine Learning and Probe Data

Real-time highly resolved spatial-temporal vehicle energy consumption is a key missing dimension in transportation data. Most roadway link-level vehicle energy consumption data are estimated using average annual daily traffic measures derived from the Highway Performance Monitoring System; however, this method does not reflect day-to-day energy consumption fluctuations. As transportation planners and operators are becoming more environmentally attentive, they need accurate real-time link-level vehicle energy consumption data to assess energy and emissions; to incentivize energy-efficient routing; and to estimate energy impact caused by congestion, major events, and severe weather. This paper presents a computational workflow to automate the estimation of time-resolved vehicle energy consumption for each link in a road network of interest using vehicle probe speed and count data in conjunction with machine learning methods in real time. The real-time pipeline can deliver energy estimates within a couple seconds on query to its interface. The proposed method was evaluated on the transportation network of the metropolitan area of Chattanooga, Tennessee. The volume estimation results were validated with ground truth traffic volume data collected in the field. To demonstrate the effectiveness of the proposed method, the energy consumption pipeline was applied to real-world data to quantify road transportation-related energy reduction because of mitigation policies to slow the spread of COVID-19 and to measure energy loss resulting from congestion.

Severino, Joseph↗