About

Qi Yang is an Assistant Professor in the Department of Design Studies at the University of Wisconsin–Madison. Their educational background spans Design, Psychology, and Systems Engineering. Qi Yang's research centers around two connected agendas: how people move through ideas and how people move through space. In the mental realm, they investigate metacognition in design processes, studying how people reflect on and guide their own thinking. They design Human AI co-creative systems that augment cognition, encourage curiosity, support long-term skill growth, and help overcome design fixation. This work aims to create tools that are wise, expanding human creativity and learning rather than simply producing outcomes. In the physical environment, Qi Yang studies wayfinding in healthcare and educational settings. Using empirical studies and computational modeling, they examine how spaces shape human wayfinding behavior and cognition, such as perceived uncertainty, with the goal of improving human health and well-being. Their research interests include wayfinding, human-building interaction, human AI interaction, creativity support tools, metacognition, spatial cognition, human behavior modeling, environmental psychology, and research through design.

Research topics

• Chemistry
• Materials science
• Composite material
• Nanotechnology
• Chromatography
• Meteorology
• Engineering
• Photochemistry
• Physics
• Nuclear chemistry
• Physical chemistry
• Optoelectronics
• Electronic engineering
• Chemical engineering
• Organic chemistry

Selected publications

• A Mild-Condition and Lignin-First Trifunctional Fractionation Strategy for Lignocellulose Valorization

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access1st authorCorresponding
  PublisherDOI

• Pathology‐Driven Design of a Biomimetic Ferromagnetic Nanomedicine for Dual‐Mode Treatment of Ulcerative Colitis and Colitis‐Associated Colorectal Cancer

  Advanced Materials · 2025-11-10 · 2 citations

  articleOpen access

  Abstract The pathological features of ulcerative colitis (UC) involve systemic abnormalities, including immune dysregulation, iron deficiency, and microbiota imbalance, and these alterations contribute to an increased risk of colitis‐associated colorectal cancer (CAC). Current therapeutic strategies remain insufficient to address these pathological features and restore physiological homeostasis. Here, a dual‐duty nanomedicine (MAC@EGCG‐Fe 3 O 4 ), engineered with an inflammation‐homing M2‐type macrophage membrane “shell” is rationally designed and developed, which encapsulates silk fibroin nanocages loading with epigallocatechin gallate (EGCG) and ferromagnetic nanoparticles (Fe 3 O 4 ). Upon intraperitoneal injection and exposure to an alternating magnetic field (AMF), the nanomedicine selectively accumulated in inflamed lesions, enabling site‐specific therapeutic effects. Controlled AMF irradiation provided localized mild hyperthermia and reductive EGCG for UC treatment or hyperpyrexia and oxidative EGCG for treating CAC. Moreover, this therapeutic strategy reprogrammed colonic immune responses, restored mucosal integrity, alleviated iron deficiency, and modulated microbiota and its metabolites. The study highlights the therapeutic potential of a single pathology‐driven nanomedicine against both UC and CAC through AMF manipulation.

  PublisherOA PDFDOI

• Accelerated Molecular Simulation-Based Model Predictive Control for Regulating Molecular Weights and Monomeric Ratios in Biomass Fractionation

  2025-07-08

  article

  The complex structure of lignin presents significant challenges in understanding its reaction kinetics and optimizing its properties. Thus, multiscale kinetic Monte Carlo (kMC) models have been developed to provide detailed insights into the fractionation processes. The kMC calculates reaction rates between species, generates a rate-based probability distribution, and executes the most probable reactions at each time step. Despite its ability to handle nonlinear dynamics, the high computational demand associated with rate calculations makes real-time control challenging. Therefore, an artificial neural network (ANN) has been trained on the kMC input/output data to replace the repetitive rate calculation step of the kMC algorithm. This accelerated kMC model predicts reaction rates given the current status instead of calculating them, thereby significantly reducing the computational loads of the original kMC model. Integrated into a model predictive control (MPC) framework, the accelerated kMC enables real-time control of lignin properties, enhancing the efficiency and feasibility of the lignin fractionation process.

