#Chem2
The wildfire smoke episode affecting the U.S. is set to invade new territory later this week, with AQIs in the 100-160 range (USG to Unhealthy) predicted from the Midwest southwards into the Carolinas, Georgia, and Alabama. Forecast for 8 am EDT Friday from NASA: fluid.nccs.nasa.gov/wxmaps/chem2...
August 5, 2025 at 5:14 PM
I love that when created in our LMS, my courses for the semester are not called "Chem2 Section 01", "Chem2 Section 02", etc., but are instead all called "Chem2 Spring 2026" so I can't tell them apart at all and have to guess which course is which section.
January 5, 2026 at 4:52 PM
From my post last year, my 4 favorite sources of wildfire smoke forecasts:

1-3 day from NOAA:
airquality.weather.gov?element=apm2...

rapidrefresh.noaa.gov/hrrr/HRRRsmo...

3-day from Environment Canada:
weather.gc.ca/firework/

5-10-day from NASA:
fluid.nccs.nasa.gov/wxmaps/chem2...
15 sources of wildfire smoke forecasts for North America » Yale Climate Connections
Forecasting wildfire smoke is hard. We review the best tools to help you predict when unhealthful levels of smoke are coming.
yaleclimateconnections.org
July 15, 2026 at 4:43 PM
PM 2.5 forecast for 8 am EDT Tuesday from NASA's model (fluid.nccs.nasa.gov/wxmaps/chem2...) calling for AQIs in the orange "Unhealthy for Sensitive Groups" to red "Unhealthy" range for most of the Midwest and Northeast. See: yaleclimateconnections.org/2025/07/15-s... for sources of smoke forecasts.
August 2, 2025 at 12:25 AM
guess who forgot everything from chem2 and is having a smol panic attack about chem1a starting rn
February 4, 2025 at 9:56 PM
NASA GEOS-FP: fluid.nccs.nasa.gov/wxmaps/chem2...

U.S. Interagency Wildland Fire Air Quality Response Program: outlooks.airfire.org/outlook/131d...?
fluid.nccs.nasa.gov
July 18, 2026 at 12:33 PM
The 10-day forecast from NASA’s GEOS-FP model suggests the smoke will be problematic over the Great Lakes and Northeast on and off for the next 10 days. Rain and cooler weather should help dampen the fires this weekend, cutting down on their smoke. (8/8)
fluid.nccs.nasa.gov/wxmaps/chem2...
Atmospheric Composition (2D) Maps - Surface PM25
Fluid provides applications for interactive analysis and visualizations of meteorological and chemical output from GMAO-supported forecast and reanalysis models
fluid.nccs.nasa.gov
July 14, 2026 at 4:39 PM
December 23, 2023 at 1:58 AM
NASA’s model forecasts much lower concentrations in NJ Sunday. fluid.nccs.nasa.gov/wxmaps/chem2...
July 16, 2026 at 6:01 PM
so far chem2 is coming back to me- im excited, i actually love this stuff. hopefully i dont get too lost. 😅
February 5, 2025 at 12:14 AM
Real convo I once witnessed at an Ivy:

How many hrs of work outside class does your course require?

Prof 1: Dunno.

Prof 2: 15

Don't students have 3 classes?

Prof 2: That's why they should never take Bio3 & Chem2 at the same time.

Isn't that a typical for a junior fall semster?

Prof 2: Dunno
August 2, 2026 at 5:17 PM
Today I honor Ms. Mayes. When she took her glasses off and gave you that look? ooh. She did not play. She taught me so much more than Chem2. I left home after HS and never saw her again, but she believed in me even when I did not in a way I have never forgotten.