  PublisherDOI

• Comparative efficacy of autologous iliac bone versus allogeneic demineralized bone matrix in lateral lumbar interbody fusion using a novel minimally invasive iliac bone retrieval tool: a self-controlled study

  Journal of Orthopaedic Surgery and Research · 2025-07-16

  articleOpen access

  OBJECTIVE: This self-controlled study evaluates the fusion efficacy of autologous iliac bone harvested via a novel minimally invasive tool versus allogeneic demineralized bone matrix (DBM) in lateral lumbar interbody fusion (LLIF), while assessing the safety profile of the retrieval tool. METHODS: This study was a prospective clinical controlled study. Patients' basic information was recorded, including the age, gender, body mass index and etc. Visual Analog Scale (VAS) and Oswestry Disability Index (ODI) were used to evaluate clinical efficacy. Three parameters were measured, including intervertebral space height, intervertebral foraminal height and lumbar lordosis angle, before surgery and 3 days/24 months after surgery. Postoperative CT scan was used to compare the difference in interbody fusion between autologous iliac bone and allogeneic bone DBM at 6 and 24 months after surgery. RESULTS: 30 patients followed up for more than 24 months were included. The preoperative VAS for lower back and leg pain was 5.00 ± 0.87, and the preoperative ODI was 48.37 ± 8.53. The VAS for lower back and leg pain was 0.87 ± 0.63, and the ODI was 12.30 ± 2.58 at 24 months after surgery. The VAS and ODI in each postoperative stage were significantly improved compared to the preoperative (P < 0.05). The VAS of the bone extraction area was 1 (0,2) after surgery, and the pain disappeared approximately 2 days after surgery. At 6 months postoperatively, the fusion rate was 66.7% (20/30) for autologous iliac bone versus 30.0% (9/30) for allogeneic DBM (P < 0.05). the fusion rate on the autogenous iliac bone side (96.7%) was significantly higher than that on the DBM side (70.0%) at 24 months after surgery (P < 0.05). CONCLUSIONS: The novel retrieval tool enables safe, minimally invasive harvest of autologous iliac bone, which achieved significantly higher fusion rates than allogeneic DBM in LLIF.

  PublisherOA PDFDOI

• The diagnostic cutoff value of vertebral bone quality score for osteoporosis is significantly influenced by the magnetic field in patients undergoing lumbar surgery

  Quantitative Imaging in Medicine and Surgery · 2025-09-24 · 1 citations

  articleOpen accessSenior authorCorresponding

  Background: The diagnostic efficacy of the magnetic resonance imaging (MRI)-based vertebral bone quality (VBQ) score for osteoporosis in patients undergoing lumbar surgery has been documented; however, whether the VBQ is influenced by different magnetic field strengths (1.5 T and 3.0 T) remains controversial. This study aimed to investigate the influence of magnetic fields on the diagnostic efficacy of the VBQ score via self-paired patients who underwent both 1.5 T and 3.0 T MRI scanning. Methods: This retrospective study included consecutive patients aged >50 years who underwent ≥2 MRI examinations within a 6-month period at our department for degenerative lumbar surgery from June 2022 to June 2024. Patients were included only if they had both dual-energy X-ray absorptiometry (DXA) and quantitative computed tomography (QCT) results obtained within the same period. There were three MRI scanners in our institution: the GE 1.5 T (General Electric), the GE 3.0 T (General Electric), and the PH 3.0 T (Philips Healthcare, Amsterdam, the Netherlands). The self-paired VBQ scores were compared between the different magnetic fields and scan manufacturers using paired t-tests. The Steiger’s Z test, correlation analysis, logistic regression analysis, and receiver operating characteristic (ROC) curve analysis were performed to explore the influence of the magnetic fields on the diagnostic value of the VBQ score. Results: A total of 104 patients were included who underwent ≥2 MRI scans with available DXA and QCT results. The mean age was 65.3±8.8 years with 56.7% female participants. In self-paired analysis, a significantly higher VBQ score was found in 1.5 T compared with 3.0 T (3.2±0.59 vs. 2.71±0.66, P<0.001), whereas no difference was observed between different MRI scanners of 3.0 T. Correlation analysis and logistic regression analysis of the self-paired patients revealed that the VBQ 1.5 T was more accurately associated with osteoporosis than the VBQ 3.0 T, with the strongest relationship in VBQ 1.5 T with QCT (r=−0.529). ROC analysis revealed that the diagnostic efficacy for osteoporosis was comparable between the VBQ 1.5 T and the VBQ 3.0 T [QCT-defined osteoporosis: VBQ 1.5 T area under the curve (AUC) =0.709 vs. VBQ 3.0 T AUC =0.697; DeLong test P=0.904]. Conclusions: The VBQ 1.5 T has a significantly higher cutoff value for osteoporosis than the VBQ 3.0 T in patients undergoing lumbar surgery. It is essential to mention the magnetic resonance (MR) field when applying the VBQ score in the screening of osteoporosis.