www.legacy.com/us/obituarie...
Marjorie MAYES Obituary (2015) - St. Petersburg, FL - Tampa Bay Times
View Marjorie D. Tyson "Auntie Marge" MAYES's obituary, send flowers and sign the guestbook.
www.legacy.com
February 1, 2025 at 6:46 PM
Zonglin Yang, Wanhao Liu, Ben Gao, Yujie Liu, Wei Li, Tong Xie, Lidong Bing, Wanli Ouyang, Erik Cambria, Dongzhan Zhou
MOOSE-Chem2: Exploring LLM Limits in Fine-Grained Scientific Hypothesis Discovery via Hierarchical Search
https://arxiv.org/abs/2505.19209
May 27, 2025 at 2:29 PM
that whips. they almost gave me stock room keys but they cut my financial aid and I wasn’t eligible for work/study a year ago 😭 so then i did the most reasonable thing to do and quit school for a semester and forgot EVERYTHING i learned in chem2 highly embarrassing
February 13, 2025 at 8:05 PM
🤣🤣 That’s all it is? That’s a lot don’t down play it. I can’t even remember what we did in either class. The labs were easy. The classes were insane. But you are right it was the teachers. Chem2 that man would solve problems wrong, skip steps, then be mad we were confused lol
November 13, 2024 at 1:57 PM
MOOSE-Chem2: Exploring LLM Limits in Fine-Grained Scientific Hypothesis Discovery via Hierarchical Search
Large language models (LLMs) have shown promise in automating scientific hypothesis generation, yet existing approaches primarily yield coarse-grained hypotheses lacking critical methodological and experimental details. We introduce and formally define the new task of fine-grained scientific hypothesis discovery, which entails generating detailed, experimentally actionable hypotheses from coarse initial research directions. We frame this as a combinatorial optimization problem and investigate the upper limits of LLMs' capacity to solve it when maximally leveraged. Specifically, we explore four foundational questions: (1) how to best harness an LLM's internal heuristics to formulate the fine-grained hypothesis it itself would judge as the most promising among all the possible hypotheses it might generate, based on its own internal scoring-thus defining a latent reward landscape over the hypothesis space; (2) whether such LLM-judged better hypotheses exhibit stronger alignment with ground-truth hypotheses; (3) whether shaping the reward landscape using an ensemble of diverse LLMs of similar capacity yields better outcomes than defining it with repeated instances of the strongest LLM among them; and (4) whether an ensemble of identical LLMs provides a more reliable reward landscape than a single LLM. To address these questions, we propose a hierarchical search method that incrementally proposes and integrates details into the hypothesis, progressing from general concepts to specific experimental configurations. We show that this hierarchical process smooths the reward landscape and enables more effective optimization. Empirical evaluations on a new benchmark of expert-annotated fine-grained hypotheses from recent literature show that our method consistently outperforms strong baselines.
arxiv.org
October 28, 2025 at 4:50 AM
MOOSE-Chem2: Exploring LLM Limits in Fine-Grained Scientific Hypothesis Discovery via Hierarchical Search
Large language models (LLMs) have shown promise in automating scientific hypothesis generation, yet existing approaches primarily yield coarse-grained hypotheses lacking critical methodological and experimental details. We introduce and formally define the new task of fine-grained scientific hypothesis discovery, which entails generating detailed, experimentally actionable hypotheses from coarse initial research directions. We frame this as a combinatorial optimization problem and investigate the upper limits of LLMs' capacity to solve it when maximally leveraged. Specifically, we explore four foundational questions: (1) how to best harness an LLM's internal heuristics to formulate the fine-grained hypothesis it itself would judge as the most promising among all the possible hypotheses it might generate, based on its own internal scoring-thus defining a latent reward landscape over the hypothesis space; (2) whether such LLM-judged better hypotheses exhibit stronger alignment with ground-truth hypotheses; (3) whether shaping the reward landscape using an ensemble of diverse LLMs of similar capacity yields better outcomes than defining it with repeated instances of the strongest LLM among them; and (4) whether an ensemble of identical LLMs provides a more reliable reward landscape than a single LLM. To address these questions, we propose a hierarchical search method that incrementally proposes and integrates details into the hypothesis, progressing from general concepts to specific experimental configurations. We show that this hierarchical process smooths the reward landscape and enables more effective optimization. Empirical evaluations on a new benchmark of expert-annotated fine-grained hypotheses from recent literature show that our method consistently outperforms strong baselines.
arxiv.org
October 28, 2025 at 4:50 AM
but yes, in that i took basic science level 1 through to orgo and biochem 😅 the online thing let me take get away with working while taking chem 1/chem2/phys 1/cell bio 1/stats/psych all in the same semester to cut 6 mo-1 year off the timeline. something i'm not sure i'd advise, but we got it done.
September 6, 2025 at 3:26 PM
The ONLY Chem II Modeling Instruction™ workshop available this summer is @weberstate.bsky.social in Utah. July 6–17.

This is your chance in summer 2026. Grab it! 🧪 bit.ly/Chem2inUtah

#ModelingInstruction #AMTATeachers #modchem #Chem2 #ScienceEducation #STEMEd #WeberState #Utah #SummerPD
June 9, 2026 at 3:53 PM
Yang, Liu, Gao, Liu, Li, Xie, Bing, Ouyang, Cambria, Zhou: MOOSE-Chem2: Exploring LLM Limits in Fine-Grained Scientific Hypothesis Discovery via Hierarchical Search https://arxiv.org/abs/2505.19209 https://arxiv.org/pdf/2505.19209 https://arxiv.org/html/2505.19209
May 27, 2025 at 6:21 AM