  PublisherDOI

• Photocatalytic materials and reactors for hydrogen production: A review

  Molecular Chemistry & Engineering · 2025-07-16 · 12 citations

  reviewOpen accessSenior authorCorresponding

  Hydrogen energy, noted for its high calorific value and eco-friendly nature, is a key focus of new energy research. However, traditional hydrogen production methods can cause severe environmental pollution, posing a threat to human survival. Therefore, the development of green and renewable hydrogen production technologies is crucial for the sustainable advancement of the hydrogen economy. Photocatalytic water splitting using semiconductor materials provides a cost-effective approach for converting solar energy into clean hydrogen fuel. Although current hydrogen production efficiencies remain below the standards required for large-scale applications, a reported solar-to-hydrogen efficiency of up to 9 ​% opens new avenues for industrial use. This review highlights the potential of photocatalytic water splitting for industrial applications, summarizing recent progress in photocatalytic materials for water splitting, with a focus on high-performance hydrogen-producing materials used in partial and overall water splitting at the laboratory scale, and advancements in photocatalytic reactors for hydrogen production are also examined. This review provides comprehensive insights into enhancements in photocatalytic materials and reactor designs, while also discussing the future challenges with scaling up photocatalytic hydrogen production technologies. • The basic reaction process of photocatalytic water splitting is introduced. • The highest hydrogen production performance of different types of photocatalysts are summarized. • The latest developments in photoreactors of different scales are introduced. • The future development prospects of photocatalytic hydrogen production are discussed.

  PublisherDOI

• A Mild-Condition and Lignin-First Trifunctional Fractionation Strategy for Lignocellulose Valorization

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access1st authorCorresponding
  PublisherDOI

• Mild-condition fractionation of lignocellulose into carbohydrates and water-soluble lignin

  Biomass and Bioenergy · 2025-08-18

  articleSenior authorCorresponding
  PublisherDOI

• Mild-Condition Fractionation of Lignocellulose into Carbohydrates and Water-Soluble Lignin

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access1st authorCorresponding
  PublisherDOI

• A population balance model for lignin: Tracking molecular weights, S/G ratio, and bond compositions

  Chemical Engineering Journal · 2025-11-05

  articleOpen access

  Lignin, a major component of lignocellulosic biomass, presents significant opportunities for sustainable applications. However, lignin remains underutilized due to its structural complexity and feedstock variability. To address these challenges, we developed a population balance equation (PBE)-based model to simulate lignin fractionation dynamics, focusing on depolymerization, condensation, and demethoxylation reactions. The model captures key transformations in lignin chains, including changes in molecular weight distribution, bond composition, and monomeric ratios, while requiring far fewer computational resources than kinetic Monte Carlo (kMC) methods. The estimated kinetic parameters showed strong agreement with experimental data across different temperatures, validating the model’s accuracy. Furthermore, the results highlighted the temperature sensitivity of demethoxylation and its impact on the S/G ratio, offering valuable insights for optimizing reaction conditions. This scalable and versatile framework provides a robust tool for lignin valorization and paves the way for improved biomass pretreatment strategies. • A PBE-based model simulates lignin fractionation with high accuracy. • Model captures depolymerization, condensation, and demethoxylation dynamics. • Various lignin properties are tracked and validated with the experiments. • Kinetic parameters for experimental data across multiple temperatures. • Model efficiently handles feedstock variability with low computational cost.

  PublisherDOI

Recent grants

• Collaborative Research: Low-Energy Tandem Process for Fractionation and Reversible Preservation of Lignocellulose Using Multifunctional Aldehyde Sulfonic Acids

  NSF · $274k · 2021–2022

Frequent coauthors

• Qingwen Tian

  119 shared

• Guigan Fang

  State Forestry and Grassland Administration

  103 shared

• Xiang Li

  Henan Normal University

  98 shared

• Yawei Zhu

  Chinese Academy of Forestry

  53 shared

• Aixiang Pan

  Institute of Chemical Industry of Forest Products

  46 shared

• Hang Yin

  33 shared

• T. W. Wu

  Chinese Academy of Forestry

  30 shared

• Xingjian Liu

  Zhejiang University of Technology

  21 shared